[{"date_updated":"2025-09-23T07:56:20Z","day":"01","type":"journal_article","status":"public","date_created":"2018-12-11T11:54:15Z","publication":"Logical Methods in Computer Science","tmp":{"short":"CC BY-ND (4.0)","image":"/image/cc_by_nd.png","name":"Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nd/4.0/legalcode"},"publisher":"International Federation of Computational Logic","ec_funded":1,"isi":1,"file_date_updated":"2020-07-14T12:45:17Z","project":[{"_id":"25832EC2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Rigorous Systems Engineering","grant_number":"S 11407_N23"},{"call_identifier":"FP7","_id":"25EE3708-B435-11E9-9278-68D0E5697425","grant_number":"267989","name":"Quantitative Reactive Modeling"}],"pubrep_id":"390","external_id":{"isi":["000353193000019"]},"doi":"10.2168/LMCS-11(1:20)2015","volume":11,"article_number":"20","language":[{"iso":"eng"}],"scopus_import":"1","abstract":[{"text":"Linearizability of concurrent data structures is usually proved by monolithic simulation arguments relying on the identification of the so-called linearization points. Regrettably, such proofs, whether manual or automatic, are often complicated and scale poorly to advanced non-blocking concurrency patterns, such as helping and optimistic updates. In response, we propose a more modular way of checking linearizability of concurrent queue algorithms that does not involve identifying linearization points. We reduce the task of proving linearizability with respect to the queue specification to establishing four basic properties, each of which can be proved independently by simpler arguments. As a demonstration of our approach, we verify the Herlihy and Wing queue, an algorithm that is challenging to verify by a simulation proof. ","lang":"eng"}],"article_processing_charge":"No","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","_id":"1832","title":"Aspect-oriented linearizability proofs","file":[{"access_level":"open_access","date_updated":"2020-07-14T12:45:17Z","creator":"system","file_size":380203,"date_created":"2018-12-12T10:11:27Z","file_id":"4881","checksum":"7370e164d0a731f442424a92669efc34","file_name":"IST-2015-390-v1+1_1502.07639.pdf","content_type":"application/pdf","relation":"main_file"}],"intvolume":"        11","quality_controlled":"1","department":[{"_id":"ToHe"}],"publist_id":"5271","oa":1,"ddc":["000"],"has_accepted_license":"1","citation":{"ama":"Chakraborty S, Henzinger TA, Sezgin A, Vafeiadis V. Aspect-oriented linearizability proofs. <i>Logical Methods in Computer Science</i>. 2015;11(1). doi:<a href=\"https://doi.org/10.2168/LMCS-11(1:20)2015\">10.2168/LMCS-11(1:20)2015</a>","mla":"Chakraborty, Soham, et al. “Aspect-Oriented Linearizability Proofs.” <i>Logical Methods in Computer Science</i>, vol. 11, no. 1, 20, International Federation of Computational Logic, 2015, doi:<a href=\"https://doi.org/10.2168/LMCS-11(1:20)2015\">10.2168/LMCS-11(1:20)2015</a>.","apa":"Chakraborty, S., Henzinger, T. A., Sezgin, A., &#38; Vafeiadis, V. (2015). Aspect-oriented linearizability proofs. <i>Logical Methods in Computer Science</i>. International Federation of Computational Logic. <a href=\"https://doi.org/10.2168/LMCS-11(1:20)2015\">https://doi.org/10.2168/LMCS-11(1:20)2015</a>","ieee":"S. Chakraborty, T. A. Henzinger, A. Sezgin, and V. Vafeiadis, “Aspect-oriented linearizability proofs,” <i>Logical Methods in Computer Science</i>, vol. 11, no. 1. International Federation of Computational Logic, 2015.","ista":"Chakraborty S, Henzinger TA, Sezgin A, Vafeiadis V. 2015. Aspect-oriented linearizability proofs. Logical Methods in Computer Science. 11(1), 20.","short":"S. Chakraborty, T.A. Henzinger, A. Sezgin, V. Vafeiadis, Logical Methods in Computer Science 11 (2015).","chicago":"Chakraborty, Soham, Thomas A Henzinger, Ali Sezgin, and Viktor Vafeiadis. “Aspect-Oriented Linearizability Proofs.” <i>Logical Methods in Computer Science</i>. International Federation of Computational Logic, 2015. <a href=\"https://doi.org/10.2168/LMCS-11(1:20)2015\">https://doi.org/10.2168/LMCS-11(1:20)2015</a>."},"issue":"1","month":"04","related_material":{"record":[{"relation":"earlier_version","status":"public","id":"2328"}]},"author":[{"first_name":"Soham","last_name":"Chakraborty","full_name":"Chakraborty, Soham"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000−0002−2985−7724","full_name":"Henzinger, Thomas A","last_name":"Henzinger","first_name":"Thomas A"},{"full_name":"Sezgin, Ali","last_name":"Sezgin","first_name":"Ali"},{"last_name":"Vafeiadis","first_name":"Viktor","full_name":"Vafeiadis, Viktor"}],"corr_author":"1","article_type":"original","date_published":"2015-04-01T00:00:00Z","license":"https://creativecommons.org/licenses/by-nd/4.0/","oa_version":"Published Version","publication_status":"published","year":"2015"},{"article_processing_charge":"No","date_published":"2015-05-30T00:00:00Z","abstract":[{"lang":"eng","text":"Nonrigid shapes are ubiquitous in nature and are encountered at all levels of life, from macro to nano. The need to model such shapes and understand their behavior arises in many applications in imaging sciences, pattern recognition, computer vision, and computer graphics. Of particular importance is understanding which properties of the shape are attributed to deformations and which are invariant, i.e., remain unchanged. This chapter presents an approach to nonrigid shapes from the point of view of metric geometry. Modeling shapes as metric spaces, one can pose the problem of shape similarity as the similarity of metric spaces and harness tools from theoretical metric geometry for the computation of such a similarity."}],"year":"2015","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"None","publication_status":"published","language":[{"iso":"eng"}],"OA_type":"closed access","scopus_import":"1","author":[{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","last_name":"Bronstein","first_name":"Alexander"},{"first_name":"Michael M.","last_name":"Bronstein","full_name":"Bronstein, Michael M."}],"editor":[{"full_name":"Scherzer, Otmar","first_name":"Otmar","last_name":"Scherzer"}],"month":"05","edition":"2","citation":{"mla":"Bronstein, Alex M., and Michael M. Bronstein. “Manifold Intrinsic Similarity.” <i>Handbook of Mathematical Methods in Imaging</i>, edited by Otmar Scherzer, 2nd ed., Springer Nature, 2015, pp. 1859–908, doi:<a href=\"https://doi.org/10.1007/978-1-4939-0790-8_57\">10.1007/978-1-4939-0790-8_57</a>.","ieee":"A. M. Bronstein and M. M. Bronstein, “Manifold Intrinsic Similarity,” in <i>Handbook of Mathematical Methods in Imaging</i>, 2nd ed., O. Scherzer, Ed. New York: Springer Nature, 2015, pp. 1859–1908.","apa":"Bronstein, A. M., &#38; Bronstein, M. M. (2015). Manifold Intrinsic Similarity. In O. Scherzer (Ed.), <i>Handbook of Mathematical Methods in Imaging</i> (2nd ed., pp. 1859–1908). New York: Springer Nature. <a href=\"https://doi.org/10.1007/978-1-4939-0790-8_57\">https://doi.org/10.1007/978-1-4939-0790-8_57</a>","ama":"Bronstein AM, Bronstein MM. Manifold Intrinsic Similarity. In: Scherzer O, ed. <i>Handbook of Mathematical Methods in Imaging</i>. 2nd ed. New York: Springer Nature; 2015:1859-1908. doi:<a href=\"https://doi.org/10.1007/978-1-4939-0790-8_57\">10.1007/978-1-4939-0790-8_57</a>","ista":"Bronstein AM, Bronstein MM. 2015.Manifold Intrinsic Similarity. In: Handbook of Mathematical Methods in Imaging. , 1859–1908.","chicago":"Bronstein, Alex M., and Michael M. Bronstein. “Manifold Intrinsic Similarity.” In <i>Handbook of Mathematical Methods in Imaging</i>, edited by Otmar Scherzer, 2nd ed., 1859–1908. New York: Springer Nature, 2015. <a href=\"https://doi.org/10.1007/978-1-4939-0790-8_57\">https://doi.org/10.1007/978-1-4939-0790-8_57</a>.","short":"A.M. Bronstein, M.M. Bronstein, in:, O. Scherzer (Ed.), Handbook of Mathematical Methods in Imaging, 2nd ed., Springer Nature, New York, 2015, pp. 1859–1908."},"doi":"10.1007/978-1-4939-0790-8_57","publisher":"Springer Nature","publication":"Handbook of Mathematical Methods in Imaging","extern":"1","page":"1859-1908","place":"New York","date_created":"2024-10-15T11:20:53Z","status":"public","quality_controlled":"1","date_updated":"2024-10-22T08:12:57Z","title":"Manifold Intrinsic Similarity","_id":"18326","type":"book_chapter","publication_identifier":{"eisbn":["9781493907908"],"isbn":["9781493907892"]},"day":"30"},{"author":[{"first_name":"Pablo","last_name":"Sprechmann","full_name":"Sprechmann, Pablo"},{"first_name":"Alexander","last_name":"Bronstein","full_name":"Bronstein, Alexander","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","orcid":"0000-0001-9699-8730"},{"last_name":"Sapiro","first_name":"Guillermo","full_name":"Sapiro, Guillermo"}],"citation":{"short":"P. Sprechmann, A.M. Bronstein, G. Sapiro, in:, Excursions in Harmonic Analysis, Volumne 4, 1st ed., Springer Nature, Cham, 2015, pp. 407–420.","chicago":"Sprechmann, Pablo, Alex M. Bronstein, and Guillermo Sapiro. “Supervised Non-Negative Matrix Factorization for Audio Source Separation.” In <i>Excursions in Harmonic Analysis, Volumne 4</i>, 1st ed., 407–20. Cham: Springer Nature, 2015. <a href=\"https://doi.org/10.1007/978-3-319-20188-7_16\">https://doi.org/10.1007/978-3-319-20188-7_16</a>.","ista":"Sprechmann P, Bronstein AM, Sapiro G. 2015.Supervised non-negative matrix factorization for audio source separation. In: Excursions in Harmonic Analysis, Volumne 4. Applied and Numerical Harmonic Analysis, , 407–420.","ama":"Sprechmann P, Bronstein AM, Sapiro G. Supervised non-negative matrix factorization for audio source separation. In: <i>Excursions in Harmonic Analysis, Volumne 4</i>. 1st ed. Cham: Springer Nature; 2015:407-420. doi:<a href=\"https://doi.org/10.1007/978-3-319-20188-7_16\">10.1007/978-3-319-20188-7_16</a>","apa":"Sprechmann, P., Bronstein, A. M., &#38; Sapiro, G. (2015). Supervised non-negative matrix factorization for audio source separation. In <i>Excursions in Harmonic Analysis, Volumne 4</i> (1st ed., pp. 407–420). Cham: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-319-20188-7_16\">https://doi.org/10.1007/978-3-319-20188-7_16</a>","ieee":"P. Sprechmann, A. M. Bronstein, and G. Sapiro, “Supervised non-negative matrix factorization for audio source separation,” in <i>Excursions in Harmonic Analysis, Volumne 4</i>, 1st ed., Cham: Springer Nature, 2015, pp. 407–420.","mla":"Sprechmann, Pablo, et al. “Supervised Non-Negative Matrix Factorization for Audio Source Separation.” <i>Excursions in Harmonic Analysis, Volumne 4</i>, 1st ed., Springer Nature, 2015, pp. 407–20, doi:<a href=\"https://doi.org/10.1007/978-3-319-20188-7_16\">10.1007/978-3-319-20188-7_16</a>."},"edition":"1","month":"10","doi":"10.1007/978-3-319-20188-7_16","date_published":"2015-10-30T00:00:00Z","abstract":[{"lang":"eng","text":"Source separation is a widely studied problem in signal processing. Despite the permanent progress reported in the literature it is still considered a significant challenge. This chapter first reviews the use of non-negative matrix factorization (NMF) algorithms for solving source separation problems, and proposes a new way for the supervised training in NMF. Matrix factorization methods have received a lot of attention in recent year in the audio processing community, producing particularly good results in source separation. Traditionally, NMF algorithms consist of two separate stages: a training stage, in which a generative model is learned; and a testing stage in which the pre-learned model is used in a high level task such as enhancement, separation, or classification. As an alternative, we propose a task-supervised NMF method for the adaptation of the basis spectra learned in the first stage to enhance the performance on the specific task used in the second stage. We cast this problem as a bilevel optimization program efficiently solved via stochastic gradient descent. The proposed approach is general enough to handle sparsity priors of the activations, and allow non-Euclidean data terms such as β-divergences. The framework is evaluated on speech enhancement."}],"article_processing_charge":"No","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"None","year":"2015","OA_type":"closed access","language":[{"iso":"eng"}],"scopus_import":"1","status":"public","date_created":"2024-10-15T11:20:53Z","place":"Cham","quality_controlled":"1","alternative_title":["Applied and Numerical Harmonic Analysis"],"_id":"18327","title":"Supervised non-negative matrix factorization for audio source separation","date_updated":"2024-10-22T08:09:36Z","day":"30","type":"book_chapter","publication_identifier":{"isbn":["9783319201870"],"issn":["2296-5009"],"eisbn":["9783319201887"],"eissn":["2296-5017"]},"publication":"Excursions in Harmonic Analysis, Volumne 4","publisher":"Springer Nature","extern":"1","page":"407-420"},{"abstract":[{"text":"Huge body of evidences demonstrated that volatile anesthetics affect the hippocampal neurogenesis and neurocognitive functions, and most of them showed impairment at anesthetic dose. Here, we investigated the effect of low dose (1.8%) sevoflurane on hippocampal neurogenesis and dentate gyrus-dependent learning. Neonatal rats at postnatal day 4 to 6 (P4-6) were treated with 1.8% sevoflurane for 6 hours. Neurogenesis was quantified by bromodeoxyuridine labeling and electrophysiology recording. Four and seven weeks after treatment, the Morris water maze and contextual-fear discrimination learning tests were performed to determine the influence on spatial learning and pattern separation. A 6-hour treatment with 1.8% sevoflurane promoted hippocampal neurogenesis and increased the survival of newborn cells and the proportion of immature granular cells in the dentate gyrus of neonatal rats. Sevoflurane-treated rats performed better during the training days of the Morris water maze test and in contextual-fear discrimination learning test. These results suggest that a subanesthetic dose of sevoflurane promotes hippocampal neurogenesis in neonatal rats and facilitates their performance in dentate gyrus-dependent learning tasks.","lang":"eng"}],"article_processing_charge":"No","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"scopus_import":"1","volume":7,"pubrep_id":"456","external_id":{"isi":["000353223200002"]},"doi":"10.1177/1759091415575845","publication":"ASN Neuro","publisher":"SAGE Publications","tmp":{"image":"/images/cc_by.png","short":"CC BY (3.0)","legal_code_url":"https://creativecommons.org/licenses/by/3.0/legalcode","name":"Creative Commons Attribution 3.0 Unported (CC BY 3.0)"},"file_date_updated":"2020-07-14T12:45:18Z","isi":1,"date_created":"2018-12-11T11:54:16Z","status":"public","date_updated":"2025-09-23T09:31:50Z","day":"13","type":"journal_article","date_published":"2015-04-13T00:00:00Z","publication_status":"published","license":"https://creativecommons.org/licenses/by/3.0/","oa_version":"Published Version","year":"2015","article_type":"original","author":[{"id":"3DFD581A-F248-11E8-B48F-1D18A9856A87","full_name":"Chen, Chong","first_name":"Chong","last_name":"Chen"},{"full_name":"Wang, Chao","last_name":"Wang","first_name":"Chao"},{"last_name":"Zhao","first_name":"Xuan","full_name":"Zhao, Xuan"},{"last_name":"Zhou","first_name":"Tao","full_name":"Zhou, Tao"},{"full_name":"Xu, Dao","first_name":"Dao","last_name":"Xu"},{"full_name":"Wang, Zhi","last_name":"Wang","first_name":"Zhi"},{"full_name":"Wang, Ying","last_name":"Wang","first_name":"Ying"}],"issue":"2","citation":{"ama":"Chen C, Wang C, Zhao X, et al. Low-dose sevoflurane promoteshippocampal neurogenesis and facilitates the development of dentate gyrus-dependent learning in neonatal rats. <i>ASN Neuro</i>. 2015;7(2). doi:<a href=\"https://doi.org/10.1177/1759091415575845\">10.1177/1759091415575845</a>","ieee":"C. Chen <i>et al.</i>, “Low-dose sevoflurane promoteshippocampal neurogenesis and facilitates the development of dentate gyrus-dependent learning in neonatal rats,” <i>ASN Neuro</i>, vol. 7, no. 2. SAGE Publications, 2015.","apa":"Chen, C., Wang, C., Zhao, X., Zhou, T., Xu, D., Wang, Z., &#38; Wang, Y. (2015). Low-dose sevoflurane promoteshippocampal neurogenesis and facilitates the development of dentate gyrus-dependent learning in neonatal rats. <i>ASN Neuro</i>. SAGE Publications. <a href=\"https://doi.org/10.1177/1759091415575845\">https://doi.org/10.1177/1759091415575845</a>","mla":"Chen, Chong, et al. “Low-Dose Sevoflurane Promoteshippocampal Neurogenesis and Facilitates the Development of Dentate Gyrus-Dependent Learning in Neonatal Rats.” <i>ASN Neuro</i>, vol. 7, no. 2, SAGE Publications, 2015, doi:<a href=\"https://doi.org/10.1177/1759091415575845\">10.1177/1759091415575845</a>.","chicago":"Chen, Chong, Chao Wang, Xuan Zhao, Tao Zhou, Dao Xu, Zhi Wang, and Ying Wang. “Low-Dose Sevoflurane Promoteshippocampal Neurogenesis and Facilitates the Development of Dentate Gyrus-Dependent Learning in Neonatal Rats.” <i>ASN Neuro</i>. SAGE Publications, 2015. <a href=\"https://doi.org/10.1177/1759091415575845\">https://doi.org/10.1177/1759091415575845</a>.","short":"C. Chen, C. Wang, X. Zhao, T. Zhou, D. Xu, Z. Wang, Y. Wang, ASN Neuro 7 (2015).","ista":"Chen C, Wang C, Zhao X, Zhou T, Xu D, Wang Z, Wang Y. 2015. Low-dose sevoflurane promoteshippocampal neurogenesis and facilitates the development of dentate gyrus-dependent learning in neonatal rats. ASN Neuro. 7(2)."},"month":"04","oa":1,"ddc":["570"],"has_accepted_license":"1","department":[{"_id":"PeJo"}],"publist_id":"5269","intvolume":"         7","quality_controlled":"1","_id":"1834","title":"Low-dose sevoflurane promoteshippocampal neurogenesis and facilitates the development of dentate gyrus-dependent learning in neonatal rats","file":[{"file_id":"5057","date_created":"2018-12-12T10:14:08Z","file_size":1146814,"creator":"system","date_updated":"2020-07-14T12:45:18Z","access_level":"open_access","relation":"main_file","content_type":"application/pdf","file_name":"IST-2016-456-v1+1_ASN_Neuro-2015-Chen-.pdf","checksum":"53e16bd3fc2ae2c0d7de9164626c37aa"}]},{"date_published":"2015-04-01T00:00:00Z","publication_status":"published","oa_version":"Preprint","year":"2015","author":[{"orcid":"0000-0001-8180-0904","id":"3444EA5E-F248-11E8-B48F-1D18A9856A87","first_name":"Mirco","last_name":"Giacobbe","full_name":"Giacobbe, Mirco"},{"first_name":"Calin C","last_name":"Guet","full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052"},{"last_name":"Gupta","first_name":"Ashutosh","full_name":"Gupta, Ashutosh","id":"335E5684-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Thomas A","last_name":"Henzinger","full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000−0002−2985−7724"},{"id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","last_name":"Paixao","first_name":"Tiago"},{"orcid":"0000-0002-9041-0905","id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","full_name":"Petrov, Tatjana","last_name":"Petrov","first_name":"Tatjana"}],"citation":{"apa":"Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., &#38; Petrov, T. (2015). Model checking gene regulatory networks. Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">https://doi.org/10.1007/978-3-662-46681-0_47</a>","ieee":"M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov, “Model checking gene regulatory networks,” vol. 9035. Springer, pp. 469–483, 2015.","mla":"Giacobbe, Mirco, et al. <i>Model Checking Gene Regulatory Networks</i>. Vol. 9035, Springer, 2015, pp. 469–83, doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">10.1007/978-3-662-46681-0_47</a>.","ama":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking gene regulatory networks. 2015;9035:469-483. doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">10.1007/978-3-662-46681-0_47</a>","short":"M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, 9035 (2015) 469–483.","chicago":"Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago Paixao, and Tatjana Petrov. “Model Checking Gene Regulatory Networks.” Lecture Notes in Computer Science. Springer, 2015. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">https://doi.org/10.1007/978-3-662-46681-0_47</a>.","ista":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2015. Model checking gene regulatory networks. 9035, 469–483."},"month":"04","related_material":{"record":[{"relation":"later_version","status":"public","id":"1351"}]},"oa":1,"main_file_link":[{"url":"http://arxiv.org/abs/1410.7704","open_access":"1"}],"department":[{"_id":"ToHe"},{"_id":"CaGu"},{"_id":"NiBa"}],"conference":{"start_date":"2015-04-11","end_date":"2015-04-18","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems","location":"London, United Kingdom"},"publist_id":"5267","intvolume":"      9035","quality_controlled":"1","alternative_title":["LNCS"],"_id":"1835","title":"Model checking gene regulatory networks","abstract":[{"text":"The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs –an important problem of interest in evolutionary biology– more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.","lang":"eng"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"scopus_import":"1","volume":9035,"project":[{"name":"Quantitative Reactive Modeling","grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"call_identifier":"FWF","_id":"25832EC2-B435-11E9-9278-68D0E5697425","name":"Rigorous Systems Engineering","grant_number":"S 11407_N23"},{"_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Formal methods for the design and analysis of complex systems","grant_number":"Z211"},{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091"},{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"},{"name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"external_id":{"arxiv":["1410.7704"]},"doi":"10.1007/978-3-662-46681-0_47","ec_funded":1,"publisher":"Springer","acknowledgement":"SNSF Early Postdoc.Mobility Fellowship, the grant number P2EZP2 148797.\r\n","page":"469 - 483","status":"public","date_created":"2018-12-11T11:54:16Z","arxiv":1,"date_updated":"2025-07-10T11:50:42Z","series_title":"Lecture Notes in Computer Science","day":"01","type":"conference"},{"_id":"1836","title":"Segment abstraction for worst-case execution time analysis","intvolume":"      9032","quality_controlled":"1","alternative_title":["LNCS"],"department":[{"_id":"ToHe"}],"conference":{"end_date":"2015-04-18","start_date":"2015-04-11","name":"ESOP: European Symposium on Programming","location":"London, United Kingdom"},"publist_id":"5266","citation":{"chicago":"Cerny, Pavol, Thomas A Henzinger, Laura Kovács, Arjun Radhakrishna, and Jakob Zwirchmayr. “Segment Abstraction for Worst-Case Execution Time Analysis.” Lecture Notes in Computer Science. Springer, 2015. <a href=\"https://doi.org/10.1007/978-3-662-46669-8_5\">https://doi.org/10.1007/978-3-662-46669-8_5</a>.","short":"P. Cerny, T.A. Henzinger, L. Kovács, A. Radhakrishna, J. Zwirchmayr, 9032 (2015) 105–131.","ista":"Cerny P, Henzinger TA, Kovács L, Radhakrishna A, Zwirchmayr J. 2015. Segment abstraction for worst-case execution time analysis. 9032, 105–131.","ama":"Cerny P, Henzinger TA, Kovács L, Radhakrishna A, Zwirchmayr J. Segment abstraction for worst-case execution time analysis. 2015;9032:105-131. doi:<a href=\"https://doi.org/10.1007/978-3-662-46669-8_5\">10.1007/978-3-662-46669-8_5</a>","apa":"Cerny, P., Henzinger, T. A., Kovács, L., Radhakrishna, A., &#38; Zwirchmayr, J. (2015). Segment abstraction for worst-case execution time analysis. Presented at the ESOP: European Symposium on Programming, London, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-662-46669-8_5\">https://doi.org/10.1007/978-3-662-46669-8_5</a>","ieee":"P. Cerny, T. A. Henzinger, L. Kovács, A. Radhakrishna, and J. Zwirchmayr, “Segment abstraction for worst-case execution time analysis,” vol. 9032. Springer, pp. 105–131, 2015.","mla":"Cerny, Pavol, et al. <i>Segment Abstraction for Worst-Case Execution Time Analysis</i>. Vol. 9032, Springer, 2015, pp. 105–31, doi:<a href=\"https://doi.org/10.1007/978-3-662-46669-8_5\">10.1007/978-3-662-46669-8_5</a>."},"month":"04","author":[{"last_name":"Cerny","first_name":"Pavol","full_name":"Cerny, Pavol","id":"4DCBEFFE-F248-11E8-B48F-1D18A9856A87"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000−0002−2985−7724","first_name":"Thomas A","last_name":"Henzinger","full_name":"Henzinger, Thomas A"},{"last_name":"Kovács","first_name":"Laura","full_name":"Kovács, Laura"},{"full_name":"Radhakrishna, Arjun","last_name":"Radhakrishna","first_name":"Arjun","id":"3B51CAC4-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Zwirchmayr, Jakob","first_name":"Jakob","last_name":"Zwirchmayr"}],"date_published":"2015-04-01T00:00:00Z","oa_version":"None","publication_status":"published","year":"2015","date_updated":"2025-09-23T10:42:04Z","series_title":"Lecture Notes in Computer Science","day":"01","type":"conference","date_created":"2018-12-11T11:54:16Z","status":"public","page":"105 - 131","ec_funded":1,"publisher":"Springer","isi":1,"project":[{"call_identifier":"FP7","_id":"25EE3708-B435-11E9-9278-68D0E5697425","grant_number":"267989","name":"Quantitative Reactive Modeling"},{"grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","_id":"25832EC2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"external_id":{"isi":["000361751400005"]},"doi":"10.1007/978-3-662-46669-8_5","volume":9032,"language":[{"iso":"eng"}],"scopus_import":"1","abstract":[{"text":"In the standard framework for worst-case execution time (WCET) analysis of programs, the main data structure is a single instance of integer linear programming (ILP) that represents the whole program. The instance of this NP-hard problem must be solved to find an estimate forWCET, and it must be refined if the estimate is not tight.We propose a new framework for WCET analysis, based on abstract segment trees (ASTs) as the main data structure. The ASTs have two advantages. First, they allow computing WCET by solving a number of independent small ILP instances. Second, ASTs store more expressive constraints, thus enabling a more efficient and precise refinement procedure. In order to realize our framework algorithmically, we develop an algorithm for WCET estimation on ASTs, and we develop an interpolation-based counterexample-guided refinement scheme for ASTs. Furthermore, we extend our framework to obtain parametric estimates of WCET. We experimentally evaluate our approach on a set of examples from WCET benchmark suites and linear-algebra packages. We show that our analysis, with comparable effort, provides WCET estimates that in many cases significantly improve those computed by existing tools.","lang":"eng"}],"article_processing_charge":"No","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345"},{"day":"22","type":"journal_article","date_updated":"2024-12-18T12:23:56Z","date_created":"2024-10-15T11:20:54Z","status":"public","page":"1865-1875","publication":"Cell Reports","publisher":"Elsevier","doi":"10.1016/j.celrep.2015.08.025","volume":12,"scopus_import":"1","language":[{"iso":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"Yeast cells with DNA damage avoid respiration, presumably because products of oxidative metabolism can be harmful to DNA. We show that DNA damage inhibits the activity of the Snf1 (AMP-activated) protein kinase (AMPK), which activates expression of genes required for respiration. Glucose and DNA damage upregulate SUMOylation of Snf1, catalyzed by the SUMO E3 ligase Mms21, which inhibits SNF1 activity. The DNA damage checkpoint kinases Mec1/ATR and Tel1/ATM, as well as the nutrient-sensing protein kinase A (PKA), regulate Mms21 activity toward Snf1. Mec1 and Tel1 are required for two SNF1-regulated processes—glucose sensing and ADH2 gene expression—even without exogenous genotoxic stress. Our results imply that inhibition of Snf1 by SUMOylation is a mechanism by which cells lower their respiration in response to DNA damage. This raises the possibility that activation of DNA damage checkpoint mechanisms could contribute to aerobic fermentation (Warburg effect), a hallmark of cancer cells."}],"article_processing_charge":"No","publication_identifier":{"issn":["2211-1247"]},"_id":"18365","title":"Cross-talk between carbon cetabolism and the DNA camage response in S. cerevisiae","quality_controlled":"1","intvolume":"        12","extern":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.celrep.2015.08.025"}],"oa":1,"citation":{"ama":"Simpson-Lavy KJ, Bronstein AM, Kupiec M, Johnston M. Cross-talk between carbon cetabolism and the DNA camage response in S. cerevisiae. <i>Cell Reports</i>. 2015;12(11):1865-1875. doi:<a href=\"https://doi.org/10.1016/j.celrep.2015.08.025\">10.1016/j.celrep.2015.08.025</a>","ieee":"K. J. Simpson-Lavy, A. M. Bronstein, M. Kupiec, and M. Johnston, “Cross-talk between carbon cetabolism and the DNA camage response in S. cerevisiae,” <i>Cell Reports</i>, vol. 12, no. 11. Elsevier, pp. 1865–1875, 2015.","apa":"Simpson-Lavy, K. J., Bronstein, A. M., Kupiec, M., &#38; Johnston, M. (2015). Cross-talk between carbon cetabolism and the DNA camage response in S. cerevisiae. <i>Cell Reports</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.celrep.2015.08.025\">https://doi.org/10.1016/j.celrep.2015.08.025</a>","mla":"Simpson-Lavy, Kobi J., et al. “Cross-Talk between Carbon Cetabolism and the DNA Camage Response in S. Cerevisiae.” <i>Cell Reports</i>, vol. 12, no. 11, Elsevier, 2015, pp. 1865–75, doi:<a href=\"https://doi.org/10.1016/j.celrep.2015.08.025\">10.1016/j.celrep.2015.08.025</a>.","short":"K.J. Simpson-Lavy, A.M. Bronstein, M. Kupiec, M. Johnston, Cell Reports 12 (2015) 1865–1875.","chicago":"Simpson-Lavy, Kobi J., Alex M. Bronstein, Martin Kupiec, and Mark Johnston. “Cross-Talk between Carbon Cetabolism and the DNA Camage Response in S. Cerevisiae.” <i>Cell Reports</i>. Elsevier, 2015. <a href=\"https://doi.org/10.1016/j.celrep.2015.08.025\">https://doi.org/10.1016/j.celrep.2015.08.025</a>.","ista":"Simpson-Lavy KJ, Bronstein AM, Kupiec M, Johnston M. 2015. Cross-talk between carbon cetabolism and the DNA camage response in S. cerevisiae. Cell Reports. 12(11), 1865–1875."},"issue":"11","month":"09","author":[{"last_name":"Simpson-Lavy","first_name":"Kobi J.","full_name":"Simpson-Lavy, Kobi J."},{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","orcid":"0000-0001-9699-8730","first_name":"Alexander","last_name":"Bronstein","full_name":"Bronstein, Alexander"},{"full_name":"Kupiec, Martin","last_name":"Kupiec","first_name":"Martin"},{"full_name":"Johnston, Mark","first_name":"Mark","last_name":"Johnston"}],"publication_status":"published","DOAJ_listed":"1","oa_version":"Published Version","year":"2015","date_published":"2015-09-22T00:00:00Z"},{"arxiv":1,"date_updated":"2025-09-23T10:50:18Z","type":"journal_article","day":"08","status":"public","date_created":"2018-12-11T11:54:17Z","publisher":"Cambridge University Press","ec_funded":1,"publication":"Journal of Fluid Mechanics","isi":1,"project":[{"grant_number":"306589","name":"Decoding the complexity of turbulence at its origin","_id":"25152F3A-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"doi":"10.1017/jfm.2015.184","external_id":{"isi":["000354190500003"],"arxiv":["1508.06559"]},"volume":770,"language":[{"iso":"eng"}],"article_number":"R3","scopus_import":"1","article_processing_charge":"No","abstract":[{"lang":"eng","text":"Transition to turbulence in straight pipes occurs in spite of the linear stability of the laminar Hagen-Poiseuille flow if both the amplitude of flow perturbations and the Reynolds number Re exceed a minimum threshold (subcritical transition). As the pipe curvature increases, centrifugal effects become important, modifying the basic flow as well as the most unstable linear modes. If the curvature (tube-to-coiling diameter d/D) is sufficiently large, a Hopf bifurcation (supercritical instability) is encountered before turbulence can be excited (subcritical instability). We trace the instability thresholds in the Re - d/D parameter space in the range 0.01 ≤ d/D\\ ≤ 0.1 by means of laser-Doppler velocimetry and determine the point where the subcritical and supercritical instabilities meet. Two different experimental set-ups are used: a closed system where the pipe forms an axisymmetric torus and an open system employing a helical pipe. Implications for the measurement of friction factors in curved pipes are discussed."}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","title":"Subcritical versus supercritical transition to turbulence in curved pipes","_id":"1837","intvolume":"       770","quality_controlled":"1","main_file_link":[{"url":"https://arxiv.org/abs/1508.06559","open_access":"1"}],"publist_id":"5265","department":[{"_id":"BjHo"}],"oa":1,"month":"04","issue":"5","citation":{"mla":"Kühnen, Jakob, et al. “Subcritical versus Supercritical Transition to Turbulence in Curved Pipes.” <i>Journal of Fluid Mechanics</i>, vol. 770, no. 5, R3, Cambridge University Press, 2015, doi:<a href=\"https://doi.org/10.1017/jfm.2015.184\">10.1017/jfm.2015.184</a>.","apa":"Kühnen, J., Braunshier, P., Schwegel, M., Kuhlmann, H., &#38; Hof, B. (2015). Subcritical versus supercritical transition to turbulence in curved pipes. <i>Journal of Fluid Mechanics</i>. Cambridge University Press. <a href=\"https://doi.org/10.1017/jfm.2015.184\">https://doi.org/10.1017/jfm.2015.184</a>","ieee":"J. Kühnen, P. Braunshier, M. Schwegel, H. Kuhlmann, and B. Hof, “Subcritical versus supercritical transition to turbulence in curved pipes,” <i>Journal of Fluid Mechanics</i>, vol. 770, no. 5. Cambridge University Press, 2015.","ama":"Kühnen J, Braunshier P, Schwegel M, Kuhlmann H, Hof B. Subcritical versus supercritical transition to turbulence in curved pipes. <i>Journal of Fluid Mechanics</i>. 2015;770(5). doi:<a href=\"https://doi.org/10.1017/jfm.2015.184\">10.1017/jfm.2015.184</a>","ista":"Kühnen J, Braunshier P, Schwegel M, Kuhlmann H, Hof B. 2015. Subcritical versus supercritical transition to turbulence in curved pipes. Journal of Fluid Mechanics. 770(5), R3.","chicago":"Kühnen, Jakob, P Braunshier, M Schwegel, Hendrik Kuhlmann, and Björn Hof. “Subcritical versus Supercritical Transition to Turbulence in Curved Pipes.” <i>Journal of Fluid Mechanics</i>. Cambridge University Press, 2015. <a href=\"https://doi.org/10.1017/jfm.2015.184\">https://doi.org/10.1017/jfm.2015.184</a>.","short":"J. Kühnen, P. Braunshier, M. Schwegel, H. Kuhlmann, B. Hof, Journal of Fluid Mechanics 770 (2015)."},"author":[{"id":"3A47AE32-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4312-0179","full_name":"Kühnen, Jakob","first_name":"Jakob","last_name":"Kühnen"},{"last_name":"Braunshier","first_name":"P","full_name":"Braunshier, P"},{"first_name":"M","last_name":"Schwegel","full_name":"Schwegel, M"},{"first_name":"Hendrik","last_name":"Kuhlmann","full_name":"Kuhlmann, Hendrik"},{"last_name":"Hof","first_name":"Björn","full_name":"Hof, Björn","orcid":"0000-0003-2057-2754","id":"3A374330-F248-11E8-B48F-1D18A9856A87"}],"corr_author":"1","article_type":"original","date_published":"2015-04-08T00:00:00Z","year":"2015","oa_version":"Preprint","publication_status":"published"},{"status":"public","date_created":"2024-10-15T11:20:54Z","type":"journal_article","day":"10","date_updated":"2024-11-12T08:54:37Z","publisher":"National Academy of Sciences","publication":"Proceedings of the National Academy of Sciences","page":"2942-2947","pmid":1,"volume":112,"doi":"10.1073/pnas.1401651112","external_id":{"pmid":["25713342"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","abstract":[{"text":"We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement. This computationally challenging problem is often relaxed as a convex quadratic program, in which the space of permutations is replaced by the space of doubly stochastic matrices. However, the applicability of such a relaxation is poorly understood. We define a broad class of friendly graphs characterized by an easily verifiable spectral property. We prove that for friendly graphs, the convex relaxation is guaranteed to find the exact isomorphism or certify its inexistence. This result is further extended to approximately isomorphic graphs, for which we develop an explicit bound on the amount of weight disagreement under which the relaxation is guaranteed to find the globally optimal approximate isomorphism. We also show that in many cases, the graph matching problem can be further harmlessly relaxed to a convex quadratic program with only n separable linear equality constraints, which is substantially more efficient than the standard relaxation involving 2n equality and n2 inequality constraints. Finally, we show that our results are still valid for unfriendly graphs if additional information in the form of seeds or attributes is allowed, with the latter satisfying an easy to verify spectral characteristic.","lang":"eng"}],"scopus_import":"1","language":[{"iso":"eng"}],"quality_controlled":"1","intvolume":"       112","publication_identifier":{"issn":["0027-8424"],"eissn":["1091-6490"]},"title":"On convex relaxation of graph isomorphism","_id":"18371","extern":"1","author":[{"full_name":"Aflalo, Yonathan","first_name":"Yonathan","last_name":"Aflalo"},{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","last_name":"Bronstein","first_name":"Alexander","full_name":"Bronstein, Alexander"},{"full_name":"Kimmel, Ron","first_name":"Ron","last_name":"Kimmel"}],"month":"03","citation":{"ista":"Aflalo Y, Bronstein AM, Kimmel R. 2015. On convex relaxation of graph isomorphism. Proceedings of the National Academy of Sciences. 112(10), 2942–2947.","short":"Y. Aflalo, A.M. Bronstein, R. Kimmel, Proceedings of the National Academy of Sciences 112 (2015) 2942–2947.","chicago":"Aflalo, Yonathan, Alex M. Bronstein, and Ron Kimmel. “On Convex Relaxation of Graph Isomorphism.” <i>Proceedings of the National Academy of Sciences</i>. National Academy of Sciences, 2015. <a href=\"https://doi.org/10.1073/pnas.1401651112\">https://doi.org/10.1073/pnas.1401651112</a>.","ama":"Aflalo Y, Bronstein AM, Kimmel R. On convex relaxation of graph isomorphism. <i>Proceedings of the National Academy of Sciences</i>. 2015;112(10):2942-2947. doi:<a href=\"https://doi.org/10.1073/pnas.1401651112\">10.1073/pnas.1401651112</a>","mla":"Aflalo, Yonathan, et al. “On Convex Relaxation of Graph Isomorphism.” <i>Proceedings of the National Academy of Sciences</i>, vol. 112, no. 10, National Academy of Sciences, 2015, pp. 2942–47, doi:<a href=\"https://doi.org/10.1073/pnas.1401651112\">10.1073/pnas.1401651112</a>.","apa":"Aflalo, Y., Bronstein, A. M., &#38; Kimmel, R. (2015). On convex relaxation of graph isomorphism. <i>Proceedings of the National Academy of Sciences</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1401651112\">https://doi.org/10.1073/pnas.1401651112</a>","ieee":"Y. Aflalo, A. M. Bronstein, and R. Kimmel, “On convex relaxation of graph isomorphism,” <i>Proceedings of the National Academy of Sciences</i>, vol. 112, no. 10. National Academy of Sciences, pp. 2942–2947, 2015."},"issue":"10","year":"2015","oa_version":"None","publication_status":"published","date_published":"2015-03-10T00:00:00Z","article_type":"original"},{"acknowledgement":"This work was supported by the Austrian Science Fund (FWF) through the research network RiSE (S11406-N23, S11407-N23) and grant nr. P23499-N23, by the European Commission through an ERC Start grant (279307: Graph Games) and project STANCE (317753), as well as by the German Research Foundation (DFG) through SFB/TR 14 AVACS and project ASDPS(JA 2357/2-1).","page":"517 - 532","publisher":"Springer","ec_funded":1,"date_updated":"2025-06-11T07:09:03Z","arxiv":1,"type":"conference","day":"01","status":"public","date_created":"2018-12-11T11:54:17Z","language":[{"iso":"eng"}],"scopus_import":"1","article_processing_charge":"No","abstract":[{"text":"Synthesis of program parts is particularly useful for concurrent systems. However, most approaches do not support common design tasks, like modifying a single process without having to re-synthesize or verify the whole system. Assume-guarantee synthesis (AGS) provides robustness against modifications of system parts, but thus far has been limited to the perfect information setting. This means that local variables cannot be hidden from other processes, which renders synthesis results cumbersome or even impossible to realize.We resolve this shortcoming by defining AGS under partial information. We analyze the complexity and decidability in different settings, showing that the problem has a high worstcase complexity and is undecidable in many interesting cases. Based on these observations, we present a pragmatic algorithm based on bounded synthesis, and demonstrate its practical applicability on several examples.","lang":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","project":[{"grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","call_identifier":"FWF","_id":"25832EC2-B435-11E9-9278-68D0E5697425"},{"_id":"2584A770-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P 23499-N23","name":"Modern Graph Algorithmic Techniques in Formal Verification"},{"call_identifier":"FP7","_id":"2581B60A-B435-11E9-9278-68D0E5697425","name":"Quantitative Graph Games: Theory and Applications","grant_number":"279307"}],"doi":"10.1007/978-3-662-46681-0_50","external_id":{"arxiv":["1411.4604"]},"volume":9035,"main_file_link":[{"url":"http://arxiv.org/abs/1411.4604","open_access":"1"}],"conference":{"end_date":"2015-04-18","start_date":"2015-04-11","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems","location":"London, United Kingdom"},"publist_id":"5264","department":[{"_id":"KrCh"}],"oa":1,"title":"Assume-guarantee synthesis for concurrent reactive programs with partial information","_id":"1838","intvolume":"      9035","alternative_title":["LNCS"],"date_published":"2015-01-01T00:00:00Z","year":"2015","publication_status":"published","oa_version":"Preprint","month":"01","citation":{"apa":"Bloem, R., Chatterjee, K., Jacobs, S., &#38; Könighofer, R. (2015). Assume-guarantee synthesis for concurrent reactive programs with partial information (Vol. 9035, pp. 517–532). Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_50\">https://doi.org/10.1007/978-3-662-46681-0_50</a>","ieee":"R. Bloem, K. Chatterjee, S. Jacobs, and R. Könighofer, “Assume-guarantee synthesis for concurrent reactive programs with partial information,” presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom, 2015, vol. 9035, pp. 517–532.","mla":"Bloem, Roderick, et al. <i>Assume-Guarantee Synthesis for Concurrent Reactive Programs with Partial Information</i>. Vol. 9035, Springer, 2015, pp. 517–32, doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_50\">10.1007/978-3-662-46681-0_50</a>.","ama":"Bloem R, Chatterjee K, Jacobs S, Könighofer R. Assume-guarantee synthesis for concurrent reactive programs with partial information. In: Vol 9035. Springer; 2015:517-532. doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_50\">10.1007/978-3-662-46681-0_50</a>","short":"R. Bloem, K. Chatterjee, S. Jacobs, R. Könighofer, in:, Springer, 2015, pp. 517–532.","chicago":"Bloem, Roderick, Krishnendu Chatterjee, Swen Jacobs, and Robert Könighofer. “Assume-Guarantee Synthesis for Concurrent Reactive Programs with Partial Information,” 9035:517–32. Springer, 2015. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_50\">https://doi.org/10.1007/978-3-662-46681-0_50</a>.","ista":"Bloem R, Chatterjee K, Jacobs S, Könighofer R. 2015. Assume-guarantee synthesis for concurrent reactive programs with partial information. TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 9035, 517–532."},"author":[{"last_name":"Bloem","first_name":"Roderick","full_name":"Bloem, Roderick"},{"last_name":"Chatterjee","first_name":"Krishnendu","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Swen","last_name":"Jacobs","full_name":"Jacobs, Swen"},{"first_name":"Robert","last_name":"Könighofer","full_name":"Könighofer, Robert"}]},{"citation":{"ama":"Litman R, Korman S, Bronstein AM, Avidan S. Inverting RANSAC: Global model detection via inlier rate estimation. In: <i>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</i>. IEEE; 2015. doi:<a href=\"https://doi.org/10.1109/cvpr.2015.7299161\">10.1109/cvpr.2015.7299161</a>","apa":"Litman, R., Korman, S., Bronstein, A. M., &#38; Avidan, S. (2015). Inverting RANSAC: Global model detection via inlier rate estimation. In <i>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</i>. Boston, MA, United States: IEEE. <a href=\"https://doi.org/10.1109/cvpr.2015.7299161\">https://doi.org/10.1109/cvpr.2015.7299161</a>","ieee":"R. Litman, S. Korman, A. M. Bronstein, and S. Avidan, “Inverting RANSAC: Global model detection via inlier rate estimation,” in <i>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</i>, Boston, MA, United States, 2015.","mla":"Litman, Roee, et al. “Inverting RANSAC: Global Model Detection via Inlier Rate Estimation.” <i>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</i>, 7299161, IEEE, 2015, doi:<a href=\"https://doi.org/10.1109/cvpr.2015.7299161\">10.1109/cvpr.2015.7299161</a>.","short":"R. Litman, S. Korman, A.M. Bronstein, S. Avidan, in:, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2015.","chicago":"Litman, Roee, Simon Korman, Alex M. Bronstein, and Shai Avidan. “Inverting RANSAC: Global Model Detection via Inlier Rate Estimation.” In <i>2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/cvpr.2015.7299161\">https://doi.org/10.1109/cvpr.2015.7299161</a>.","ista":"Litman R, Korman S, Bronstein AM, Avidan S. 2015. Inverting RANSAC: Global model detection via inlier rate estimation. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Conference on Computer Vision and Pattern Recognition, 7299161."},"month":"10","doi":"10.1109/cvpr.2015.7299161","author":[{"last_name":"Litman","first_name":"Roee","full_name":"Litman, Roee"},{"full_name":"Korman, Simon","first_name":"Simon","last_name":"Korman"},{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","first_name":"Alexander","last_name":"Bronstein"},{"full_name":"Avidan, Shai","last_name":"Avidan","first_name":"Shai"}],"article_number":"7299161","language":[{"iso":"eng"}],"scopus_import":"1","abstract":[{"text":"This work presents a novel approach for detecting inliers in a given set of correspondences (matches). It does so without explicitly identifying any consensus set, based on a method for inlier rate estimation (IRE). Given such an estimator for the inlier rate, we also present an algorithm that detects a globally optimal transformation. We provide a theoretical analysis of the IRE method using a stochastic generative model on the continuous spaces of matches and transformations. This model allows rigorous investigation of the limits of our IRE method for the case of 2D-translation, further giving bounds and insights for the more general case. Our theoretical analysis is validated empirically and is shown to hold in practice for the more general case of 2D-affinities. In addition, we show that the combined framework works on challenging cases of 2D-homography estimation, with very few and possibly noisy inliers, where RANSAC generally fails.","lang":"eng"}],"date_published":"2015-10-15T00:00:00Z","article_processing_charge":"No","oa_version":"None","publication_status":"published","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2015","_id":"18380","date_updated":"2024-12-04T14:06:06Z","title":"Inverting RANSAC: Global model detection via inlier rate estimation","day":"15","type":"conference","publication_identifier":{"eissn":["1063-6919"],"isbn":["9781467369640"]},"date_created":"2024-10-15T11:20:54Z","status":"public","quality_controlled":"1","extern":"1","conference":{"location":"Boston, MA, United States","name":"IEEE Conference on Computer Vision and Pattern Recognition","end_date":"2015-06-12","start_date":"2015-06-07"},"publication":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","publisher":"IEEE"},{"extern":"1","conference":{"location":"South Brisbane, QLD, Australia","name":"40th IEEE International Conference on Acoustics, Speech, and Signal Processing","end_date":"2015-04-24","start_date":"2015-04-19"},"publication":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","publisher":"IEEE","_id":"18387","title":"Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis","date_updated":"2024-12-04T14:01:05Z","day":"06","publication_identifier":{"eisbn":["9781467369978"],"eissn":["2379-190X"]},"type":"conference","date_created":"2024-10-15T11:20:54Z","status":"public","quality_controlled":"1","article_number":"7178678","language":[{"iso":"eng"}],"scopus_import":"1","date_published":"2015-08-06T00:00:00Z","abstract":[{"lang":"eng","text":"Sparse models in dictionary learning have been successfully applied in a wide variety of machine learning and computer vision problems, and have also recently been of increasing research interest. Another interesting related problem based on a linear equality constraint, namely the sparse null space problem (SNS), first appeared in 1986, and has since inspired results on sparse basis pursuit. In this paper, we investigate the relation between the SNS problem and the analysis dictionary learning problem, and show that the SNS problem plays a central role, and may be utilized to solve dictionary learning problems. Moreover, we propose an efficient algorithm of sparse null space basis pursuit, and extend it to a solution of analysis dictionary learning. Experimental results on numerical synthetic data and real-world data are further presented to validate the performance of our method."}],"article_processing_charge":"No","oa_version":"None","publication_status":"published","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2015","citation":{"ama":"Bian X, Krim H, Bronstein AM, Dai L. Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis. In: <i>2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. IEEE; 2015. doi:<a href=\"https://doi.org/10.1109/icassp.2015.7178678\">10.1109/icassp.2015.7178678</a>","ieee":"X. Bian, H. Krim, A. M. Bronstein, and L. Dai, “Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis,” in <i>2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, South Brisbane, QLD, Australia, 2015.","apa":"Bian, X., Krim, H., Bronstein, A. M., &#38; Dai, L. (2015). Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis. In <i>2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. South Brisbane, QLD, Australia: IEEE. <a href=\"https://doi.org/10.1109/icassp.2015.7178678\">https://doi.org/10.1109/icassp.2015.7178678</a>","mla":"Bian, Xiao, et al. “Sparse Null Space Basis Pursuit and Analysis Dictionary Learning for High-Dimensional Data Analysis.” <i>2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, 7178678, IEEE, 2015, doi:<a href=\"https://doi.org/10.1109/icassp.2015.7178678\">10.1109/icassp.2015.7178678</a>.","chicago":"Bian, Xiao, Hamid Krim, Alex M. Bronstein, and Liyi Dai. “Sparse Null Space Basis Pursuit and Analysis Dictionary Learning for High-Dimensional Data Analysis.” In <i>2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/icassp.2015.7178678\">https://doi.org/10.1109/icassp.2015.7178678</a>.","short":"X. Bian, H. Krim, A.M. Bronstein, L. Dai, in:, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2015.","ista":"Bian X, Krim H, Bronstein AM, Dai L. 2015. Sparse null space basis pursuit and analysis dictionary learning for high-dimensional data analysis. 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 40th IEEE International Conference on Acoustics, Speech, and Signal Processing, 7178678."},"month":"08","doi":"10.1109/icassp.2015.7178678","author":[{"last_name":"Bian","first_name":"Xiao","full_name":"Bian, Xiao"},{"last_name":"Krim","first_name":"Hamid","full_name":"Krim, Hamid"},{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","first_name":"Alexander","last_name":"Bronstein"},{"full_name":"Dai, Liyi","first_name":"Liyi","last_name":"Dai"}]},{"year":"2015","oa_version":"Preprint","publication_status":"published","date_published":"2015-01-01T00:00:00Z","author":[{"last_name":"Brázdil","first_name":"Tomáš","full_name":"Brázdil, Tomáš"},{"full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","last_name":"Chatterjee","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Forejt, Vojtěch","first_name":"Vojtěch","last_name":"Forejt"},{"full_name":"Kučera, Antonín","first_name":"Antonín","last_name":"Kučera"}],"month":"01","citation":{"mla":"Brázdil, Tomáš, et al. <i>Multigain: A Controller Synthesis Tool for MDPs with Multiple Mean-Payoff Objectives</i>. Vol. 9035, Springer, 2015, pp. 181–87, doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_12\">10.1007/978-3-662-46681-0_12</a>.","ieee":"T. Brázdil, K. Chatterjee, V. Forejt, and A. Kučera, “Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives,” vol. 9035. Springer, pp. 181–187, 2015.","apa":"Brázdil, T., Chatterjee, K., Forejt, V., &#38; Kučera, A. (2015). Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_12\">https://doi.org/10.1007/978-3-662-46681-0_12</a>","ama":"Brázdil T, Chatterjee K, Forejt V, Kučera A. Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. 2015;9035:181-187. doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_12\">10.1007/978-3-662-46681-0_12</a>","ista":"Brázdil T, Chatterjee K, Forejt V, Kučera A. 2015. Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives. 9035, 181–187.","chicago":"Brázdil, Tomáš, Krishnendu Chatterjee, Vojtěch Forejt, and Antonín Kučera. “Multigain: A Controller Synthesis Tool for MDPs with Multiple Mean-Payoff Objectives.” Lecture Notes in Computer Science. Springer, 2015. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_12\">https://doi.org/10.1007/978-3-662-46681-0_12</a>.","short":"T. Brázdil, K. Chatterjee, V. Forejt, A. Kučera, 9035 (2015) 181–187."},"oa":1,"publist_id":"5263","conference":{"location":"London, United Kingdom","start_date":"2015-04-11","end_date":"2015-04-18","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems"},"department":[{"_id":"KrCh"}],"main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1501.03093"}],"alternative_title":["LNCS"],"quality_controlled":"1","intvolume":"      9035","title":"Multigain: A controller synthesis tool for MDPs with multiple mean-payoff objectives","_id":"1839","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","abstract":[{"lang":"eng","text":"We present MultiGain, a tool to synthesize strategies for Markov decision processes (MDPs) with multiple mean-payoff objectives. Our models are described in PRISM, and our tool uses the existing interface and simulator of PRISM. Our tool extends PRISM by adding novel algorithms for multiple mean-payoff objectives, and also provides features such as (i) generating strategies and exploring them for simulation, and checking them with respect to other properties; and (ii) generating an approximate Pareto curve for two mean-payoff objectives. In addition, we present a new practical algorithm for the analysis of MDPs with multiple mean-payoff objectives under memoryless strategies."}],"scopus_import":"1","language":[{"iso":"eng"}],"volume":9035,"doi":"10.1007/978-3-662-46681-0_12","external_id":{"arxiv":["1501.03093"]},"project":[{"grant_number":"P 23499-N23","name":"Modern Graph Algorithmic Techniques in Formal Verification","_id":"2584A770-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","_id":"25832EC2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"name":"Quantitative Graph Games: Theory and Applications","grant_number":"279307","_id":"2581B60A-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"publisher":"Springer","ec_funded":1,"page":"181 - 187","status":"public","date_created":"2018-12-11T11:54:18Z","type":"conference","day":"01","series_title":"Lecture Notes in Computer Science","arxiv":1,"date_updated":"2025-06-11T07:09:21Z"},{"author":[{"full_name":"Geiger, Bernhard","first_name":"Bernhard","last_name":"Geiger"},{"orcid":"0000-0002-9041-0905","id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","last_name":"Petrov","first_name":"Tatjana","full_name":"Petrov, Tatjana"},{"last_name":"Kubin","first_name":"Gernot","full_name":"Kubin, Gernot"},{"full_name":"Koeppl, Heinz","first_name":"Heinz","last_name":"Koeppl"}],"citation":{"ama":"Geiger B, Petrov T, Kubin G, Koeppl H. Optimal Kullback-Leibler aggregation via information bottleneck. <i>IEEE Transactions on Automatic Control</i>. 2015;60(4):1010-1022. doi:<a href=\"https://doi.org/10.1109/TAC.2014.2364971\">10.1109/TAC.2014.2364971</a>","ieee":"B. Geiger, T. Petrov, G. Kubin, and H. Koeppl, “Optimal Kullback-Leibler aggregation via information bottleneck,” <i>IEEE Transactions on Automatic Control</i>, vol. 60, no. 4. IEEE, pp. 1010–1022, 2015.","apa":"Geiger, B., Petrov, T., Kubin, G., &#38; Koeppl, H. (2015). Optimal Kullback-Leibler aggregation via information bottleneck. <i>IEEE Transactions on Automatic Control</i>. IEEE. <a href=\"https://doi.org/10.1109/TAC.2014.2364971\">https://doi.org/10.1109/TAC.2014.2364971</a>","mla":"Geiger, Bernhard, et al. “Optimal Kullback-Leibler Aggregation via Information Bottleneck.” <i>IEEE Transactions on Automatic Control</i>, vol. 60, no. 4, IEEE, 2015, pp. 1010–22, doi:<a href=\"https://doi.org/10.1109/TAC.2014.2364971\">10.1109/TAC.2014.2364971</a>.","chicago":"Geiger, Bernhard, Tatjana Petrov, Gernot Kubin, and Heinz Koeppl. “Optimal Kullback-Leibler Aggregation via Information Bottleneck.” <i>IEEE Transactions on Automatic Control</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/TAC.2014.2364971\">https://doi.org/10.1109/TAC.2014.2364971</a>.","short":"B. Geiger, T. Petrov, G. Kubin, H. Koeppl, IEEE Transactions on Automatic Control 60 (2015) 1010–1022.","ista":"Geiger B, Petrov T, Kubin G, Koeppl H. 2015. Optimal Kullback-Leibler aggregation via information bottleneck. IEEE Transactions on Automatic Control. 60(4), 1010–1022."},"issue":"4","month":"04","publication_status":"published","oa_version":"Preprint","year":"2015","date_published":"2015-04-01T00:00:00Z","quality_controlled":"1","intvolume":"        60","publication_identifier":{"issn":["0018-9286"]},"_id":"1840","title":"Optimal Kullback-Leibler aggregation via information bottleneck","oa":1,"department":[{"_id":"CaGu"},{"_id":"ToHe"}],"publist_id":"5262","main_file_link":[{"url":"http://arxiv.org/abs/1304.6603","open_access":"1"}],"volume":60,"external_id":{"isi":["000351731600009"],"arxiv":["1304.6603"]},"doi":"10.1109/TAC.2014.2364971","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","abstract":[{"text":"In this paper, we present a method for reducing a regular, discrete-time Markov chain (DTMC) to another DTMC with a given, typically much smaller number of states. The cost of reduction is defined as the Kullback-Leibler divergence rate between a projection of the original process through a partition function and a DTMC on the correspondingly partitioned state space. Finding the reduced model with minimal cost is computationally expensive, as it requires an exhaustive search among all state space partitions, and an exact evaluation of the reduction cost for each candidate partition. Our approach deals with the latter problem by minimizing an upper bound on the reduction cost instead of minimizing the exact cost. The proposed upper bound is easy to compute and it is tight if the original chain is lumpable with respect to the partition. Then, we express the problem in the form of information bottleneck optimization, and propose using the agglomerative information bottleneck algorithm for searching a suboptimal partition greedily, rather than exhaustively. The theory is illustrated with examples and one application scenario in the context of modeling bio-molecular interactions.","lang":"eng"}],"article_processing_charge":"No","scopus_import":"1","language":[{"iso":"eng"}],"status":"public","date_created":"2018-12-11T11:54:18Z","day":"01","type":"journal_article","date_updated":"2025-09-23T09:45:33Z","arxiv":1,"isi":1,"publication":"IEEE Transactions on Automatic Control","publisher":"IEEE","page":"1010 - 1022","acknowledgement":"This work was supported by the Austrian Research Association under Project 06/12684, by the Swiss National Science Foundation (SNSF) under Grant PP00P2 128503/1, by the SystemsX.ch (the Swiss Inititative for Systems Biology), and by a SNSF Early Postdoc.Mobility Fellowship grant P2EZP2_148797.\r\n"},{"author":[{"full_name":"Menashe, Ohad","first_name":"Ohad","last_name":"Menashe"},{"last_name":"Bronstein","first_name":"Alexander","full_name":"Bronstein, Alexander","orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"}],"citation":{"ista":"Menashe O, Bronstein AM. 2015. Real-time compressed imaging of scattering volumes. 2014 IEEE International Conference on Image Processing (ICIP). IEEE International Conference on Image Processing, 7025264.","chicago":"Menashe, Ohad, and Alex M. Bronstein. “Real-Time Compressed Imaging of Scattering Volumes.” In <i>2014 IEEE International Conference on Image Processing (ICIP)</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/icip.2014.7025264\">https://doi.org/10.1109/icip.2014.7025264</a>.","short":"O. Menashe, A.M. Bronstein, in:, 2014 IEEE International Conference on Image Processing (ICIP), IEEE, 2015.","mla":"Menashe, Ohad, and Alex M. Bronstein. “Real-Time Compressed Imaging of Scattering Volumes.” <i>2014 IEEE International Conference on Image Processing (ICIP)</i>, 7025264, IEEE, 2015, doi:<a href=\"https://doi.org/10.1109/icip.2014.7025264\">10.1109/icip.2014.7025264</a>.","ieee":"O. Menashe and A. M. Bronstein, “Real-time compressed imaging of scattering volumes,” in <i>2014 IEEE International Conference on Image Processing (ICIP)</i>, Paris, France, 2015.","apa":"Menashe, O., &#38; Bronstein, A. M. (2015). Real-time compressed imaging of scattering volumes. In <i>2014 IEEE International Conference on Image Processing (ICIP)</i>. Paris, France: IEEE. <a href=\"https://doi.org/10.1109/icip.2014.7025264\">https://doi.org/10.1109/icip.2014.7025264</a>","ama":"Menashe O, Bronstein AM. Real-time compressed imaging of scattering volumes. In: <i>2014 IEEE International Conference on Image Processing (ICIP)</i>. IEEE; 2015. doi:<a href=\"https://doi.org/10.1109/icip.2014.7025264\">10.1109/icip.2014.7025264</a>"},"month":"01","doi":"10.1109/icip.2014.7025264","abstract":[{"lang":"eng","text":"We propose a method and a prototype imaging system for real-time reconstruction of volumetric piecewise-smooth scattering media. The volume is illuminated by a sequence of structured binary patterns emitted from a fan beam projector, and the scattered light is collected by a two-dimensional sensor, thus creating an under-complete set of compressed measurements. We show a fixed-complexity and latency reconstruction algorithm capable of estimating the scattering coefficients in real-time. We also show a simple greedy algorithm for learning the optimal illumination patterns. Our results demonstrate faithful reconstruction from highly compressed measurements. Furthermore, a method for compressed registration of the measured volume to a known template is presented, showing excellent alignment with just a single projection. Though our prototype system operates in visible light, the presented methodology is suitable for fast x-ray scattering imaging, in particular in real-time vascular medical imaging."}],"date_published":"2015-01-29T00:00:00Z","article_processing_charge":"No","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa_version":"None","publication_status":"published","year":"2015","article_number":"7025264","language":[{"iso":"eng"}],"scopus_import":"1","status":"public","date_created":"2024-10-15T11:20:54Z","quality_controlled":"1","_id":"18400","title":"Real-time compressed imaging of scattering volumes","date_updated":"2024-12-04T13:56:28Z","day":"29","publication_identifier":{"eisbn":["9781479957514"],"eissn":["2381-8549"]},"type":"conference","publication":"2014 IEEE International Conference on Image Processing (ICIP)","publisher":"IEEE","extern":"1","conference":{"location":"Paris, France","name":"IEEE International Conference on Image Processing","start_date":"2014-10-27","end_date":"2014-10-30"}},{"_id":"18401","title":"Intel realsense = Real low cost gaze","date_updated":"2024-12-05T08:13:05Z","day":"10","publication_identifier":{"eisbn":["9781479983391"]},"type":"conference","status":"public","date_created":"2024-10-15T11:20:54Z","quality_controlled":"1","extern":"1","conference":{"location":"Quebec City, QC, Canada","end_date":"2015-09-30","start_date":"2015-09-27","name":"IEEE International Conference on Image Processing"},"publication":"2015 IEEE International Conference on Image Processing (ICIP)","publisher":"IEEE","citation":{"mla":"Draelos, Mark, et al. “Intel Realsense = Real Low Cost Gaze.” <i>2015 IEEE International Conference on Image Processing (ICIP)</i>, 7351256, IEEE, 2015, doi:<a href=\"https://doi.org/10.1109/icip.2015.7351256\">10.1109/icip.2015.7351256</a>.","apa":"Draelos, M., Qiu, Q., Bronstein, A. M., &#38; Sapiro, G. (2015). Intel realsense = Real low cost gaze. In <i>2015 IEEE International Conference on Image Processing (ICIP)</i>. Quebec City, QC, Canada: IEEE. <a href=\"https://doi.org/10.1109/icip.2015.7351256\">https://doi.org/10.1109/icip.2015.7351256</a>","ieee":"M. Draelos, Q. Qiu, A. M. Bronstein, and G. Sapiro, “Intel realsense = Real low cost gaze,” in <i>2015 IEEE International Conference on Image Processing (ICIP)</i>, Quebec City, QC, Canada, 2015.","ama":"Draelos M, Qiu Q, Bronstein AM, Sapiro G. Intel realsense = Real low cost gaze. In: <i>2015 IEEE International Conference on Image Processing (ICIP)</i>. IEEE; 2015. doi:<a href=\"https://doi.org/10.1109/icip.2015.7351256\">10.1109/icip.2015.7351256</a>","ista":"Draelos M, Qiu Q, Bronstein AM, Sapiro G. 2015. Intel realsense = Real low cost gaze. 2015 IEEE International Conference on Image Processing (ICIP). IEEE International Conference on Image Processing, 7351256.","short":"M. Draelos, Q. Qiu, A.M. Bronstein, G. Sapiro, in:, 2015 IEEE International Conference on Image Processing (ICIP), IEEE, 2015.","chicago":"Draelos, Mark, Qiang Qiu, Alex M. Bronstein, and Guillermo Sapiro. “Intel Realsense = Real Low Cost Gaze.” In <i>2015 IEEE International Conference on Image Processing (ICIP)</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/icip.2015.7351256\">https://doi.org/10.1109/icip.2015.7351256</a>."},"month":"12","doi":"10.1109/icip.2015.7351256","author":[{"full_name":"Draelos, Mark","first_name":"Mark","last_name":"Draelos"},{"full_name":"Qiu, Qiang","last_name":"Qiu","first_name":"Qiang"},{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","last_name":"Bronstein","first_name":"Alexander"},{"last_name":"Sapiro","first_name":"Guillermo","full_name":"Sapiro, Guillermo"}],"article_number":"7351256","language":[{"iso":"eng"}],"scopus_import":"1","date_published":"2015-12-10T00:00:00Z","abstract":[{"text":"Intel's newly-announced low-cost RealSense 3D camera claims significantly better precision than other currently available low-cost platforms and is expected to become ubiquitous in laptops and mobile devices starting this year. In this paper, we demonstrate for the first time that the RealSense camera can be easily converted into a real low-cost gaze tracker. Gaze has become increasingly relevant as an input for human-computer interaction due to its association with attention. It is also critical in clinical mental health diagnosis. We present a novel 3D gaze and fixation tracker based on the eye surface geometry captured with the RealSense 3D camera. First, eye surface 3D point clouds are segmented to extract the pupil center and iris using registered infrared images. With non-ellipsoid eye surface and single fixation point assumptions, pupil centers and iris normal vectors are used to first estimate gaze (for each eye), and then a single fixation point for both eyes simultaneously using a RANSAC-based approach. With a simple learned bias field correction model, the fixation tracker demonstrates mean error of approximately 1 cm at 20-30 cm, which is sufficiently adequate for gaze and fixation tracking in human-computer interaction and mental health diagnosis applications.","lang":"eng"}],"article_processing_charge":"No","publication_status":"published","oa_version":"None","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2015"},{"author":[{"first_name":"Vladimir","last_name":"Kolmogorov","full_name":"Kolmogorov, Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87"}],"month":"05","citation":{"apa":"Kolmogorov, V. (2015). A new look at reweighted message passing. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE. <a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">https://doi.org/10.1109/TPAMI.2014.2363465</a>","ieee":"V. Kolmogorov, “A new look at reweighted message passing,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 5. IEEE, pp. 919–930, 2015.","mla":"Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 5, IEEE, 2015, pp. 919–30, doi:<a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">10.1109/TPAMI.2014.2363465</a>.","ama":"Kolmogorov V. A new look at reweighted message passing. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2015;37(5):919-930. doi:<a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">10.1109/TPAMI.2014.2363465</a>","chicago":"Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">https://doi.org/10.1109/TPAMI.2014.2363465</a>.","short":"V. Kolmogorov, IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2015) 919–930.","ista":"Kolmogorov V. 2015. A new look at reweighted message passing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(5), 919–930."},"issue":"5","related_material":{"record":[{"relation":"earlier_version","status":"public","id":"2273"}]},"OA_place":"repository","date_published":"2015-05-01T00:00:00Z","year":"2015","publication_status":"published","oa_version":"Preprint","corr_author":"1","article_type":"original","intvolume":"        37","quality_controlled":"1","title":"A new look at reweighted message passing","_id":"1841","oa":1,"main_file_link":[{"url":"http://arxiv.org/abs/1309.5655","open_access":"1"}],"publist_id":"5261","department":[{"_id":"VlKo"}],"volume":37,"project":[{"call_identifier":"FP7","_id":"25FBA906-B435-11E9-9278-68D0E5697425","grant_number":"616160","name":"Discrete Optimization in Computer Vision: Theory and Practice"}],"doi":"10.1109/TPAMI.2014.2363465","external_id":{"isi":["000352533000002"],"arxiv":["1309.5655"]},"article_processing_charge":"No","abstract":[{"lang":"eng","text":"We propose a new family of message passing techniques for MAP estimation in graphical models which we call Sequential Reweighted Message Passing (SRMP). Special cases include well-known techniques such as Min-Sum Diffusion (MSD) and a faster Sequential Tree-Reweighted Message Passing (TRW-S). Importantly, our derivation is simpler than the original derivation of TRW-S, and does not involve a decomposition into trees. This allows easy generalizations. The new family of algorithms can be viewed as a generalization of TRW-S from pairwise to higher-order graphical models. We test SRMP on several real-world problems with promising results."}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"OA_type":"green","scopus_import":"1","date_created":"2018-12-11T11:54:18Z","status":"public","date_updated":"2025-09-22T14:33:14Z","arxiv":1,"type":"journal_article","day":"01","ec_funded":1,"publisher":"IEEE","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","isi":1,"page":"919 - 930"},{"publisher":"IEEE","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","pmid":1,"page":"1821-1833","status":"public","date_created":"2024-10-15T11:20:55Z","date_updated":"2024-12-18T11:40:35Z","arxiv":1,"type":"journal_article","day":"01","article_processing_charge":"No","abstract":[{"text":"Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with parsimony-promoting terms. The inherently sequential structure and data-dependent complexity and latency of iterative optimization constitute a major limitation in many applications requiring real-time performance or involving large-scale data. Another limitation encountered by these modeling techniques is the difficulty of their inclusion in discriminative learning scenarios. In this work, we propose to move the emphasis from the model to the pursuit algorithm, and develop a process-centric view of parsimonious modeling, in which a learned deterministic fixed-complexity pursuit process is used in lieu of iterative optimization. We show a principled way to construct learnable pursuit process architectures for structured sparse and robust low rank models, derived from the iteration of proximal descent algorithms. These architectures learn to approximate the exact parsimonious representation at a fraction of the complexity of the standard optimization methods. We also show that appropriate training regimes allow to naturally extend parsimonious models to discriminative settings. State-of-the-art results are demonstrated on several challenging problems in image and audio processing with several orders of magnitude speed-up compared to the exact optimization algorithms.","lang":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"scopus_import":"1","volume":37,"doi":"10.1109/tpami.2015.2392779","external_id":{"pmid":["26353129"],"arxiv":["1212.3631"]},"oa":1,"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1212.3631","open_access":"1"}],"extern":"1","intvolume":"        37","quality_controlled":"1","title":"Learning efficient sparse and low rank models","_id":"18415","publication_identifier":{"issn":["0162-8828"],"eissn":["1939-3539"]},"date_published":"2015-09-01T00:00:00Z","year":"2015","oa_version":"Preprint","publication_status":"published","author":[{"full_name":"Sprechmann, P.","last_name":"Sprechmann","first_name":"P."},{"full_name":"Bronstein, Alexander","last_name":"Bronstein","first_name":"Alexander","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","orcid":"0000-0001-9699-8730"},{"first_name":"G.","last_name":"Sapiro","full_name":"Sapiro, G."}],"month":"09","citation":{"mla":"Sprechmann, P., et al. “Learning Efficient Sparse and Low Rank Models.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 9, IEEE, 2015, pp. 1821–33, doi:<a href=\"https://doi.org/10.1109/tpami.2015.2392779\">10.1109/tpami.2015.2392779</a>.","apa":"Sprechmann, P., Bronstein, A. M., &#38; Sapiro, G. (2015). Learning efficient sparse and low rank models. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE. <a href=\"https://doi.org/10.1109/tpami.2015.2392779\">https://doi.org/10.1109/tpami.2015.2392779</a>","ieee":"P. Sprechmann, A. M. Bronstein, and G. Sapiro, “Learning efficient sparse and low rank models,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 9. IEEE, pp. 1821–1833, 2015.","ama":"Sprechmann P, Bronstein AM, Sapiro G. Learning efficient sparse and low rank models. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2015;37(9):1821-1833. doi:<a href=\"https://doi.org/10.1109/tpami.2015.2392779\">10.1109/tpami.2015.2392779</a>","ista":"Sprechmann P, Bronstein AM, Sapiro G. 2015. Learning efficient sparse and low rank models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(9), 1821–1833.","short":"P. Sprechmann, A.M. Bronstein, G. Sapiro, IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2015) 1821–1833.","chicago":"Sprechmann, P., Alex M. Bronstein, and G. Sapiro. “Learning Efficient Sparse and Low Rank Models.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/tpami.2015.2392779\">https://doi.org/10.1109/tpami.2015.2392779</a>."},"issue":"9"},{"intvolume":"        37","quality_controlled":"1","_id":"18416","title":"Multimodal manifold snalysis by simultaneous diagonalization of Laplacians","publication_identifier":{"eissn":["1939-3539"],"issn":["0162-8828"]},"extern":"1","author":[{"full_name":"Eynard, Davide","first_name":"Davide","last_name":"Eynard"},{"full_name":"Kovnatsky, Artiom","first_name":"Artiom","last_name":"Kovnatsky"},{"last_name":"Bronstein","first_name":"Michael M.","full_name":"Bronstein, Michael M."},{"last_name":"Glashoff","first_name":"Klaus","full_name":"Glashoff, Klaus"},{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","last_name":"Bronstein","first_name":"Alexander"}],"issue":"12","citation":{"ieee":"D. Eynard, A. Kovnatsky, M. M. Bronstein, K. Glashoff, and A. M. Bronstein, “Multimodal manifold snalysis by simultaneous diagonalization of Laplacians,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 12. IEEE, pp. 2505–2517, 2015.","apa":"Eynard, D., Kovnatsky, A., Bronstein, M. M., Glashoff, K., &#38; Bronstein, A. M. (2015). Multimodal manifold snalysis by simultaneous diagonalization of Laplacians. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE. <a href=\"https://doi.org/10.1109/tpami.2015.2408348\">https://doi.org/10.1109/tpami.2015.2408348</a>","mla":"Eynard, Davide, et al. “Multimodal Manifold Snalysis by Simultaneous Diagonalization of Laplacians.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 12, IEEE, 2015, pp. 2505–17, doi:<a href=\"https://doi.org/10.1109/tpami.2015.2408348\">10.1109/tpami.2015.2408348</a>.","ama":"Eynard D, Kovnatsky A, Bronstein MM, Glashoff K, Bronstein AM. Multimodal manifold snalysis by simultaneous diagonalization of Laplacians. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2015;37(12):2505-2517. doi:<a href=\"https://doi.org/10.1109/tpami.2015.2408348\">10.1109/tpami.2015.2408348</a>","short":"D. Eynard, A. Kovnatsky, M.M. Bronstein, K. Glashoff, A.M. Bronstein, IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2015) 2505–2517.","chicago":"Eynard, Davide, Artiom Kovnatsky, Michael M. Bronstein, Klaus Glashoff, and Alex M. Bronstein. “Multimodal Manifold Snalysis by Simultaneous Diagonalization of Laplacians.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/tpami.2015.2408348\">https://doi.org/10.1109/tpami.2015.2408348</a>.","ista":"Eynard D, Kovnatsky A, Bronstein MM, Glashoff K, Bronstein AM. 2015. Multimodal manifold snalysis by simultaneous diagonalization of Laplacians. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(12), 2505–2517."},"month":"12","date_published":"2015-12-01T00:00:00Z","publication_status":"published","oa_version":"None","year":"2015","date_created":"2024-10-15T11:20:55Z","status":"public","date_updated":"2024-12-12T14:08:46Z","day":"01","type":"journal_article","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","publisher":"IEEE","pmid":1,"page":"2505-2517","volume":37,"external_id":{"pmid":["26539854"]},"doi":"10.1109/tpami.2015.2408348","abstract":[{"text":"We construct an extension of spectral and diffusion geometry to multiple modalities through simultaneous diagonalization of Laplacian matrices. This naturally extends classical data analysis tools based on spectral geometry, such as diffusion maps and spectral clustering. We provide several synthetic and real examples of manifold learning, object classification, and clustering, showing that the joint spectral geometry better captures the inherent structure of multi-modal data. We also show the relation of many previous approaches for multimodal manifold analysis to our framework.","lang":"eng"}],"article_processing_charge":"No","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"scopus_import":"1"},{"intvolume":"        34","quality_controlled":"1","_id":"18424","title":"Probably approximately symmetric: Fast rigid symmetry detection with global guarantees","publication_identifier":{"eissn":["1467-8659"],"issn":["0167-7055"]},"oa":1,"extern":"1","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1403.6637","open_access":"1"}],"author":[{"last_name":"Korman","first_name":"Simon","full_name":"Korman, Simon"},{"last_name":"Litman","first_name":"Roee","full_name":"Litman, Roee"},{"first_name":"Shai","last_name":"Avidan","full_name":"Avidan, Shai"},{"orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","first_name":"Alexander","last_name":"Bronstein","full_name":"Bronstein, Alexander"}],"issue":"1","citation":{"ista":"Korman S, Litman R, Avidan S, Bronstein AM. 2015. Probably approximately symmetric: Fast rigid symmetry detection with global guarantees. Computer Graphics Forum. 34(1), 2–13.","chicago":"Korman, Simon, Roee Litman, Shai Avidan, and Alex M. Bronstein. “Probably Approximately Symmetric: Fast Rigid Symmetry Detection with Global Guarantees.” <i>Computer Graphics Forum</i>. Wiley, 2015. <a href=\"https://doi.org/10.1111/cgf.12454\">https://doi.org/10.1111/cgf.12454</a>.","short":"S. Korman, R. Litman, S. Avidan, A.M. Bronstein, Computer Graphics Forum 34 (2015) 2–13.","ama":"Korman S, Litman R, Avidan S, Bronstein AM. Probably approximately symmetric: Fast rigid symmetry detection with global guarantees. <i>Computer Graphics Forum</i>. 2015;34(1):2-13. doi:<a href=\"https://doi.org/10.1111/cgf.12454\">10.1111/cgf.12454</a>","mla":"Korman, Simon, et al. “Probably Approximately Symmetric: Fast Rigid Symmetry Detection with Global Guarantees.” <i>Computer Graphics Forum</i>, vol. 34, no. 1, Wiley, 2015, pp. 2–13, doi:<a href=\"https://doi.org/10.1111/cgf.12454\">10.1111/cgf.12454</a>.","ieee":"S. Korman, R. Litman, S. Avidan, and A. M. Bronstein, “Probably approximately symmetric: Fast rigid symmetry detection with global guarantees,” <i>Computer Graphics Forum</i>, vol. 34, no. 1. Wiley, pp. 2–13, 2015.","apa":"Korman, S., Litman, R., Avidan, S., &#38; Bronstein, A. M. (2015). Probably approximately symmetric: Fast rigid symmetry detection with global guarantees. <i>Computer Graphics Forum</i>. Wiley. <a href=\"https://doi.org/10.1111/cgf.12454\">https://doi.org/10.1111/cgf.12454</a>"},"month":"02","date_published":"2015-02-01T00:00:00Z","publication_status":"published","oa_version":"Preprint","year":"2015","status":"public","date_created":"2024-10-15T11:20:55Z","date_updated":"2024-12-19T10:12:48Z","arxiv":1,"day":"01","type":"journal_article","publication":"Computer Graphics Forum","publisher":"Wiley","page":"2-13","volume":34,"external_id":{"arxiv":["1403.6637"]},"doi":"10.1111/cgf.12454","abstract":[{"lang":"eng","text":"We present a fast algorithm for global rigid symmetry detection with approximation guarantees. The algorithm is guaranteed to find the best approximate symmetry of a given shape, to within a user-specified threshold, with very high probability. Our method uses a carefully designed sampling of the transformation space, where each transformation is efficiently evaluated using a sublinear algorithm. We prove that the density of the sampling depends on the total variation of the shape, allowing us to derive formal bounds on the algorithm's complexity and approximation quality. We further investigate different volumetric shape representations (in the form of truncated distance transforms), and in such a way control the total variation of the shape and hence the sampling density and the runtime of the algorithm. A comprehensive set of experiments assesses the proposed method, including an evaluation on the eight categories of the COSEG data set. This is the first large-scale evaluation of any symmetry detection technique that we are aware of."}],"article_processing_charge":"No","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"scopus_import":"1"}]