Christoph Lampert

134 Publications

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[134]
2025 | Published | Conference Paper | IST-REx-ID: 20296 | OA
F. Kresse, E. Yu, C. Lampert, and T. A. Henzinger, “Logic gate neural networks are good for verification,” in 2nd International Conferenceon Neuro-Symbolic Systems, Philadephia, PA, United States, 2025, vol. 288.
[Published Version] View | Files available | arXiv
 
[133]
2025 | Published | Conference Paper | IST-REx-ID: 20455 | OA
B. Prach and C. Lampert, “Intriguing properties of robust classification,” in 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Nashville, TN, United States, 2025, pp. 660–669.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[132]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
J. A. Scott, H. Zakerinia, and C. Lampert, “PEFLL: Personalized federated learning by learning to learn,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
[Published Version] View | Files available | arXiv
 
[131]
2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
H. Zakerinia, A. Behjati, and C. Lampert, “More flexible PAC-Bayesian meta-learning by learning learning algorithms,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 58122–58139.
[Published Version] View | Download Published Version (ext.) | arXiv
 
[130]
2024 | Epub ahead of print | Journal Article | IST-REx-ID: 12662 | OA
P. Súkeník and C. Lampert, “Generalization in multi-objective machine learning,” Neural Computing and Applications. Springer Nature, 2024.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[129]
2024 | Published | Preprint | IST-REx-ID: 19063 | OA
E. Zverev, S. Abdelnabi, S. Tabesh, M. Fritz, and C. Lampert, “Can LLMs separate instructions from data? And what do we even mean by that?,” arXiv. 2024.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[128]
2024 | Published | Journal Article | IST-REx-ID: 19408 | OA
E. Verwimp et al., “Continual learning: Applications and the road forward,” Transactions on Machine Learning Research, vol. 2024. Transactions on Machine Learning Research, 2024.
[Published Version] View | Files available | arXiv
 
[127]
2024 | Published | Conference Paper | IST-REx-ID: 18875 | OA
N. Kalinin and C. Lampert, “Banded square root matrix factorization for differentially private model training,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version] View | Files available | arXiv
 
[126]
2024 | Published | Conference Paper | IST-REx-ID: 18891 | OA
P. Súkeník, C. Lampert, and M. Mondelli, “Neural collapse versus low-rank bias: Is deep neural collapse really optimal?,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version] View | Files available | arXiv
 
[125]
2024 | Published | Journal Article | IST-REx-ID: 18856 | OA
K. Lutsai and C. Lampert, “Predicting the geolocation of tweets using transformer models on customized data,” Journal of Spatial Information Science, no. 29. University of Maine, pp. 69–99, 2024.
[Published Version] View | Files available | DOI
 
[124]
2024 | Published | Conference Paper | IST-REx-ID: 17426 | OA
B. Prach, F. Brau, G. Buttazzo, and C. Lampert, “1-Lipschitz layers compared: Memory, speed, and certifiable robustness,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, United States, 2024, pp. 24574–24583.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[123]
2024 | Draft | Preprint | IST-REx-ID: 18874 | OA
B. Prach and C. Lampert, “Intriguing properties of robust classification,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[122]
2023 | Published | Conference Paper | IST-REx-ID: 14410
P. Tomaszewska and C. Lampert, “On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift,” in International Workshop on Reproducible Research in Pattern Recognition, Montreal, Canada, 2023, vol. 14068, pp. 67–73.
View | DOI
 
[121]
2023 | Published | Conference Paper | IST-REx-ID: 12660 | OA
J. A. Scott, M. X. Yeo, and C. Lampert, “Cross-client label propagation for transductive and semi-supervised federated learning,” in Transactions in Machine Learning, 2023.
[Preprint] View | Files available | arXiv
 
[120]
2023 | Published | Conference Paper | IST-REx-ID: 13053 | OA
A. Krumes, A. Vladu, E. Kurtic, C. Lampert, and D.-A. Alistarh, “CrAM: A Compression-Aware Minimizer,” in 11th International Conference on Learning Representations , Kigali, Rwanda , 2023.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[119]
2023 | Published | Conference Paper | IST-REx-ID: 14921 | OA
P. Súkeník, M. Mondelli, and C. Lampert, “Deep neural collapse is provably optimal for the deep unconstrained features model,” in 37th Annual Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[118]
2023 | Draft | Preprint | IST-REx-ID: 15039 | OA
B. Prach and C. Lampert, “1-Lipschitz neural networks are more expressive with N-activations,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[117]
2022 | Published | Conference Paper | IST-REx-ID: 13241 | OA
N. H. Konstantinov and C. Lampert, “On the impossibility of fairness-aware learning from corrupted data,” in Proceedings of Machine Learning Research, 2022, vol. 171, pp. 59–83.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[116]
2022 | Published | Conference Paper | IST-REx-ID: 12161 | OA
P. Tomaszewska and C. Lampert, “Lightweight conditional model extrapolation for streaming data under class-prior shift,” in 26th International Conference on Pattern Recognition, Montreal, Canada, 2022, vol. 2022, pp. 2128–2134.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[115]
2022 | Published | Conference Paper | IST-REx-ID: 10752
J. Lampert and C. Lampert, “Overcoming rare-language discrimination in multi-lingual sentiment analysis,” in 2021 IEEE International Conference on Big Data, Orlando, FL, United States, 2022, pp. 5185–5192.
View | DOI | WoS
 
[114]
2022 | Published | Journal Article | IST-REx-ID: 10802 | OA
N. H. Konstantinov and C. Lampert, “Fairness-aware PAC learning from corrupted data,” Journal of Machine Learning Research, vol. 23. ML Research Press, pp. 1–60, 2022.
[Published Version] View | Files available | arXiv
 
[113]
2022 | Published | Journal Article | IST-REx-ID: 12495 | OA
E. B. Iofinova, N. H. Konstantinov, and C. Lampert, “FLEA: Provably robust fair multisource learning from unreliable training data,” Transactions on Machine Learning Research. ML Research Press, 2022.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[112]
2022 | Published | Conference Paper | IST-REx-ID: 11839 | OA
B. Prach and C. Lampert, “Almost-orthogonal layers for efficient general-purpose Lipschitz networks,” in Computer Vision – ECCV 2022, Tel Aviv, Israel, 2022, vol. 13681, pp. 350–365.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[111]
2021 | Published | Book Chapter | IST-REx-ID: 14987
C. Lampert, “Zero-Shot Learning,” in Computer Vision, 2nd ed., K. Ikeuchi, Ed. Cham: Springer, 2021, pp. 1395–1397.
View | DOI
 
[110]
2021 | Draft | Preprint | IST-REx-ID: 10803 | OA
N. H. Konstantinov and C. Lampert, “Fairness through regularization for learning to rank,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[109]
2021 | Published | Conference Paper | IST-REx-ID: 9416 | OA
M. Phuong and C. Lampert, “The inductive bias of ReLU networks on orthogonally separable data,” in 9th International Conference on Learning Representations, Virtual, 2021.
[Published Version] View | Files available | Download Published Version (ext.)
 
[108]
2021 | Published | Conference Paper | IST-REx-ID: 9210 | OA
V. Volhejn and C. Lampert, “Does SGD implicitly optimize for smoothness?,” in 42nd German Conference on Pattern Recognition, Tübingen, Germany, 2021, vol. 12544, pp. 246–259.
[Submitted Version] View | Files available | DOI | WoS
 
[107]
2020 | Published | Conference Paper | IST-REx-ID: 8186 | OA
P. M. Henderson, V. Tsiminaki, and C. Lampert, “Leveraging 2D data to learn textured 3D mesh generation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Virtual, 2020, pp. 7498–7507.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | arXiv
 
[106]
2020 | Submitted | Preprint | IST-REx-ID: 8063 | OA
T. Anciukevicius, C. Lampert, and P. M. Henderson, “Object-centric image generation with factored depths, locations, and appearances,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[105]
2020 | Published | Conference Paper | IST-REx-ID: 7936 | OA
A. Royer and C. Lampert, “Localizing grouped instances for efficient detection in low-resource scenarios,” in IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, CO, United States, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[104]
2020 | Published | Journal Article | IST-REx-ID: 6944 | OA
R. Sun and C. Lampert, “KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications,” International Journal of Computer Vision, vol. 128, no. 4. Springer Nature, pp. 970–995, 2020.
[Published Version] View | Files available | DOI | WoS
 
[103]
2020 | Published | Conference Paper | IST-REx-ID: 8188 | OA
P. M. Henderson and C. Lampert, “Unsupervised object-centric video generation and decomposition in 3D,” in 34th Conference on Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 3106–3117.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[102]
2020 | Published | Conference Paper | IST-REx-ID: 8724 | OA
N. H. Konstantinov, E. Frantar, D.-A. Alistarh, and C. Lampert, “On the sample complexity of adversarial multi-source PAC learning,” in Proceedings of the 37th International Conference on Machine Learning, Online, 2020, vol. 119, pp. 5416–5425.
[Published Version] View | Files available | arXiv
 
[101]
2020 | Published | Conference Paper | IST-REx-ID: 7481 | OA
M. Phuong and C. Lampert, “Functional vs. parametric equivalence of ReLU networks,” in 8th International Conference on Learning Representations, Online, 2020.
[Published Version] View | Files available
 
[100]
2020 | Published | Conference Paper | IST-REx-ID: 7937 | OA
A. Royer and C. Lampert, “A flexible selection scheme for minimum-effort transfer learning,” in 2020 IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, CO, United States, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[99]
2019 | Published | Book (Editor) | IST-REx-ID: 7171
K. Kersting, C. Lampert, and C. Rothkopf, Eds., Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt, 1st ed. Wiesbaden: Springer Nature, 2019.
View | Files available | DOI
 
[98]
2019 | Published | Journal Article | IST-REx-ID: 6554 | OA
Y. Xian, C. Lampert, B. Schiele, and Z. Akata, “Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9. Institute of Electrical and Electronics Engineers, pp. 2251–2265, 2019.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[97]
2019 | Published | Conference Paper | IST-REx-ID: 7640 | OA
A. Kolesnikov, A. Kuznetsova, C. Lampert, and V. Ferrari, “Detecting visual relationships using box attention,” in Proceedings of the 2019 International Conference on Computer Vision Workshop, Seoul, South Korea, 2019.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[96]
2019 | Published | Conference Paper | IST-REx-ID: 6482 | OA
R. Sun and C. Lampert, “KS(conf): A light-weight test if a ConvNet operates outside of Its specifications,” presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany, 2019, vol. 11269, pp. 244–259.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[95]
2019 | Published | Conference Paper | IST-REx-ID: 6590 | OA
N. H. Konstantinov and C. Lampert, “Robust learning from untrusted sources,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA, 2019, vol. 97, pp. 3488–3498.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[94]
2019 | Published | Conference Paper | IST-REx-ID: 6942 | OA
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, and V. Toman, “Strategy representation by decision trees with linear classifiers,” in 16th International Conference on Quantitative Evaluation of Systems, Glasgow, United Kingdom, 2019, vol. 11785, pp. 109–128.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[93]
2019 | Published | Conference Paper | IST-REx-ID: 6569 | OA
M. Phuong and C. Lampert, “Towards understanding knowledge distillation,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, United States, 2019, vol. 97, pp. 5142–5151.
[Published Version] View | Files available
 
[92]
2019 | Published | Conference Paper | IST-REx-ID: 7479 | OA
M. Phuong and C. Lampert, “Distillation-based training for multi-exit architectures,” in IEEE International Conference on Computer Vision, Seoul, Korea, 2019, vol. 2019–October, pp. 1355–1364.
[Submitted Version] View | Files available | DOI | WoS
 
[91]
2018 | Published | Conference Paper | IST-REx-ID: 10882 | OA
J. Uijlings, K. Konyushkova, C. Lampert, and V. Ferrari, “Learning intelligent dialogs for bounding box annotation,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, United States, 2018, pp. 9175–9184.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[90]
2018 | Published | Journal Article | IST-REx-ID: 321 | OA
T. Darrell, C. Lampert, N. Sebe, Y. Wu, and Y. Yan, “Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5. IEEE, pp. 1029–1031, 2018.
[Published Version] View | Files available | DOI | WoS
 
[89]
2018 | Published | Conference Paper | IST-REx-ID: 6012 | OA
S. Sahoo, C. Lampert, and G. S. Martius, “Learning equations for extrapolation and control,” in Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 4442–4450.
[Preprint] View | Files available | Download Preprint (ext.) | WoS | arXiv
 
[88]
2018 | Published | Conference Paper | IST-REx-ID: 6011 | OA
I. Kuzborskij and C. Lampert, “Data-dependent stability of stochastic gradient descent,” in Proceedings of the 35 th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 2815–2824.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 
[87]
2017 | Published | Conference Paper | IST-REx-ID: 750
J. Pielorz, M. Prandtstetter, M. Straub, and C. Lampert, “Optimal geospatial volunteer allocation needs realistic distances,” in 2017 IEEE International Conference on Big Data, Boston, MA, United States, 2017, pp. 3760–3763.
View | DOI
 
[86]
2017 | Published | Conference Paper | IST-REx-ID: 911 | OA
A. Royer, A. Kolesnikov, and C. Lampert, “Probabilistic image colorization,” presented at the BMVC: British Machine Vision Conference, London, United Kingdom, 2017, p. 85.1-85.12.
[Published Version] View | Files available | DOI | arXiv
 
[85]
2017 | Published | Conference Paper | IST-REx-ID: 1000 | OA
A. Kolesnikov and C. Lampert, “PixelCNN models with auxiliary variables for natural image modeling,” in 34th International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 1905–1914.
[Submitted Version] View | Download Submitted Version (ext.) | WoS | arXiv
 
[84]
2017 | Published | Conference Paper | IST-REx-ID: 1108 | OA
A. Zimin and C. Lampert, “Learning theory for conditional risk minimization,” presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States, 2017, vol. 54, pp. 213–222.
[Submitted Version] View | Download Submitted Version (ext.) | WoS
 
[83]
2017 | Published | Conference Paper | IST-REx-ID: 6841 | OA
G. S. Martius and C. Lampert, “Extrapolation and learning equations,” in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, Toulon, France, 2017.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[82]
2017 | Published | Conference Paper | IST-REx-ID: 999 | OA
A. Pentina and C. Lampert, “Multi-task learning with labeled and unlabeled tasks,” presented at the ICML: International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 2807–2816.
[Submitted Version] View | Download Submitted Version (ext.) | WoS | arXiv
 
[81]
2017 | Published | Conference Paper | IST-REx-ID: 998 | OA
S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS | arXiv
 
[80]
2016 | Published | Conference Paper | IST-REx-ID: 1707
J. Pielorz and C. Lampert, “Optimal geospatial allocation of volunteers for crisis management,” presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France, 2016.
View | DOI
 
[79]
2016 | Published | Conference Paper | IST-REx-ID: 1102 | OA
A. Kolesnikov and C. Lampert, “Improving weakly-supervised object localization by micro-annotation,” in Proceedings of the British Machine Vision Conference 2016, York, United Kingdom, 2016, vol. 2016–September, p. 92.1-92.12.
[Published Version] View | DOI | Download Published Version (ext.)
 
[78]
2016 | Published | Conference Paper | IST-REx-ID: 1369 | OA
A. Kolesnikov and C. Lampert, “Seed, expand and constrain: Three principles for weakly-supervised image segmentation,” presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands, 2016, vol. 9908, pp. 695–711.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[77]
2015 | Published | Conference Paper | IST-REx-ID: 1858 | OA
C. Lampert, “Predicting the future behavior of a time-varying probability distribution,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 942–950.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[76]
2015 | Published | Conference Paper | IST-REx-ID: 1860 | OA
A. Royer and C. Lampert, “Classifier adaptation at prediction time,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 1401–1409.
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[75]
2015 | Published | Conference Paper | IST-REx-ID: 1425 | OA
A. Pentina and C. Lampert, “Lifelong learning with non-i.i.d. tasks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2015, vol. 2015, pp. 1540–1548.
View | Download None (ext.)
 
[74]
2015 | Published | Conference Paper | IST-REx-ID: 1859 | OA
N. Shah, V. Kolmogorov, and C. Lampert, “A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 2737–2745.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[73]
2015 | Published | Conference Paper | IST-REx-ID: 1857 | OA
A. Pentina, V. Sharmanska, and C. Lampert, “Curriculum learning of multiple tasks,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 5492–5500.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[72]
2014 | Published | Book Chapter | IST-REx-ID: 1829
K. Muelling, O. Kroemer, C. Lampert, and B. Schölkopf, “Movement templates for learning of hitting and batting,” in Learning Motor Skills, vol. 97, J. Kober and J. Peters, Eds. Springer, 2014, pp. 69–82.
View | DOI
 
[71]
2014 | Published | Conference Paper | IST-REx-ID: 2160 | OA
A. Pentina and C. Lampert, “A PAC-Bayesian bound for Lifelong Learning,” presented at the ICML: International Conference on Machine Learning, Beijing, China, 2014, vol. 32, pp. 991–999.
[Submitted Version] View | Download Submitted Version (ext.)
 
[70]
2014 | Published | Conference Paper | IST-REx-ID: 2173 | OA
S. Khamis and C. Lampert, “CoConut: Co-classification with output space regularization,” in Proceedings of the British Machine Vision Conference 2014, Nottingham, UK, 2014.
[Published Version] View | Files available
 
[69]
2014 | Published | Conference Paper | IST-REx-ID: 2033 | OA
D. Hernandez Lobato, V. Sharmanska, K. Kersting, C. Lampert, and N. Quadrianto, “Mind the nuisance: Gaussian process classification using privileged noise,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2014, vol. 1, no. January, pp. 837–845.
[Submitted Version] View | Download Submitted Version (ext.)
 
[68]
2014 | Published | Conference Paper | IST-REx-ID: 2171 | OA
A. Kolesnikov, M. Guillaumin, V. Ferrari, and C. Lampert, “Closed-form approximate CRF training for scalable image segmentation,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Zurich, Switzerland, 2014, vol. 8691, no. PART 3, pp. 550–565.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | arXiv
 
[67]
2014 | Published | Conference Paper | IST-REx-ID: 2172
V. Sydorov, M. Sakurada, and C. Lampert, “Deep Fisher Kernels – End to end learning of the Fisher Kernel GMM parameters,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Columbus, USA, 2014, pp. 1402–1409.
View | DOI | WoS
 
[66]
2013 | Published | Conference Paper | IST-REx-ID: 2948 | OA
T. Tommasi, N. Quadrianto, B. Caputo, and C. Lampert, “Beyond dataset bias: Multi-task unaligned shared knowledge transfer,” vol. 7724. Springer, pp. 1–15, 2013.
[Submitted Version] View | Files available | DOI
 
[65]
2013 | Published | Encyclopedia Article | IST-REx-ID: 3321
N. Quadrianto and C. Lampert, “Kernel based learning,” in Encyclopedia of Systems Biology, vol. 3, W. Dubitzky, O. Wolkenhauer, K. Cho, and H. Yokota, Eds. Springer, 2013, pp. 1069–1069.
View | DOI
 
[64]
2013 | Published | Conference Paper | IST-REx-ID: 2901 | OA
C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, and C. Lampert, “Computing the M most probable modes of a graphical model,” presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States, 2013, vol. 31, pp. 161–169.
View | Download None (ext.)
 
[63]
2013 | Published | Journal Article | IST-REx-ID: 2516
C. Lampert, H. Nickisch, and S. Harmeling, “Attribute-based classification for zero-shot learning of object categories,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 3. IEEE, pp. 453–465, 2013.
View | DOI | WoS
 
[62]
2013 | Published | Conference Paper | IST-REx-ID: 2294 | OA
T. Kazmar, E. Kvon, A. Stark, and C. Lampert, “Drosophila Embryo Stage Annotation using Label Propagation,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[61]
2013 | Published | Conference Paper | IST-REx-ID: 2293 | OA
V. Sharmanska, N. Quadrianto, and C. Lampert, “Learning to rank using privileged information,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013, pp. 825–832.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[60]
2012 | Published | Conference Paper | IST-REx-ID: 2915
O. Kroemer, C. Lampert, and J. Peters, “Multi-modal learning for dynamic tactile sensing,” 2012.
View
 
[59]
2012 | Published | Conference Paper | IST-REx-ID: 3124 | OA
F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete energy minimization,” presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland, 2012.
[Submitted Version] View | Files available
 
[58]
2012 | Published | Conference Paper | IST-REx-ID: 3125 | OA
V. Sharmanska, N. Quadrianto, and C. Lampert, “Augmented attribute representations,” presented at the ECCV: European Conference on Computer Vision, Florence, Italy, 2012, vol. 7576, no. PART 5, pp. 242–255.
[Submitted Version] View | Files available | DOI
 
[57]
2012 | Published | Conference Paper | IST-REx-ID: 3126
A. Müller, S. Nowozin, and C. Lampert, “Information theoretic clustering using minimal spanning trees,” presented at the DAGM: German Association For Pattern Recognition, Graz, Austria, 2012, vol. 7476, pp. 205–215.
View | DOI
 
[56]
2012 | Published | Technical Report | IST-REx-ID: 5396 | OA
F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.
[Published Version] View | Files available | DOI
 
[55]
2012 | Published | Conference Paper | IST-REx-ID: 2825
C. Lampert, “Dynamic pruning of factor graphs for maximum marginal prediction,” presented at the NIPS: Neural Information Processing Systems, Lake Tahoe, NV, United States, 2012, vol. 1, pp. 82–90.
View
 
[54]
2012 | Published | Conference Paper | IST-REx-ID: 3127 | OA
N. Quadrianto, C. Lampert, and C. Chen, “The most persistent soft-clique in a set of sampled graphs,” in Proceedings of the 29th International Conference on Machine Learning, Edinburgh, United Kingdom, 2012, pp. 211–218.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[53]
2012 | Published | Journal Article | IST-REx-ID: 3248 | OA
C. Lampert and J. Peters, “Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components,” Journal of Real-Time Image Processing, vol. 7, no. 1. Springer, pp. 31–41, 2012.
[Submitted Version] View | Files available | DOI | WoS
 
[52]
2012 | Published | Journal Article | IST-REx-ID: 3164
M. Blaschko and C. Lampert, “Guest editorial: Special issue on structured prediction and inference,” International Journal of Computer Vision, vol. 99, no. 3. Springer, pp. 257–258, 2012.
View | DOI | WoS
 
[51]
2011 | Published | Technical Report | IST-REx-ID: 5386 | OA
C. Chen, D. Freedman, and C. Lampert, Enforcing topological constraints in random field image segmentation. IST Austria, 2011.
[Published Version] View | Files available | DOI
 
[50]
2011 | Published | Conference Paper | IST-REx-ID: 3319
N. Quadrianto and C. Lampert, “Learning multi-view neighborhood preserving projections,” presented at the ICML: International Conference on Machine Learning, Bellevue, United States, 2011, pp. 425–432.
View
 
[49]
2011 | Published | Journal Article | IST-REx-ID: 3320 | OA
S. Nowozin and C. Lampert, “Structured learning and prediction in computer vision,” Foundations and Trends in Computer Graphics and Vision, vol. 6, no. 3–4. Now Publishers, pp. 185–365, 2011.
[Published Version] View | Files available | DOI
 
[48]
2011 | Published | Conference Paper | IST-REx-ID: 3336
C. Chen, D. Freedman, and C. Lampert, “Enforcing topological constraints in random field image segmentation,” in CVPR: Computer Vision and Pattern Recognition, Colorado Springs, CO, United States, 2011, pp. 2089–2096.
View | Files available | DOI
 
[47]
2011 | Published | Conference Paper | IST-REx-ID: 3163
C. Lampert, “Maximum margin multi-label structured prediction,” presented at the NIPS: Neural Information Processing Systems, Granada, Spain, 2011.
View | Files available
 
[46]
2011 | Published | Conference Poster | IST-REx-ID: 3322
C. Lampert, Maximum margin multi label structured prediction. Neural Information Processing Systems Foundation, 2011.
View | Files available
 
[45]
2011 | Published | Conference Paper | IST-REx-ID: 3337
Z. Wang, C. Lampert, K. Mülling, B. Schölkopf, and J. Peters, “Learning anticipation policies for robot table tennis,” presented at the IROS: Intelligent Robots and Systems, San Francisco, USA, 2011, pp. 332–337.
View | DOI
 
[44]
2011 | Published | Journal Article | IST-REx-ID: 3389
M. Blaschko, J. Shelton, A. Bartels, C. Lampert, and A. Gretton, “Semi supervised kernel canonical correlation analysis with application to human fMRI,” Pattern Recognition Letters, vol. 32, no. 11. Elsevier, pp. 1572–1583, 2011.
View | DOI | WoS
 
[43]
2011 | Published | Journal Article | IST-REx-ID: 3382
O. Kroemer, C. Lampert, and J. Peters, “Learning dynamic tactile sensing with robust vision based training,” IEEE Transactions on Robotics, vol. 27, no. 3. IEEE, pp. 545–557, 2011.
View | DOI | WoS
 
[42]
2010 | Published | Conference Paper | IST-REx-ID: 3676
J. Wanke, A. Ulges, C. Lampert, and T. Breuel, “Topic models for semantic video compression,” presented at the MIR: Multimedia Information Retrieval, 2010, pp. 275–284.
View | DOI | Download (ext.)
 
[41]
2010 | Published | Conference Paper | IST-REx-ID: 3682
K. Tang, M. Tappen, R. Sukthankar, and C. Lampert, “Optimizing one-shot recognition with micro-set learning,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 3027–3034.
View | DOI
 
[40]
2010 | Published | Journal Article | IST-REx-ID: 3686
S. Nowozin and C. Lampert, “Global interactions in random field models: A potential function ensuring connectedness,” SIAM Journal on Imaging Sciences, vol. 3, no. 4 (Special Section on Optimization in Imaging Sciences). Society for Industrial and Applied Mathematics , pp. 1048–1074, 2010.
View | DOI
 
[39]
2010 | Published | Journal Article | IST-REx-ID: 3697
T. Tuytelaars, C. Lampert, M. Blaschko, and W. Buntine, “Unsupervised object discovery: A comparison,” International Journal of Computer Vision, vol. 88, no. 2. Springer, pp. 284–302, 2010.
View | DOI
 
[38]
2010 | Published | Conference Paper | IST-REx-ID: 3702
J. Kober, K. Mülling, O. Krömer, C. Lampert, B. Schölkopf, and J. Peters, “Movement templates for learning of hitting and batting,” presented at the ICRA: International Conference on Robotics and Automation, 2010, pp. 853–858.
View | DOI | Download (ext.)
 
[37]
2010 | Published | Conference Paper | IST-REx-ID: 3713
C. Lampert, “An efficient divide-and-conquer cascade for nonlinear object detection,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 1022–1029.
View | DOI
 
[36]
2010 | Published | Conference Paper | IST-REx-ID: 3793 | OA
S. Nowozin, P. Gehler, and C. Lampert, “On parameter learning in CRF-based approaches to object class image segmentation,” presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6316, pp. 98–111.
[Submitted Version] View | Files available | DOI
 
[35]
2010 | Published | Conference Paper | IST-REx-ID: 3794
C. Lampert and O. Krömer, “Weakly-paired maximum covariance analysis for multimodal dimensionality reduction and transfer learning,” in 11th European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6312, pp. 566–579.
View | DOI
 
[34]
2009 | Published | Journal Article | IST-REx-ID: 3696
C. Lampert and M. Blaschko, “Structured prediction by joint kernel support estimation,” Machine Learning, vol. 77, no. 2–3. Springer, pp. 249–269, 2009.
View | DOI
 
[33]
2009 | Published | Conference Poster | IST-REx-ID: 3699
M. Blaschko, C. Lampert, and A. Bartels, Semi-supervised analysis of human fMRI data. Berlin Institute of Technology, 2009.
View | Download (ext.)
 
[32]
2009 | Published | Conference Paper | IST-REx-ID: 3703
M. Blaschko and C. Lampert, “Object localization with global and local context kernels,” presented at the BMVC: British Machine Vision Conference, 2009, pp. 1–11.
View | DOI | Download (ext.)
 
[31]
2009 | Published | Conference Paper | IST-REx-ID: 3704
C. Lampert, H. Nickisch, and S. Harmeling, “Learning to detect unseen object classes by between-class attribute transfer,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 951–958.
View | DOI
 
[30]
2009 | Published | Book | IST-REx-ID: 3707
C. Lampert, Kernel Methods in Computer Vision, vol. 4. now publishers, 2009.
View | DOI
 
[29]
2009 | Published | Conference Paper | IST-REx-ID: 3708
S. Nowozin and C. Lampert, “Global connectivity potentials for random field models,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 818–825.
View | DOI
 
[28]
2009 | Published | Conference Paper | IST-REx-ID: 3709
C. Lampert, “Detecting objects in large image collections and videos by efficient subimage retrieval,” presented at the ICCV: International Conference on Computer Vision, 2009, pp. 987–994.
View | DOI
 
[27]
2009 | Published | Journal Article | IST-REx-ID: 3710
C. Lampert, M. Blaschko, and T. Hofmann, “Efficient subwindow search: A branch and bound framework for object localization,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 12. IEEE, pp. 2129–2142, 2009.
View | DOI | Download (ext.)
 
[26]
2009 | Published | Conference Paper | IST-REx-ID: 3715
C. Lampert and J. Peters, “Active structured learning for high-speed object detection,” presented at the DAGM: German Association For Pattern Recognition, 2009, vol. 5748, pp. 221–231.
View | DOI
 
[25]
2009 | Published | Conference Poster | IST-REx-ID: 3717
C. Lampert and J. Peters, A high-speed object tracker from off-the-shelf components. IEEE, 2009.
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[24]
2009 | Published | Conference Paper | IST-REx-ID: 3711 | OA
P. Dhillon, S. Nowozin, and C. Lampert, “Combining appearance and motion for human action classification in videos,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 22–29.
View | DOI | Download None (ext.)
 
[23]
2008 | Published | Conference Paper | IST-REx-ID: 3694
M. Goldstein, C. Lampert, M. Reif, A. Stahl, and T. Breuel, “Bayes optimal DDoS mitigation by adaptive history-based IP filtering,” presented at the ICN: International Conference on Networking, 2008, pp. 174–179.
View | DOI | Download (ext.)
 
[22]
2008 | Published | Conference Paper | IST-REx-ID: 3698
M. Blaschko, C. Lampert, and A. Gretton, “Semi-supervised Laplacian regularization of kernel canonical correlation analysis,” presented at the ECML: European Conference on Machine Learning, 2008, vol. 5211, no. Part 1, pp. 133–145.
View | DOI
 
[21]
2008 | Published | Conference Paper | IST-REx-ID: 3700
C. Lampert, “Partitioning of image datasets using discriminative context information,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI | Download (ext.)
 
[20]
2008 | Published | Conference Paper | IST-REx-ID: 3705
M. Blaschko and C. Lampert, “Learning to localize objects with structured output regression,” presented at the ECCV: European Conference on Computer Vision, 2008, vol. 5302, pp. 2–15.
View | DOI | Download (ext.)
 
[19]
2008 | Published | Conference Paper | IST-REx-ID: 3706
C. Lampert and M. Blaschko, “Joint kernel support estimation for structured prediction,” presented at the NIPS SISO: NIPS Workshop on “Structured Input - Structured Output,” 2008, pp. 1–4.
View | Download (ext.)
 
[18]
2008 | Published | Conference Paper | IST-REx-ID: 3712
M. Blaschko and C. Lampert, “Correlational spectral clustering,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI
 
[17]
2008 | Published | Conference Paper | IST-REx-ID: 3714
C. Lampert, M. Blaschko, and T. Hofmann, “Beyond sliding windows: Object localization by efficient subwindow search,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI | Download (ext.)
 
[16]
2008 | Published | Conference Paper | IST-REx-ID: 3716
C. Lampert and M. Blaschko, “A multiple kernel learning approach to joint multi-class object detection,” presented at the DAGM: German Association For Pattern Recognition, 2008, vol. 5096, pp. 31–40.
View | DOI | Download (ext.)
 
[15]
2007 | Published | Conference Paper | IST-REx-ID: 3681
A. Ulges, C. Lampert, D. Keysers, and T. Breuel, “Optimal dominant motion estimation using adaptive search of transformation space,” presented at the DAGM: German Association For Pattern Recognition, 2007, vol. 4713, pp. 204–213.
View | DOI
 
[14]
2007 | Published | Report | IST-REx-ID: 3687
M. Blaschko, T. Hofmann, and C. Lampert, Efficient subwindow search for object localization, no. 164. Max-Planck-Institute for Biological Cybernetics, 2007.
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[13]
2006 | Published | Conference Paper | IST-REx-ID: 3677
A. Ulges, C. Lampert, and D. Keysers, “Spatiogram-based shot distances for video retrieval,” presented at the TRECVID Workshop, 2006, pp. 1–10.
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[12]
2006 | Published | Conference Paper | IST-REx-ID: 3679
H. Ali, C. Lampert, and T. Breuel, “Satellite tracks removal in astronomical images,” presented at the CIARP: Iberoamerican Congress in Pattern Recognition, 2006, vol. 4225, pp. 892–901.
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[11]
2006 | Published | Conference Paper | IST-REx-ID: 3680
C. Lampert, L. Mei, and T. Breuel, “Printing technique classification for document counterfeit detection,” presented at the CIS: Computational Intelligence and Security, 2006, vol. 1, pp. 639–634.
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[10]
2006 | Published | Conference Paper | IST-REx-ID: 3683
C. Lampert and T. Breuel, “Objective quality measurement for geometric document image restoration,” presented at the DAS: Document Analysis Systems, 2006.
View | Download (ext.)
 
[9]
2006 | Published | Conference Paper | IST-REx-ID: 3685
C. Lampert, “Machine learning for video compression: Macroblock mode decision,” presented at the ICPR: International Conference on Pattern Recognition, 2006, pp. 936–940.
View | DOI
 
[8]
2006 | Published | Conference Paper | IST-REx-ID: 3692
D. Keysers, C. Lampert, and T. Breuel, “Color image dequantization by constrained diffusion,” presented at the SPIE Electronic Imaging, 2006, vol. 6058.
View | DOI
 
[7]
2006 | Published | Conference Paper | IST-REx-ID: 3693
C. Lampert and O. Wirjadi, “Anisotropic Gaussian filtering using fixed point arithmetic,” presented at the ICIP: IEEE International Conference on Image Processing, 2006, pp. 1565–1568.
View | DOI
 
[6]
2006 | Published | Journal Article | IST-REx-ID: 3695 | OA
C. Lampert and O. Wirjadi, “An optimal non-orthogonal separation of the anisotropic Gaussian convolution filter,” IEEE Transactions on Image Processing (TIP), vol. 15, no. 11. IEEE, pp. 3501–3513, 2006.
View | DOI | Download (ext.)
 
[5]
2005 | Published | Conference Paper | IST-REx-ID: 3684
C. Lampert, T. Braun, A. Ulges, D. Keysers, and T. Breuel, “Oblivious document capture and real-time retrieval,” presented at the CBDAR: Camera Based Document Analysis and Recognition , 2005, pp. 79–86.
View | Download (ext.)
 
[4]
2005 | Published | Conference Paper | IST-REx-ID: 3689
A. Ulges, C. Lampert, and T. Breuel, “Document image dewarping using robust estimation of curled text lines,” presented at the ICDAR: International Conference on Document Analysis and Recognition, 2005, vol. 2, pp. 1001–1005.
View | DOI | Download (ext.)
 
[3]
2005 | Published | Journal Article | IST-REx-ID: 3691
C. Lampert, “Boundary regularity of admissible operators,” Publicacions Matemàtiques, vol. 49, no. 1. Universitat Autònoma de Barcelona, Departament de Matemàtique, pp. 179–195, 2005.
View | DOI
 
[2]
2004 | Published | Conference Paper | IST-REx-ID: 3688
A. Ulges, C. Lampert, and T. Breuel, “Document capture using stereo vision,” presented at the DocEng: ACM Symposium on Document Engineering, 2004, pp. 198–200.
View | DOI | Download (ext.)
 
[1]
2003 | Published | Thesis | IST-REx-ID: 3678
C. Lampert, “The Neumann operator in strictly pseudoconvex domains with weighted Bergman metric ,” Universität Bonn, Fachbibliothek Mathematik, 2003.
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134 Publications

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[134]
2025 | Published | Conference Paper | IST-REx-ID: 20296 | OA
F. Kresse, E. Yu, C. Lampert, and T. A. Henzinger, “Logic gate neural networks are good for verification,” in 2nd International Conferenceon Neuro-Symbolic Systems, Philadephia, PA, United States, 2025, vol. 288.
[Published Version] View | Files available | arXiv
 
[133]
2025 | Published | Conference Paper | IST-REx-ID: 20455 | OA
B. Prach and C. Lampert, “Intriguing properties of robust classification,” in 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Nashville, TN, United States, 2025, pp. 660–669.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[132]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
J. A. Scott, H. Zakerinia, and C. Lampert, “PEFLL: Personalized federated learning by learning to learn,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
[Published Version] View | Files available | arXiv
 
[131]
2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
H. Zakerinia, A. Behjati, and C. Lampert, “More flexible PAC-Bayesian meta-learning by learning learning algorithms,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 58122–58139.
[Published Version] View | Download Published Version (ext.) | arXiv
 
[130]
2024 | Epub ahead of print | Journal Article | IST-REx-ID: 12662 | OA
P. Súkeník and C. Lampert, “Generalization in multi-objective machine learning,” Neural Computing and Applications. Springer Nature, 2024.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[129]
2024 | Published | Preprint | IST-REx-ID: 19063 | OA
E. Zverev, S. Abdelnabi, S. Tabesh, M. Fritz, and C. Lampert, “Can LLMs separate instructions from data? And what do we even mean by that?,” arXiv. 2024.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[128]
2024 | Published | Journal Article | IST-REx-ID: 19408 | OA
E. Verwimp et al., “Continual learning: Applications and the road forward,” Transactions on Machine Learning Research, vol. 2024. Transactions on Machine Learning Research, 2024.
[Published Version] View | Files available | arXiv
 
[127]
2024 | Published | Conference Paper | IST-REx-ID: 18875 | OA
N. Kalinin and C. Lampert, “Banded square root matrix factorization for differentially private model training,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version] View | Files available | arXiv
 
[126]
2024 | Published | Conference Paper | IST-REx-ID: 18891 | OA
P. Súkeník, C. Lampert, and M. Mondelli, “Neural collapse versus low-rank bias: Is deep neural collapse really optimal?,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
[Published Version] View | Files available | arXiv
 
[125]
2024 | Published | Journal Article | IST-REx-ID: 18856 | OA
K. Lutsai and C. Lampert, “Predicting the geolocation of tweets using transformer models on customized data,” Journal of Spatial Information Science, no. 29. University of Maine, pp. 69–99, 2024.
[Published Version] View | Files available | DOI
 
[124]
2024 | Published | Conference Paper | IST-REx-ID: 17426 | OA
B. Prach, F. Brau, G. Buttazzo, and C. Lampert, “1-Lipschitz layers compared: Memory, speed, and certifiable robustness,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, United States, 2024, pp. 24574–24583.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[123]
2024 | Draft | Preprint | IST-REx-ID: 18874 | OA
B. Prach and C. Lampert, “Intriguing properties of robust classification,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[122]
2023 | Published | Conference Paper | IST-REx-ID: 14410
P. Tomaszewska and C. Lampert, “On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift,” in International Workshop on Reproducible Research in Pattern Recognition, Montreal, Canada, 2023, vol. 14068, pp. 67–73.
View | DOI
 
[121]
2023 | Published | Conference Paper | IST-REx-ID: 12660 | OA
J. A. Scott, M. X. Yeo, and C. Lampert, “Cross-client label propagation for transductive and semi-supervised federated learning,” in Transactions in Machine Learning, 2023.
[Preprint] View | Files available | arXiv
 
[120]
2023 | Published | Conference Paper | IST-REx-ID: 13053 | OA
A. Krumes, A. Vladu, E. Kurtic, C. Lampert, and D.-A. Alistarh, “CrAM: A Compression-Aware Minimizer,” in 11th International Conference on Learning Representations , Kigali, Rwanda , 2023.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[119]
2023 | Published | Conference Paper | IST-REx-ID: 14921 | OA
P. Súkeník, M. Mondelli, and C. Lampert, “Deep neural collapse is provably optimal for the deep unconstrained features model,” in 37th Annual Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[118]
2023 | Draft | Preprint | IST-REx-ID: 15039 | OA
B. Prach and C. Lampert, “1-Lipschitz neural networks are more expressive with N-activations,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[117]
2022 | Published | Conference Paper | IST-REx-ID: 13241 | OA
N. H. Konstantinov and C. Lampert, “On the impossibility of fairness-aware learning from corrupted data,” in Proceedings of Machine Learning Research, 2022, vol. 171, pp. 59–83.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[116]
2022 | Published | Conference Paper | IST-REx-ID: 12161 | OA
P. Tomaszewska and C. Lampert, “Lightweight conditional model extrapolation for streaming data under class-prior shift,” in 26th International Conference on Pattern Recognition, Montreal, Canada, 2022, vol. 2022, pp. 2128–2134.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[115]
2022 | Published | Conference Paper | IST-REx-ID: 10752
J. Lampert and C. Lampert, “Overcoming rare-language discrimination in multi-lingual sentiment analysis,” in 2021 IEEE International Conference on Big Data, Orlando, FL, United States, 2022, pp. 5185–5192.
View | DOI | WoS
 
[114]
2022 | Published | Journal Article | IST-REx-ID: 10802 | OA
N. H. Konstantinov and C. Lampert, “Fairness-aware PAC learning from corrupted data,” Journal of Machine Learning Research, vol. 23. ML Research Press, pp. 1–60, 2022.
[Published Version] View | Files available | arXiv
 
[113]
2022 | Published | Journal Article | IST-REx-ID: 12495 | OA
E. B. Iofinova, N. H. Konstantinov, and C. Lampert, “FLEA: Provably robust fair multisource learning from unreliable training data,” Transactions on Machine Learning Research. ML Research Press, 2022.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[112]
2022 | Published | Conference Paper | IST-REx-ID: 11839 | OA
B. Prach and C. Lampert, “Almost-orthogonal layers for efficient general-purpose Lipschitz networks,” in Computer Vision – ECCV 2022, Tel Aviv, Israel, 2022, vol. 13681, pp. 350–365.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[111]
2021 | Published | Book Chapter | IST-REx-ID: 14987
C. Lampert, “Zero-Shot Learning,” in Computer Vision, 2nd ed., K. Ikeuchi, Ed. Cham: Springer, 2021, pp. 1395–1397.
View | DOI
 
[110]
2021 | Draft | Preprint | IST-REx-ID: 10803 | OA
N. H. Konstantinov and C. Lampert, “Fairness through regularization for learning to rank,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[109]
2021 | Published | Conference Paper | IST-REx-ID: 9416 | OA
M. Phuong and C. Lampert, “The inductive bias of ReLU networks on orthogonally separable data,” in 9th International Conference on Learning Representations, Virtual, 2021.
[Published Version] View | Files available | Download Published Version (ext.)
 
[108]
2021 | Published | Conference Paper | IST-REx-ID: 9210 | OA
V. Volhejn and C. Lampert, “Does SGD implicitly optimize for smoothness?,” in 42nd German Conference on Pattern Recognition, Tübingen, Germany, 2021, vol. 12544, pp. 246–259.
[Submitted Version] View | Files available | DOI | WoS
 
[107]
2020 | Published | Conference Paper | IST-REx-ID: 8186 | OA
P. M. Henderson, V. Tsiminaki, and C. Lampert, “Leveraging 2D data to learn textured 3D mesh generation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Virtual, 2020, pp. 7498–7507.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | arXiv
 
[106]
2020 | Submitted | Preprint | IST-REx-ID: 8063 | OA
T. Anciukevicius, C. Lampert, and P. M. Henderson, “Object-centric image generation with factored depths, locations, and appearances,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[105]
2020 | Published | Conference Paper | IST-REx-ID: 7936 | OA
A. Royer and C. Lampert, “Localizing grouped instances for efficient detection in low-resource scenarios,” in IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, CO, United States, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[104]
2020 | Published | Journal Article | IST-REx-ID: 6944 | OA
R. Sun and C. Lampert, “KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications,” International Journal of Computer Vision, vol. 128, no. 4. Springer Nature, pp. 970–995, 2020.
[Published Version] View | Files available | DOI | WoS
 
[103]
2020 | Published | Conference Paper | IST-REx-ID: 8188 | OA
P. M. Henderson and C. Lampert, “Unsupervised object-centric video generation and decomposition in 3D,” in 34th Conference on Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 3106–3117.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[102]
2020 | Published | Conference Paper | IST-REx-ID: 8724 | OA
N. H. Konstantinov, E. Frantar, D.-A. Alistarh, and C. Lampert, “On the sample complexity of adversarial multi-source PAC learning,” in Proceedings of the 37th International Conference on Machine Learning, Online, 2020, vol. 119, pp. 5416–5425.
[Published Version] View | Files available | arXiv
 
[101]
2020 | Published | Conference Paper | IST-REx-ID: 7481 | OA
M. Phuong and C. Lampert, “Functional vs. parametric equivalence of ReLU networks,” in 8th International Conference on Learning Representations, Online, 2020.
[Published Version] View | Files available
 
[100]
2020 | Published | Conference Paper | IST-REx-ID: 7937 | OA
A. Royer and C. Lampert, “A flexible selection scheme for minimum-effort transfer learning,” in 2020 IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, CO, United States, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[99]
2019 | Published | Book (Editor) | IST-REx-ID: 7171
K. Kersting, C. Lampert, and C. Rothkopf, Eds., Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt, 1st ed. Wiesbaden: Springer Nature, 2019.
View | Files available | DOI
 
[98]
2019 | Published | Journal Article | IST-REx-ID: 6554 | OA
Y. Xian, C. Lampert, B. Schiele, and Z. Akata, “Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9. Institute of Electrical and Electronics Engineers, pp. 2251–2265, 2019.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[97]
2019 | Published | Conference Paper | IST-REx-ID: 7640 | OA
A. Kolesnikov, A. Kuznetsova, C. Lampert, and V. Ferrari, “Detecting visual relationships using box attention,” in Proceedings of the 2019 International Conference on Computer Vision Workshop, Seoul, South Korea, 2019.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[96]
2019 | Published | Conference Paper | IST-REx-ID: 6482 | OA
R. Sun and C. Lampert, “KS(conf): A light-weight test if a ConvNet operates outside of Its specifications,” presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany, 2019, vol. 11269, pp. 244–259.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[95]
2019 | Published | Conference Paper | IST-REx-ID: 6590 | OA
N. H. Konstantinov and C. Lampert, “Robust learning from untrusted sources,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA, 2019, vol. 97, pp. 3488–3498.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[94]
2019 | Published | Conference Paper | IST-REx-ID: 6942 | OA
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, and V. Toman, “Strategy representation by decision trees with linear classifiers,” in 16th International Conference on Quantitative Evaluation of Systems, Glasgow, United Kingdom, 2019, vol. 11785, pp. 109–128.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[93]
2019 | Published | Conference Paper | IST-REx-ID: 6569 | OA
M. Phuong and C. Lampert, “Towards understanding knowledge distillation,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, United States, 2019, vol. 97, pp. 5142–5151.
[Published Version] View | Files available
 
[92]
2019 | Published | Conference Paper | IST-REx-ID: 7479 | OA
M. Phuong and C. Lampert, “Distillation-based training for multi-exit architectures,” in IEEE International Conference on Computer Vision, Seoul, Korea, 2019, vol. 2019–October, pp. 1355–1364.
[Submitted Version] View | Files available | DOI | WoS
 
[91]
2018 | Published | Conference Paper | IST-REx-ID: 10882 | OA
J. Uijlings, K. Konyushkova, C. Lampert, and V. Ferrari, “Learning intelligent dialogs for bounding box annotation,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, United States, 2018, pp. 9175–9184.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[90]
2018 | Published | Journal Article | IST-REx-ID: 321 | OA
T. Darrell, C. Lampert, N. Sebe, Y. Wu, and Y. Yan, “Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5. IEEE, pp. 1029–1031, 2018.
[Published Version] View | Files available | DOI | WoS
 
[89]
2018 | Published | Conference Paper | IST-REx-ID: 6012 | OA
S. Sahoo, C. Lampert, and G. S. Martius, “Learning equations for extrapolation and control,” in Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 4442–4450.
[Preprint] View | Files available | Download Preprint (ext.) | WoS | arXiv
 
[88]
2018 | Published | Conference Paper | IST-REx-ID: 6011 | OA
I. Kuzborskij and C. Lampert, “Data-dependent stability of stochastic gradient descent,” in Proceedings of the 35 th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 2815–2824.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 
[87]
2017 | Published | Conference Paper | IST-REx-ID: 750
J. Pielorz, M. Prandtstetter, M. Straub, and C. Lampert, “Optimal geospatial volunteer allocation needs realistic distances,” in 2017 IEEE International Conference on Big Data, Boston, MA, United States, 2017, pp. 3760–3763.
View | DOI
 
[86]
2017 | Published | Conference Paper | IST-REx-ID: 911 | OA
A. Royer, A. Kolesnikov, and C. Lampert, “Probabilistic image colorization,” presented at the BMVC: British Machine Vision Conference, London, United Kingdom, 2017, p. 85.1-85.12.
[Published Version] View | Files available | DOI | arXiv
 
[85]
2017 | Published | Conference Paper | IST-REx-ID: 1000 | OA
A. Kolesnikov and C. Lampert, “PixelCNN models with auxiliary variables for natural image modeling,” in 34th International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 1905–1914.
[Submitted Version] View | Download Submitted Version (ext.) | WoS | arXiv
 
[84]
2017 | Published | Conference Paper | IST-REx-ID: 1108 | OA
A. Zimin and C. Lampert, “Learning theory for conditional risk minimization,” presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States, 2017, vol. 54, pp. 213–222.
[Submitted Version] View | Download Submitted Version (ext.) | WoS
 
[83]
2017 | Published | Conference Paper | IST-REx-ID: 6841 | OA
G. S. Martius and C. Lampert, “Extrapolation and learning equations,” in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, Toulon, France, 2017.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[82]
2017 | Published | Conference Paper | IST-REx-ID: 999 | OA
A. Pentina and C. Lampert, “Multi-task learning with labeled and unlabeled tasks,” presented at the ICML: International Conference on Machine Learning, Sydney, Australia, 2017, vol. 70, pp. 2807–2816.
[Submitted Version] View | Download Submitted Version (ext.) | WoS | arXiv
 
[81]
2017 | Published | Conference Paper | IST-REx-ID: 998 | OA
S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS | arXiv
 
[80]
2016 | Published | Conference Paper | IST-REx-ID: 1707
J. Pielorz and C. Lampert, “Optimal geospatial allocation of volunteers for crisis management,” presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France, 2016.
View | DOI
 
[79]
2016 | Published | Conference Paper | IST-REx-ID: 1102 | OA
A. Kolesnikov and C. Lampert, “Improving weakly-supervised object localization by micro-annotation,” in Proceedings of the British Machine Vision Conference 2016, York, United Kingdom, 2016, vol. 2016–September, p. 92.1-92.12.
[Published Version] View | DOI | Download Published Version (ext.)
 
[78]
2016 | Published | Conference Paper | IST-REx-ID: 1369 | OA
A. Kolesnikov and C. Lampert, “Seed, expand and constrain: Three principles for weakly-supervised image segmentation,” presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands, 2016, vol. 9908, pp. 695–711.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[77]
2015 | Published | Conference Paper | IST-REx-ID: 1858 | OA
C. Lampert, “Predicting the future behavior of a time-varying probability distribution,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 942–950.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[76]
2015 | Published | Conference Paper | IST-REx-ID: 1860 | OA
A. Royer and C. Lampert, “Classifier adaptation at prediction time,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 1401–1409.
[Submitted Version] View | DOI | Download Submitted Version (ext.)
 
[75]
2015 | Published | Conference Paper | IST-REx-ID: 1425 | OA
A. Pentina and C. Lampert, “Lifelong learning with non-i.i.d. tasks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2015, vol. 2015, pp. 1540–1548.
View | Download None (ext.)
 
[74]
2015 | Published | Conference Paper | IST-REx-ID: 1859 | OA
N. Shah, V. Kolmogorov, and C. Lampert, “A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 2737–2745.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[73]
2015 | Published | Conference Paper | IST-REx-ID: 1857 | OA
A. Pentina, V. Sharmanska, and C. Lampert, “Curriculum learning of multiple tasks,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States, 2015, pp. 5492–5500.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[72]
2014 | Published | Book Chapter | IST-REx-ID: 1829
K. Muelling, O. Kroemer, C. Lampert, and B. Schölkopf, “Movement templates for learning of hitting and batting,” in Learning Motor Skills, vol. 97, J. Kober and J. Peters, Eds. Springer, 2014, pp. 69–82.
View | DOI
 
[71]
2014 | Published | Conference Paper | IST-REx-ID: 2160 | OA
A. Pentina and C. Lampert, “A PAC-Bayesian bound for Lifelong Learning,” presented at the ICML: International Conference on Machine Learning, Beijing, China, 2014, vol. 32, pp. 991–999.
[Submitted Version] View | Download Submitted Version (ext.)
 
[70]
2014 | Published | Conference Paper | IST-REx-ID: 2173 | OA
S. Khamis and C. Lampert, “CoConut: Co-classification with output space regularization,” in Proceedings of the British Machine Vision Conference 2014, Nottingham, UK, 2014.
[Published Version] View | Files available
 
[69]
2014 | Published | Conference Paper | IST-REx-ID: 2033 | OA
D. Hernandez Lobato, V. Sharmanska, K. Kersting, C. Lampert, and N. Quadrianto, “Mind the nuisance: Gaussian process classification using privileged noise,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2014, vol. 1, no. January, pp. 837–845.
[Submitted Version] View | Download Submitted Version (ext.)
 
[68]
2014 | Published | Conference Paper | IST-REx-ID: 2171 | OA
A. Kolesnikov, M. Guillaumin, V. Ferrari, and C. Lampert, “Closed-form approximate CRF training for scalable image segmentation,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Zurich, Switzerland, 2014, vol. 8691, no. PART 3, pp. 550–565.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | arXiv
 
[67]
2014 | Published | Conference Paper | IST-REx-ID: 2172
V. Sydorov, M. Sakurada, and C. Lampert, “Deep Fisher Kernels – End to end learning of the Fisher Kernel GMM parameters,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Columbus, USA, 2014, pp. 1402–1409.
View | DOI | WoS
 
[66]
2013 | Published | Conference Paper | IST-REx-ID: 2948 | OA
T. Tommasi, N. Quadrianto, B. Caputo, and C. Lampert, “Beyond dataset bias: Multi-task unaligned shared knowledge transfer,” vol. 7724. Springer, pp. 1–15, 2013.
[Submitted Version] View | Files available | DOI
 
[65]
2013 | Published | Encyclopedia Article | IST-REx-ID: 3321
N. Quadrianto and C. Lampert, “Kernel based learning,” in Encyclopedia of Systems Biology, vol. 3, W. Dubitzky, O. Wolkenhauer, K. Cho, and H. Yokota, Eds. Springer, 2013, pp. 1069–1069.
View | DOI
 
[64]
2013 | Published | Conference Paper | IST-REx-ID: 2901 | OA
C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, and C. Lampert, “Computing the M most probable modes of a graphical model,” presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States, 2013, vol. 31, pp. 161–169.
View | Download None (ext.)
 
[63]
2013 | Published | Journal Article | IST-REx-ID: 2516
C. Lampert, H. Nickisch, and S. Harmeling, “Attribute-based classification for zero-shot learning of object categories,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 3. IEEE, pp. 453–465, 2013.
View | DOI | WoS
 
[62]
2013 | Published | Conference Paper | IST-REx-ID: 2294 | OA
T. Kazmar, E. Kvon, A. Stark, and C. Lampert, “Drosophila Embryo Stage Annotation using Label Propagation,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[61]
2013 | Published | Conference Paper | IST-REx-ID: 2293 | OA
V. Sharmanska, N. Quadrianto, and C. Lampert, “Learning to rank using privileged information,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013, pp. 825–832.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
[60]
2012 | Published | Conference Paper | IST-REx-ID: 2915
O. Kroemer, C. Lampert, and J. Peters, “Multi-modal learning for dynamic tactile sensing,” 2012.
View
 
[59]
2012 | Published | Conference Paper | IST-REx-ID: 3124 | OA
F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete energy minimization,” presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland, 2012.
[Submitted Version] View | Files available
 
[58]
2012 | Published | Conference Paper | IST-REx-ID: 3125 | OA
V. Sharmanska, N. Quadrianto, and C. Lampert, “Augmented attribute representations,” presented at the ECCV: European Conference on Computer Vision, Florence, Italy, 2012, vol. 7576, no. PART 5, pp. 242–255.
[Submitted Version] View | Files available | DOI
 
[57]
2012 | Published | Conference Paper | IST-REx-ID: 3126
A. Müller, S. Nowozin, and C. Lampert, “Information theoretic clustering using minimal spanning trees,” presented at the DAGM: German Association For Pattern Recognition, Graz, Austria, 2012, vol. 7476, pp. 205–215.
View | DOI
 
[56]
2012 | Published | Technical Report | IST-REx-ID: 5396 | OA
F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.
[Published Version] View | Files available | DOI
 
[55]
2012 | Published | Conference Paper | IST-REx-ID: 2825
C. Lampert, “Dynamic pruning of factor graphs for maximum marginal prediction,” presented at the NIPS: Neural Information Processing Systems, Lake Tahoe, NV, United States, 2012, vol. 1, pp. 82–90.
View
 
[54]
2012 | Published | Conference Paper | IST-REx-ID: 3127 | OA
N. Quadrianto, C. Lampert, and C. Chen, “The most persistent soft-clique in a set of sampled graphs,” in Proceedings of the 29th International Conference on Machine Learning, Edinburgh, United Kingdom, 2012, pp. 211–218.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[53]
2012 | Published | Journal Article | IST-REx-ID: 3248 | OA
C. Lampert and J. Peters, “Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components,” Journal of Real-Time Image Processing, vol. 7, no. 1. Springer, pp. 31–41, 2012.
[Submitted Version] View | Files available | DOI | WoS
 
[52]
2012 | Published | Journal Article | IST-REx-ID: 3164
M. Blaschko and C. Lampert, “Guest editorial: Special issue on structured prediction and inference,” International Journal of Computer Vision, vol. 99, no. 3. Springer, pp. 257–258, 2012.
View | DOI | WoS
 
[51]
2011 | Published | Technical Report | IST-REx-ID: 5386 | OA
C. Chen, D. Freedman, and C. Lampert, Enforcing topological constraints in random field image segmentation. IST Austria, 2011.
[Published Version] View | Files available | DOI
 
[50]
2011 | Published | Conference Paper | IST-REx-ID: 3319
N. Quadrianto and C. Lampert, “Learning multi-view neighborhood preserving projections,” presented at the ICML: International Conference on Machine Learning, Bellevue, United States, 2011, pp. 425–432.
View
 
[49]
2011 | Published | Journal Article | IST-REx-ID: 3320 | OA
S. Nowozin and C. Lampert, “Structured learning and prediction in computer vision,” Foundations and Trends in Computer Graphics and Vision, vol. 6, no. 3–4. Now Publishers, pp. 185–365, 2011.
[Published Version] View | Files available | DOI
 
[48]
2011 | Published | Conference Paper | IST-REx-ID: 3336
C. Chen, D. Freedman, and C. Lampert, “Enforcing topological constraints in random field image segmentation,” in CVPR: Computer Vision and Pattern Recognition, Colorado Springs, CO, United States, 2011, pp. 2089–2096.
View | Files available | DOI
 
[47]
2011 | Published | Conference Paper | IST-REx-ID: 3163
C. Lampert, “Maximum margin multi-label structured prediction,” presented at the NIPS: Neural Information Processing Systems, Granada, Spain, 2011.
View | Files available
 
[46]
2011 | Published | Conference Poster | IST-REx-ID: 3322
C. Lampert, Maximum margin multi label structured prediction. Neural Information Processing Systems Foundation, 2011.
View | Files available
 
[45]
2011 | Published | Conference Paper | IST-REx-ID: 3337
Z. Wang, C. Lampert, K. Mülling, B. Schölkopf, and J. Peters, “Learning anticipation policies for robot table tennis,” presented at the IROS: Intelligent Robots and Systems, San Francisco, USA, 2011, pp. 332–337.
View | DOI
 
[44]
2011 | Published | Journal Article | IST-REx-ID: 3389
M. Blaschko, J. Shelton, A. Bartels, C. Lampert, and A. Gretton, “Semi supervised kernel canonical correlation analysis with application to human fMRI,” Pattern Recognition Letters, vol. 32, no. 11. Elsevier, pp. 1572–1583, 2011.
View | DOI | WoS
 
[43]
2011 | Published | Journal Article | IST-REx-ID: 3382
O. Kroemer, C. Lampert, and J. Peters, “Learning dynamic tactile sensing with robust vision based training,” IEEE Transactions on Robotics, vol. 27, no. 3. IEEE, pp. 545–557, 2011.
View | DOI | WoS
 
[42]
2010 | Published | Conference Paper | IST-REx-ID: 3676
J. Wanke, A. Ulges, C. Lampert, and T. Breuel, “Topic models for semantic video compression,” presented at the MIR: Multimedia Information Retrieval, 2010, pp. 275–284.
View | DOI | Download (ext.)
 
[41]
2010 | Published | Conference Paper | IST-REx-ID: 3682
K. Tang, M. Tappen, R. Sukthankar, and C. Lampert, “Optimizing one-shot recognition with micro-set learning,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 3027–3034.
View | DOI
 
[40]
2010 | Published | Journal Article | IST-REx-ID: 3686
S. Nowozin and C. Lampert, “Global interactions in random field models: A potential function ensuring connectedness,” SIAM Journal on Imaging Sciences, vol. 3, no. 4 (Special Section on Optimization in Imaging Sciences). Society for Industrial and Applied Mathematics , pp. 1048–1074, 2010.
View | DOI
 
[39]
2010 | Published | Journal Article | IST-REx-ID: 3697
T. Tuytelaars, C. Lampert, M. Blaschko, and W. Buntine, “Unsupervised object discovery: A comparison,” International Journal of Computer Vision, vol. 88, no. 2. Springer, pp. 284–302, 2010.
View | DOI
 
[38]
2010 | Published | Conference Paper | IST-REx-ID: 3702
J. Kober, K. Mülling, O. Krömer, C. Lampert, B. Schölkopf, and J. Peters, “Movement templates for learning of hitting and batting,” presented at the ICRA: International Conference on Robotics and Automation, 2010, pp. 853–858.
View | DOI | Download (ext.)
 
[37]
2010 | Published | Conference Paper | IST-REx-ID: 3713
C. Lampert, “An efficient divide-and-conquer cascade for nonlinear object detection,” presented at the CVPR: Computer Vision and Pattern Recognition, 2010, pp. 1022–1029.
View | DOI
 
[36]
2010 | Published | Conference Paper | IST-REx-ID: 3793 | OA
S. Nowozin, P. Gehler, and C. Lampert, “On parameter learning in CRF-based approaches to object class image segmentation,” presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6316, pp. 98–111.
[Submitted Version] View | Files available | DOI
 
[35]
2010 | Published | Conference Paper | IST-REx-ID: 3794
C. Lampert and O. Krömer, “Weakly-paired maximum covariance analysis for multimodal dimensionality reduction and transfer learning,” in 11th European Conference on Computer Vision, Heraklion, Crete, Greece, 2010, vol. 6312, pp. 566–579.
View | DOI
 
[34]
2009 | Published | Journal Article | IST-REx-ID: 3696
C. Lampert and M. Blaschko, “Structured prediction by joint kernel support estimation,” Machine Learning, vol. 77, no. 2–3. Springer, pp. 249–269, 2009.
View | DOI
 
[33]
2009 | Published | Conference Poster | IST-REx-ID: 3699
M. Blaschko, C. Lampert, and A. Bartels, Semi-supervised analysis of human fMRI data. Berlin Institute of Technology, 2009.
View | Download (ext.)
 
[32]
2009 | Published | Conference Paper | IST-REx-ID: 3703
M. Blaschko and C. Lampert, “Object localization with global and local context kernels,” presented at the BMVC: British Machine Vision Conference, 2009, pp. 1–11.
View | DOI | Download (ext.)
 
[31]
2009 | Published | Conference Paper | IST-REx-ID: 3704
C. Lampert, H. Nickisch, and S. Harmeling, “Learning to detect unseen object classes by between-class attribute transfer,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 951–958.
View | DOI
 
[30]
2009 | Published | Book | IST-REx-ID: 3707
C. Lampert, Kernel Methods in Computer Vision, vol. 4. now publishers, 2009.
View | DOI
 
[29]
2009 | Published | Conference Paper | IST-REx-ID: 3708
S. Nowozin and C. Lampert, “Global connectivity potentials for random field models,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 818–825.
View | DOI
 
[28]
2009 | Published | Conference Paper | IST-REx-ID: 3709
C. Lampert, “Detecting objects in large image collections and videos by efficient subimage retrieval,” presented at the ICCV: International Conference on Computer Vision, 2009, pp. 987–994.
View | DOI
 
[27]
2009 | Published | Journal Article | IST-REx-ID: 3710
C. Lampert, M. Blaschko, and T. Hofmann, “Efficient subwindow search: A branch and bound framework for object localization,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 12. IEEE, pp. 2129–2142, 2009.
View | DOI | Download (ext.)
 
[26]
2009 | Published | Conference Paper | IST-REx-ID: 3715
C. Lampert and J. Peters, “Active structured learning for high-speed object detection,” presented at the DAGM: German Association For Pattern Recognition, 2009, vol. 5748, pp. 221–231.
View | DOI
 
[25]
2009 | Published | Conference Poster | IST-REx-ID: 3717
C. Lampert and J. Peters, A high-speed object tracker from off-the-shelf components. IEEE, 2009.
View | Download (ext.)
 
[24]
2009 | Published | Conference Paper | IST-REx-ID: 3711 | OA
P. Dhillon, S. Nowozin, and C. Lampert, “Combining appearance and motion for human action classification in videos,” presented at the CVPR: Computer Vision and Pattern Recognition, 2009, pp. 22–29.
View | DOI | Download None (ext.)
 
[23]
2008 | Published | Conference Paper | IST-REx-ID: 3694
M. Goldstein, C. Lampert, M. Reif, A. Stahl, and T. Breuel, “Bayes optimal DDoS mitigation by adaptive history-based IP filtering,” presented at the ICN: International Conference on Networking, 2008, pp. 174–179.
View | DOI | Download (ext.)
 
[22]
2008 | Published | Conference Paper | IST-REx-ID: 3698
M. Blaschko, C. Lampert, and A. Gretton, “Semi-supervised Laplacian regularization of kernel canonical correlation analysis,” presented at the ECML: European Conference on Machine Learning, 2008, vol. 5211, no. Part 1, pp. 133–145.
View | DOI
 
[21]
2008 | Published | Conference Paper | IST-REx-ID: 3700
C. Lampert, “Partitioning of image datasets using discriminative context information,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI | Download (ext.)
 
[20]
2008 | Published | Conference Paper | IST-REx-ID: 3705
M. Blaschko and C. Lampert, “Learning to localize objects with structured output regression,” presented at the ECCV: European Conference on Computer Vision, 2008, vol. 5302, pp. 2–15.
View | DOI | Download (ext.)
 
[19]
2008 | Published | Conference Paper | IST-REx-ID: 3706
C. Lampert and M. Blaschko, “Joint kernel support estimation for structured prediction,” presented at the NIPS SISO: NIPS Workshop on “Structured Input - Structured Output,” 2008, pp. 1–4.
View | Download (ext.)
 
[18]
2008 | Published | Conference Paper | IST-REx-ID: 3712
M. Blaschko and C. Lampert, “Correlational spectral clustering,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI
 
[17]
2008 | Published | Conference Paper | IST-REx-ID: 3714
C. Lampert, M. Blaschko, and T. Hofmann, “Beyond sliding windows: Object localization by efficient subwindow search,” presented at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.
View | DOI | Download (ext.)
 
[16]
2008 | Published | Conference Paper | IST-REx-ID: 3716
C. Lampert and M. Blaschko, “A multiple kernel learning approach to joint multi-class object detection,” presented at the DAGM: German Association For Pattern Recognition, 2008, vol. 5096, pp. 31–40.
View | DOI | Download (ext.)
 
[15]
2007 | Published | Conference Paper | IST-REx-ID: 3681
A. Ulges, C. Lampert, D. Keysers, and T. Breuel, “Optimal dominant motion estimation using adaptive search of transformation space,” presented at the DAGM: German Association For Pattern Recognition, 2007, vol. 4713, pp. 204–213.
View | DOI
 
[14]
2007 | Published | Report | IST-REx-ID: 3687
M. Blaschko, T. Hofmann, and C. Lampert, Efficient subwindow search for object localization, no. 164. Max-Planck-Institute for Biological Cybernetics, 2007.
View | Download (ext.)
 
[13]
2006 | Published | Conference Paper | IST-REx-ID: 3677
A. Ulges, C. Lampert, and D. Keysers, “Spatiogram-based shot distances for video retrieval,” presented at the TRECVID Workshop, 2006, pp. 1–10.
View | Download (ext.)
 
[12]
2006 | Published | Conference Paper | IST-REx-ID: 3679
H. Ali, C. Lampert, and T. Breuel, “Satellite tracks removal in astronomical images,” presented at the CIARP: Iberoamerican Congress in Pattern Recognition, 2006, vol. 4225, pp. 892–901.
View | DOI | Download (ext.)
 
[11]
2006 | Published | Conference Paper | IST-REx-ID: 3680
C. Lampert, L. Mei, and T. Breuel, “Printing technique classification for document counterfeit detection,” presented at the CIS: Computational Intelligence and Security, 2006, vol. 1, pp. 639–634.
View | DOI | Download (ext.)
 
[10]
2006 | Published | Conference Paper | IST-REx-ID: 3683
C. Lampert and T. Breuel, “Objective quality measurement for geometric document image restoration,” presented at the DAS: Document Analysis Systems, 2006.
View | Download (ext.)
 
[9]
2006 | Published | Conference Paper | IST-REx-ID: 3685
C. Lampert, “Machine learning for video compression: Macroblock mode decision,” presented at the ICPR: International Conference on Pattern Recognition, 2006, pp. 936–940.
View | DOI
 
[8]
2006 | Published | Conference Paper | IST-REx-ID: 3692
D. Keysers, C. Lampert, and T. Breuel, “Color image dequantization by constrained diffusion,” presented at the SPIE Electronic Imaging, 2006, vol. 6058.
View | DOI
 
[7]
2006 | Published | Conference Paper | IST-REx-ID: 3693
C. Lampert and O. Wirjadi, “Anisotropic Gaussian filtering using fixed point arithmetic,” presented at the ICIP: IEEE International Conference on Image Processing, 2006, pp. 1565–1568.
View | DOI
 
[6]
2006 | Published | Journal Article | IST-REx-ID: 3695 | OA
C. Lampert and O. Wirjadi, “An optimal non-orthogonal separation of the anisotropic Gaussian convolution filter,” IEEE Transactions on Image Processing (TIP), vol. 15, no. 11. IEEE, pp. 3501–3513, 2006.
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[5]
2005 | Published | Conference Paper | IST-REx-ID: 3684
C. Lampert, T. Braun, A. Ulges, D. Keysers, and T. Breuel, “Oblivious document capture and real-time retrieval,” presented at the CBDAR: Camera Based Document Analysis and Recognition , 2005, pp. 79–86.
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[4]
2005 | Published | Conference Paper | IST-REx-ID: 3689
A. Ulges, C. Lampert, and T. Breuel, “Document image dewarping using robust estimation of curled text lines,” presented at the ICDAR: International Conference on Document Analysis and Recognition, 2005, vol. 2, pp. 1001–1005.
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[3]
2005 | Published | Journal Article | IST-REx-ID: 3691
C. Lampert, “Boundary regularity of admissible operators,” Publicacions Matemàtiques, vol. 49, no. 1. Universitat Autònoma de Barcelona, Departament de Matemàtique, pp. 179–195, 2005.
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[2]
2004 | Published | Conference Paper | IST-REx-ID: 3688
A. Ulges, C. Lampert, and T. Breuel, “Document capture using stereo vision,” presented at the DocEng: ACM Symposium on Document Engineering, 2004, pp. 198–200.
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[1]
2003 | Published | Thesis | IST-REx-ID: 3678
C. Lampert, “The Neumann operator in strictly pseudoconvex domains with weighted Bergman metric ,” Universität Bonn, Fachbibliothek Mathematik, 2003.
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