Pentina, Anastasia, and Ruth Urner. “Lifelong Learning with Weighted Majority Votes,” 29:3619–27. Neural Information Processing Systems, 2016.

Kolesnikov, Alexander, and Christoph Lampert. “Improving Weakly-Supervised Object Localization by Micro-Annotation.”https://doi.org/10.5244/C.30.92__In Proceedings of the British Machine Vision Conference 2016, 2016–September:92.1-92.12. BMVA Press, 2016.https://doi.org/10.5244/C.30.92 .

Martius, Georg S, Raphael Hostettler, Alois Knoll, and Ralf Der. “Compliant Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic Arm,”https://doi.org/10.1109/IROS.2016.7759138__Vol. 2016–November. IEEE, 2016.https://doi.org/10.1109/IROS.2016.7759138 .

Kolesnikov, Alexander, and Christoph Lampert. “Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation,”https://doi.org/10.1007/978-3-319-46493-0_42__9908:695–711. Springer, 2016.https://doi.org/10.1007/978-3-319-46493-0_42 .

Pielorz, Jasmin, and Christoph Lampert. “Optimal Geospatial Allocation of Volunteers for Crisis Management.”https://doi.org/10.1109/ICT-DM.2015.7402041__IEEE, 2016.https://doi.org/10.1109/ICT-DM.2015.7402041 .

Martius, Georg S, Rafael Hostettler, Alois Knoll, and Ralf Der. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.”https://doi.org/10.7551/978-0-262-33936-0-ch029__In Proceedings of the Artificial Life Conference 2016, 28:142–43. MIT Press, 2016.https://doi.org/10.7551/978-0-262-33936-0-ch029 .

Pentina, Anastasia. “Theoretical Foundations of Multi-Task Lifelong Learning.”https://doi.org/10.15479/AT:ISTA:TH_776__Institute of Science and Technology Austria, 2016.https://doi.org/10.15479/AT:ISTA:TH_776 .

Pentina, Anastasia, and Christoph Lampert. “Lifelong Learning with Non-i.i.d. Tasks,” 2015:1540–48. Neural Information Processing Systems, 2015.

Xia, Wei, Csaba Domokos, Junjun Xiong, Loongfah Cheong, and Shuicheng Yan. “Segmentation over Detection via Optimal Sparse Reconstructions.”https://doi.org/10.1109/TCSVT.2014.2379972__IEEE Transactions on Circuits and Systems for Video Technology. IEEE, 2015.https://doi.org/10.1109/TCSVT.2014.2379972 .

Der, Ralf, and Georg S Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.”https://doi.org/10.1073/pnas.1508400112__PNAS. National Academy of Sciences, 2015.https://doi.org/10.1073/pnas.1508400112 .

Pentina, Anastasia, and Shai Ben David. “Multi-Task and Lifelong Learning of Kernels,”https://doi.org/10.1007/978-3-319-24486-0_13__9355:194–208. Springer, 2015.https://doi.org/10.1007/978-3-319-24486-0_13 .

Shah, Neel, Vladimir Kolmogorov, and Christoph Lampert. “A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly Max-Oracle,”https://doi.org/10.1109/CVPR.2015.7298890__2737–45. IEEE, 2015.https://doi.org/10.1109/CVPR.2015.7298890 .

Royer, Amélie, and Christoph Lampert. “Classifier Adaptation at Prediction Time,”https://doi.org/10.1109/CVPR.2015.7298746__1401–9. IEEE, 2015.https://doi.org/10.1109/CVPR.2015.7298746 .

Lampert, Christoph. “Predicting the Future Behavior of a Time-Varying Probability Distribution,”https://doi.org/10.1109/CVPR.2015.7298696__942–50. IEEE, 2015.https://doi.org/10.1109/CVPR.2015.7298696 .

Pentina, Anastasia, Viktoriia Sharmanska, and Christoph Lampert. “Curriculum Learning of Multiple Tasks,”https://doi.org/10.1109/CVPR.2015.7299188__5492–5500. IEEE, 2015.https://doi.org/10.1109/CVPR.2015.7299188 .

Martius, Georg S, and Eckehard Olbrich. “Quantifying Self-Organizing Behavior of Autonomous Robots.”https://doi.org/10.7551/978-0-262-33027-5-ch018__In Proceedings of the 13th European Conference on Artificial Life, 78. MIT Press, 2015.https://doi.org/10.7551/978-0-262-33027-5-ch018 .

Sharmanska, Viktoriia. “Learning with Attributes for Object Recognition: Parametric and Non-Parametrics Views.”https://doi.org/10.15479/at:ista:1401__Institute of Science and Technology Austria, 2015.https://doi.org/10.15479/at:ista:1401 .

Martius, Georg S, and Eckehard Olbrich. “Quantifying Emergent Behavior of Autonomous Robots.”https://doi.org/10.3390/e17107266__Entropy. MDPI, 2015.https://doi.org/10.3390/e17107266 .

Muelling, Katharina, Oliver Kroemer, Christoph Lampert, and Bernhard Schölkopf. “Movement Templates for Learning of Hitting and Batting.”https://doi.org/10.1007/978-3-319-03194-1_3__In Learning Motor Skills, edited by Jens Kober and Jan Peters, 97:69–82. From Algorithms to Robot Experiments. Springer, 2014.https://doi.org/10.1007/978-3-319-03194-1_3 .

Hernandez Lobato, Daniel, Viktoriia Sharmanska, Kristian Kersting, Christoph Lampert, and Novi Quadrianto. “Mind the Nuisance: Gaussian Process Classification Using Privileged Noise.” In Advances in Neural Information Processing Systems, 1:837–45. Neural Information Processing Systems, 2014.

Morvant, Emilie, Amaury Habrard, and Stéphane Ayache. “Majority Vote of Diverse Classifiers for Late Fusion.”https://doi.org/10.1007/978-3-662-44415-3_16__In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8621:153–62. Springer, 2014.https://doi.org/10.1007/978-3-662-44415-3_16 .

Kolesnikov, Alexander, Matthieu Guillaumin, Vittorio Ferrari, and Christoph Lampert. “Closed-Form Approximate CRF Training for Scalable Image Segmentation.”https://doi.org/10.1007/978-3-319-10578-9_36__In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), edited by David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars, 8691:550–65. Springer, 2014.https://doi.org/10.1007/978-3-319-10578-9_36 .

Khamis, Sameh, and Christoph Lampert. “CoConut: Co-Classification with Output Space Regularization.” In Proceedings of the British Machine Vision Conference 2014. BMVA Press, 2014.

Sydorov, Vladyslav, Mayu Sakurada, and Christoph Lampert. “Deep Fisher Kernels – End to End Learning of the Fisher Kernel GMM Parameters.”https://doi.org/10.1109/CVPR.2014.182__In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1402–9. IEEE, 2014.https://doi.org/10.1109/CVPR.2014.182 .

Bellet, Aurélien, Amaury Habrard, Emilie Morvant, and Marc Sebban. “Learning a Priori Constrained Weighted Majority Votes.”https://doi.org/10.1007/s10994-014-5462-z__Machine Learning. Springer, 2014.https://doi.org/10.1007/s10994-014-5462-z .

Morvant, Emilie. “Adaptation de Domaine de Vote de Majorité Par Auto-Étiquetage Non Itératif,” 1:49–58. Elsevier, 2014.

Pentina, Anastasia, and Christoph Lampert. “A PAC-Bayesian Bound for Lifelong Learning,” 32:991–99. ML Research Press, 2014.

Kazmar, Tomas, Evgeny Kvon, Alexander Stark, and Christoph Lampert. “Drosophila Embryo Stage Annotation Using Label Propagation.”https://doi.org/10.1109/ICCV.2013.139__IEEE, 2013.https://doi.org/10.1109/ICCV.2013.139 .

Sharmanska, Viktoriia, Novi Quadrianto, and Christoph Lampert. “Learning to Rank Using Privileged Information,”https://doi.org/10.1109/ICCV.2013.107__825–32. IEEE, 2013.https://doi.org/10.1109/ICCV.2013.107 .

Lampert, Christoph, Hannes Nickisch, and Stefan Harmeling. “Attribute-Based Classification for Zero-Shot Learning of Object Categories.”https://doi.org/10.1109/TPAMI.2013.140__IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2013.https://doi.org/10.1109/TPAMI.2013.140 .

Quadrianto, Novi, Viktoriia Sharmanska, David Knowles, and Zoubin Ghahramani. “The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models.” In Proceedings of the 29th Conference Uncertainty in Artificial Intelligence, 527–36. AUAI Press, 2013.

Chen, Chao, Vladimir Kolmogorov, Zhu Yan, Dimitris Metaxas, and Christoph Lampert. “Computing the M Most Probable Modes of a Graphical Model,” 31:161–69. JMLR, 2013.

Tommasi, Tatiana, Novi Quadrianto, Barbara Caputo, and Christoph Lampert. “Beyond Dataset Bias: Multi-Task Unaligned Shared Knowledge Transfer.”https://doi.org/10.1007/978-3-642-37331-2_1__Lecture Notes in Computer Science. Springer, 2013.https://doi.org/10.1007/978-3-642-37331-2_1 .

Quadrianto, Novi, and Christoph Lampert. “Kernel Based Learning.”https://doi.org/10.1007/978-1-4419-9863-7_604__In Encyclopedia of Systems Biology, edited by Werner Dubitzky, Olaf Wolkenhauer, Kwang Cho, and Hiroki Yokota, 3:1069–1069. Springer, 2013.https://doi.org/10.1007/978-1-4419-9863-7_604 .

Lampert, Christoph. “Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction,” 1:82–90. Neural Information Processing Systems, 2012.

Blaschko, Matthew, and Christoph Lampert. “Guest Editorial: Special Issue on Structured Prediction and Inference.”https://doi.org/10.1007/s11263-012-0530-y__International Journal of Computer Vision. Springer, 2012.https://doi.org/10.1007/s11263-012-0530-y .

Sharmanska, Viktoriia, Novi Quadrianto, and Christoph Lampert. “Augmented Attribute Representations,”https://doi.org/10.1007/978-3-642-33715-4_18__7576:242–55. Springer, 2012.https://doi.org/10.1007/978-3-642-33715-4_18 .

Müller, Andreas, Sebastian Nowozin, and Christoph Lampert. “Information Theoretic Clustering Using Minimal Spanning Trees,”https://doi.org/10.1007/978-3-642-32717-9_21__7476:205–15. Springer, 2012.https://doi.org/10.1007/978-3-642-32717-9_21 .

Lampert, Christoph, and Jan Peters. “Real-Time Detection of Colored Objects in Multiple Camera Streams with off-the-Shelf Hardware Components.”https://doi.org/10.1007/s11554-010-0168-3__Journal of Real-Time Image Processing. Springer, 2012.https://doi.org/10.1007/s11554-010-0168-3 .

Korc, Filip, Vladimir Kolmogorov, and Christoph Lampert. “Approximating Marginals Using Discrete Energy Minimization.” ICML, 2012.

Korc, Filip, Vladimir Kolmogorov, and Christoph Lampert. Approximating Marginals Using Discrete Energy Minimization. IST Austria, 2012.https://doi.org/10.15479/AT:IST-2012-0003 .

Kroemer, Oliver, Christoph Lampert, and Jan Peters. “Multi-Modal Learning for Dynamic Tactile Sensing.” Deutsches Zentrum für Luft und Raumfahrt, 2012.

Quadrianto, Novi, Christoph Lampert, and Chao Chen. “The Most Persistent Soft-Clique in a Set of Sampled Graphs.” In Proceedings of the 29th International Conference on Machine Learning, 211–18. ML Research Press, 2012.

Wang, Zhikun, Christoph Lampert, Katharina Mülling, Bernhard Schölkopf, and Jan Peters. “Learning Anticipation Policies for Robot Table Tennis,”https://doi.org/10.1109/IROS.2011.6094892__332–37. IEEE, 2011.https://doi.org/10.1109/IROS.2011.6094892 .

Blaschko, Matthew, Jacquelyn Shelton, Andreas Bartels, Christoph Lampert, and Arthur Gretton. “Semi Supervised Kernel Canonical Correlation Analysis with Application to Human FMRI.”https://doi.org/10.1016/j.patrec.2011.02.011__Pattern Recognition Letters. Elsevier, 2011.https://doi.org/10.1016/j.patrec.2011.02.011 .

Kroemer, Oliver, Christoph Lampert, and Jan Peters. “Learning Dynamic Tactile Sensing with Robust Vision Based Training.”https://doi.org/10.1109/TRO.2011.2121130__IEEE Transactions on Robotics. IEEE, 2011.https://doi.org/10.1109/TRO.2011.2121130 .

Chen, Chao, Daniel Freedman, and Christoph Lampert. Enforcing Topological Constraints in Random Field Image Segmentation. IST Austria, 2011.https://doi.org/10.15479/AT:IST-2011-0002 .

Chen, Chao, Daniel Freedman, and Christoph Lampert. “Enforcing Topological Constraints in Random Field Image Segmentation.”https://doi.org/10.1109/CVPR.2011.5995503__In CVPR: Computer Vision and Pattern Recognition, 2089–96. IEEE, 2011.https://doi.org/10.1109/CVPR.2011.5995503 .

Lampert, Christoph. “Maximum Margin Multi-Label Structured Prediction.” Neural Information Processing Systems, 2011.

Lampert, Christoph. Maximum Margin Multi Label Structured Prediction. NIPS: Neural Information Processing Systems. Neural Information Processing Systems Foundation, 2011.

Nowozin, Sebastian, and Christoph Lampert. “Structured Learning and Prediction in Computer Vision.”https://doi.org/10.1561/0600000033__Foundations and Trends in Computer Graphics and Vision. Now Publishers, 2011.https://doi.org/10.1561/0600000033 .

Quadrianto, Novi, and Christoph Lampert. “Learning Multi-View Neighborhood Preserving Projections,” 425–32. ML Research Press, 2011.

Lampert, Christoph, and Oliver Krömer. “Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer Learning,”https://doi.org/10.1007/978-3-642-15552-9_41__6312:566–79. Springer, 2010.https://doi.org/10.1007/978-3-642-15552-9_41 .

Nowozin, Sebastian, Peter Gehler, and Christoph Lampert. “On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation,”https://doi.org/10.1007/978-3-642-15567-3_8__6316:98–111. Springer, 2010.https://doi.org/10.1007/978-3-642-15567-3_8 .