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ORCIDChristoph H. Lampert
Christoph Lampert
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- affiliation: Institute of Science and Technology Austria, Klosterneuburg, Austria
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2020 – today
- 2024
[j20]Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven:
Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 2024 (2024)- [c86]Bernd Prach, Fabio Brau, Giorgio C. Buttazzo, Christoph H. Lampert:
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness. CVPR 2024: 24574-24583 - [c85]Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert:
PeFLL: Personalized Federated Learning by Learning to Learn. ICLR 2024 - [c84]Hossein Zakerinia, Amin Behjati, Christoph H. Lampert:
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms. ICML 2024 - [i58]Hossein Zakerinia, Amin Behjati, Christoph H. Lampert:
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms. CoRR abs/2402.04054 (2024) - [i57]Egor Zverev, Sahar Abdelnabi, Mario Fritz, Christoph H. Lampert:
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That? CoRR abs/2403.06833 (2024) - [i56]Nikita Kalinin, Christoph Lampert:
Banded Square Root Matrix Factorization for Differentially Private Model Training. CoRR abs/2405.13763 (2024) - [i55]Peter Súkeník, Marco Mondelli, Christoph Lampert:
Neural Collapse versus Low-rank Bias: Is Deep Neural Collapse Really Optimal? CoRR abs/2405.14468 (2024) - [i54]Nikita P. Kalinin, Simone Bombari, Hossein Zakerinia, Christoph H. Lampert:
DP-KAN: Differentially Private Kolmogorov-Arnold Networks. CoRR abs/2407.12569 (2024) - [i53]Bernd Prach, Christoph H. Lampert:
Intriguing Properties of Robust Classification. CoRR abs/2412.04245 (2024) - 2023
- [j19]Jonathan Scott, Michelle Yeo, Christoph H. Lampert:
Cross-client Label Propagation for Transductive and Semi-Supervised Federated Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c83]Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh:
CrAM: A Compression-Aware Minimizer. ICLR 2023 - [c82]Peter Súkeník, Marco Mondelli, Christoph H. Lampert:
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. NeurIPS 2023 - [i52]Kateryna Lutsai, Christoph H. Lampert:
Geolocation Predicting of Tweets Using BERT-Based Models. CoRR abs/2303.07865 (2023) - [i51]Peter Súkeník, Marco Mondelli, Christoph Lampert:
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. CoRR abs/2305.13165 (2023) - [i50]Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert:
PeFLL: A Lifelong Learning Approach to Personalized Federated Learning. CoRR abs/2306.05515 (2023) - [i49]Bernd Prach, Christoph H. Lampert:
1-Lipschitz Neural Networks are more expressive with N-Activations. CoRR abs/2311.06103 (2023) - [i48]Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven:
Continual Learning: Applications and the Road Forward. CoRR abs/2311.11908 (2023) - [i47]Bernd Prach, Fabio Brau, Giorgio C. Buttazzo, Christoph H. Lampert:
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness. CoRR abs/2311.16833 (2023) - [i46]Paniz Halvachi, Alexandra Peste, Dan Alistarh, Christoph H. Lampert:
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network Deployment. CoRR abs/2312.06872 (2023) - 2022
- [j18]Nikola Konstantinov, Christoph H. Lampert:
Fairness-Aware PAC Learning from Corrupted Data. J. Mach. Learn. Res. 23: 160:1-160:60 (2022) - [j17]Eugenia Iofinova, Nikola Konstantinov, Christoph H. Lampert:
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data. Trans. Mach. Learn. Res. 2022 (2022) - [c81]Bernd Prach, Christoph H. Lampert:
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. ECCV (21) 2022: 350-365 - [c80]Paulina Tomaszewska
, Christoph H. Lampert:
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift. ICPR 2022: 2128-2134 - [c79]Paulina Tomaszewska, Christoph H. Lampert:
On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) Under Class-Prior Shift. RRPR 2022: 67-73 - [i45]Paulina Tomaszewska, Christoph H. Lampert:
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift. CoRR abs/2206.05181 (2022) - [i44]Alexandra Peste, Adrian Vladu, Dan Alistarh, Christoph H. Lampert:
CrAM: A Compression-Aware Minimizer. CoRR abs/2207.14200 (2022) - [i43]Bernd Prach, Christoph H. Lampert:
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. CoRR abs/2208.03160 (2022) - [i42]Peter Súkeník, Christoph H. Lampert:
Generalization In Multi-Objective Machine Learning. CoRR abs/2208.13499 (2022) - [i41]Jonathan Scott, Michelle Yeo, Christoph H. Lampert:
FedProp: Cross-client Label Propagation for Federated Semi-supervised Learning. CoRR abs/2210.06434 (2022) - 2021
- [c78]Nikola Konstantinov, Christoph H. Lampert:
On the Impossibility of Fairness-Aware Learning from Corrupted Data. AFCR 2021: 59-83 - [c77]Jasmin Lampert, Christoph H. Lampert:
Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis. IEEE BigData 2021: 5185-5192 - [c76]Mary Phuong, Christoph H. Lampert:
The inductive bias of ReLU networks on orthogonally separable data. ICLR 2021 - [i40]Nikola Konstantinov, Christoph H. Lampert:
Fairness Through Regularization for Learning to Rank. CoRR abs/2102.05996 (2021) - [i39]Nikola Konstantinov, Christoph H. Lampert:
Fairness-Aware Learning from Corrupted Data. CoRR abs/2102.06004 (2021) - [i38]Mary Phuong, Christoph H. Lampert:
Towards Understanding Knowledge Distillation. CoRR abs/2105.13093 (2021) - [i37]Paul Henderson, Christoph H. Lampert, Bernd Bickel:
Unsupervised Video Prediction from a Single Frame by Estimating 3D Dynamic Scene Structure. CoRR abs/2106.09051 (2021) - [i36]Eugenia Iofinova, Nikola Konstantinov, Christoph H. Lampert:
FLEA: Provably Fair Multisource Learning from Unreliable Training Data. CoRR abs/2106.11732 (2021) - [i35]Alexandra Peste, Dan Alistarh, Christoph H. Lampert:
SSSE: Efficiently Erasing Samples from Trained Machine Learning Models. CoRR abs/2107.03860 (2021) - 2020
- [j16]Rémy Sun, Christoph H. Lampert:
KS(conf): A Light-Weight Test if a Multiclass Classifier Operates Outside of Its Specifications. Int. J. Comput. Vis. 128(4): 970-995 (2020) - [j15]Rémy Sun, Christoph H. Lampert:
Correction to: KS(conf): A Light-Weight Test if a Multiclass Classifier Operates Outside of Its Specifications. Int. J. Comput. Vis. 128(4): 996 (2020) - [c75]Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert:
Leveraging 2D Data to Learn Textured 3D Mesh Generation. CVPR 2020: 7495-7504 - [c74]Václav Volhejn, Christoph Lampert:
Does SGD Implicitly Optimize for Smoothness? GCPR 2020: 246-259 - [c73]Mary Phuong, Christoph H. Lampert:
Functional vs. parametric equivalence of ReLU networks. ICLR 2020 - [c72]Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph Lampert:
On the Sample Complexity of Adversarial Multi-Source PAC Learning. ICML 2020: 5416-5425 - [c71]Paul Henderson, Christoph H. Lampert:
Unsupervised object-centric video generation and decomposition in 3D. NeurIPS 2020 - [c70]Amélie Royer, Christoph H. Lampert:
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios. WACV 2020: 1716-1725 - [c69]Amélie Royer, Christoph H. Lampert:
A Flexible Selection Scheme for Minimum-Effort Transfer Learning. WACV 2020: 2180-2189 - [i34]Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph H. Lampert:
On the Sample Complexity of Adversarial Multi-Source PAC Learning. CoRR abs/2002.10384 (2020) - [i33]Titas Anciukevicius, Christoph H. Lampert, Paul Henderson:
Object-Centric Image Generation with Factored Depths, Locations, and Appearances. CoRR abs/2004.00642 (2020) - [i32]Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert:
Leveraging 2D Data to Learn Textured 3D Mesh Generation. CoRR abs/2004.04180 (2020) - [i31]Amelie Royer, Christoph H. Lampert:
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios. CoRR abs/2004.12623 (2020) - [i30]Paul Henderson, Christoph H. Lampert:
Unsupervised object-centric video generation and decomposition in 3D. CoRR abs/2007.06705 (2020) - [i29]Amelie Royer, Christoph H. Lampert:
A Flexible Selection Scheme for Minimum-Effort Transfer Learning. CoRR abs/2008.11995 (2020)
2010 – 2019
- 2019
- [j14]Yongqin Xian, Christoph H. Lampert, Bernt Schiele, Zeynep Akata:
Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2251-2265 (2019) - [c68]Mary Phuong, Christoph Lampert:
Distillation-Based Training for Multi-Exit Architectures. ICCV 2019: 1355-1364 - [c67]Alexander Kolesnikov, Alina Kuznetsova, Christoph Lampert, Vittorio Ferrari:
Detecting Visual Relationships Using Box Attention. ICCV Workshops 2019: 1749-1753 - [c66]Nikola Konstantinov, Christoph Lampert:
Robust Learning from Untrusted Sources. ICML 2019: 3488-3498 - [c65]Mary Phuong, Christoph Lampert:
Towards Understanding Knowledge Distillation. ICML 2019: 5142-5151 - [c64]Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman:
Strategy Representation by Decision Trees with Linear Classifiers. QEST 2019: 109-128 - [i28]Nikola Konstantinov, Christoph Lampert:
Robust Learning from Untrusted Sources. CoRR abs/1901.10310 (2019) - [i27]Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman:
Strategy Representation by Decision Trees with Linear Classifiers. CoRR abs/1906.08178 (2019) - 2018
- [j13]Trevor Darrell, Christoph Lampert, Nicu Sebe, Ying Wu, Yan Yan:
Guest Editors' Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 40(5): 1029-1031 (2018) - [c63]Ksenia Konyushkova, Jasper R. R. Uijlings, Christoph H. Lampert, Vittorio Ferrari:
Learning Intelligent Dialogs for Bounding Box Annotation. CVPR 2018: 9175-9184 - [c62]Rémy Sun, Christoph H. Lampert:
KS(conf): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications. GCPR 2018: 244-259 - [c61]Ilja Kuzborskij, Christoph H. Lampert:
Data-Dependent Stability of Stochastic Gradient Descent. ICML 2018: 2820-2829 - [c60]Subham S. Sahoo, Christoph H. Lampert, Georg Martius:
Learning Equations for Extrapolation and Control. ICML 2018: 4439-4447 - [i26]Alexander Zimin, Christoph H. Lampert:
Towards Practical Conditional Risk Minimization. CoRR abs/1801.00507 (2018) - [i25]Rémy Sun, Christoph H. Lampert:
KS(conf ): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications. CoRR abs/1804.04171 (2018) - [i24]Subham S. Sahoo, Christoph H. Lampert, Georg Martius:
Learning Equations for Extrapolation and Control. CoRR abs/1806.07259 (2018) - [i23]Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari:
Detecting Visual Relationships Using Box Attention. CoRR abs/1807.02136 (2018) - [i22]Ehsan Pajouheshgar, Christoph H. Lampert:
Back to square one: probabilistic trajectory forecasting without bells and whistles. CoRR abs/1812.02984 (2018) - 2017
- [c59]Alexander Zimin, Christoph H. Lampert:
Learning Theory for Conditional Risk Minimization. AISTATS 2017: 213-222 - [c58]Jasmin Pielorz, Matthias Prandtstetter, Markus Straub, Christoph H. Lampert:
Optimal geospatial volunteer allocation needs realistic distances. IEEE BigData 2017: 3760-3763 - [c57]Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert:
Probabilistic Image Colorization. BMVC 2017 - [c56]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CVPR 2017: 5533-5542 - [c55]Georg Martius, Christoph H. Lampert:
Extrapolation and learning equations. ICLR (Workshop) 2017 - [c54]Alexander Kolesnikov, Christoph H. Lampert:
PixelCNN Models with Auxiliary Variables for Natural Image Modeling. ICML 2017: 1905-1914 - [c53]Anastasia Pentina, Christoph H. Lampert:
Multi-task Learning with Labeled and Unlabeled Tasks. ICML 2017: 2807-2816 - [i21]Ilja Kuzborskij, Christoph H. Lampert:
Data-Dependent Stability of Stochastic Gradient Descent. CoRR abs/1703.01678 (2017) - [i20]Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert:
Probabilistic Image Colorization. CoRR abs/1705.04258 (2017) - [i19]Yongqin Xian, Christoph H. Lampert, Bernt Schiele, Zeynep Akata:
Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly. CoRR abs/1707.00600 (2017) - [i18]Ksenia Konyushkova, Jasper R. R. Uijlings, Christoph H. Lampert, Vittorio Ferrari:
Learning Intelligent Dialogs for Bounding Box Annotation. CoRR abs/1712.08087 (2017) - 2016
- [c52]Alexander Kolesnikov, Christoph H. Lampert:
Improving Weakly-Supervised Object Localization By Micro-Annotation. BMVC 2016 - [c51]Alexander Kolesnikov, Christoph H. Lampert:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. ECCV (4) 2016: 695-711 - [i17]Anastasia Pentina, Christoph H. Lampert:
Active Task Selection for Multi-Task Learning. CoRR abs/1602.06518 (2016) - [i16]Alexander Kolesnikov, Christoph H. Lampert:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. CoRR abs/1603.06098 (2016) - [i15]Alexander Kolesnikov, Christoph H. Lampert:
Improving Weakly-Supervised Object Localization By Micro-Annotation. CoRR abs/1605.05538 (2016) - [i14]Georg Martius, Christoph H. Lampert:
Extrapolation and learning equations. CoRR abs/1610.02995 (2016) - [i13]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CoRR abs/1611.07725 (2016) - [i12]Alexander Kolesnikov, Christoph H. Lampert:
Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition. CoRR abs/1612.08185 (2016) - 2015
- [c50]Christoph H. Lampert:
Predicting the future behavior of a time-varying probability distribution. CVPR 2015: 942-950 - [c49]Amelie Royer, Christoph H. Lampert:
Classifier adaptation at prediction time. CVPR 2015: 1401-1409 - [c48]Neel Shah, Vladimir Kolmogorov, Christoph H. Lampert:
A multi-plane block-coordinate frank-wolfe algorithm for training structural SVMs with a costly max-oracle. CVPR 2015: 2737-2745 - [c47]Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert:
Curriculum learning of multiple tasks. CVPR 2015: 5492-5500 - [c46]Jasmin Pielorz, Christoph H. Lampert:
Optimal geospatial allocation of volunteers for crisis management. ICT-DM 2015: 152-158 - [c45]Anastasia Pentina, Christoph H. Lampert:
Lifelong Learning with Non-i.i.d. Tasks. NIPS 2015: 1540-1548 - [i11]Alexander Kolesnikov, Christoph H. Lampert:
Identifying Reliable Annotations for Large Scale Image Segmentation. CoRR abs/1504.07460 (2015) - [i10]Alexander Zimin, Christoph H. Lampert:
Conditional Risk Minimization for Stochastic Processes. CoRR abs/1510.02706 (2015) - 2014
- [j12]Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling:
Attribute-Based Classification for Zero-Shot Visual Object Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 36(3): 453-465 (2014) - [c44]Sameh Khamis, Christoph H. Lampert:
CoConut: Co-Classification with Output Space Regularization. BMVC 2014 - [c43]Vladyslav Sydorov, Mayu Sakurada, Christoph H. Lampert:
Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters. CVPR 2014: 1402-1409 - [c42]Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert:
Closed-Form Approximate CRF Training for Scalable Image Segmentation. ECCV (3) 2014: 550-565 - [c41]Anastasia Pentina, Christoph H. Lampert:
A PAC-Bayesian bound for Lifelong Learning. ICML 2014: 991-999 - [c40]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS 2014: 837-845 - [i9]Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert:
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation. CoRR abs/1403.7057 (2014) - [i8]Vladimir Kolmogorov, Christoph H. Lampert, Emilie Morvant, Rustem Takhanov:
Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014. CoRR abs/1404.3538 (2014) - [i7]Christoph H. Lampert:
Blind Domain Adaptation: An RKHS Approach. CoRR abs/1406.5362 (2014) - [i6]Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR abs/1407.0179 (2014) - [i5]Neel Shah, Vladimir Kolmogorov, Christoph H. Lampert:
A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Structural SVMs with a Costly max-Oracle. CoRR abs/1408.6804 (2014) - [i4]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Learning to Transfer Privileged Information. CoRR abs/1410.0389 (2014) - [i3]Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert:
Curriculum Learning of Multiple Tasks. CoRR abs/1412.1353 (2014) - 2013
- [c39]Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris N. Metaxas, Christoph H. Lampert:
Computing the M Most Probable Modes of a Graphical Model. AISTATS 2013: 161-169 - [c38]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Learning to Rank Using Privileged Information. ICCV 2013: 825-832 - [c37]Tomas Kazmar, Evgeny Z. Kvon, Alexander Stark, Christoph H. Lampert:
Drosophila Embryo Stage Annotation Using Label Propagation. ICCV 2013: 1089-1096 - [i2]Anastasia Pentina, Christoph H. Lampert:
A PAC-Bayesian bound for Lifelong Learning. CoRR abs/1311.2838 (2013) - 2012
- [j11]Matthew B. Blaschko, Christoph H. Lampert:
Guest Editorial: Special Issue on Structured Prediction and Inference. Int. J. Comput. Vis. 99(3): 257-258 (2012) - [j10]Christoph H. Lampert, Jan Peters:
Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. J. Real Time Image Process. 7(1): 31-41 (2012) - [c36]Tatiana Tommasi, Novi Quadrianto, Barbara Caputo, Christoph H. Lampert:
Beyond Dataset Bias: Multi-task Unaligned Shared Knowledge Transfer. ACCV (1) 2012: 1-15 - [c35]Andreas C. Müller, Sebastian Nowozin, Christoph H. Lampert:
Information Theoretic Clustering Using Minimum Spanning Trees. DAGM/OAGM Symposium 2012: 205-215 - [c34]Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert:
Augmented Attribute Representations. ECCV (5) 2012: 242-255 - [c33]Novi Quadrianto, Chao Chen, Christoph H. Lampert:
The Most Persistent Soft-Clique in a Set of Sampled Graphs. ICML 2012 - [c32]Christoph H. Lampert:
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction. NIPS 2012: 82-90 - [i1]Novi Quadrianto, Chao Chen, Christoph H. Lampert:
The Most Persistent Soft-Clique in a Set of Sampled Graphs. CoRR abs/1206.4652 (2012) - 2011
- [j9]Sebastian Nowozin, Christoph H. Lampert:
Structured Learning and Prediction in Computer Vision. Found. Trends Comput. Graph. Vis. 6(3-4): 185-365 (2011) - [j8]Matthew B. Blaschko, Jacquelyn A. Shelton, Andreas M. Bartels, Christoph H. Lampert, Arthur Gretton:
Semi-supervised kernel canonical correlation analysis with application to human fMRI. Pattern Recognit. Lett. 32(11): 1572-1583 (2011) - [j7]Oliver Kroemer, Christoph H. Lampert, Jan Peters:
Learning Dynamic Tactile Sensing With Robust Vision-Based Training. IEEE Trans. Robotics 27(3): 545-557 (2011) - [c31]Chao Chen, Daniel Freedman, Christoph H. Lampert:
Enforcing topological constraints in random field image segmentation. CVPR 2011: 2089-2096 - [c30]