Christoph H. Lampert

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 85

Top Venues

Publications

Nikita P. Kalinin, Simone Bombari, Hossein Zakerinia, Christoph H. Lampert
DP-KAN: Differentially Private Kolmogorov-Arnold Networks. CoRR (2024)
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)
Hossein Zakerinia, Amin Behjati, Christoph H. Lampert
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms. CoRR (2024)
Egor Zverev, Sahar Abdelnabi, Mario Fritz, Christoph H. Lampert
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That? CoRR (2024)
Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert
PeFLL: Personalized Federated Learning by Learning to Learn. ICLR (2024)
Eli Verwimp, 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 (2023)
Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert
PeFLL: A Lifelong Learning Approach to Personalized Federated Learning. CoRR (2023)
Bernd Prach, Christoph H. Lampert
1-Lipschitz Neural Networks are more expressive with N-Activations. CoRR (2023)
Peter Súkeník, Marco Mondelli, Christoph H. Lampert
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. NeurIPS (2023)
Bernd Prach, Fabio Brau, Giorgio C. Buttazzo, Christoph H. Lampert
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness. CoRR (2023)
Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh
CrAM: A Compression-Aware Minimizer. ICLR (2023)
Paniz Halvachi, Alexandra Peste, Dan Alistarh, Christoph H. Lampert
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network Deployment. CoRR (2023)
Kateryna Lutsai, Christoph H. Lampert
Geolocation Predicting of Tweets Using BERT-Based Models. CoRR (2023)
Jonathan Scott, Michelle Yeo, Christoph H. Lampert
Cross-client Label Propagation for Transductive and Semi-Supervised Federated Learning. Trans. Mach. Learn. Res. 2023 (2023)
Bernd Prach, Christoph H. Lampert
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. ECCV (21) (2022)
Paulina Tomaszewska, Christoph H. Lampert
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift. ICPR (2022)
Nikola Konstantinov, Christoph H. Lampert
Fairness-Aware PAC Learning from Corrupted Data. J. Mach. Learn. Res. 23 (2022)
Paulina Tomaszewska, Christoph H. Lampert
On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) Under Class-Prior Shift. RRPR (2022)
Peter Súkeník, Christoph H. Lampert
Generalization In Multi-Objective Machine Learning. CoRR (2022)
Jonathan Scott, Michelle Yeo, Christoph H. Lampert
FedProp: Cross-client Label Propagation for Federated Semi-supervised Learning. CoRR (2022)
Paulina Tomaszewska, Christoph H. Lampert
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift. CoRR (2022)
Alexandra Peste, Adrian Vladu, Dan Alistarh, Christoph H. Lampert
CrAM: A Compression-Aware Minimizer. CoRR (2022)
Eugenia Iofinova, Nikola Konstantinov, Christoph H. Lampert
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data. Trans. Mach. Learn. Res. 2022 (2022)
Bernd Prach, Christoph H. Lampert
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. CoRR (2022)
Nikola Konstantinov, Christoph H. Lampert
On the Impossibility of Fairness-Aware Learning from Corrupted Data. AFCR (2021)
Mary Phuong, Christoph H. Lampert
Towards Understanding Knowledge Distillation. CoRR (2021)
Nikola Konstantinov, Christoph H. Lampert
Fairness-Aware Learning from Corrupted Data. CoRR (2021)
Mary Phuong, Christoph H. Lampert
The inductive bias of ReLU networks on orthogonally separable data. ICLR (2021)
Paul Henderson, Christoph H. Lampert, Bernd Bickel
Unsupervised Video Prediction from a Single Frame by Estimating 3D Dynamic Scene Structure. CoRR (2021)
Nikola Konstantinov, Christoph H. Lampert
Fairness Through Regularization for Learning to Rank. CoRR (2021)
Jasmin Lampert, Christoph H. Lampert
Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis. IEEE BigData (2021)
Eugenia Iofinova, Nikola Konstantinov, Christoph H. Lampert
FLEA: Provably Fair Multisource Learning from Unreliable Training Data. CoRR (2021)
Alexandra Peste, Dan Alistarh, Christoph H. Lampert
SSSE: Efficiently Erasing Samples from Trained Machine Learning Models. CoRR (2021)
Amélie Royer, Christoph H. Lampert
A Flexible Selection Scheme for Minimum-Effort Transfer Learning. WACV (2020)
Titas Anciukevicius, Christoph H. Lampert, Paul Henderson
Object-Centric Image Generation with Factored Depths, Locations, and Appearances. CoRR (2020)
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) (2020)
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) (2020)
Amelie Royer, Christoph H. Lampert
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios. CoRR (2020)
Amelie Royer, Christoph H. Lampert
A Flexible Selection Scheme for Minimum-Effort Transfer Learning. CoRR (2020)
Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph H. Lampert
On the Sample Complexity of Adversarial Multi-Source PAC Learning. CoRR (2020)
Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert
Leveraging 2D Data to Learn Textured 3D Mesh Generation. CVPR (2020)
Paul Henderson, Christoph H. Lampert
Unsupervised object-centric video generation and decomposition in 3D. NeurIPS (2020)
Paul Henderson, Vagia Tsiminaki, Christoph H. Lampert
Leveraging 2D Data to Learn Textured 3D Mesh Generation. CoRR (2020)
Paul Henderson, Christoph H. Lampert
Unsupervised object-centric video generation and decomposition in 3D. CoRR (2020)
Amélie Royer, Christoph H. Lampert
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios. WACV (2020)
Mary Phuong, Christoph H. Lampert
Functional vs. parametric equivalence of ReLU networks. ICLR (2020)
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) (2019)
Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman
Strategy Representation by Decision Trees with Linear Classifiers. QEST (2019)
Pranav Ashok, Tomás Brázdil, Krishnendu Chatterjee, Jan Kretínský, Christoph H. Lampert, Viktor Toman
Strategy Representation by Decision Trees with Linear Classifiers. CoRR (2019)
Ksenia Konyushkova, Jasper R. R. Uijlings, Christoph H. Lampert, Vittorio Ferrari
Learning Intelligent Dialogs for Bounding Box Annotation. CVPR (2018)
Ehsan Pajouheshgar, Christoph H. Lampert
Back to square one: probabilistic trajectory forecasting without bells and whistles. CoRR (2018)
Rémy Sun, Christoph H. Lampert
KS(conf ): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications. CoRR (2018)
Ilja Kuzborskij, Christoph H. Lampert
Data-Dependent Stability of Stochastic Gradient Descent. ICML (2018)
Subham S. Sahoo, Christoph H. Lampert, Georg Martius
Learning Equations for Extrapolation and Control. ICML (2018)
Alexander Zimin, Christoph H. Lampert
Towards Practical Conditional Risk Minimization. CoRR (2018)
Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari
Detecting Visual Relationships Using Box Attention. CoRR (2018)
Subham S. Sahoo, Christoph H. Lampert, Georg Martius
Learning Equations for Extrapolation and Control. CoRR (2018)
Rémy Sun, Christoph H. Lampert
KS(conf): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications. GCPR (2018)
Yongqin Xian, Christoph H. Lampert, Bernt Schiele, Zeynep Akata
Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly. CoRR (2017)
Ilja Kuzborskij, Christoph H. Lampert
Data-Dependent Stability of Stochastic Gradient Descent. CoRR (2017)
Jasmin Pielorz, Matthias Prandtstetter, Markus Straub, Christoph H. Lampert
Optimal geospatial volunteer allocation needs realistic distances. IEEE BigData (2017)
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert
iCaRL: Incremental Classifier and Representation Learning. CVPR (2017)
Georg Martius, Christoph H. Lampert
Extrapolation and learning equations. ICLR (Workshop) (2017)
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert
Probabilistic Image Colorization. BMVC (2017)
Alexander Kolesnikov, Christoph H. Lampert
PixelCNN Models with Auxiliary Variables for Natural Image Modeling. ICML (2017)
Ksenia Konyushkova, Jasper R. R. Uijlings, Christoph H. Lampert, Vittorio Ferrari
Learning Intelligent Dialogs for Bounding Box Annotation. CoRR (2017)
Anastasia Pentina, Christoph H. Lampert
Multi-task Learning with Labeled and Unlabeled Tasks. ICML (2017)
Alexander Zimin, Christoph H. Lampert
Learning Theory for Conditional Risk Minimization. AISTATS (2017)
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert
Probabilistic Image Colorization. CoRR (2017)
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert
iCaRL: Incremental Classifier and Representation Learning. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. ECCV (4) (2016)
Alexander Kolesnikov, Christoph H. Lampert
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. CoRR (2016)
Anastasia Pentina, Christoph H. Lampert
Active Task Selection for Multi-Task Learning. CoRR (2016)
Georg Martius, Christoph H. Lampert
Extrapolation and learning equations. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Improving Weakly-Supervised Object Localization By Micro-Annotation. BMVC (2016)
Alexander Kolesnikov, Christoph H. Lampert
Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Improving Weakly-Supervised Object Localization By Micro-Annotation. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Identifying Reliable Annotations for Large Scale Image Segmentation. CoRR (2015)
Christoph H. Lampert
Predicting the future behavior of a time-varying probability distribution. CVPR (2015)
Anastasia Pentina, Christoph H. Lampert
Lifelong Learning with Non-i.i.d. Tasks. NIPS (2015)
Amelie Royer, Christoph H. Lampert
Classifier adaptation at prediction time. CVPR (2015)
Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert
Curriculum learning of multiple tasks. CVPR (2015)
Jasmin Pielorz, Christoph H. Lampert
Optimal geospatial allocation of volunteers for crisis management. ICT-DM (2015)
Alexander Zimin, Christoph H. Lampert
Conditional Risk Minimization for Stochastic Processes. CoRR (2015)
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)
Christoph H. Lampert
Blind Domain Adaptation: An RKHS Approach. CoRR (2014)
Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert
Learning to Transfer Privileged Information. CoRR (2014)
Sameh Khamis, Christoph H. Lampert
CoConut: Co-Classification with Output Space Regularization. BMVC (2014)
Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert
Curriculum Learning of Multiple Tasks. CoRR (2014)
Vladyslav Sydorov, Mayu Sakurada, Christoph H. Lampert
Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters. CVPR (2014)
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert
Closed-Form Approximate CRF Training for Scalable Image Segmentation. ECCV (3) (2014)
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS (2014)
Neel Shah, Vladimir Kolmogorov, Christoph H. Lampert
A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Structural SVMs with a Costly max-Oracle. CoRR (2014)
Anastasia Pentina, Christoph H. Lampert
A PAC-Bayesian bound for Lifelong Learning. ICML (2014)
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 (2014)
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR (2014)
Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling
Attribute-Based Classification for Zero-Shot Visual Object Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 36 (3) (2014)
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation. CoRR (2014)
Tomas Kazmar, Evgeny Z. Kvon, Alexander Stark, Christoph H. Lampert
Drosophila Embryo Stage Annotation Using Label Propagation. ICCV (2013)
Anastasia Pentina, Christoph H. Lampert
A PAC-Bayesian bound for Lifelong Learning. CoRR (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Christoph H. Lampert