Lampert, Christoph H.

61 publications

ICLRW 2025 ASIDE: Architectural Separation of Instructions and Data in Language Models Egor Zverev, Evgenii Kortukov, Alexander Panfilov, Soroush Tabesh, Sebastian Lapuschkin, Wojciech Samek, Christoph H. Lampert

ICLR 2025 Can LLMs Separate Instructions from Data? and What Do We Even Mean by That? Egor Zverev, Sahar Abdelnabi, Soroush Tabesh, Mario Fritz, Christoph H. Lampert

NeurIPS 2025 Continual Release Moment Estimation with Differential Privacy Nikita Kalinin, Jalaj Upadhyay, Christoph H. Lampert

ICML 2025 Differentially Private Federated $k$-Means Clustering with Server-Side Data Jonathan Scott, Christoph H. Lampert, David Saulpic

NeurIPS 2025 Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes Hossein Zakerinia, Christoph H. Lampert

CVPRW 2025 Intriguing Properties of Robust Classification Bernd Prach, Christoph H. Lampert

NeurIPS 2025 Neural Collapse Is Globally Optimal in Deep Regularized ResNets and Transformers Peter Súkeník, Christoph H. Lampert, Marco Mondelli

CVPR 2024 1-Lipschitz Layers Compared: Memory Speed and Certifiable Robustness Bernd Prach, Fabio Brau, Giorgio Buttazzo, Christoph H. Lampert

ICLRW 2024 Can LLMs Separate Instructions from Data? and What Do We Even Mean by That? Egor Zverev, Sahar Abdelnabi, Mario Fritz, Christoph H. Lampert

TMLR 2024 Continual Learning: Applications and the Road Forward 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

ICML 2024 More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms Hossein Zakerinia, Amin Behjati, Christoph H. Lampert

ICMLW 2024 Neural Collapse Versus Low-Rank Bias: Is Deep Neural Collapse Really Optimal? Peter Súkeník, Marco Mondelli, Christoph H. Lampert

ICLR 2024 PeFLL: Personalized Federated Learning by Learning to Learn Jonathan Scott, Hossein Zakerinia, Christoph H Lampert

ICLR 2023 CrAM: A Compression-Aware Minimizer Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H Lampert, Dan Alistarh

TMLR 2023 Cross-Client Label Propagation for Transductive and Semi-Supervised Federated Learning Jonathan Scott, Michelle Yeo, Christoph H Lampert

NeurIPS 2023 Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model Peter Súkeník, Marco Mondelli, Christoph H. Lampert

ECCV 2022 Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks Bernd Prach, Christoph H. Lampert

TMLR 2022 FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data Eugenia Iofinova, Nikola Konstantinov, Christoph H Lampert

JMLR 2022 Fairness-Aware PAC Learning from Corrupted Data Nikola Konstantinov, Christoph H. Lampert

NeurIPSW 2021 SSSE: Efficiently Erasing Samples from Trained Machine Learning Models Alexandra Peste, Dan Alistarh, Christoph H Lampert

ICLR 2021 The Inductive Bias of ReLU Networks on Orthogonally Separable Data Mary Phuong, Christoph H Lampert

ICLR 2020 Functional vs. Parametric Equivalence of ReLU Networks Mary Phuong, Christoph H. Lampert

NeurIPS 2020 Unsupervised Object-Centric Video Generation and Decomposition in 3D Paul Henderson, Christoph H. Lampert

ICMLW 2019 Tasks Without Borders: A New Approach to Online Multi-Task Learning Alexander Zimin, Christoph H. Lampert

ICLR 2017 Extrapolation and Learning Equations Georg Martius, Christoph H. Lampert

AISTATS 2017 Learning Theory for Conditional Risk Minimization Alexander Zimin, Christoph H. Lampert

ICML 2017 Multi-Task Learning with Labeled and Unlabeled Tasks Anastasia Pentina, Christoph H. Lampert

ICML 2017 PixelCNN Models with Auxiliary Variables for Natural Image Modeling Alexander Kolesnikov, Christoph H. Lampert

CVPR 2017 iCaRL: Incremental Classifier and Representation Learning Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert

ECCV 2016 Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation Alexander Kolesnikov, Christoph H. Lampert

CVPR 2015 A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly Max-Oracle Neel Shah, Vladimir Kolmogorov, Christoph H. Lampert

CVPR 2015 Classifier Adaptation at Prediction Time Amelie Royer, Christoph H. Lampert

CVPR 2015 Curriculum Learning of Multiple Tasks Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert

NeurIPS 2015 Lifelong Learning with Non-I.i.d. Tasks Anastasia Pentina, Christoph H. Lampert

CVPR 2015 Predicting the Future Behavior of a Time-Varying Probability Distribution Christoph H. Lampert

ECCV 2014 Closed-Form Approximate CRF Training for Scalable Image Segmentation Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert

CVPR 2014 Deep Fisher Kernels - End to End Learning of the Fisher Kernel GMM Parameters Vladyslav Sydorov, Mayu Sakurada, Christoph H. Lampert

NeurIPS 2014 Mind the Nuisance: Gaussian Process Classification Using Privileged Noise Daniel Hernández-lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto

AISTATS 2013 Computing the M Most Probable Modes of a Graphical Model Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris N. Metaxas, Christoph H. Lampert

ICCV 2013 Drosophila Embryo Stage Annotation Using Label Propagation Tomas Kazmar, Evgeny Z. Kvon, Alexander Stark, Christoph H. Lampert

ICCV 2013 Learning to Rank Using Privileged Information Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert

ECCV 2012 Augmented Attribute Representations Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert

NeurIPS 2012 Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction Christoph H. Lampert

ICML 2012 The Most Persistent Soft-Clique in a Set of Sampled Graphs Novi Quadrianto, Chao Chen, Christoph H. Lampert

CVPR 2011 Enforcing Topological Constraints in Random Field Image Segmentation Chao Chen, Daniel Freedman, Christoph H. Lampert

ICML 2011 Learning Multi-View Neighborhood Preserving Projections Novi Quadrianto, Christoph H. Lampert

NeurIPS 2011 Maximum Margin Multi-Label Structured Prediction Christoph H. Lampert

CVPR 2010 An Efficient Divide-and-Conquer Cascade for Nonlinear Object Detection Christoph H. Lampert

ECCV 2010 On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation Sebastian Nowozin, Peter V. Gehler, Christoph H. Lampert

CVPR 2010 Optimizing One-Shot Recognition with Micro-Set Learning Kevin D. Tang, Marshall F. Tappen, Rahul Sukthankar, Christoph H. Lampert

ECCV 2010 Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer Learning Christoph H. Lampert, Oliver Krömer

CVPRW 2009 Combining Appearance and Motion for Human Action Classification in Videos Paramveer S. Dhillon, Sebastian Nowozin, Christoph H. Lampert

ICCV 2009 Detecting Objects in Large Image Collections and Videos by Efficient Subimage Retrieval Christoph H. Lampert

CVPR 2009 Global Connectivity Potentials for Random Field Models Sebastian Nowozin, Christoph H. Lampert

CVPR 2009 Learning to Detect Unseen Object Classes by Between-Class Attribute Transfer Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling

MLJ 2009 Structured Prediction by Joint Kernel Support Estimation Christoph H. Lampert, Matthew B. Blaschko

CVPR 2008 Beyond Sliding Windows: Object Localization by Efficient Subwindow Search Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann

CVPR 2008 Correlational Spectral Clustering Matthew B. Blaschko, Christoph H. Lampert

ECCV 2008 Learning to Localize Objects with Structured Output Regression Matthew B. Blaschko, Christoph H. Lampert

CVPR 2008 Partitioning of Image Datasets Using Discriminative Context Information Christoph H. Lampert

ECML-PKDD 2008 Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton