Christoph H. Lampert
Institute of Science and Technology Austria
H-index: 49
Europe-Austria
Top articles of Christoph H. Lampert
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?
arXiv preprint arXiv:2403.06833
2024/3/11
Deep neural collapse is provably optimal for the deep unconstrained features model
Advances in Neural Information Processing Systems
2024/2/13
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
arXiv preprint arXiv:2402.04054
2024/2/6
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network Deployment
arXiv preprint arXiv:2312.06872
2023/12/11
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness
arXiv preprint arXiv:2311.16833
2023/11/28
Continual learning: Applications and the road forward
arXiv preprint arXiv:2311.11908
2023/11/20
1-Lipschitz Neural Networks are more expressive with N-Activations
arXiv preprint arXiv:2311.06103
2023/11/10
Cross-client Label Propagation for Transductive and Semi-Supervised Federated Learning
Transactions on Machine Learning Research
2023/6/7
FedProp: Cross-client Label Propagation for Federated Semi-supervised Learning
arXiv preprint arXiv:2210.06434
2022/10/12
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data
2022/12/22
Generalization In Multi-Objective Machine Learning
arXiv preprint arXiv:2208.13499
2022/8/29
On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) Under Class-Prior Shift
2022/8/21
Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift
2022/8/21
On the Impossibility of Fairness-Aware Learning from Corrupted Data
2022/3/1
Fairness-aware PAC learning from corrupted data
Journal of Machine Learning Research
2022
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks
2022
Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis
2021/12/15
SSSE: Efficiently Erasing Samples from Trained Machine Learning Models
arXiv preprint arXiv:2107.03860
2021/7/8
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