news
| May 2026 | A new preprint From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD is on arXiv. |
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| May 2026 | Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions got accepted to ICML 2026. |
| Sep 2025 | Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes got accepted to NeurIPS 2025. |
| Jan 2025 | A new preprint From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning is on arXiv. |
| May 2024 | More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms got accepted to ICML 2024. |
| Jan 2024 | Communication-Efficient Federated Learning With Data and Client Heterogeneity got accepted to AISTATS 2024. |
| Jan 2024 | PeFLL: Personalized Federated Learning by Learning to Learn got accepted to ICLR 2024. |