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12 résultats
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triés par
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Concentrated Differential Privacy for Bandits2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), IEEE, Apr 2024, Toronto, Canada. pp.78-109, ⟨10.1109/SaTML59370.2024.00013⟩
Communication dans un congrès
hal-04611650v1
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Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024, Auckland, New Zealand. pp.516-524, ⟨10.5555/3635637.3662902⟩
Communication dans un congrès
hal-04260795v1
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A PAC-Bayesian Link Between Generalisation and Flat Minima2024
Pré-publication, Document de travail
hal-04455639v1
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Improved Stability and Generalization Guarantees of the Decentralized SGD AlgorithmICML 2024 - The Forty-first International Conference on Machine Learning, Jul 2024, Vienne, Austria
Communication dans un congrès
hal-04611418v1
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Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits?Proceedings of Thirty Seventh Conference on Learning Theory, Jul 2024, Edmonton (Alberta), Canada
Communication dans un congrès
hal-04621903v1
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Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic AlgorithmsTransactions on Machine Learning Research Journal, 2024
Article dans une revue
hal-04615733v1
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On the Impact of Output Perturbation on Fairness in Binary Linear Classification2024
Pré-publication, Document de travail
hal-04440982v1
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Tighter Generalisation Bounds via Interpolation2024
Pré-publication, Document de travail
hal-04456925v1
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On the Complexity of Differentially Private Best-Arm Identification with Fixed ConfidenceNeurIPS 2023 – Conference on Neural Information Processing Systems, Dec 2023, New Orleans (US), United States. pp.71150--71194
Communication dans un congrès
hal-04215474v1
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CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic CorruptionInternational Conference on Algorithmic Learning Theory (ALT), Feb 2024, San Diego (CA), United States. pp.74-124
Communication dans un congrès
hal-04260464v1
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FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits2024
Pré-publication, Document de travail
hal-04615697v1
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Differentially Private Best-Arm Identification2024
Pré-publication, Document de travail
hal-04615690v1
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