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Minimax Optimal Bandits for Heavy Tail Rewards.

, и . IEEE Trans. Neural Networks Learn. Syst., 35 (4): 5280-5294 (апреля 2024)

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Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?, , , , , , , , , и 2 other автор(ы). CoRR, (2023)Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots., , , , , , , и . Robotics: Science and Systems, (2020)Bag of Tricks for In-Distribution Calibration of Pretrained Transformers., , , и . EACL (Findings), стр. 551. Association for Computational Linguistics, (2023)Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards., , , и . NeurIPS, (2020)Uncertainty-Aware Learning from Demonstration Using Mixture Density Networks with Sampling-Free Variance Modeling., , , и . ICRA, стр. 6915-6922. IEEE, (2018)Slice and Conquer: A Planar-to-3D Framework for Efficient Interactive Segmentation of Volumetric Images., , , , , , , и . WACV, стр. 7599-7608. IEEE, (2024)Minimax Optimal Bandits for Heavy Tail Rewards., и . IEEE Trans. Neural Networks Learn. Syst., 35 (4): 5280-5294 (апреля 2024)ChoiceNet: Robust Learning by Revealing Output Correlations, , и . (2018)cite arxiv:1805.06431.Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds., , , , и . AAAI, стр. 9916-9924. AAAI Press, (2020)Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks., , , и . CVPR, стр. 3871-3880. Computer Vision Foundation / IEEE, (2020)