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Jingfeng Wu's Projects

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[AISTATS 2022] Gap-Dependent Unsupervised Exploration for Reinforcement Learning

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[ICML 2020] Obtaining Adjustable Regularization for Free via Iterate Averaging

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[NeurIPS 2021] Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning

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[ICML 2020] On the Noisy Gradient Descent that Generalizes as SGD

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[ICML 2019] The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects

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[CVPR 2019] Tangent-Normal Adversarial Regularization for Semi-supervised Learning

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