17 citations · 25 across the 11 of their papers we have counts for
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stat.ML2025
Accelerated Distributional Temporal Difference Learning with Linear Function Approximation
Kaicheng Jin, Yang Peng, Jiansheng Yang +1
In this paper, we study the finite-sample statistical rates of distributional temporal difference (TD) learning with linear function approximation. The purpose of distributional TD…
stat.ML2021
Reparameterized Sampling for Generative Adversarial Networks
Yifei Wang, Yisen Wang, Jiansheng Yang +1
Recently, sampling methods have been successfully applied to enhance the sample quality of Generative Adversarial Networks (GANs). However, in practice, they typically have poor sa…
stat.ML2020
Decoder-free Robustness Disentanglement without (Additional) Supervision
Yifei Wang, Dan Peng, Furui Liu +3
Adversarial Training (AT) is proposed to alleviate the adversarial vulnerability of machine learning models by extracting only robust features from the input, which, however, inevi…