145 citations · 255 across the 25 of their papers we have counts for
18 papers · 1 filter
Supported Trust Region Optimization for Offline Reinforcement Learning
Yixiu Mao, Hongchang Zhang, Chen Chen +2
Offline reinforcement learning suffers from the out-of-distribution issue and extrapolation error. Most policy constraint methods regularize the density of the trained policy towar…
Adversarial Defenses via Vector Quantization
Zhiyi Dong, Yongyi Mao
Adversarial attacks pose significant challenges to the robustness of modern deep neural networks in computer vision, and defending these networks against adversarial attacks has at…
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States
Ziqiao Wang, Yongyi Mao
Stochastic differential equations (SDEs) have been shown recently to characterize well the dynamics of training machine learning models with SGD. When the generalization error of t…
Information-Theoretic Analysis of Unsupervised Domain Adaptation
Ziqiao Wang, Yongyi Mao
This paper uses information-theoretic tools to analyze the generalization error in unsupervised domain adaptation (UDA). We present novel upper bounds for two notions of generaliza…
Cross Domain Few-Shot Learning via Meta Adversarial Training
Jirui Qi, Richong Zhang, Chune Li +1
Few-shot relation classification (RC) is one of the critical problems in machine learning. Current research merely focuses on the set-ups that both training and testing are from th…
ifMixup: Interpolating Graph Pair to Regularize Graph Classification
Hongyu Guo, Yongyi Mao
We present a simple and yet effective interpolation-based regularization technique, aiming to improve the generalization of Graph Neural Networks (GNNs) on supervised graph classif…