47 citations · 142 across the 27 of their papers we have counts for
8 papers · 1 filter
Learning Robust Recommenders from Noisy Implicit Feedback via GMM-Weighted Bayesian Transition Matrix
Zongyu Li, Xuanyu Liu, Gongce Cao +3
Label noise is a central challenge in learning from implicit feedback for recommendation. Conventional approaches discard noisy examples for robustness, but this sacrifices data ef…
Refined Edge Usage of Graph Neural Networks for Edge Prediction
Jiarui Jin, Yangkun Wang, Weinan Zhang +5
Graph Neural Networks (GNNs), originally proposed for node classification, have also motivated many recent works on edge prediction (a.k.a., link prediction). However, existing met…
Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning
Hua Wei, Jingxiao Chen, Xiyang Ji +11
This paper introduces Honor of Kings Arena, a reinforcement learning (RL) environment based on Honor of Kings, one of the world's most popular games at present. Compared to other e…
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
Zeren Huang, Wenhao Chen, Weinan Zhang +7
Deriving a good variable selection strategy in branch-and-bound is essential for the efficiency of modern mixed-integer programming (MIP) solvers. With MIP branching data collected…
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization
Minghuan Liu, Zhengbang Zhu, Yuzheng Zhuang +4
Recent progress in state-only imitation learning extends the scope of applicability of imitation learning to real-world settings by relieving the need for observing expert actions.…
Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
Ting Long, Yutong Xie, Xianyu Chen +3
Program representation, which aims at converting program source code into vectors with automatically extracted features, is a fundamental problem in programming language processing…
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction
Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao +14
Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity si…
Activation Maximization Generative Adversarial Nets
Zhiming Zhou, Han Cai, Shu Rong +5
Class labels have been empirically shown useful in improving the sample quality of generative adversarial nets (GANs). In this paper, we mathematically study the properties of the…