498 citations · 1.8k across the 44 of their papers we have counts for
12 papers · 1 filter
Small Towers Make Big Differences
Yuyan Wang, Zhe Zhao, Bo Dai +4
Multi-task learning aims at solving multiple machine learning tasks at the same time. A good solution to a multi-task learning problem should be generalizable in addition to being…
Off-Policy Evaluation via the Regularized Lagrangian
Mengjiao Yang, Ofir Nachum, Bo Dai +2
The recently proposed distribution correction estimation (DICE) family of estimators has advanced the state of the art in off-policy evaluation from behavior-agnostic data. While t…
Energy-based View of Retrosynthesis
Ruoxi Sun, Hanjun Dai, Li Li +2
Retrosynthesis -- the process of identifying a set of reactants to synthesize a target molecule -- is of vital importance to material design and drug discovery. Existing machine le…
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach
Luofeng Liao, You-Lin Chen, Zhuoran Yang +3
Structural equation models (SEMs) are widely used in sciences, ranging from economics to psychology, to uncover causal relationships underlying a complex system under consideration…
Scalable Deep Generative Modeling for Sparse Graphs
Hanjun Dai, Azade Nazi, Yujia Li +2
Learning graph generative models is a challenging task for deep learning and has wide applicability to a range of domains like chemistry, biology and social science. However curren…
Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations
Zhuangdi Zhu, Kaixiang Lin, Bo Dai +1
Model-free deep reinforcement learning (RL) has demonstrated its superiority on many complex sequential decision-making problems. However, heavy dependence on dense rewards and hig…