activity
20152020
most citedMeta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks

117 citations · 286 across the 21 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

cs.LG2020★ 3 cited

Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity

Tanmay Gangwani, Jian Peng, Yuan Zhou

Quality-Diversity (QD) is a concept from Neuroevolution with some intriguing applications to Reinforcement Learning. It facilitates learning a population of agents where each membe…

cs.LG2020

Off-Policy Interval Estimation with Lipschitz Value Iteration

Ziyang Tang, Yihao Feng, Na Zhang +2

Off-policy evaluation provides an essential tool for evaluating the effects of different policies or treatments using only observed data. When applied to high-stakes scenarios such…

astro-ph.CO2020★ 4 cited

Hunting for Dark Matter Subhalos in Strong Gravitational Lensing with Neural Networks

Joshua Yao-Yu Lin, Hang Yu, Warren Morningstar +2

Dark matter substructures are interesting since they can reveal the properties of dark matter. Collisionless N-body simulations of cold dark matter show more substructures compared…

cs.LG2020★ 4 cited

Learning Guidance Rewards with Trajectory-space Smoothing

Tanmay Gangwani, Yuan Zhou, Jian Peng

Long-term temporal credit assignment is an important challenge in deep reinforcement learning (RL). It refers to the ability of the agent to attribute actions to consequences that…

cs.LG2020★ 1 cited

Efficient Competitive Self-Play Policy Optimization

Yuanyi Zhong, Yuan Zhou, Jian Peng

Reinforcement learning from self-play has recently reported many successes. Self-play, where the agents compete with themselves, is often used to generate training data for iterati…

stat.ML2020★ 10 cited

State-only Imitation with Transition Dynamics Mismatch

Tanmay Gangwani, Jian Peng

Imitation Learning (IL) is a popular paradigm for training agents to achieve complicated goals by leveraging expert behavior, rather than dealing with the hardships of designing a…

cs.LG2020★ 2 cited

Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning

Yuanyi Zhong, Alexander Schwing, Jian Peng

In many vision-based reinforcement learning (RL) problems, the agent controls a movable object in its visual field, e.g., the player's avatar in video games and the robotic arm in…