734 citations · 1.2k across the 8 of their papers we have counts for
9 papers
Towards Learning Multi-agent Negotiations via Self-Play
Yichuan Charlie Tang
Making sophisticated, robust, and safe sequential decisions is at the heart of intelligent systems. This is especially critical for planning in complex multi-agent environments, wh…
Relational Mimic for Visual Adversarial Imitation Learning
Lionel Blondé, Yichuan Charlie Tang, Jian Zhang +1
In this work, we introduce a new method for imitation learning from video demonstrations. Our method, Relational Mimic (RM), improves on previous visual imitation learning methods…
Multiple Futures Prediction
Yichuan Charlie Tang, Ruslan Salakhutdinov
Temporal prediction is critical for making intelligent and robust decisions in complex dynamic environments. Motion prediction needs to model the inherently uncertain future which…
Worst Cases Policy Gradients
Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov
Recent advances in deep reinforcement learning have demonstrated the capability of learning complex control policies from many types of environments. When learning policies for saf…
Learning Generative Models with Visual Attention
Yichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov
Attention has long been proposed by psychologists as important for effectively dealing with the enormous sensory stimulus available in the neocortex. Inspired by the visual attenti…
Challenges in Representation Learning: A report on three machine learning contests
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier +25
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the…