papers
Publications (9)
cs.LG2019
CoT: Cooperative Training for Generative Modeling of Discrete Data
Sidi Lu, Lantao Yu, Siyuan Feng +3
cs.CY2018
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching
Swaminathan Gurumurthy, Lantao Yu, Chenyan Zhang +4
cs.LG2019
Lipschitz Generative Adversarial Nets
Zhiming Zhou, Jiadong Liang, Yuxuan Song +5
cs.MA2018
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu +4
cs.LG2019
Multi-Agent Adversarial Inverse Reinforcement Learning
Lantao Yu, Jiaming Song, Stefano Ermon
The paper introduces MA-AIRL, a scalable framework for multi-agent inverse reinforcement learning that learns reward functions in high-dimensional Markov games using an adversarial…
#multi-agent reinforcement learning#inverse reinforcement learning#adversarial learning#markov games
cs.AI2018
A Study of AI Population Dynamics with Million-agent Reinforcement Learning
Yaodong Yang, Lantao Yu, Yiwei Bai +4
cs.IR2018
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
Jun Wang, Lantao Yu, Weinan Zhang +5
cs.LG2017
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
Lantao Yu, Weinan Zhang, Jun Wang +1
cs.LG2018
Understanding the Effectiveness of Lipschitz-Continuity in Generative Adversarial Nets
Zhiming Zhou, Yuxuan Song, Lantao Yu +5