144 citations · 966 across the 20 of their papers we have counts for
6 papers · 1 filter
On the Discrimination-Generalization Tradeoff in GANs
Pengchuan Zhang, Qiang Liu, Dengyong Zhou +2
Generative adversarial training can be generally understood as minimizing certain moment matching loss defined by a set of discriminator functions, typically neural networks. The d…
Action-depedent Control Variates for Policy Optimization via Stein's Identity
Hao Liu, Yihao Feng, Yi Mao +3
Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems. However, it still often suffers from the large variance issue on…
Towards Neural Phrase-based Machine Translation
Po-Sen Huang, Chong Wang, Sitao Huang +2
In this paper, we present Neural Phrase-based Machine Translation (NPMT). Our method explicitly models the phrase structures in output sequences using Sleep-WAke Networks (SWAN), a…
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li, Yu Lu, Dengyong Zhou
Contextual bandits are widely used in Internet services from news recommendation to advertising, and to Web search. Generalized linear models (logistical regression in particular)…
Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li +2
Policy evaluation is a crucial step in many reinforcement-learning procedures, which estimates a value function that predicts states' long-term value under a given policy. In this…
Sequence Modeling via Segmentations
Chong Wang, Yining Wang, Po-Sen Huang +3
Segmental structure is a common pattern in many types of sequences such as phrases in human languages. In this paper, we present a probabilistic model for sequences via their segme…