117 citations · 181 across the 4 of their papers we have counts for
5 papers
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement
Szu-Wei Fu, Chien-Feng Liao, Yu Tsao +1
Adversarial loss in a conditional generative adversarial network (GAN) is not designed to directly optimize evaluation metrics of a target task, and thus, may not always guide the…
A Regulation Enforcement Solution for Multi-agent Reinforcement Learning
Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu +1
Human behaviors are regularized by a variety of norms or regulations, either to maintain orders or to enhance social welfare. If artificially intelligent (AI) agents make decisions…
ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models
Yueh-Hua Wu, Fan-Yun Sun, Yen-Yu Chang +1
This work provides a thorough study on how reward scaling can affect performance of deep reinforcement learning agents. In particular, we would like to answer the question that how…
A Memory-Network Based Solution for Multivariate Time-Series Forecasting
Yen-Yu Chang, Fan-Yun Sun, Yueh-Hua Wu +1
Multivariate time series forecasting is extensively studied throughout the years with ubiquitous applications in areas such as finance, traffic, environment, etc. Still, concerns h…
A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents
Yueh-Hua Wu, Shou-De Lin
This paper proposes a low-cost, easily realizable strategy to equip a reinforcement learning (RL) agent the capability of behaving ethically. Our model allows the designers of RL a…