16 citations · 27 across the 2 of their papers we have counts for
5 papers
Universal Successor Features for Transfer Reinforcement Learning
Chen Ma, Dylan R. Ashley, Junfeng Wen +1
Transfer in Reinforcement Learning (RL) refers to the idea of applying knowledge gained from previous tasks to solving related tasks. Learning a universal value function (Schaul et…
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning
Chenjun Xiao, Yifan Wu, Chen Ma +2
Despite its potential to improve sample complexity versus model-free approaches, model-based reinforcement learning can fail catastrophically if the model is inaccurate. An algorit…
The Hitchhiker's Guide to LDA
Chen Ma
Latent Dirichlet Allocation (LDA) model is a famous model in the topic model field, it has been studied for years due to its extensive application value in industry and academia. H…
MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks
Chen Ma, Chenxu Zhao, Hailin Shi +3
Deep neural networks (DNNs) are vulnerable to adversarial attack which is maliciously implemented by adding human-imperceptible perturbation to images and thus leads to incorrect p…
AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection
Chen Ma, Li Chen, Junhai Yong
Detecting action units (AUs) on human faces is challenging because various AUs make subtle facial appearance change over various regions at different scales. Current works have att…