43 citations · 81 across the 6 of their papers we have counts for
6 papers
Unbiased Knowledge Distillation for Recommendation
Gang Chen, Jiawei Chen, Fuli Feng +2
As a promising solution for model compression, knowledge distillation (KD) has been applied in recommender systems (RS) to reduce inference latency. Traditional solutions first tra…
Deep Reinforcement Learning based Dynamic Optimization of Bus Timetable
Guanqun Ai, Xingquan Zuo, Gang chen +1
Bus timetable optimization is a key issue to reduce operational cost of bus companies and improve the service quality. Existing methods use exact or heuristic algorithms to optimiz…
Decorrelated Double Q-learning
Gang Chen
Q-learning with value function approximation may have the poor performance because of overestimation bias and imprecise estimate. Specifically, overestimation bias is from the maxi…
Context-aware Active Multi-Step Reinforcement Learning
Gang Chen, Dingcheng Li, Ran Xu
Reinforcement learning has attracted great attention recently, especially policy gradient algorithms, which have been demonstrated on challenging decision making and control tasks.…
A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation
Gang Chen
Deep reinforcement learning (DRL) is a booming area of artificial intelligence. Many practical applications of DRL naturally involve more than one collaborative learners, making it…
Generalized K-fan Multimodal Deep Model with Shared Representations
Gang Chen, Sargur N. Srihari
Multimodal learning with deep Boltzmann machines (DBMs) is an generative approach to fuse multimodal inputs, and can learn the shared representation via Contrastive Divergence (CD)…