27 citations · 63 across the 7 of their papers we have counts for
7 papers
MA2CL:Masked Attentive Contrastive Learning for Multi-Agent Reinforcement Learning
Haolin Song, Mingxiao Feng, Wengang Zhou +1
Recent approaches have utilized self-supervised auxiliary tasks as representation learning to improve the performance and sample efficiency of vision-based reinforcement learning a…
H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem
Xuanhao Pan, Yan Jin, Yuandong Ding +4
We propose an end-to-end learning framework based on hierarchical reinforcement learning, called H-TSP, for addressing the large-scale Travelling Salesman Problem (TSP). The propos…
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management
Yuandong Ding, Mingxiao Feng, Guozi Liu +7
In this paper, we consider the inventory management (IM) problem where we need to make replenishment decisions for a large number of stock keeping units (SKUs) to balance their sup…
Stabilizing Voltage in Power Distribution Networks via Multi-Agent Reinforcement Learning with Transformer
Minrui Wang, Mingxiao Feng, Wengang Zhou +1
The increased integration of renewable energy poses a slew of technical challenges for the operation of power distribution networks. Among them, voltage fluctuations caused by the…
Underwater Acoustic Communication Channel Modeling using Reservoir Computing
Oluwaseyi Onasami, Ming Feng, Hao Xu +2
Underwater acoustic (UWA) communications have been widely used but greatly impaired due to the complicated nature of the underwater environment. In order to improve UWA communicati…
A Deep Learning Model for Forecasting Global Monthly Mean Sea Surface Temperature Anomalies
John Taylor, Ming Feng
Sea surface temperature (SST) variability plays a key role in the global weather and climate system, with phenomena such as El Niño-Southern Oscillation regarded as a major source…
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning
Weiquan Huang, Yan Bai, Qiuyu Ren +3
Existing public person Re-Identification~(ReID) datasets are small in modern terms because of labeling difficulty. Although unlabeled surveillance video is abundant and relatively…