1 citations · 4 across the 12 of their papers we have counts for
14 papers
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
Na Li, Hangguan Shan, Wei Ni +2
Actor-critic (AC) methods are a cornerstone of reinforcement learning (RL) but offer limited interpretability. Current explainable RL methods seldom use state attributions to assis…
Learning Causal States Under Partial Observability and Perturbation
Na Li, Hangguan Shan, Wei Ni +3
A critical challenge for reinforcement learning (RL) is making decisions based on incomplete and noisy observations, especially in perturbed and partially observable Markov decisio…
Sample-Efficient Tabular Self-Play for Offline Robust Reinforcement Learning
Na Li, Zewu Zheng, Wei Ni +3
Multi-agent reinforcement learning (MARL), as a thriving field, explores how multiple agents independently make decisions in a shared dynamic environment. Due to environmental unce…
Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning
Na Li, Yuchen Jiao, Hangguan Shan +1
The thriving field of multi-agent reinforcement learning (MARL) studies how a group of interacting agents make decisions autonomously in a shared dynamic environment. Existing theo…
RayFusion: Ray Fusion Enhanced Collaborative Visual Perception
Shaohong Wang, Bin Lu, Xinyu Xiao +6
Collaborative visual perception methods have gained widespread attention in the autonomous driving community in recent years due to their ability to address sensor limitation probl…
IFTR: An Instance-Level Fusion Transformer for Visual Collaborative Perception
Shaohong Wang, Lu Bin, Xinyu Xiao +3
Multi-agent collaborative perception has emerged as a widely recognized technology in the field of autonomous driving in recent years. However, current collaborative perception pre…
Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
Shiyuan Zuo, Xingrun Yan, Rongfei Fan +4
This paper addresses federated learning (FL) in the context of malicious Byzantine attacks and data heterogeneity. We introduce a novel Robust Average Gradient Algorithm (RAGA), wh…
Adaptive Base-class Suppression and Prior Guidance Network for One-Shot Object Detection
Wenwen Zhang, Xinyu Xiao, Hangguan Shan +1
One-shot object detection (OSOD) aims to detect all object instances towards the given category specified by a query image. Most existing studies in OSOD endeavor to explore effect…
Throughput Analysis of Small Cell Networks under D-TDD and FFR
Meiyan Song, Hangguan Shan, Howard H. Yang +1
Dynamic time-division duplex (D-TDD) has emerged as an effective solution to accommodate the unaligned downlink and uplink traffic in small cell networks. However, the flexibility…
Energy Efficient Massive MIMO through Distributed Precoder Design
Shuai Zhang, Lu Liu, Yu Cheng +4
This paper presents an energy-efficient downlink precoding scheme with the objective of maximizing system energy efficiency in a multi-cell massive MIMO system. The proposed precod…
Throughput Analysis and Energy Efficiency Optimization for Standalone LTE-U Networks with Randomly Delayed CSI
Hangguan Shan, Taojie Qin, Guanding Yu +3
To coexist with Wi-Fi friendly, a standalone long-term evolution network over unlicensed spectrum (LTE-U) under listen-before-talk (LBT) mechanism can only access channel in a rand…
Simulation Results of User Behavior-Aware Scheduling Based on Time-Frequency Resource Conversion
Hangguan Shan, Yani Zhang, Weihua Zhuang +2
Integrating time-frequency resource conversion (TFRC), a new network resource allocation strategy, with call admission control can not only increase the cell capacity but also redu…
State Transition Analysis of Time-Frequency Resource Conversion-based Call Admission Control for LTE-Type Cellular Network
Hangguan Shan, Zhifeng Ni, Weihua Zhuang +2
To address network congestion stemmed from traffic generated by advanced user equipments, in [1] we propose a novel network resource allocation strategy, time-frequency resource co…
Moving Window Network Coding in Cooperative Multicast (v1)
Fei Wu, Cunqing Hua, Hangguan Shan +1
Cooperative multicast is an effective solution to address the bottleneck problem of single-hop broadcast in wireless networks. By incorporating with the random linear network codin…