14 citations · 39 across the 27 of their papers we have counts for
28 papers
A Modular and Scalable Simulator for Connected-UAVs Communication in 5G Networks
Yong Su, Yiyi Chen, Shenghong Yi +4
Cellular-connected UAV systems have enabled a wide range of low-altitude aerial services. However, these systems still face many challenges, such as frequent handovers and the inef…
On Sampling of Multiple Correlated Stochastic Signals
Lin Jin, Hang Sheng, Hui Feng +1
Multiple stochastic signals possess inherent statistical correlations, yet conventional sampling methods that process each channel independently result in data redundancy. To lever…
Subset Random Sampling and Reconstruction of Finite Time-Vertex Graph Signals
Hang Sheng, Qinji Shu, Hui Feng +1
Finite time-vertex graph signals (FTVGS) provide an efficient representation for capturing spatio-temporal correlations across multiple data sources on irregular structures. Althou…
Sampling Theory of Jointly Bandlimited Time-vertex Graph Signals
Hang Sheng, Hui Feng, Junhao Yu +2
Time-vertex graph signal (TVGS) models describe time-varying data with irregular structures. The bandlimitedness in the joint time-vertex Fourier spectral domain reflects smoothnes…
Invariant Federated Learning for Edge Intelligence: Mitigating Heterogeneity and Asynchrony via Exit Strategy and Invariant Penalty
Ziruo Hao, Zhenhua Cui, Tao Yang +3
This paper provides an invariant federated learning system for resource-constrained edge intelligence. This framework can mitigate the impact of heterogeneity and asynchrony via ex…
The Impact Analysis of Delays in Asynchronous Federated Learning with Data Heterogeneity for Edge Intelligence
Ziruo Hao, Zhenhua Cui, Tao Yang +3
Federated learning (FL) has provided a new methodology for coordinating a group of clients to train a machine learning model collaboratively, bringing an efficient paradigm in edge…
Subset Random Sampling of Finite Time-vertex Graph Signals
Hang Sheng, Qinji Shu, Hui Feng +1
Time-varying data with irregular structures can be described by finite time-vertex graph signals (FTVGS), which represent potential temporal and spatial relationships among multipl…
The Transferability of Downsamped Sparse Graph Convolutional Networks
Qinji Shu, Hang Sheng, Feng Ji +2
To accelerate the training of graph convolutional networks (GCNs) on real-world large-scale sparse graphs, downsampling methods are commonly employed as a preprocessing step. Howev…
Online Signed Sampling of Bandlimited Graph Signals
Wenwei Liu, Hui Feng, Feng Ji +1
The theory of sampling and recovery of bandlimited graph signals has been extensively studied. However, in many cases, the observation of a signal is quite coarse. For example, use…
Sampling of Correlated Bandlimited Continuous Signals by Joint Time-vertex Graph Fourier Transform
Zhongyi Ni, Feng Ji, Hang Sheng +2
When sampling multiple signals, the correlation between the signals can be exploited to reduce the overall number of samples. In this paper, we study the sampling theory of multipl…
Recovery of Graph Signals from Sign Measurements
Wenwei Liu, Hui Feng, Kaixuan Wang +2
Sampling and interpolation have been extensively studied, in order to reconstruct or estimate the entire graph signal from the signal values on a subset of vertexes, of which most…
Regularized Recovery by Multi-order Partial Hypergraph Total Variation
Ruyuan Qu, Jiaqi He, Hui Feng +2
Capturing complex high-order interactions among data is an important task in many scenarios. A common way to model high-order interactions is to use hypergraphs whose topology can…
Two-Timescale Resource Allocation for Cooperative D2D Communication: A Matching Game Approach
Yiling Yuan, Tao Yang, Yulin Hu +2
In this paper, we consider a cooperative device-todevice (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist the densified cellular network users (…
Sampling Policy Design for Tracking Time-Varying Graph Signals with Adaptive Budget Allocation
Xuan Xie, Hui Feng, Bo Hu
There have been many works that focus on the sampling set design for a static graph signal, but few for time-varying graph signals (GS). In this paper, we concentrate on how to sel…
Fast Color-guided Depth Denoising for RGB-D Images by Graph Filtering
Qiwei Huang, Ruikang Li, Zidong Jiang +4
Depth images captured by off-the-shelf RGB-D cameras suffer from much stronger noise than color images. In this paper, we propose a method to denoise the depth images in RGB-D imag…
Bayesian Design of Sampling Set for Bandlimited Graph Signals
Xuan Xie, Junhao Yu, Hui Feng +1
The design of sampling set (DoS) for bandlimited graph signals (GS) has been extensively studied in recent years, but few of them exploit the benefits of the stochastic prior of GS…
On Critical Sampling of Time-Vertex Graph Signals
Junhao Yu, Xuan Xie, Hui Feng +1
Joint time-vertex graph signals are pervasive in real-world. This paper focuses on the fundamental problem of sampling and reconstruction of joint time-vertex graph signals. We pro…
OD-GCN: Object Detection Boosted by Knowledge GCN
Zheng Liu, Zidong Jiang, Wei Feng +1
Classical CNN based object detection methods only extract the objects' image features, but do not consider the high-level relationship among objects in context. In this article, th…
Learning for Matching Game in Cooperative D2D Communication with Incomplete Information
Yiling Yuan, Tao Yang, Hui Feng +1
This paper considers a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the op…
Toward Packet Routing with Fully-distributed Multi-agent Deep Reinforcement Learning
Xinyu You, Xuanjie Li, Yuedong Xu +3
Packet routing is one of the fundamental problems in computer networks in which a router determines the next-hop of each packet in the queue to get it as quickly as possible to its…
Active Sampling for Approximately Bandlimited Graph Signals
Sijie Lin, Xuan Xie, Hui Feng +1
This paper investigates the active sampling for estimation of approximately bandlimited graph signals. With the assistance of a graph filter, an approximately bandlimited graph sig…
Robust Beamforming for Downlink 3D-MIMO Systems with -norm Bounded CSI Uncertainty
Kai Liu, Hui Feng, Tao Yang +1
In this paper, a novel robust beamforming scheme is proposed in three dimensional multi-input multi-output (3D-MIMO) systems. As one of the typical deployments of massive MIMO, a 3…
A Cascaded Channel-Power Allocation for D2D Underlaid Cellular Networks Using Matching Theory
Yiling Yuan, Tao Yang, Yuedong Xu +2
We consider a device-to-device (D2D) underlaid cellular network, where each cellular channel can be shared by several D2D pairs and only one channel can be allocated to each D2D pa…
Matching Based Two-Timescale Resource Allocation for Cooperative D2D Communication
Yiling Yuan, Tao Yang, Yulin Hu +2
We consider a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the opportuniti…