b'Huaiyu Dai'

research

∙ 05/22/2023

Distributed Learning over Networks with Graph-Attention-Based Personalization

In conventional distributed learning over a network, multiple agents col...

0 Zhuojun Tian, et al. ∙

research

∙ 02/19/2023

Magnitude Matters: Fixing SIGNSGD Through Magnitude-Aware Sparsification in the Presence of Data Heterogeneity

Communication overhead has become one of the major bottlenecks in the di...

0 Richeng Jin, et al. ∙

research

∙ 02/19/2023

On the f-Differential Privacy Guarantees of Discrete-Valued Mechanisms

We consider a federated data analytics problem in which a server coordin...

0 Richeng Jin, et al. ∙

research

∙ 12/08/2022

Graph Neural Networks Meet Wireless Communications: Motivation, Applications, and Future Directions

As an efficient graph analytical tool, graph neural networks (GNNs) have...

0 Mengyuan Lee, et al. ∙

research

∙ 11/24/2022

Multi-Job Intelligent Scheduling with Cross-Device Federated Learning

Recent years have witnessed a large amount of decentralized data in vari...

0 Ji Liu, et al. ∙

research

∙ 10/27/2022

Resource Constrained Vehicular Edge Federated Learning with Highly Mobile Connected Vehicles

This paper proposes a vehicular edge federated learning (VEFL) solution,...

0 Md Ferdous Pervej, et al. ∙

research

∙ 08/26/2022

RFID: Towards Low Latency and Reliable DAG Task Scheduling over Dynamic Vehicular Clouds

Vehicular cloud (VC) platforms integrate heterogeneous and distributed r...

0 Zhang Liu, et al. ∙

research

∙ 08/15/2022

Privacy-Preserving Decentralized Inference with Graph Neural Networks in Wireless Networks

As an efficient neural network model for graph data, graph neural networ...

0 Mengyuan Lee, et al. ∙

research

∙ 06/08/2022

Gradient Obfuscation Gives a False Sense of Security in Federated Learning

Federated learning has been proposed as a privacy-preserving machine lea...

0 Kai Yue, et al. ∙

research

∙ 05/17/2022

Mobility, Communication and Computation Aware Federated Learning for Internet of Vehicles

While privacy concerns entice connected and automated vehicles to incorp...

0 Md Ferdous Pervej, et al. ∙

research

∙ 04/25/2022

FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server

Despite achieving remarkable performance, Federated Learning (FL) suffer...

0 Hong Zhang, et al. ∙

research

∙ 02/15/2022

Efficient Content Delivery in Cache-Enabled VEN with Deadline-Constrained Heterogeneous Demands: A User-Centric Approach

Modern connected vehicles (CVs) frequently require diverse types of cont...

0 Md Ferdous Pervej, et al. ∙

research

∙ 12/11/2021

Efficient Device Scheduling with Multi-Job Federated Learning

Recent years have witnessed a large amount of decentralized data in mult...

1 Chendi Zhou, et al. ∙

research

∙ 10/07/2021

Neural Tangent Kernel Empowered Federated Learning

Federated learning (FL) is a privacy-preserving paradigm where multiple ...

6 Kai Yue, et al. ∙

research

∙ 10/06/2021

Federated Learning via Plurality Vote

Federated learning allows collaborative workers to solve a machine learn...

0 Kai Yue, et al. ∙

research

∙ 08/02/2021

Communication-Efficient Federated Learning via Predictive Coding

Federated learning can enable remote workers to collaboratively train a ...

0 Kai Yue, et al. ∙

research

∙ 07/24/2021

Adversarial training may be a double-edged sword

Adversarial training has been shown as an effective approach to improve ...

0 Ali Rahmati, et al. ∙

research

∙ 04/19/2021

Decentralized Inference with Graph Neural Networks in Wireless Communication Systems

Graph neural network (GNN) is an efficient neural network model for grap...

0 Mengyuan Lee, et al. ∙

research

∙ 03/26/2021

Modeling the Nonsmoothness of Modern Neural Networks

Modern neural networks have been successful in many regression-based tas...

0 Runze Liu, et al. ∙

research

∙ 02/06/2021

Spectral Graph Theory Based Resource Allocation for IRS-Assisted Multi-Hop Edge Computing

The performance of mobile edge computing (MEC) depends critically on the...

0 Huilian Zhang, et al. ∙

research

∙ 10/26/2020

Application of Deep Learning to Sphere Decoding for Large MIMO Systems

Although the sphere decoder (SD) is a powerful detector for multiple-inp...

0 Nhan Thanh Nguyen, et al. ∙

research

∙ 10/19/2020

Hybrid Beamforming and Adaptive RF Chain Activation for Uplink Cell-Free Millimeter-Wave Massive MIMO Systems

In this work, we investigate hybrid analog–digital beamforming (HBF) arc...

0 Nhan Thanh Nguyen, et al. ∙

research

∙ 09/29/2020

Distributed ADMM with Synergetic Communication and Computation

In this paper, we propose a novel distributed alternating direction meth...

0 Zhuojun Tian, et al. ∙

research

∙ 09/29/2020

A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions

The combinatorial auction (CA) is an efficient mechanism for resource al...

0 Mengyuan Lee, et al. ∙

research

∙ 07/18/2020

Multi-Stage Hybrid Federated Learning over Large-Scale Wireless Fog Networks

One of the popular methods for distributed machine learning (ML) is fede...

0 Seyyedali Hosseinalipour, et al. ∙

research

∙ 06/07/2020

From Federated Learning to Fog Learning: Towards Large-Scale Distributed Machine Learning in Heterogeneous Wireless Networks

Contemporary network architectures are pushing computing tasks from the ...

0 Seyyedali Hosseinalipour, et al. ∙

research

∙ 04/15/2020

On the Design of Communication Efficient Federated Learning over Wireless Networks

Recently, federated learning (FL), as a promising distributed machine le...

0 Richeng Jin, et al. ∙

research

∙ 04/04/2020

Energy-aware Allocation of Graph Jobs in Vehicular Cloud Computing-enabled Software-defined IoV

Software-defined internet of vehicles (SDIoV) has emerged as a promising...

0 Minghui LiWang, et al. ∙

research

∙ 03/27/2020

A Truthful Auction for Graph Job Allocation in Vehicular Cloud-assisted Networks

Vehicular cloud computing has emerged as a promising solution to fulfill...

0 Zhibin Gao, et al. ∙

research

∙ 03/13/2020

GeoDA: a geometric framework for black-box adversarial attacks

Adversarial examples are known as carefully perturbed images fooling ima...

0 Ali Rahmati, et al. ∙

research

∙ 03/03/2020

Accelerating Generalized Benders Decomposition for Wireless Resource Allocation

Generalized Benders decomposition (GBD) is a globally optimal algorithm ...

0 Mengyuan Lee, et al. ∙

research

∙ 02/25/2020

Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Federated learning (FL) has emerged as a prominent distributed learning ...

17 Richeng Jin, et al. ∙

research

∙ 02/17/2020

Precoder Design for mmWave UAV Communications with Physical Layer Security

The integration of unmanned aerial vehicles (UAVs) into the terrestrial ...

0 Sung Joon Maeng, et al. ∙

research

∙ 01/14/2020

Physical Layer Security for NOMA Transmission in mmWave Drone Networks

The non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) t...

0 Yavuz Yapici, et al. ∙

research

∙ 12/12/2019

Multi-Task Offloading over Vehicular Clouds under Graph-based Representation

Vehicular cloud computing has emerged as a promising paradigm for realiz...

0 Minghui LiWang, et al. ∙

research

∙ 10/01/2019

Low-Resolution Limited-Feedback NOMA for mmWave Communications

The spectrum-efficient millimeter-wave (mmWave) communications has recen...

0 Yavuz Yapici, et al. ∙

research

∙ 09/26/2019

Dynamic Interference Management for UAV-Assisted Wireless Networks

The deployment of unmanned aerial vehicles (UAVs) is proliferating as th...

0 Ali Rahmati, et al. ∙

research

∙ 07/02/2019

Interference Avoidance Position Planning in Dual-hop and Multi-hop UAV Relay Networks

We consider unmanned aerial vehicle (UAV)-assisted wireless communicatio...

0 Seyyedali Hosseinalipour, et al. ∙

research

∙ 05/18/2019

Quantifying Differential Privacy of Gossip Protocols in General Networks

In this work, we generalize the study of quantifying the differential pr...

0 Yufan Huang, et al. ∙

research

∙ 04/16/2019

Interference Avoidance in UAV-Assisted Networks: Joint 3D Trajectory Design and Power Allocation

The use of the unmanned aerial vehicle (UAV) has been foreseen as a prom...

0 Ali Rahmati, et al. ∙

research

∙ 03/21/2019

Prevention and Mitigation of Catastrophic Failures in Demand-Supply Interdependent Networks

We propose a generic system model for a special category of interdepende...

0 Seyyedali Hosseinalipour, et al. ∙

research

∙ 03/11/2019

Optimal Time Allocation in VANETs Advertising: A Price-based Approach using Stackelberg Game

Vehicular ad-hoc networks (VANETs) have recently attracted a lot of atte...

0 Ali Rahmati, et al. ∙

research

∙ 03/07/2019

Allocation of Computation-Intensive Graph Jobs over Vehicular Clouds

Recent years have witnessed dramatic growth in smart vehicles and comput...

0 Minghui LiWang, et al. ∙

research

∙ 03/04/2019

Interference Avoidance Position Planning in UAV-assisted Wireless Communication

We consider unmanned aerial vehicle (UAV)-assisted wireless communicatio...

0 Seyyedali Hosseinalipour, et al. ∙

research

∙ 02/27/2019

Distributed Byzantine Tolerant Stochastic Gradient Descent in the Era of Big Data

The recent advances in sensor technologies and smart devices enable the ...

0 Richeng Jin, et al. ∙

research

∙ 02/12/2019

SLNR Based Precoding for One-Bit Quantized Massive MIMO in mmWave Communications

Massive multiple-input multiple-output (MIMO) is a key technology for 5G...

0 Yavuz Yapici, et al. ∙

research

∙ 01/09/2019

Dynamic Mobility-Aware Interference Avoidance for Aerial Base Stations in Cognitive Radio Networks

Aerial base station (ABS) is a promising solution for public safety as i...

0 Ali Rahmati, et al. ∙

research

∙ 12/04/2018

Enhancing Physical Layer Security for NOMA Transmission in mmWave Drone Networks

Physical layer security (PLS) is critically important for emerging wirel...

0 Nadisanka Rupasinghe, et al. ∙

research

∙ 09/08/2018

Decentralized Differentially Private Without-Replacement Stochastic Gradient Descent

While machine learning has achieved remarkable results in a wide variety...

0 Richeng Jin, et al. ∙

research

∙ 08/13/2018

Allocation of Graph Jobs in Geo-Distributed Cloud Networks

Recently, processing of big-data has drawn tremendous attention, where c...

0 Seyyedali Hosseinalipour, et al. ∙

Huaiyu Dai

Featured Co-authors