Tony Q. S. Quek

research

∙ 09/04/2023

SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems

Recently proliferated semantic communications (SC) aim at effectively tr...

0 Xinghan Liu, et al. ∙

research

∙ 08/10/2023

Optimizing Cache Content Placement in Integrated Terrestrial and Non-terrestrial Networks

Non-terrestrial networks (NTN) offer potential for efficient content bro...

0 Feng Wang, et al. ∙

research

∙ 07/23/2023

QoE-Driven Video Transmission: Energy-Efficient Multi-UAV Network Optimization

This paper is concerned with the issue of improving video subscribers' q...

0 Kesong Wu, et al. ∙

research

∙ 06/17/2023

Edge Intelligence Over the Air: Two Faces of Interference in Federated Learning

Federated edge learning is envisioned as the bedrock of enabling intelli...

0 Zihan Chen, et al. ∙

research

∙ 06/16/2023

Analysis of the Age of Information in Age-Threshold Slotted ALOHA

We investigate the performance of a random access network consisting of ...

0 Howard H. Yang, et al. ∙

research

∙ 06/07/2023

Towards Fast Personalized Semi-Supervised Federated Learning in Edge Networks: Algorithm Design and Theoretical Guarantee

Recent years have witnessed a huge demand for artificial intelligence an...

0 Shuai Wang, et al. ∙

research

∙ 04/13/2023

CoMP Transmission in Downlink NOMA-Based Cellular-Connected UAV Networks

In this paper, we study the integration between the coordinated multipoi...

0 HongGuang Sun, et al. ∙

research

∙ 04/09/2023

Energy-Efficient URLLC Service Provision via a Near-Space Information Network

The integration of a near-space information network (NSIN) with the reco...

0 Puguang An, et al. ∙

research

∙ 03/30/2023

DPP-based Client Selection for Federated Learning with Non-IID Data

This paper proposes a client selection (CS) method to tackle the communi...

0 Yuxuan Zhang, et al. ∙

research

∙ 03/23/2023

Automated Federated Learning in Mobile Edge Networks – Fast Adaptation and Convergence

Federated Learning (FL) can be used in mobile edge networks to train mac...

0 Chaoqun You, et al. ∙

research

∙ 03/19/2023

Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks

Personalized Federated Learning (PFL) is a new Federated Learning (FL) p...

0 Chaoqun You, et al. ∙

research

∙ 02/24/2023

Personalizing Federated Learning with Over-the-Air Computations

Federated edge learning is a promising technology to deploy intelligence...

0 Zihan Chen, et al. ∙

research

∙ 02/09/2023

Differentially Private Deep Q-Learning for Pattern Privacy Preservation in MEC Offloading

Mobile edge computing (MEC) is a promising paradigm to meet the quality ...

0 Shuying Gan, et al. ∙

research

∙ 02/07/2023

Understanding the Gain of Deploying IRSs in Large-scale Heterogeneous Cellular Networks

As the superior improvement on wireless network coverage, spectrum effic...

0 Hu Cheng, et al. ∙

research

∙ 01/03/2023

Differentially Private Federated Clustering over Non-IID Data

Federated clustering (FedC) is an adaptation of centralized clustering i...

0 Yiwei Li, et al. ∙

research

∙ 12/03/2022

Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework

As a novel distributed learning paradigm, federated learning (FL) faces ...

0 Shuai Wang, et al. ∙

research

∙ 11/27/2022

Coverage Analysis for Cellular-Connected Random 3D Mobile UAVs with Directional Antennas

This letter proposes an analytical framework to evaluate the coverage pe...

0 HongGuang Sun, et al. ∙

research

∙ 11/13/2022

Social Welfare Maximization for Collaborative Edge Computing: A Deep Reinforcement Learning-Based Approach

Collaborative Edge Computing (CEC) is an effective method that improves ...

0 Xingqiu He, et al. ∙

research

∙ 11/01/2022

MDC Enhanced IoT Networks: Network Modeling and Performance Analysis

As a promising architecture, Mobile Data Collector (MDC) enhanced Intern...

0 HongGuang Sun, et al. ∙

research

∙ 10/29/2022

IRS-Assisted RF-powered IoT Networks:System Modeling and Performance Analysis

Emerged as a promising solution for future wireless communication system...

0 HongGuang Sun, et al. ∙

research

∙ 09/28/2022

FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations

In edge computing, users' service profiles must be migrated in response ...

0 Marie Siew, et al. ∙

research

∙ 09/27/2022

Semi-Synchronous Personalized Federated Learning over Mobile Edge Networks

Personalized Federated Learning (PFL) is a new Federated Learning (FL) a...

0 Chaoqun You, et al. ∙

research

∙ 08/14/2022

Joint User Association and Resource Pricing for Metaverse: Distributed and Centralized Approaches

Metaverse as the next-generation Internet provides users with physical-v...

0 Xumin Huang, et al. ∙

research

∙ 07/21/2022

UAV Trajectory, User Association and Power Control for Multi-UAV Enabled Energy Harvesting Communications: Offline Design and Online Reinforcement Learning

In this paper, we consider multiple solar-powered wireless nodes which u...

0 Chien-Wei Fu, et al. ∙

research

∙ 07/02/2022

Analysis of Age of Information in Dual Updating Systems

We study the average Age of Information (AoI) and peak AoI (PAoI) of a d...

0 Zhengchuan Chen, et al. ∙

research

∙ 06/30/2022

Towards Federated Long-Tailed Learning

Data privacy and class imbalance are the norm rather than the exception ...

0 Zihan Chen, et al. ∙

research

∙ 06/12/2022

Age of Information: A Two-Sensor Status Update System Monitoring The Same Process

This work studies the average age of information (AoI) of a monitoring s...

0 Tianqing Yang, et al. ∙

research

∙ 04/15/2022

Server Free Wireless Federated Learning: Architecture, Algorithm, and Analysis

We demonstrate that merely analog transmissions and match filtering can ...

0 Howard H. Yang, et al. ∙

research

∙ 04/10/2022

FedCorr: Multi-Stage Federated Learning for Label Noise Correction

Federated learning (FL) is a privacy-preserving distributed learning par...

5 Jingyi Xu, et al. ∙

research

∙ 03/23/2022

Minimizing Age-upon-Decisions in Bufferless System: Service Scheduling and Decision Interval

In Internet of Things (IoT), the decision timeliness of time-sensitive a...

0 Shutong Chen, et al. ∙

research

∙ 03/19/2022

UAV Trajectory and Beamforming Optimization for Integrated Periodic Sensing and Communication

Unmanned aerial vehicle (UAV) is expected to bring transformative improv...

0 Kaitao Meng, et al. ∙

research

∙ 03/02/2022

Towards Effective Resource Procurement in MEC: a Resource Re-selling Framework

On-demand and resource reservation pricing models have been widely used ...

0 Marie Siew, et al. ∙

research

∙ 02/17/2022

Federated Stochastic Gradient Descent Begets Self-Induced Momentum

Federated learning (FL) is an emerging machine learning method that can ...

0 Howard H. Yang, et al. ∙

research

∙ 11/13/2021

Networking of Internet of UAVs: Challenges and Intelligent Approaches

Internet of unmanned aerial vehicle (I-UAV) networks promise to accompli...

6 Peng Yang, et al. ∙

research

∙ 11/03/2021

Belief Propagation based Joint Detection and Decoding for Resistive Random Access Memories

Despite the great promises that the resistive random access memory (ReRA...

0 Ce Sun, et al. ∙

research

∙ 10/20/2021

Distributed Reinforcement Learning for Privacy-Preserving Dynamic Edge Caching

Mobile edge computing (MEC) is a prominent computing paradigm which expa...

0 Shengheng Liu, et al. ∙

research

∙ 10/15/2021

Optimal Distribution Design for Irregular Repetition Slotted ALOHA with Multi-Packet Reception

Associated with multi-packet reception at the access point, irregular re...

0 Zhengchuan Chen, et al. ∙

research

∙ 09/21/2021

Secrecy Offloading Rate Maximization for Multi-Access Mobile Edge Computing Networks

This letter considers a multi-access mobile edge computing (MEC) network...

0 Mingxiong Zhao, et al. ∙

research

∙ 09/18/2021

Spatiotemporal Analysis for Age of Information in Random Access Networks under Last-Come First-Serve with Replacement Protocol

We investigate the age-of-information (AoI) in the context of random acc...

0 Howard H. Yang, et al. ∙

research

∙ 08/20/2021

Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks

Implementing federated learning (FL) algorithms in wireless networks has...

0 Chenyuan Feng, et al. ∙

research

∙ 08/12/2021

Dynamic Attention-based Communication-Efficient Federated Learning

Federated learning (FL) offers a solution to train a global machine lear...

0 Zihan Chen, et al. ∙

research

∙ 08/09/2021

Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach

The advances in deep neural networks (DNN) have significantly enhanced r...

0 Mao V. Ngo, et al. ∙

research

∙ 08/04/2021

When to Preprocess? Keeping Information Fresh for Computing Enable Internet of Things

Age of information (AoI), a notion that measures the information freshne...

0 Xijun Wang, et al. ∙

research

∙ 07/25/2021

Revisiting Analog Over-the-Air Machine Learning: The Blessing and Curse of Interference

We study a distributed machine learning problem carried out by an edge s...

0 Howard H. Yang, et al. ∙

research

∙ 06/15/2021

Learning Autonomy in Management of Wireless Random Networks

This paper presents a machine learning strategy that tackles a distribut...

0 Hoon Lee, et al. ∙

research

∙ 06/13/2021

Optimal Status Update for Caching Enabled IoT Networks: A Dueling Deep R-Network Approach

In the Internet of Things (IoT) networks, caching is a promising techniq...

0 Chao Xu, et al. ∙

research

∙ 06/03/2021

Feeling of Presence Maximization: mmWave-Enabled Virtual Reality Meets Deep Reinforcement Learning

This paper investigates the problem of providing ultra-reliable and ener...

0 Peng Yang, et al. ∙

research

∙ 05/27/2021

Training Classifiers that are Universally Robust to All Label Noise Levels

For classification tasks, deep neural networks are prone to overfitting ...

10 Jingyi Xu, et al. ∙

research

∙ 05/18/2021

Learning-Based Robust Resource allocation for D2D Underlaying Cellular Network

In this paper, we study the resource allocation in D2D underlaying cellu...

0 Weihua Wu, et al. ∙

research

∙ 05/05/2021

Two-Stage Stochastic Optimization via Primal-Dual Decomposition and Deep Unrolling

We consider a two-stage stochastic optimization problem, in which a long...

0 An Liu, et al. ∙

Tony Q. S. Quek

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