3 citations · 18 across the 20 of their papers we have counts for
20 papers
Towards Serverless Semi-Decentralized Federated Learning with Heterogeneous Optimizers
Su Wang, Mung Chiang, H. Vincent Poor
We investigate cluster formation, involving the number and composition of clusters, in decentralized federated learning (FL) with heterogeneous machine learning (ML) optimizers. Wh…
Optimizing Server Placement for Vertical Federated Learning in Dynamic Edge/Fog Networks
Su Wang, Mung Chiang, H. Vincent Poor
We investigate the control and optimization of vertical federated learning (VFL), a class of distributed machine learning (ML) methods in which edge/fog devices contain separate da…
Large Language Models over Networks: Collaborative Intelligence under Resource Constraints
Liangqi Yuan, Wenzhi Fang, Shiqiang Wang +2
Large language models (LLMs) are transforming society, powering applications from smartphone assistants to autonomous driving. Yet cloud-based LLM services alone cannot serve a gro…
A New Pathway to Integrated Learning and Communication (ILAC): Large AI Model and Hyperdimensional Computing for Communication
Wei Xu, Zhaohui Yang, Derrick Wing Kwan Ng +4
The rapid evolution of forthcoming sixth-generation (6G) wireless networks necessitates the seamless integration of artificial intelligence (AI) with wireless communications to sup…
LLM-Integrated Digital Twins for Hierarchical Resource Allocation in 6G Networks
Majumder Haider, Imtiaz Ahmed, Zoheb Hassan +2
Next-generation (NextG) wireless networks are expected to require intelligent, scalable, and context-aware radio resource management (RRM) to support ultra-dense deployments, diver…
Route-and-Aggregate Decentralized Federated Learning Under Communication Errors
Weicai Li, Tiejun Lv, Wei Ni +3
Decentralized federated learning (D-FL) allows clients to aggregate learning models locally, offering flexibility and scalability. Existing D-FL methods use gossip protocols, which…
A MIMO ISAC System for Ultra-Reliable and Low-Latency Communications
Homa Nikbakht, Yonina C. Eldar, H. Vincent Poor
In this paper, we propose a bi-static multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system to detect the arrival of ultra-reliable and low-laten…
Wireless Federated Learning over Resource-Constrained Networks: Digital versus Analog Transmissions
Jiacheng Yao, Wei Xu, Zhaohui Yang +3
To enable wireless federated learning (FL) in communication resource-constrained networks, two communication schemes, i.e., digital and analog ones, are effective solutions. In thi…
A Reconfigurable Subarray Architecture and Hybrid Beamforming for Millimeter-Wave Dual-Function-Radar-Communication Systems
Xin Jin, Tiejun Lv, Wei Ni +4
Dual-function-radar-communication (DFRC) is a promising candidate technology for next-generation networks. By integrating hybrid analog-digital (HAD) beamforming into a multi-user…
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Arman Adibi, Nicolo Dal Fabbro, Luca Schenato +5
Motivated by applications in large-scale and multi-agent reinforcement learning, we study the non-asymptotic performance of stochastic approximation (SA) schemes with delayed updat…
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation
Nicolò Dal Fabbro, Arman Adibi, H. Vincent Poor +3
We consider a setting in which agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume tha…
Digital versus Analog Transmissions for Federated Learning over Wireless Networks
Jiacheng Yao, Wei Xu, Zhaohui Yang +3
In this paper, we quantitatively compare these two effective communication schemes, i.e., digital and analog ones, for wireless federated learning (FL) over resource-constrained ne…
Private Knowledge Sharing in Distributed Learning: A Survey
Yasas Supeksala, Dinh C. Nguyen, Ming Ding +5
The rise of Artificial Intelligence (AI) has revolutionized numerous industries and transformed the way society operates. Its widespread use has led to the distribution of AI and i…
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach
Kai Li, Jingjing Zheng, Xin Yuan +3
This paper proposes a novel, data-agnostic, model poisoning attack on Federated Learning (FL), by designing a new adversarial graph autoencoder (GAE)-based framework. The attack re…
From OTFS to DD-ISAC: Integrating Sensing and Communications in the Delay Doppler Domain
Weijie Yuan, Lin Zhou, Saeid K. Dehkordi +4
Next-generation vehicular networks are expected to provide the capability of robust environmental sensing in addition to reliable communications to meet intelligence requirements.…
Federated Learning via Active RIS Assisted Over-the-Air Computation
Deyou Zhang, Ming Xiao, Mikael Skoglund +1
In this paper, we propose leveraging the active reconfigurable intelligence surface (RIS) to support reliable gradient aggregation for over-the-air computation (AirComp) enabled fe…
Charge Manipulation Attacks Against Smart Electric Vehicle Charging Stations and Deep Learning-based Detection Mechanisms
Hamidreza Jahangir, Subhash Lakshminarayana, H. Vincent Poor
The widespread deployment of "smart" electric vehicle charging stations (EVCSs) will be a key step toward achieving green transportation. The connectivity features of smart EVCSs c…
IRS Assisted Federated Learning A Broadband Over-the-Air Aggregation Approach
Deyou Zhang, Ming Xiao, Zhibo Pang +2
We consider a broadband over-the-air computation empowered model aggregation approach for wireless federated learning (FL) systems and propose to leverage an intelligent reflecting…
Adversarial Learning for Implicit Semantic-Aware Communications
Zhimin Lu, Yong Xiao, Zijian Sun +5
Semantic communication is a novel communication paradigm that focuses on recognizing and delivering the desired meaning of messages to the destination users. Most existing works in…
Towards Self-learning Edge Intelligence in 6G
Yong Xiao, Guangming Shi, Yingyu Li +2
Edge intelligence, also called edge-native artificial intelligence (AI), is an emerging technological framework focusing on seamless integration of AI, communication networks, and…