<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>J. Yan | NIULAB</title><link>https://souig.github.io/authors/j.-yan/</link><atom:link href="https://souig.github.io/authors/j.-yan/index.xml" rel="self" type="application/rss+xml"/><description>J. Yan</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en</language><lastBuildDate>Tue, 01 Jul 2025 00:00:00 +0000</lastBuildDate><image><url>https://souig.github.io/media/icon_hu_7d2a9e6dbe042ff1.png</url><title>J. Yan</title><link>https://souig.github.io/authors/j.-yan/</link></image><item><title>Robust Task Offloading and Resource Allocation Under Imperfect Computing Capacity Information in Edge Intelligence Systems</title><link>https://souig.github.io/publication/robust-task-010/</link><pubDate>Tue, 01 Jul 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/robust-task-010/</guid><description/></item><item><title>Dynamic Scheduling for Vehicle-to-Vehicle Communications Enhanced Federated Learning</title><link>https://souig.github.io/publication/dynamic-scheduling-007/</link><pubDate>Sun, 01 Jun 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/dynamic-scheduling-007/</guid><description/></item><item><title>FedCGD: Collective Gradient Divergence Optimized Scheduling for Wireless Federated Learning</title><link>https://souig.github.io/publication/fedcgd-collective-001/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/fedcgd-collective-001/</guid><description/></item><item><title>Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks</title><link>https://souig.github.io/publication/mobility-accelerates-016/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/mobility-accelerates-016/</guid><description/></item><item><title>Mobility-Aware Asynchronous Federated Learning with Dynamic Sparsification</title><link>https://souig.github.io/publication/mobility-aware-asynchronous-274/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/mobility-aware-asynchronous-274/</guid><description/></item><item><title>On the Impact of Mobility in Asynchronous Federated Learning over Device-to-Device Networks</title><link>https://souig.github.io/publication/impact-mobility-d2d-275/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/impact-mobility-d2d-275/</guid><description/></item><item><title>SNAKE: Sequential Continual Learning for Knowledge Extension over Communication-Constrained Networks</title><link>https://souig.github.io/publication/snake-sequential-273/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/snake-sequential-273/</guid><description/></item><item><title>CPU-Utilization-Aware Scheduling for In-Vehicle Distributed Computing</title><link>https://souig.github.io/publication/cpu-utilization-156/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/cpu-utilization-156/</guid><description/></item><item><title>Data-heterogeneous hierarchical federated learning with mobility</title><link>https://souig.github.io/publication/data-heterogeneous-161/</link><pubDate>Fri, 01 Sep 2023 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/data-heterogeneous-161/</guid><description/></item><item><title>Hierarchical Federated Learning: Architecture, Challenges, and Its Implementation in Vehicular Networks</title><link>https://souig.github.io/publication/hierarchical-federated-031/</link><pubDate>Wed, 01 Mar 2023 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/hierarchical-federated-031/</guid><description/></item><item><title>V2V-Assisted Timely Hierarchical Federated Learning</title><link>https://souig.github.io/publication/v2v-assisted-162/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/v2v-assisted-162/</guid><description/></item></channel></rss>