<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>J. Song | NIULAB</title><link>https://souig.github.io/authors/j.-song/</link><atom:link href="https://souig.github.io/authors/j.-song/index.xml" rel="self" type="application/rss+xml"/><description>J. Song</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en</language><lastBuildDate>Mon, 01 Jan 2024 00:00:00 +0000</lastBuildDate><image><url>https://souig.github.io/media/icon_hu_7d2a9e6dbe042ff1.png</url><title>J. Song</title><link>https://souig.github.io/authors/j.-song/</link></image><item><title>Adaptive learning-based task of- floading for vehicular edge computing systems</title><link>https://souig.github.io/publication/adaptive-learning-074/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/adaptive-learning-074/</guid><description/></item><item><title>Task Replication for Vehicular Edge Computing: A Combinatorial Multi-Armed Banditbased Approach</title><link>https://souig.github.io/publication/task-replication-195/</link><pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/task-replication-195/</guid><description/></item></channel></rss>