<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sparse-Learning | Hao Yan</title><link>https://hyan46.github.io/tag/sparse-learning/</link><atom:link href="https://hyan46.github.io/tag/sparse-learning/index.xml" rel="self" type="application/rss+xml"/><description>Sparse-Learning</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-US</language><copyright>© 2026 Hao Yan</copyright><lastBuildDate>Fri, 01 Jan 2021 00:00:00 +0000</lastBuildDate><image><url>https://hyan46.github.io/media/icon_hudffdcafa99c609c7e4dfde01dba38f93_35970_512x512_fill_lanczos_center_3.png</url><title>Sparse-Learning</title><link>https://hyan46.github.io/tag/sparse-learning/</link></image><item><title>Image Decomposition-Based Sparse Extreme Pixel-Level Feature Detection Model with Application to Medical Images</title><link>https://hyan46.github.io/publication/lahoti-image-2021/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/publication/lahoti-image-2021/</guid><description/></item><item><title>Real-Time Detection of Clustered Events in Video-Imaging Data with Applications to Additive Manufacturing</title><link>https://hyan46.github.io/publication/yan-realtime-2021/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/publication/yan-realtime-2021/</guid><description/></item><item><title>AKM2D: An Adaptive Framework for Online Sensing and Anomaly Quantification</title><link>https://hyan46.github.io/publication/yan-akm-2-d-2020/</link><pubDate>Tue, 01 Sep 2020 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/publication/yan-akm-2-d-2020/</guid><description/></item><item><title>Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning</title><link>https://hyan46.github.io/publication/zhang-dynamic-2020/</link><pubDate>Wed, 01 Jan 2020 00:00:00 +0000</pubDate><guid>https://hyan46.github.io/publication/zhang-dynamic-2020/</guid><description/></item></channel></rss>