<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multi-Task Learning | Benjamin M. Ampel</title><link>https://bampel.com/tag/multi-task-learning/</link><atom:link href="https://bampel.com/tag/multi-task-learning/index.xml" rel="self" type="application/rss+xml"/><description>Multi-Task Learning</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Wed, 05 Aug 2026 00:00:00 +0000</lastBuildDate><image><url>https://bampel.com/media/icon_hu_cc9cb5646de94589.png</url><title>Multi-Task Learning</title><link>https://bampel.com/tag/multi-task-learning/</link></image><item><title>Identifying Protected Health Information in Online Hacker Communities: A Multi-Task Relation Learning Approach</title><link>https://bampel.com/journal_publication/phi-hacker-jmis/</link><pubDate>Wed, 05 Aug 2026 00:00:00 +0000</pubDate><guid>https://bampel.com/journal_publication/phi-hacker-jmis/</guid><description>
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&lt;span class="pub-plain-tag">In Plain Terms&lt;/span>
&lt;p>Stolen medical records are increasingly bought and sold in encrypted chat groups on platforms like Telegram and Discord, buried in huge amounts of unrelated chatter. This paper introduces PHI-NEXT, a system that automatically finds those posts, pulls out what kind of health information is being traded, and tracks how the activity changes over time. It outperforms existing detection methods and gives security teams and regulators a practical way to monitor this underground market at scale.&lt;/p>
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&lt;h3>Key Contributions&lt;/h3>
&lt;p class="pub-muted">Key contributions will be added soon.&lt;/p>
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&lt;h3>Artifacts&lt;/h3>
&lt;p class="pub-muted">No artifacts listed yet.&lt;/p>
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&lt;h3>Related Papers&lt;/h3>
&lt;ul class="pub-related">
&lt;li>
&lt;a href="https://bampel.com/conference_publication/phi-hacker-hicss-2026/">Automatic Extraction of Protected Health Information from Multilingual Hacker Communities&lt;/a>
&lt;span>2026 · HICSS&lt;/span>
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&lt;li>
&lt;a href="https://bampel.com/conference_publication/dtlel-isi/">Labeling Hacker Exploits for Proactive Cyber Threat Intelligence: A Deep Transfer Learning Approach&lt;/a>
&lt;span>2020 · IEEE ISI&lt;/span>
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&lt;li>
&lt;a href="https://bampel.com/journal_publication/dtl-el-misq/">Creating Proactive Cyber Threat Intelligence with Hacker Exploit Labels: A Deep Transfer Learning Approach&lt;/a>
&lt;span>2024 · MIS Quarterly&lt;/span>
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&lt;h3>Citation&lt;/h3>
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&lt;div class="pub-citation-text">Cade Dacosta, Benjamin M. Ampel, Matthew Hashim, &amp;amp; Hsinchun Chen (2026). Identifying Protected Health Information in Online Hacker Communities: A Multi-Task Relation Learning Approach. *Journal of Management Information Systems (JMIS)*, Forthcoming&lt;/div>
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