26 lines
2.1 KiB
XML
26 lines
2.1 KiB
XML
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<?xml version="1.0" encoding="utf-8" standalone="yes"?>
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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
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<channel>
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<title>theses on aethrvmn</title>
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<link>http://localhost:1313/theses/</link>
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<description>Recent content in theses on aethrvmn</description>
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<generator>Hugo</generator>
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<language>en</language>
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<atom:link href="http://localhost:1313/theses/index.xml" rel="self" type="application/rss+xml" />
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<item>
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<title>masters thesis</title>
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<link>http://localhost:1313/theses/master-thesis/</link>
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<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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<guid>http://localhost:1313/theses/master-thesis/</guid>
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<description>Reinforcement LearningTheory and Implementation in a Custom Environment # you can find the thesis here and the code here
Abstract # Reinforcement Learning (RL) is a subcategory of Machine Learning that consis- tently surpasses human performance and demonstrates superhuman understand- ing in various environments and datasets. Its applications span from master- ing games like Go and Chess to optimizing real-world operations in robotics, fi- nance, and healthcare. The adaptability and efficiency of RL algorithms in dynamic and complex scenarios highlight their transformative potential across multiple do- mains.</description>
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</item>
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<item>
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<title>bachelor thesis</title>
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<link>http://localhost:1313/theses/bachelor-thesis/</link>
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<pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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<guid>http://localhost:1313/theses/bachelor-thesis/</guid>
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<description>The One–Dimensional Heisenberg ModelRG Methods and Numerical Simulation of the SDRG Process # you can find the thesis here and the code here
Abstract # The Strong Disorder Renormalisation Group (SDRG) method, first introduced by Dasgupta, Ma and Hu, and later greatly expanded by Fisher, yields asymptotically exact results in distributions where the disorder grows without limit in large scales, whilst Fisher also calculated limit values as well as scaling factors for random spin chains.</description>
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</item>
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</channel>
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</rss>
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