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  <title>e-sygoing.link — Machine Learning</title>
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  <description>Latest links in the Machine Learning category</description>
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    <title>Machine Learning in Games</title>
    <link>https://e-sygoing.link/link/5633149-machine-learning-in-games</link>
    <description>How computers can learn to get better at playing games.  This site is for artificial intelligence researchers and intrepid game programmers. I describe game programs and their workings; they rely on heuristic search algorithms, neural networks, genetic algorithms, temporal differences, and other methods.</description>
    <pubDate>Mon, 01 Dec 2025 02:03:37 -0500</pubDate>
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    <title>Kernel machines</title>
    <link>https://e-sygoing.link/link/5633143-kernel-machines</link>
    <description>A central information source for the area of Support Vector Machines, Gaussian Process prediction, Mathematical Programming with Kernels, Regularization Networks, Reproducing Kernel Hilbert Spaces, and related methods.  Provides links to papers, upcoming events, datasets, code.</description>
    <pubDate>Mon, 13 Oct 2025 03:01:58 -0400</pubDate>
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    <title>Machine Learning Network Online Information Service</title>
    <link>https://e-sygoing.link/link/5633141-machine-learning-network-online-information-service</link>
    <description>The MLnet OiS offers software, datasets, information about events, research groups, persons and other interesting stuff related to machine learning, knowledge discovery, case-based reasoning, knowledge acquisition, and data mining.</description>
    <pubDate>Tue, 12 Aug 2025 22:14:15 -0400</pubDate>
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    <title>Gowachin</title>
    <link>https://e-sygoing.link/link/5633147-gowachin</link>
    <description>A competition on Grammatical Inference.</description>
    <pubDate>Sun, 22 Jun 2025 02:03:08 -0400</pubDate>
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    <title>Group Method of Data Handling (GMDH)</title>
    <link>https://e-sygoing.link/link/5633155-group-method-of-data-handling-gmdh</link>
    <description>Review of the GMDH approach for data mining and forecasting, with examples and software</description>
    <pubDate>Sun, 15 Jun 2025 09:19:42 -0400</pubDate>
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    <title>Integrated Optimization - Artificial Intelligence</title>
    <link>https://e-sygoing.link/link/5633159-integrated-optimization-artificial-intelligence</link>
    <description>Site dedicated to research of artificial intelligence algorithms applied to information retrieval, data mining and optimization methods. Includes FAQs and AI resources for math/science teachers and students.</description>
    <pubDate>Sat, 07 Jun 2025 00:14:26 -0400</pubDate>
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    <title>Computational Learning Theory</title>
    <link>https://e-sygoing.link/link/5633144-computational-learning-theory</link>
    <description>A research field devoted to studying the design and analysis of algorithms for making predictions about the future based on past experiences. The emphasis in COLT is on rigorous mathematical analysis. COLT is largely concerned with computational and data efficiency.</description>
    <pubDate>Sat, 29 Mar 2025 04:07:53 -0400</pubDate>
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    <title>Reinforcement Learning Repository</title>
    <link>https://e-sygoing.link/link/5633161-reinforcement-learning-repository</link>
    <description>A centralized resource for researchers of reinforcement learning.  Maintained at University of Massachusetts, Amherst.</description>
    <pubDate>Wed, 19 Feb 2025 00:03:55 -0500</pubDate>
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    <title>k-means clustering tutorial</title>
    <link>https://e-sygoing.link/link/5633162-k-means-clustering-tutorial</link>
    <description>Introduction to k-means clustering, a popular data mining and unsupervised learning algorithm.  Free code, software, resources and examples are available for download.</description>
    <pubDate>Sat, 15 Feb 2025 15:21:18 -0500</pubDate>
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    <title>Pattern Recognition on The Web</title>
    <link>https://e-sygoing.link/link/5633154-pattern-recognition-on-the-web</link>
    <description>Links to various pattern recognition and machine learning resources</description>
    <pubDate>Fri, 14 Feb 2025 22:29:33 -0500</pubDate>
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