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  1. Quantization in machine learning (Part 1): Theory, sample code, analysis of implementation in CatBoost

    by , 03-21-2024 at 04:35 PM
    The article considers the theoretical application of quantization in the construction of tree models No complex mathematical equations are used. While writing the article, I discovered the absence of established unified terminology in the scientific works of different authors, so I will choose the terminology options that, in my opinion, best reflect the meaning. Besides, I will use the terms of my own in the matters left unattended by other researchers. This article will use terms and concepts
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  2. Neural networks made easy (Part 39): Go-Explore, a different approach to exploration

    by , 03-21-2024 at 03:24 PM
    We continue the theme of environmental exploration in reinforcement learning. In previous articles within this series, we have already looked at algorithms for exploring the environment through curiosity and disagreement in an ensemble of models. Both approaches exploited intrinsic rewards to motivate the agent to perform different actions in similar situations while exploring new areas. But the problem is that the intrinsic reward decreases as the environment gets better explored. In complex cases
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