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    <title>Lilian-Weng on The Kiseki Log</title>
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      <title>Fully Annotated Guide to &#34;A (Long) Peek into Reinforcement Learning&#34;</title>
      <link>https://ki-seki.github.io/posts/260531-lilian-rl-overview/</link>
      <pubDate>Sun, 31 May 2026 22:20:53 +0800</pubDate>
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      <description>This is a fully annotated guide to Lilian Weng&amp;rsquo;s post A (Long) Peek into Reinforcement Learning.</description>
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      <title>Fully Annotated Guide to &#34;The Multi-Armed Bandit Problem and Its Solutions&#34;</title>
      <link>https://ki-seki.github.io/posts/260430-multi-armed-bandit/</link>
      <pubDate>Thu, 30 Apr 2026 14:25:31 +0800</pubDate>
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      <description>The multi-armed bandit problem is a classic exploration–exploitation dilemma in reinforcement learning. Lilian Weng&amp;rsquo;s post is an excellent introduction, but some mathematical details and motivations can be cryptic. This article annotates it with step-by-step explanations and supplementary notes.</description>
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      <title>Fully Annotated Guide to &#34;What are Diffusion Models?&#34;</title>
      <link>https://ki-seki.github.io/posts/250902-diffusion-annotated/</link>
      <pubDate>Tue, 02 Sep 2025 18:49:24 +0800</pubDate>
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      <description>Diffusion models are the de facto standard for image generation. Lilian Weng’s &amp;ldquo;What Are Diffusion Models?&amp;rdquo; is an excellent introduction to it, but readers without a solid mathematical background may struggle. This article fills that gap with clear, step‑by‑step derivations and explanations.</description>
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