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    <title>홍석쓰 블로그</title>
    <link>https://redstarhong.tistory.com/</link>
    <description>Hongsuk Choi
</description>
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    <pubDate>Wed, 6 May 2026 17:57:56 +0900</pubDate>
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    <ttl>100</ttl>
    <managingEditor>홍돌</managingEditor>
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      <title>Retargeting and Optimization</title>
      <link>https://redstarhong.tistory.com/359</link>
      <description>And solving the linear equation system when the system matrix is a triangular matrix is very efficient!

# Normal equations:
(J^TJ)x = J^Ty

# This is exactly our Ax = b where:
A = J^TJ # symmetric positive definite!
b = J^Ty

# Solve using Cholesky:
A = ..</description>
      <category>Research (연구 관련)</category>
      <author>홍돌</author>
      <guid isPermaLink="true">https://redstarhong.tistory.com/359</guid>
      <comments>https://redstarhong.tistory.com/359#entry359comment</comments>
      <pubDate>Mon, 17 Feb 2025 12:06:35 +0900</pubDate>
    </item>
    <item>
      <title>Inference-Time Techniques for LLM Reasoning</title>
      <link>https://redstarhong.tistory.com/358</link>
      <description>Lecture 1, Jan 27th, 2025, https://rdi.berkeley.edu/adv-llm-agents/slides/inference_time_techniques_lecture_sp25.pdf

&amp;nbsp;

Background: How do we evaluate consistency of free-form answers from multiple answer generation?</description>
      <category>Research (연구 관련)</category>
      <author>홍돌</author>
      <guid isPermaLink="true">https://redstarhong.tistory.com/358</guid>
      <comments>https://redstarhong.tistory.com/358#entry358comment</comments>
      <pubDate>Mon, 3 Feb 2025 08:24:24 +0900</pubDate>
    </item>
    <item>
      <title>Dual Contouring</title>
      <link>https://redstarhong.tistory.com/357</link>
      <description>What is Dual contouring?
Dual contouring (DC) is a popular isosurface extraction (surface reconstruction) algorithm for converting a volumetric representation (e.g., an implicit field or voxel grid) into a polygon mesh. It is called &amp;ldquo;dual&amp;rdquo; bec..</description>
      <category>Research (연구 관련)</category>
      <author>홍돌</author>
      <guid isPermaLink="true">https://redstarhong.tistory.com/357</guid>
      <comments>https://redstarhong.tistory.com/357#entry357comment</comments>
      <pubDate>Fri, 17 Jan 2025 18:36:48 +0900</pubDate>
    </item>
    <item>
      <title>Generative AI - Diffusion  / Lecture 1</title>
      <link>https://redstarhong.tistory.com/356</link>
      <description>Jitendra lunch group meeting; source: (Israel&amp;nbsp;/&amp;nbsp;The&amp;nbsp;Technion)
Probability Theory 101
What is the &quot;convolution property of a PDF (probability density function)&quot;?
For two independent random variables, the PDF of their sum is the convolution o..</description>
      <category>Research (연구 관련)</category>
      <author>홍돌</author>
      <guid isPermaLink="true">https://redstarhong.tistory.com/356</guid>
      <comments>https://redstarhong.tistory.com/356#entry356comment</comments>
      <pubDate>Wed, 27 Nov 2024 09:48:12 +0900</pubDate>
    </item>
    <item>
      <title>Transformer / Large models</title>
      <link>https://redstarhong.tistory.com/355</link>
      <description>What is KV caching?&amp;nbsp;
KV caching is specifically related to the auto-regressive approach of a transformer decoder. In a transformer decoder, it attends to the past and current tokens, but not to future tokens. At each time step, the transformer repeat..</description>
      <category>Research (연구 관련)</category>
      <author>홍돌</author>
      <guid isPermaLink="true">https://redstarhong.tistory.com/355</guid>
      <comments>https://redstarhong.tistory.com/355#entry355comment</comments>
      <pubDate>Mon, 25 Nov 2024 14:47:14 +0900</pubDate>
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