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Yunbum Kook

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Articles

In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies

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By Yunbum Kook, Santosh S. Vempala, Matthew Zhang
| Wiley Online Library Verified
Y., S. S.Vempala, and M. S.Zhang. 2026. “In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies.” Random Structures & Algorithms68, no. 3: e70061. Kook, https://doi.org/10.1002/rsa.70061. 1 Introduction Generating random samples from a high-dimensional convex body is a basic algorithmic problem with myriad connections and applications. The core of the celebrated result of Dyer et al.
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[2502.09534] Fast Tensor Completion via Approximate Richardson Iteration

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By Matthew Fahrbach, Ali Jadbabaie, Yunbum Kook
| arXiv
arXiv:2502.09534 (cs) View PDF HTML (experimental) Comments: Subjects: Data Structures and Algorithms (cs.DS); Machine Learning (cs.LG); Statistics Theory (math.ST) Cite as: arXiv:2502.09534 [cs.DS] (or arXiv:2502.09534v1 [cs.DS] for this version) https://doi.org/10.48550/arXiv.2502.09534 Submission history From: Matthew Fahrbach [ view email] [v1] Thu, 13 Feb 2025 17:50:27 UTC (5,209 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Connected Papers Toggle...
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