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Sinho Chewi
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2020 – today
- 2024
- [j4]Jason M. Altschuler, Sinho Chewi:
Faster High-accuracy Log-concave Sampling via Algorithmic Warm Starts. J. ACM 71(3): 24 (2024) - [j3]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query Lower Bounds for Log-concave Sampling. J. ACM 71(4): 29:1-29:42 (2024) - [c26]Nima Anari, Sinho Chewi, Thuy-Duong Vuong:
Fast parallel sampling under isoperimetry. COLT 2024: 161-185 - [c25]Yiheng Jiang, Sinho Chewi, Aram-Alexandre Pooladian:
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space. COLT 2024: 2720-2721 - [c24]Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li:
Sampling from the Mean-Field Stationary Distribution. COLT 2024: 3099-3136 - [i24]Jason M. Altschuler, Sinho Chewi:
Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds. CoRR abs/2401.00071 (2024) - [i23]Nima Anari, Sinho Chewi, Thuy-Duong Vuong:
Fast parallel sampling under isoperimetry. CoRR abs/2401.09016 (2024) - [i22]Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan Bill Li:
Sampling from the Mean-Field Stationary Distribution. CoRR abs/2402.07355 (2024) - 2023
- [c23]Sinho Chewi, Sébastien Bubeck, Adil Salim:
On the complexity of finding stationary points of smooth functions in one dimension. ALT 2023: 358-374 - [c22]Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu:
Fisher information lower bounds for sampling. ALT 2023: 375-410 - [c21]Matthew Shunshi Zhang, Sinho Chewi, Mufan (Bill) Li, Krishna Balasubramanian, Murat A. Erdogdu:
Improved Discretization Analysis for Underdamped Langevin Monte Carlo. COLT 2023: 36-71 - [c20]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query lower bounds for log-concave sampling. FOCS 2023: 2139-2148 - [c19]Jason M. Altschuler, Sinho Chewi:
Faster high-accuracy log-concave sampling via algorithmic warm starts. FOCS 2023: 2169-2176 - [c18]Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang:
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. ICLR 2023 - [c17]Michael Ziyang Diao, Krishna Balasubramanian, Sinho Chewi, Adil Salim:
Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space. ICML 2023: 7960-7991 - [c16]Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang:
Learning threshold neurons via edge of stability. NeurIPS 2023 - [c15]Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim:
The probability flow ODE is provably fast. NeurIPS 2023 - [i21]Jason M. Altschuler, Sinho Chewi:
Faster high-accuracy log-concave sampling via algorithmic warm starts. CoRR abs/2302.10249 (2023) - [i20]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query lower bounds for log-concave sampling. CoRR abs/2304.02599 (2023) - [i19]Michael Diao, Krishnakumar Balasubramanian, Sinho Chewi, Adil Salim:
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space. CoRR abs/2304.05398 (2023) - [i18]Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim:
The probability flow ODE is provably fast. CoRR abs/2305.11798 (2023) - [i17]Jason M. Altschuler, Sinho Chewi:
Shifted Composition I: Harnack and Reverse Transport Inequalities. CoRR abs/2311.14520 (2023) - [i16]Yiheng Jiang, Sinho Chewi, Aram-Alexandre Pooladian:
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space. CoRR abs/2312.02849 (2023) - 2022
- [j2]Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner:
Gaussian discrepancy: A probabilistic relaxation of vector balancing. Discret. Appl. Math. 322: 123-141 (2022) - [c14]Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet:
Rejection sampling from shape-constrained distributions in sublinear time. AISTATS 2022: 2249-2265 - [c13]Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Shunshi Zhang:
Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev. COLT 2022: 1-2 - [c12]Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet:
The query complexity of sampling from strongly log-concave distributions in one dimension. COLT 2022: 2041-2059 - [c11]Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang:
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo. COLT 2022: 2896-2923 - [c10]Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono:
Improved analysis for a proximal algorithm for sampling. COLT 2022: 2984-3014 - [c9]Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet:
Variational inference via Wasserstein gradient flows. NeurIPS 2022 - [i15]Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet:
Variational inference via Wasserstein gradient flows. CoRR abs/2205.15902 (2022) - [i14]Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang:
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. CoRR abs/2209.11215 (2022) - [i13]Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu:
Fisher information lower bounds for sampling. CoRR abs/2210.02482 (2022) - [i12]Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang:
Learning threshold neurons via the "edge of stability". CoRR abs/2212.07469 (2022) - 2021
- [c8]Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin J. Stromme:
Fast and Smooth Interpolation on Wasserstein Space. AISTATS 2021: 3061-3069 - [c7]Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet:
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. COLT 2021: 1260-1300 - [c6]Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme:
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. NeurIPS 2021: 22132-22145 - [c5]Kwangjun Ahn, Sinho Chewi:
Efficient constrained sampling via the mirror-Langevin algorithm. NeurIPS 2021: 28405-28418 - [i11]Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet:
The query complexity of sampling from strongly log-concave distributions in one dimension. CoRR abs/2105.14163 (2021) - [i10]Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet:
Rejection sampling from shape-constrained distributions in sublinear time. CoRR abs/2105.14166 (2021) - [i9]Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme:
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. CoRR abs/2106.08502 (2021) - [i8]Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner:
Gaussian discrepancy: a probabilistic relaxation of vector balancing. CoRR abs/2109.08280 (2021) - [i7]Sinho Chewi:
The entropic barrier is n-self-concordant. CoRR abs/2112.10947 (2021) - 2020
- [c4]Sinho Chewi, Tyler Maunu, Philippe Rigollet, Austin J. Stromme:
Gradient descent algorithms for Bures-Wasserstein barycenters. COLT 2020: 1276-1304 - [c3]Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet:
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. NeurIPS 2020 - [c2]Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme:
Exponential ergodicity of mirror-Langevin diffusions. NeurIPS 2020 - [i6]Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme:
Exponential ergodicity of mirror-Langevin diffusions. CoRR abs/2005.09669 (2020) - [i5]Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet:
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. CoRR abs/2006.02509 (2020) - [i4]Kwangjun Ahn, Sinho Chewi:
Efficient constrained sampling via the mirror-Langevin algorithm. CoRR abs/2010.16212 (2020) - [i3]Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet:
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. CoRR abs/2012.12810 (2020)
2010 – 2019
- 2019
- [c1]Sinho Chewi, Forest Yang, Avishek Ghosh, Abhay Parekh, Kannan Ramchandran:
Matching Observations to Distributions: Efficient Estimation via Sparsified Hungarian Algorithm. Allerton 2019: 368-375 - 2018
- [j1]Sinho Chewi, Venkat Anantharam:
A Combinatorial Proof of a Formula of Biane and Chapuy. Electron. J. Comb. 25(1): 1 (2018) - [i2]Sinho Chewi, Forest Yang, Avishek Ghosh, Abhay Parekh, Kannan Ramchandran:
Online Absolute Ranking with Partial Information: A Bipartite Graph Matching Approach. CoRR abs/1806.06766 (2018) - 2017
- [i1]Sinho Chewi, Venkat Anantharam:
A combinatorial proof of a formula of Biane and Chapuy. CoRR abs/1705.10925 (2017)
Coauthor Index
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last updated on 2024-09-10 01:17 CEST by the dblp team
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