Xiang Cheng
Xiang Cheng
Geverifieerd e-mailadres voor berkeley.edu
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Underdamped Langevin MCMC: A non-asymptotic analysis
X Cheng, NS Chatterji, PL Bartlett, MI Jordan
Conference on Learning Theory, 300-323, 2018
1332018
Sharp convergence rates for Langevin dynamics in the nonconvex setting
X Cheng, NS Chatterji, Y Abbasi-Yadkori, PL Bartlett, MI Jordan
arXiv preprint arXiv:1805.01648, 2018
812018
Convergence of Langevin MCMC in KL-divergence
X Cheng, P Bartlett
Algorithmic Learning Theory, 186-211, 2018
802018
Asymptotic behavior of\ell_p-based laplacian regularization in semi-supervised learning
A El Alaoui, X Cheng, A Ramdas, MJ Wainwright, MI Jordan
Conference on Learning Theory, 879-906, 2016
672016
Is there an analog of Nesterov acceleration for MCMC?
YA Ma, N Chatterji, X Cheng, N Flammarion, P Bartlett, MI Jordan
arXiv preprint arXiv:1902.00996, 2019
502019
Exploiting optimization for local graph clustering
K Fountoulakis, X Cheng, J Shun, F Roosta-Khorasani, MW Mahoney
arXiv preprint arXiv:1602.01886, 2016
25*2016
Stochastic Gradient and Langevin Processes
X Cheng, D Yin, PL Bartlett, MI Jordan
arXiv preprint arXiv:1907.03215, 2019
10*2019
Is there an analog of Nesterov acceleration for gradient-based MCMC?
YA Ma, NS Chatterji, X Cheng, N Flammarion, PL Bartlett, MI Jordan
Bernoulli 27 (3), 1942-1992, 2021
32021
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm
S Chewi, C Lu, K Ahn, X Cheng, TL Gouic, P Rigollet
arXiv preprint arXiv:2012.12810, 2020
32020
The Interplay between Sampling and Optimization
X Cheng
UC Berkeley, 2020
2020
FLAG n’FLARE: Fast Linearly-Coupled Adaptive Gradient Methods
X Cheng, F Roosta, S Palombo, P Bartlett, M Mahoney
International Conference on Artificial Intelligence and Statistics, 404-414, 2018
2018
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Artikelen 1–11