Xiang Cheng
Xiang Cheng
Bekræftet mail på berkeley.edu
Titel
Citeret af
Citeret af
År
Underdamped Langevin MCMC: A non-asymptotic analysis
X Cheng, NS Chatterji, PL Bartlett, MI Jordan
Conference on learning theory, 300-323, 2018
1532018
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
972018
Convergence of Langevin MCMC in KL-divergence
X Cheng, P Bartlett
Algorithmic Learning Theory, 186-211, 2018
942018
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
712016
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
592019
Exploiting optimization for local graph clustering
K Fountoulakis, X Cheng, J Shun, F Roosta-Khorasani, MW Mahoney
arXiv preprint arXiv:1602.01886, 2016
26*2016
Stochastic Gradient and Langevin Processes
X Cheng, D Yin, PL Bartlett, MI Jordan
arXiv preprint arXiv:1907.03215, 2019
15*2019
Optimal dimension dependence of the metropolis-adjusted langevin algorithm
S Chewi, C Lu, K Ahn, X Cheng, T Le Gouic, P Rigollet
Conference on Learning Theory, 1260-1300, 2021
72021
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
72021
The Interplay between Sampling and Optimization
X Cheng
University of California, 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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Artikler 1–11