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Xiang Cheng

8 papers hereh-index 121.3k citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author2

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • stat.ML4
  • cs.LG2
  • math.ST2
same name
  • Xiang Cheng — 14 papers, h 23
  • Xiang Cheng — 5 papers
  • Xiang Cheng — 3 papers
  • Xiang Cheng — 2 papers
  • Xiang Cheng — 2 papers, h 54
  • Xiang Cheng — 2 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162020
most citedUnderdamped Langevin MCMC: A non-asymptotic analysis

97 citations · 108 across the 3 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2019

Is There an Analog of Nesterov Acceleration for MCMC?

Yi-An Ma, Niladri Chatterji, Xiang Cheng +3

We formulate gradient-based Markov chain Monte Carlo (MCMC) sampling as optimization on the space of probability measures, with Kullback-Leibler (KL) divergence as the objective fu…

stat.ML2018

Sharp convergence rates for Langevin dynamics in the nonconvex setting

Xiang Cheng, Niladri S. Chatterji, Yasin Abbasi-Yadkori +2

We study the problem of sampling from a distribution p∗(x)∝exp(−U(x)), where the function U is L-smooth everywhere and m-strongly convex outside a ball…

stat.ML2017★ 97 cited

Underdamped Langevin MCMC: A non-asymptotic analysis

Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett +1

We study the underdamped Langevin diffusion when the log of the target distribution is smooth and strongly concave. We present a MCMC algorithm based on its discretization and show…

stat.ML2017

Convergence of Langevin MCMC in KL-divergence

Xiang Cheng, Peter Bartlett

Langevin diffusion is a commonly used tool for sampling from a given distribution. In this work, we establish that when the target density p∗ is such that logp∗ is L smoo…

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