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Sqrt(d) Dimension Dependence of Langevin Monte Carlo
International Conference on Learning Representations (ICLR), 2021
8 September 2021
Ruilin Li
H. Zha
Molei Tao
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Papers citing
"Sqrt(d) Dimension Dependence of Langevin Monte Carlo"
23 / 23 papers shown
Non-asymptotic error bounds for probability flow ODEs under weak log-concavity
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Francesco Iafrate
Mahsa Taheri
Johannes Lederer
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237
3
0
20 Oct 2025
When Langevin Monte Carlo Meets Randomization: Non-asymptotic Error Bounds beyond Log-Concavity and Gradient Lipschitzness
Xiaojie Wang
Bin Yang
162
0
0
30 Sep 2025
Anchored Langevin Algorithms
Mert Gurbuzbalaban
Hoang M. Nguyen
Xicheng Zhang
Lingjiong Zhu
225
0
0
23 Sep 2025
Mirror Mean-Field Langevin Dynamics
Anming Gu
Juno Kim
337
2
0
05 May 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics
Luke Shaw
Peter A. Whalley
453
4
0
27 Jan 2025
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
Ye He
Alireza Mousavi-Hosseini
Krishnakumar Balasubramanian
Murat A. Erdogdu
322
4
0
27 May 2024
Hierarchic Flows to Estimate and Sample High-dimensional Probabilities
Etienne Lempereur
Stéphane Mallat
271
3
0
06 May 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
Ye He
Kevin Rojas
Molei Tao
DiffM
520
21
0
27 Feb 2024
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm
Annual Conference Computational Learning Theory (COLT), 2023
Vishwak Srinivasan
Andre Wibisono
Ashia Wilson
397
11
0
14 Dec 2023
Nearly
d
d
d
-Linear Convergence Bounds for Diffusion Models via Stochastic Localization
International Conference on Learning Representations (ICLR), 2023
Joe Benton
Valentin De Bortoli
Arnaud Doucet
George Deligiannidis
DiffM
476
200
0
07 Aug 2023
On a Class of Gibbs Sampling over Networks
Annual Conference Computational Learning Theory (COLT), 2023
Bo Yuan
JiaoJiao Fan
Jiaming Liang
Andre Wibisono
Yongxin Chen
236
11
0
23 Jun 2023
Chain of Log-Concave Markov Chains
International Conference on Learning Representations (ICLR), 2023
Saeed Saremi
Ji Won Park
Francis R. Bach
314
15
0
31 May 2023
Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality
Annual Conference Computational Learning Theory (COLT), 2023
Alireza Mousavi-Hosseini
Tyler Farghly
Ye He
Krishnakumar Balasubramanian
Murat A. Erdogdu
438
33
0
07 Mar 2023
Improved dimension dependence of a proximal algorithm for sampling
Annual Conference Computational Learning Theory (COLT), 2023
JiaoJiao Fan
Bo Yuan
Yongxin Chen
534
37
0
20 Feb 2023
A Dynamical System View of Langevin-Based Non-Convex Sampling
Neural Information Processing Systems (NeurIPS), 2022
Mohammad Reza Karimi
Ya-Ping Hsieh
Andreas Krause
384
4
0
25 Oct 2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
International Conference on Learning Representations (ICLR), 2022
Jun-Kun Wang
Andre Wibisono
281
11
0
05 Jul 2022
Self-Consistency of the Fokker-Planck Equation
Annual Conference Computational Learning Theory (COLT), 2022
Zebang Shen
Zhenfu Wang
Satyen Kale
Alejandro Ribeiro
Aim Karbasi
Hamed Hassani
271
28
0
02 Jun 2022
Constrained Langevin Algorithms with L-mixing External Random Variables
Neural Information Processing Systems (NeurIPS), 2022
Yu Zheng
Andrew G. Lamperski
313
7
0
27 May 2022
Convergence of the Riemannian Langevin Algorithm
Khashayar Gatmiry
Santosh Vempala
251
25
0
22 Apr 2022
On Convergence of Federated Averaging Langevin Dynamics
Wei Deng
Qian Zhang
Yi-An Ma
Zhao Song
Guang Lin
FedML
483
18
0
09 Dec 2021
The Mirror Langevin Algorithm Converges with Vanishing Bias
International Conference on Algorithmic Learning Theory (ALT), 2021
Ruilin Li
Molei Tao
Santosh Vempala
Andre Wibisono
261
45
0
24 Sep 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1
International Conference on Machine Learning (ICML), 2021
Adil Salim
Lukang Sun
Peter Richtárik
267
27
0
06 Jun 2021
Hessian-Free High-Resolution Nesterov Acceleration for Sampling
Ruilin Li
H. Zha
Molei Tao
474
10
0
16 Jun 2020
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