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1812.07725
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Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization
19 December 2018
Ningyuan Chen
Mert Gurbuzbalaban
Lingjiong Zhu
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Papers citing
"Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization"
20 / 20 papers shown
Contractive kinetic Langevin samplers beyond global Lipschitz continuity
Iosif Lytras
P. Mertikopoulos
103
0
0
15 Sep 2025
Regime-Switching Langevin Monte Carlo Algorithms
Xiaoyu Wang
Yingli Wang
Lingjiong Zhu
89
0
0
31 Aug 2025
Accelerating Constrained Sampling: A Large Deviations Approach
Yingli Wang
Changwei Tu
Xiaoyu Wang
Lingjiong Zhu
200
0
0
09 Jun 2025
Accelerating Langevin Monte Carlo Sampling: A Large Deviations Analysis
Nian Yao
Pervez Ali
Xihua Tao
Lingjiong Zhu
249
1
0
24 Mar 2025
Neural Sampling in Hierarchical Exponential-family Energy-based Models
Neural Information Processing Systems (NeurIPS), 2023
Xingsi Dong
Si Wu
244
3
0
12 Oct 2023
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case
Journal of Complexity (J. Complexity), 2023
Tim Johnston
Iosif Lytras
Sotirios Sabanis
152
11
0
19 Jan 2023
Revisiting the Effects of Stochasticity for Hamiltonian Samplers
International Conference on Machine Learning (ICML), 2021
Giulio Franzese
Dimitrios Milios
Maurizio Filippone
Pietro Michiardi
197
3
0
30 Jun 2021
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
International Conference on Machine Learning (ICML), 2021
A. Camuto
Xiaoyu Wang
Lingjiong Zhu
Chris Holmes
Mert Gurbuzbalaban
Umut Simsekli
177
16
0
13 Feb 2021
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Difan Zou
Pan Xu
Quanquan Gu
334
39
0
19 Oct 2020
Non-Convex Optimization via Non-Reversible Stochastic Gradient Langevin Dynamics
Yuanhan Hu
Xiaoyu Wang
Ningyuan Chen
Mert Gurbuzbalaban
Lingjiong Zhu
152
5
0
06 Apr 2020
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
International Conference on Machine Learning (ICML), 2020
Umut Simsekli
Lingjiong Zhu
Yee Whye Teh
Mert Gurbuzbalaban
196
53
0
13 Feb 2020
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks
Umut Simsekli
Mert Gurbuzbalaban
T. H. Nguyen
G. Richard
Levent Sagun
303
64
0
29 Nov 2019
On Distributed Stochastic Gradient Algorithms for Global Optimization
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
Brian Swenson
Anirudh Sridhar
H. Vincent Poor
213
10
0
21 Oct 2019
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
Neural Information Processing Systems (NeurIPS), 2019
T. H. Nguyen
Umut Simsekli
Mert Gurbuzbalaban
G. Richard
180
71
0
21 Jun 2019
Is There an Analog of Nesterov Acceleration for MCMC?
Yian Ma
Niladri Chatterji
Xiang Cheng
Nicolas Flammarion
Peter L. Bartlett
Sai Li
BDL
179
79
0
04 Feb 2019
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
N. Aybat
Alireza Fallah
Mert Gurbuzbalaban
Asuman Ozdaglar
ODL
427
63
0
23 Jan 2019
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization
T. H. Nguyen
Umut Simsekli
G. Richard
149
30
0
22 Jan 2019
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
Bugra Can
Mert Gurbuzbalaban
Lingjiong Zhu
237
46
0
22 Jan 2019
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration
Ningyuan Chen
Mert Gurbuzbalaban
Lingjiong Zhu
266
65
0
12 Sep 2018
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions
N. Aybat
Alireza Fallah
Mert Gurbuzbalaban
Asuman Ozdaglar
324
62
0
27 May 2018
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