Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning

22 December 2020

Papers citing "Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning"

20 / 20 papers shown

Title
Accelerating Constrained Sampling: A Large Deviations Approach Yingli Wang Changwei Tu Xiaoyu Wang Lingjiong Zhu 18 0 0 09 Jun 2025
Accelerating Langevin Monte Carlo Sampling: A Large Deviations Analysis Nian Yao Pervez Ali Xihua Tao Lingjiong Zhu 75 1 0 24 Mar 2025
Langevin Multiplicative Weights Update with Applications in Polynomial Portfolio Management Yi-Hu Feng Tianlin Li Tian Xie 112 0 0 26 Feb 2025
Constrained Sampling with Primal-Dual Langevin Monte Carlo Luiz F. O. Chamon Mohammad Reza Karimi Anna Korba 89 3 0 08 Jan 2025
Self-normalized Cramér-type Moderate Deviation of Stochastic Gradient Langevin Dynamics Hongsheng Dai Xiequan Fan Jianya Lu 27 1 0 29 Oct 2024
How to beat a Bayesian adversary Zihan Ding Kexin Jin J. Latz Chenguang Liu AAML BDL 80 0 0 11 Jul 2024
Reflected Flow Matching Tianyu Xie Yu Zhu Longlin Yu Tong Yang Ziheng Cheng Shiyue Zhang Xiangyu Zhang Cheng Zhang 84 6 0 26 May 2024
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics Haoyang Zheng Hengrong Du Qi Feng Wei Deng Guang Lin 65 5 0 13 May 2024
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning Eli Chien Haoyu Wang Ziang Chen Pan Li MU 106 17 0 18 Jan 2024
Reflected Schrödinger Bridge for Constrained Generative Modeling Wei Deng Yu Chen Nicole Tianjiao Yang Hengrong Du Qi Feng Ricky T. Q. Chen 54 8 0 06 Jan 2024
Constructing Semantics-Aware Adversarial Examples with Probabilistic Perspective Andi Zhang Mingtian Zhang Damon J. Wischik GAN AAML 46 1 0 01 Jun 2023
Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets Mengmeng Li Daniel Kuhn Tobias Sutter 67 11 0 30 May 2023
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms Tim Tsz-Kit Lau Han Liu Thomas Pock 97 4 0 25 May 2023
Subsampling Error in Stochastic Gradient Langevin Diffusions Kexin Jin Chenguang Liu J. Latz 68 0 0 23 May 2023
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models Anant Raj Umut Simsekli Alessandro Rudi DiffM 114 2 0 30 Mar 2023
Function Approximation with Randomly Initialized Neural Networks for Approximate Model Reference Adaptive Control Tyler Lekang Andrew G. Lamperski 50 0 0 28 Mar 2023
Efficient Bayesian computation for low-photon imaging problems Savvas Melidonis P. Dobson Y. Altmann Marcelo Pereyra K. Zygalakis 44 12 0 10 Jun 2022
Constrained Langevin Algorithms with L-mixing External Random Variables Yu Zheng Andrew G. Lamperski 78 6 0 27 May 2022
Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions Natesh S. Pillai 58 2 0 21 Apr 2022
Convergence Error Analysis of Reflected Gradient Langevin Dynamics for Globally Optimizing Non-Convex Constrained Problems Kanji Sato Akiko Takeda Reiichiro Kawai Taiji Suzuki 57 6 0 19 Mar 2022