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Sampling Can Be Faster Than Optimization

Sampling Can Be Faster Than Optimization

20 November 2018
Yian Ma
Yuansi Chen
Chi Jin
Nicolas Flammarion
Michael I. Jordan
ArXivPDFHTML

Papers citing "Sampling Can Be Faster Than Optimization"

28 / 28 papers shown
Title
Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm
Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm
Oleksandr Borysenko
Mykhailo Bratchenko
Ilya Lukin
Mykola Luhanko
Ihor Omelchenko
Andrii Sotnikov
Alessandro Lomi
52
0
0
17 Feb 2025
On the query complexity of sampling from non-log-concave distributions
On the query complexity of sampling from non-log-concave distributions
Yuchen He
Chihao Zhang
41
1
0
10 Feb 2025
SniffySquad: Patchiness-Aware Gas Source Localization with Multi-Robot Collaboration
SniffySquad: Patchiness-Aware Gas Source Localization with Multi-Robot Collaboration
Yuhan Cheng
Xuecheng Chen
Yixuan Yang
Haoyang Wang
J. Xu
Chaopeng Hong
Susu Xu
Xiao-Ping Zhang
Yunhao Liu
36
0
0
09 Nov 2024
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling
Matthew Burns
Qingyuan Hou
Michael Huang
143
1
0
08 Oct 2024
High-Rate Phase Association with Travel Time Neural Fields
High-Rate Phase Association with Travel Time Neural Fields
Chengzhi Shi
Maarten V. de Hoop
Ivan Dokmanić
27
1
0
14 Jul 2023
DiffFlow: A Unified SDE Framework for Score-Based Diffusion Models and
  Generative Adversarial Networks
DiffFlow: A Unified SDE Framework for Score-Based Diffusion Models and Generative Adversarial Networks
Jingwei Zhang
Han Shi
Jincheng Yu
Enze Xie
Zhenguo Li
DiffM
26
3
0
05 Jul 2023
Policy Representation via Diffusion Probability Model for Reinforcement
  Learning
Policy Representation via Diffusion Probability Model for Reinforcement Learning
Long Yang
Zhixiong Huang
Fenghao Lei
Yucun Zhong
Yiming Yang
Cong Fang
Shiting Wen
Binbin Zhou
Zhouchen Lin
DiffM
28
40
0
22 May 2023
Convergence Rates for Non-Log-Concave Sampling and Log-Partition
  Estimation
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
David Holzmüller
Francis R. Bach
36
8
0
06 Mar 2023
Privacy Risk for anisotropic Langevin dynamics using relative entropy
  bounds
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds
Anastasia Borovykh
N. Kantas
P. Parpas
G. Pavliotis
19
1
0
01 Feb 2023
Non-convex sampling for a mixture of locally smooth potentials
Non-convex sampling for a mixture of locally smooth potentials
D. Nguyen
33
0
0
31 Jan 2023
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior
  distributions
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions
Marelys Crespo Navas
S. Gadat
X. Gendre
29
0
0
08 Jan 2023
Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling
Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling
Jacopo Guidolin
Vyacheslav Kungurtsev
Ondvrej Kuvzelka
BDL
21
0
0
02 Nov 2022
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling
  Walks
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
Yizhou Liu
Weijie J. Su
Tongyang Li
24
17
0
29 Sep 2022
Composable Text Controls in Latent Space with ODEs
Composable Text Controls in Latent Space with ODEs
Guangyi Liu
Zeyu Feng
Yuan Gao
Zichao Yang
Xiaodan Liang
Junwei Bao
Xiaodong He
Shuguang Cui
Zhen Li
Zhiting Hu
AI4CE
DiffM
36
32
0
01 Aug 2022
COLD Decoding: Energy-based Constrained Text Generation with Langevin
  Dynamics
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics
Lianhui Qin
Sean Welleck
Daniel Khashabi
Yejin Choi
AI4CE
49
144
0
23 Feb 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview,
  Implementation, and Applications
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
19
18
0
28 Jan 2022
On Convergence of Federated Averaging Langevin Dynamics
On Convergence of Federated Averaging Langevin Dynamics
Wei Deng
Qian Zhang
Yi Ma
Zhao Song
Guang Lin
FedML
30
16
0
09 Dec 2021
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
Yindong Chen
Yiwei Wang
Lulu Kang
Chun Liu
23
1
0
21 Nov 2021
When is the Convergence Time of Langevin Algorithms Dimension
  Independent? A Composite Optimization Viewpoint
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint
Y. Freund
Yi Ma
Tong Zhang
37
16
0
05 Oct 2021
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Jian Huang
Yuling Jiao
Lican Kang
Xu Liao
Jin Liu
Yanyan Liu
35
27
0
21 Jun 2021
On the cost of Bayesian posterior mean strategy for log-concave models
On the cost of Bayesian posterior mean strategy for log-concave models
S. Gadat
Fabien Panloup
Clément Pellegrini
26
7
0
08 Oct 2020
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of
  Generative Model
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model
Zhuonan He
Yikun Zhang
Yu Guan
S. Niu
Yi Zhang
Yang Chen
Qiegen Liu
DiffM
MedIm
33
12
0
27 Sep 2020
On stochastic mirror descent with interacting particles: convergence
  properties and variance reduction
On stochastic mirror descent with interacting particles: convergence properties and variance reduction
Anastasia Borovykh
N. Kantas
P. Parpas
G. Pavliotis
28
12
0
15 Jul 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail
  Growth and Smoothness
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness
Murat A. Erdogdu
Rasa Hosseinzadeh
6
74
0
27 May 2020
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with
  Swarm Intelligence
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with Swarm Intelligence
Rohan Mohapatra
Snehanshu Saha
C. Coello
Anwesh Bhattacharya
S. Dhavala
S. Saha
ODL
18
21
0
19 May 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized
  Hamiltonian Monte Carlo
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
Y. Lee
Ruoqi Shen
Kevin Tian
25
37
0
10 Feb 2020
Replica Exchange for Non-Convex Optimization
Replica Exchange for Non-Convex Optimization
Jing-rong Dong
Xin T. Tong
19
21
0
23 Jan 2020
Coupling and Convergence for Hamiltonian Monte Carlo
Coupling and Convergence for Hamiltonian Monte Carlo
Nawaf Bou-Rabee
A. Eberle
Raphael Zimmer
77
136
0
01 May 2018
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