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1809.01293
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Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory
5 September 2018
Jianyi Zhang
Ruiyi Zhang
Lawrence Carin
Changyou Chen
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ArXiv (abs)
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Papers citing
"Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory"
22 / 22 papers shown
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models
Neural Information Processing Systems (NeurIPS), 2024
Jianyi Zhang
Da-Cheng Juan
Cyrus Rashtchian
Chun-Sung Ferng
Heinrich Jiang
Yiran Chen
396
13
0
01 Nov 2024
Stein Variational Evolution Strategies
Conference on Uncertainty in Artificial Intelligence (UAI), 2024
Cornelius V. Braun
Robert T. Lange
Marc Toussaint
473
4
0
14 Oct 2024
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
Junbo Li
Zichen Miao
Qiang Qiu
Ruqi Zhang
BDL
UQCV
203
10
0
16 Feb 2024
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Gabriele Corso
Yilun Xu
Valentin De Bortoli
Regina Barzilay
Tommi Jaakkola
DiffM
386
40
0
19 Oct 2023
Towards Building the Federated GPT: Federated Instruction Tuning
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Jianyi Zhang
Saeed Vahidian
Martin Kuo
Chunyuan Li
Ruiyi Zhang
Tong Yu
Jiuxiang Gu
Guoyin Wang
Yiran Chen
ALM
FedML
298
182
0
09 May 2023
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction
International Conference on Machine Learning (ICML), 2022
Jianyi Zhang
Ang Li
Minxue Tang
Jingwei Sun
Xiang Chen
Fan Zhang
Chang Chen
Yiran Chen
Xue Yang
FedML
148
70
0
30 Sep 2022
Feature Space Particle Inference for Neural Network Ensembles
International Conference on Machine Learning (ICML), 2022
Shingo Yashima
Teppei Suzuki
Kohta Ishikawa
Ikuro Sato
Rei Kawakami
BDL
239
12
0
02 Jun 2022
Interacting Contour Stochastic Gradient Langevin Dynamics
International Conference on Learning Representations (ICLR), 2022
Wei Deng
Siqi Liang
Botao Hao
Guang Lin
F. Liang
BDL
194
12
0
20 Feb 2022
DPVI: A Dynamic-Weight Particle-Based Variational Inference Framework
Chao Zhang
Zhijian Li
Hui Qian
Xin Du
190
10
0
02 Dec 2021
De-randomizing MCMC dynamics with the diffusion Stein operator
Zheyan Shen
Markus Heinonen
Samuel Kaski
DiffM
223
4
0
07 Oct 2021
Stein Variational Gradient Descent with Multiple Kernel
Cognitive Computation (Cogn Comput), 2021
Qingzhong Ai
Shiyu Liu
Lirong He
Zenglin Xu
340
8
0
20 Jul 2021
On Stein Variational Neural Network Ensembles
Francesco DÁngelo
Vincent Fortuin
F. Wenzel
UQCV
BDL
229
31
0
20 Jun 2021
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent
Neural Information Processing Systems (NeurIPS), 2021
P. Jaini
Lars Holdijk
Max Welling
324
13
0
15 Jun 2021
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
Bang An
Jie Lyu
Zhenyi Wang
Chunyuan Li
Changwei Hu
Fei Tan
Ruiyi Zhang
Yifan Hu
Changyou Chen
AAML
266
29
0
20 Sep 2020
Blindness of score-based methods to isolated components and mixing proportions
Wenliang K. Li
Heishiro Kanagawa
376
36
0
23 Aug 2020
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems
International Conference on Machine Learning (ICML), 2020
Tong Yu
Branislav Kveton
Zheng Wen
Ruiyi Zhang
Ole J. Mengshoel
TDI
201
2
0
09 Jul 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
Neural Information Processing Systems (NeurIPS), 2020
Sinho Chewi
Thibaut Le Gouic
Chen Lu
Tyler Maunu
Philippe Rigollet
308
78
0
03 Jun 2020
Stabilizing Training of Generative Adversarial Nets via Langevin Stein Variational Gradient Descent
Dong Wang
Xiaoqian Qin
F. Song
Li Cheng
GAN
173
26
0
22 Apr 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples
Neural Information Processing Systems (NeurIPS), 2020
Mao Ye
Zhaolin Ren
Qiang Liu
175
8
0
21 Feb 2020
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Ziyu Wang
Shuyu Cheng
Yueru Li
Jun Zhu
Bo Zhang
150
14
0
18 Feb 2020
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
International Conference on Learning Representations (ICLR), 2019
Ruqi Zhang
Chunyuan Li
Jianyi Zhang
Changyou Chen
A. Wilson
BDL
271
290
0
11 Feb 2019
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
Antoine Liutkus
Umut Simsekli
Szymon Majewski
Alain Durmus
Fabian-Robert Stöter
DiffM
324
126
0
21 Jun 2018
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