Sampling Approximately Low-Rank Ising Models: MCMC meets Variational
Methods

Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods

17 February 2022

Frederic Koehler

Andrej Risteski

Papers citing "Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods"

9 / 9 papers shown

Title
On the query complexity of sampling from non-log-concave distributions Yuchen He Chihao Zhang 41 1 0 10 Feb 2025
Learning Hard-Constrained Models with One Sample Andreas Galanis Alkis Kalavasis Anthimos Vardis Kandiros 20 2 0 06 Nov 2023
Low-rank combinatorial optimization and statistical learning by spatial photonic Ising machine Hiroshi Yamashita Ken-ichi Okubo Suguru Shimomura Y. Ogura J. Tanida Hideyuki Suzuki 27 17 0 27 Mar 2023
Hubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detection Satoshi Takabe Takashi Abe 12 1 0 09 Feb 2023
Private estimation algorithms for stochastic block models and mixture models Hongjie Chen Vincent Cohen-Addad Tommaso dÓrsi Alessandro Epasto Jacob Imola David Steurer Stefan Tiegel FedML 43 20 0 11 Jan 2023
Complexity of High-Dimensional Identity Testing with Coordinate Conditional Sampling Antonio Blanca Zongchen Chen Daniel Stefankovic Eric Vigoda 16 3 0 19 Jul 2022
Algorithmic Obstructions in the Random Number Partitioning Problem D. Gamarnik Eren C. Kizildaug 21 21 0 02 Mar 2021
From Sampling to Optimization on Discrete Domains with Applications to Determinant Maximization Nima Anari T. Vuong 24 9 0 10 Feb 2021
Contextual Stochastic Block Models Y. Deshpande Andrea Montanari Elchanan Mossel S. Sen 103 153 0 23 Jul 2018