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Efficiently learning Ising models on arbitrary graphs

Efficiently learning Ising models on arbitrary graphs

22 November 2014
Guy Bresler
ArXivPDFHTML

Papers citing "Efficiently learning Ising models on arbitrary graphs"

34 / 34 papers shown
Title
One-Shot Learning for k-SAT
One-Shot Learning for k-SAT
Andreas Galanis
Leslie Ann Goldberg
Xusheng Zhang
36
0
0
10 Feb 2025
Efficient Hamiltonian, structure and trace distance learning of Gaussian states
Efficient Hamiltonian, structure and trace distance learning of Gaussian states
Marco Fanizza
Cambyse Rouzé
Daniel Stilck França
35
4
0
05 Nov 2024
Discrete distributions are learnable from metastable samples
Discrete distributions are learnable from metastable samples
Abhijith Jayakumar
A. Lokhov
Sidhant Misra
Marc Vuffray
39
1
0
17 Oct 2024
Network reconstruction via the minimum description length principle
Network reconstruction via the minimum description length principle
Tiago P. Peixoto
18
5
0
02 May 2024
Structure learning of Hamiltonians from real-time evolution
Structure learning of Hamiltonians from real-time evolution
Ainesh Bakshi
Allen Liu
Ankur Moitra
Ewin Tang
24
13
0
30 Apr 2024
Interaction Screening and Pseudolikelihood Approaches for Tensor
  Learning in Ising Models
Interaction Screening and Pseudolikelihood Approaches for Tensor Learning in Ising Models
Tianyu Liu
Somabha Mukherjee
19
0
0
20 Oct 2023
Limit Theorems and Phase Transitions in the Tensor Curie-Weiss Potts
  Model
Limit Theorems and Phase Transitions in the Tensor Curie-Weiss Potts Model
Sanchayan Bhowal
Somabha Mukherjee
23
2
0
03 Jul 2023
A survey on the complexity of learning quantum states
A survey on the complexity of learning quantum states
Anurag Anshu
Srinivasan Arunachalam
24
66
0
31 May 2023
Learning and Testing Latent-Tree Ising Models Efficiently
Learning and Testing Latent-Tree Ising Models Efficiently
Davin Choo
Y. Dagan
C. Daskalakis
Anthimos Vardis Kandiros
22
8
0
23 Nov 2022
Structure learning in polynomial time: Greedy algorithms, Bregman
  information, and exponential families
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families
Goutham Rajendran
Bohdan Kivva
Ming Gao
Bryon Aragam
24
17
0
10 Oct 2021
Optimal learning of quantum Hamiltonians from high-temperature Gibbs
  states
Optimal learning of quantum Hamiltonians from high-temperature Gibbs states
Jeongwan Haah
Robin Kothari
Ewin Tang
16
67
0
10 Aug 2021
Learned Optimizers for Analytic Continuation
Learned Optimizers for Analytic Continuation
Dongchen Huang
Yi-Feng Yang
11
9
0
28 Jul 2021
Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A
  Statistical Mechanics Analysis
Ising Model Selection Using ℓ1\ell_{1}ℓ1​-Regularized Linear Regression: A Statistical Mechanics Analysis
Xiangming Meng
T. Obuchi
Y. Kabashima
24
4
0
08 Feb 2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition
Ilias Diakonikolas
D. Kane
Alistair Stewart
Yuxin Sun
22
15
0
03 Feb 2021
From Boltzmann Machines to Neural Networks and Back Again
From Boltzmann Machines to Neural Networks and Back Again
Surbhi Goel
Adam R. Klivans
Frederic Koehler
13
5
0
25 Jul 2020
Logistic-Regression with peer-group effects via inference in higher
  order Ising models
Logistic-Regression with peer-group effects via inference in higher order Ising models
C. Daskalakis
Nishanth Dikkala
Ioannis Panageas
16
11
0
18 Mar 2020
On Testing for Parameters in Ising Models
On Testing for Parameters in Ising Models
Rajarshi Mukherjee
G. Ray
20
10
0
02 Jun 2019
Data Amplification: Instance-Optimal Property Estimation
Data Amplification: Instance-Optimal Property Estimation
Yi Hao
A. Orlitsky
15
20
0
04 Mar 2019
Learning Ising Models with Independent Failures
Learning Ising Models with Independent Failures
Surbhi Goel
D. Kane
Adam R. Klivans
22
15
0
13 Feb 2019
Predictive Learning on Hidden Tree-Structured Ising Models
Predictive Learning on Hidden Tree-Structured Ising Models
Konstantinos E. Nikolakakis
Dionysios S. Kalogerias
Anand D. Sarwate
18
12
0
11 Dec 2018
The Minimax Learning Rates of Normal and Ising Undirected Graphical
  Models
The Minimax Learning Rates of Normal and Ising Undirected Graphical Models
Luc Devroye
Abbas Mehrabian
Tommy Reddad
16
29
0
18 Jun 2018
Learning Restricted Boltzmann Machines via Influence Maximization
Learning Restricted Boltzmann Machines via Influence Maximization
Guy Bresler
Frederic Koehler
Ankur Moitra
Elchanan Mossel
AI4CE
12
29
0
25 May 2018
Learning Data Dependency with Communication Cost
Learning Data Dependency with Communication Cost
Hyeryung Jang
Hyungseok Song
Yung Yi
8
1
0
29 Apr 2018
Joint estimation of parameters in Ising model
Joint estimation of parameters in Ising model
Promit Ghosal
S. Mukherjee
22
45
0
19 Jan 2018
Lower Bounds for Two-Sample Structural Change Detection in Ising and
  Gaussian Models
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models
Aditya Gangrade
B. Nazer
Venkatesh Saligrama
24
6
0
28 Oct 2017
Learning Graphical Models Using Multiplicative Weights
Learning Graphical Models Using Multiplicative Weights
Adam R. Klivans
Raghu Meka
20
112
0
20 Jun 2017
Optimal structure and parameter learning of Ising models
Optimal structure and parameter learning of Ising models
A. Lokhov
Marc Vuffray
Sidhant Misra
Michael Chertkov
25
79
0
15 Dec 2016
Exact recovery in the Ising blockmodel
Exact recovery in the Ising blockmodel
Quentin Berthet
Philippe Rigollet
P. Srivastava
TPM
16
44
0
12 Dec 2016
Lower Bounds on Active Learning for Graphical Model Selection
Lower Bounds on Active Learning for Graphical Model Selection
Jonathan Scarlett
V. Cevher
30
8
0
08 Jul 2016
Robust Learning of Fixed-Structure Bayesian Networks
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng
Ilias Diakonikolas
D. Kane
Alistair Stewart
OOD
36
46
0
23 Jun 2016
Learning a Tree-Structured Ising Model in Order to Make Predictions
Learning a Tree-Structured Ising Model in Order to Make Predictions
Guy Bresler
Mina Karzand
52
46
0
22 Apr 2016
On the Difficulty of Selecting Ising Models with Approximate Recovery
On the Difficulty of Selecting Ising Models with Approximate Recovery
Jonathan Scarlett
V. Cevher
30
12
0
11 Feb 2016
Inference in Ising Models
Inference in Ising Models
B. Bhattacharya
S. Mukherjee
37
58
0
25 Jul 2015
Learning Polytrees
Learning Polytrees
S. Dasgupta
TPM
67
129
0
23 Jan 2013
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