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Latent variable graphical model selection via convex optimization

Latent variable graphical model selection via convex optimization

6 August 2010
V. Chandrasekaran
P. Parrilo
A. Willsky
    CML
ArXivPDFHTML

Papers citing "Latent variable graphical model selection via convex optimization"

50 / 57 papers shown
Title
Extremal graphical modeling with latent variables via convex optimization
Extremal graphical modeling with latent variables via convex optimization
Sebastian Engelke
Armeen Taeb
31
2
0
14 Mar 2024
Optimal vintage factor analysis with deflation varimax
Optimal vintage factor analysis with deflation varimax
Xin Bing
Dian Jin
Yuqian Zhang
Yuqian Zhang
27
1
0
16 Oct 2023
Causality-oriented robustness: exploiting general noise interventions
Causality-oriented robustness: exploiting general noise interventions
Xinwei Shen
Peter Buhlmann
Armeen Taeb
OOD
67
8
0
18 Jul 2023
Sparse Graphical Linear Dynamical Systems
Sparse Graphical Linear Dynamical Systems
Émilie Chouzenoux
Victor Elvira
36
7
0
06 Jul 2023
SKI to go Faster: Accelerating Toeplitz Neural Networks via Asymmetric
  Kernels
SKI to go Faster: Accelerating Toeplitz Neural Networks via Asymmetric Kernels
Alexander Moreno
Jonathan Mei
Luke Walters
26
0
0
15 May 2023
Bayesian Causal Inference in Doubly Gaussian DAG-probit Models
Bayesian Causal Inference in Doubly Gaussian DAG-probit Models
R. Tahmasbi
Keyvan Tahmasbi
19
0
0
12 Apr 2023
Hidden Factor estimation in Dynamic Generalized Factor Analysis Models
Hidden Factor estimation in Dynamic Generalized Factor Analysis Models
G. Picci
Lucia Falconi
A. Ferrante
Mattia Zorzi
13
3
0
23 Nov 2022
Recovering the Graph Underlying Networked Dynamical Systems under
  Partial Observability: A Deep Learning Approach
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach
Sérgio Machado
Anirudh Sridhar
P. Gil
J. Henriques
J. M. F. Moura
A. Santos
CML
15
2
0
08 Aug 2022
Structure Learning in Graphical Models from Indirect Observations
Structure Learning in Graphical Models from Indirect Observations
Hang Zhang
Afshin Abdi
Faramarz Fekri
CML
26
0
0
06 May 2022
A Computationally Efficient Method for Learning Exponential Family
  Distributions
A Computationally Efficient Method for Learning Exponential Family Distributions
Abhin Shah
Devavrat Shah
G. Wornell
30
10
0
28 Oct 2021
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Tianyi Yao
Minjie Wang
Genevera I. Allen
16
1
0
22 Oct 2021
Joint Gaussian Graphical Model Estimation: A Survey
Joint Gaussian Graphical Model Estimation: A Survey
Katherine Tsai
Oluwasanmi Koyejo
Mladen Kolar
CML
41
20
0
19 Oct 2021
Joint inference of multiple graphs with hidden variables from stationary
  graph signals
Joint inference of multiple graphs with hidden variables from stationary graph signals
Samuel Rey
Andrei Buciulea
Madeline Navarro
Santiago Segarra
A. Marques
30
8
0
05 Oct 2021
Convex Latent Effect Logit Model via Sparse and Low-rank Decomposition
Convex Latent Effect Logit Model via Sparse and Low-rank Decomposition
Hongyuan Zhan
Kamesh Madduri
V. Shankar
10
0
0
22 Aug 2021
Learning latent causal graphs via mixture oracles
Learning latent causal graphs via mixture oracles
Bohdan Kivva
Goutham Rajendran
Pradeep Ravikumar
Bryon Aragam
CML
33
47
0
29 Jun 2021
Learning Gaussian Graphical Models with Latent Confounders
Learning Gaussian Graphical Models with Latent Confounders
Ke Wang
Alexander M. Franks
Sang-Yun Oh
CML
32
2
0
14 May 2021
Spectral Methods for Data Science: A Statistical Perspective
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
44
165
0
15 Dec 2020
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
21
5
0
25 Jul 2020
Learning Restricted Boltzmann Machines with Sparse Latent Variables
Learning Restricted Boltzmann Machines with Sparse Latent Variables
Guy Bresler
Rares-Darius Buhai
18
2
0
07 Jun 2020
Ivy: Instrumental Variable Synthesis for Causal Inference
Ivy: Instrumental Variable Synthesis for Causal Inference
Zhaobin Kuang
Frederic Sala
N. Sohoni
Sen Wu
A. Córdova-Palomera
Jared A. Dunnmon
J. Priest
Christopher Ré
CML
19
26
0
11 Apr 2020
Universality in Learning from Linear Measurements
Universality in Learning from Linear Measurements
Ehsan Abbasi
Fariborz Salehi
B. Hassibi
22
22
0
20 Jun 2019
Learning Dependency Structures for Weak Supervision Models
Learning Dependency Structures for Weak Supervision Models
P. Varma
Frederic Sala
A. He
Alexander Ratner
Christopher Ré
NoLa
19
67
0
14 Mar 2019
Ising Models with Latent Conditional Gaussian Variables
Ising Models with Latent Conditional Gaussian Variables
Frank Nussbaum
Joachim Giesen
CML
17
6
0
28 Jan 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
25
12
0
11 Dec 2018
Group induced graphical lasso allows for discovery of molecular
  pathways-pathways interactions
Group induced graphical lasso allows for discovery of molecular pathways-pathways interactions
Veronica Tozzo
Federico Tomasi
M. Squillario
A. Barla
24
1
0
21 Nov 2018
Learning Latent Fractional dynamics with Unknown Unknowns
Learning Latent Fractional dynamics with Unknown Unknowns
Gaurav Gupta
S. Pequito
P. Bogdan
23
32
0
02 Nov 2018
Robust Sparse Reduced Rank Regression in High Dimensions
Robust Sparse Reduced Rank Regression in High Dimensions
Kean Ming Tan
Qiang Sun
Daniela Witten
27
3
0
18 Oct 2018
Learning Restricted Boltzmann Machines via Influence Maximization
Learning Restricted Boltzmann Machines via Influence Maximization
Guy Bresler
Frederic Koehler
Ankur Moitra
Elchanan Mossel
AI4CE
28
29
0
25 May 2018
Causal Queries from Observational Data in Biological Systems via
  Bayesian Networks: An Empirical Study in Small Networks
Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks
Alex E. White
Matthieu Vignes
CML
17
5
0
04 May 2018
Interpolation and Extrapolation of Toeplitz Matrices via Optimal Mass
  Transport
Interpolation and Extrapolation of Toeplitz Matrices via Optimal Mass Transport
Filip Elvander
A. Jakobsson
Johan Karlsson
24
22
0
10 Nov 2017
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback
Peng Yang
P. Zhao
Xin Gao
Yong Liu
29
20
0
03 Jul 2017
SILVar: Single Index Latent Variable Models
SILVar: Single Index Latent Variable Models
Jonathan Mei
José M. F. Moura
15
24
0
09 May 2017
Learning Semidefinite Regularizers
Learning Semidefinite Regularizers
Yong Sheng Soh
V. Chandrasekaran
37
6
0
05 Jan 2017
Fast Algorithms for Demixing Sparse Signals from Nonlinear Observations
Fast Algorithms for Demixing Sparse Signals from Nonlinear Observations
Mohammadreza Soltani
C. Hegde
27
29
0
03 Aug 2016
Graph-Guided Banding of the Covariance Matrix
Graph-Guided Banding of the Covariance Matrix
Jacob Bien
19
6
0
01 Jun 2016
Generalized Network Psychometrics: Combining Network and Latent Variable
  Models
Generalized Network Psychometrics: Combining Network and Latent Variable Models
S. Epskamp
M. Rhemtulla
D. Borsboom
20
424
0
30 May 2016
Interpreting Latent Variables in Factor Models via Convex Optimization
Interpreting Latent Variables in Factor Models via Convex Optimization
Armeen Taeb
V. Chandrasekaran
16
9
0
04 Jan 2016
Decomposition into Low-rank plus Additive Matrices for
  Background/Foreground Separation: A Review for a Comparative Evaluation with
  a Large-Scale Dataset
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset
T. Bouwmans
A. Sobral
S. Javed
Soon Ki Jung
E. Zahzah
39
330
0
04 Nov 2015
Sparse plus low-rank autoregressive identification in neuroimaging time
  series
Sparse plus low-rank autoregressive identification in neuroimaging time series
Raphaël Liégeois
Bamdev Mishra
Mattia Zorzi
R. Sepulchre
26
26
0
30 Mar 2015
Signal Processing on Graphs: Causal Modeling of Unstructured Data
Signal Processing on Graphs: Causal Modeling of Unstructured Data
Jonathan Mei
José M. F. Moura
CML
AI4TS
25
191
0
28 Feb 2015
A Primal-Dual Algorithmic Framework for Constrained Convex Minimization
A Primal-Dual Algorithmic Framework for Constrained Convex Minimization
Quoc Tran-Dinh
V. Cevher
34
47
0
20 Jun 2014
Linear Estimating Equations for Exponential Families with Application to
  Gaussian Linear Concentration Models
Linear Estimating Equations for Exponential Families with Application to Gaussian Linear Concentration Models
Peter G. M. Forbes
Steffen Lauritzen
38
34
0
04 Nov 2013
Linearized Alternating Direction Method with Parallel Splitting and
  Adaptive Penalty for Separable Convex Programs in Machine Learning
Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning
Zhouchen Lin
Risheng Liu
Zhixun Su
26
193
0
18 Oct 2013
Partial Gaussian Graphical Model Estimation
Partial Gaussian Graphical Model Estimation
Xiao-Tong Yuan
Tong Zhang
54
42
0
28 Sep 2012
On the Linear Convergence of the Alternating Direction Method of
  Multipliers
On the Linear Convergence of the Alternating Direction Method of Multipliers
Mingyi Hong
Zhi-Quan Luo
43
720
0
20 Aug 2012
Alternating Direction Methods for Latent Variable Gaussian Graphical
  Model Selection
Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection
Shiqian Ma
Lingzhou Xue
H. Zou
60
101
0
06 Jun 2012
Learning loopy graphical models with latent variables: Efficient methods
  and guarantees
Learning loopy graphical models with latent variables: Efficient methods and guarantees
Anima Anandkumar
R. Valluvan
52
50
0
17 Mar 2012
Learning a Common Substructure of Multiple Graphical Gaussian Models
Learning a Common Substructure of Multiple Graphical Gaussian Models
Satoshi Hara
Takashi Washio
CML
59
32
0
01 Mar 2012
Clustering using Max-norm Constrained Optimization
Clustering using Max-norm Constrained Optimization
A. Jalali
Nathan Srebro
39
32
0
25 Feb 2012
Sparse Nonparametric Graphical Models
Sparse Nonparametric Graphical Models
John D. Lafferty
Han Liu
Larry A. Wasserman
53
64
0
04 Jan 2012
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