Fetching the paper…
Reading the bibliography…
Factorizing low-rank matrices is a problem with many applications in machine learning and statistics, ranging from sparse PCA to community detection and sub-matrix localization.
The thermodynamic limit in mean field spin glass models
Francesco Guerra and Fabio Lucio Toninelli · 2002
Earlier work this paper cites.
Finite-range spin glasses in the kac limit: free energy and local observables
Silvio Franz and Fabio Lucio Toninelli · 2004
Earlier work this paper cites.
Sparse principal components analysis
Iain M Johnstone and Arthur Yu Lu · 2004
Earlier work this paper cites.
Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
Jinho Baik, Gérard Ben Arous, and Sandrine Péché · 2005
Earlier work this paper cites.
An introduction to mean field spin glass theory: methods and results
Francesco Guerra · 2005
Earlier work this paper cites.
Mutual information and minimum mean-square error in gaussian channels
Dongning Guo, Shlomo Shamai, and Sergio Verdú · 2005
Earlier work this paper cites.
Sparse principal component analysis
Hui Zou, Trevor Hastie, and Robert Tibshirani · 2006
Earlier work this paper cites.
A direct formulation for sparse pca using semidefinite programming
Alexandre d’Aspremont, Laurent El Ghaoui, Michael I Jordan, and Gert RG Lanckriet · 2007
Earlier work this paper cites.
High-dimensional analysis of semidefinite relaxations for sparse principal components
Arash A Amini and Martin J Wainwright · 2008
Earlier work this paper cites.
A nonparametric view of network models and newman–girvan and other modularities
Peter J Bickel and Aiyou Chen · 2009
Earlier work this paper cites.
Exact matrix completion via convex optimization
Emmanuel J Candès and Benjamin Recht · 2009
Earlier work this paper cites.
Matrix completion from a few entries
Raghunandan H Keshavan, Sewoong Oh, and Andrea Montanari · 2009
Earlier work this paper cites.
Exact solution of the gauge symmetric p-spin glass model on a complete graph
Satish Babu Korada and Nicolas Macris · 2009
Earlier work this paper cites.
A singular value thresholding algorithm for matrix completion
Jian-Feng Cai, Emmanuel J Candès, and Zuowei Shen · 2010
Earlier work this paper cites.
Coupled graphical models and their thresholds
S Hamed Hassani, Nicolas Macris, and Rüdiger Urbanke · 2010
Cited alongside, same era.
The dynamics of message passing on dense graphs, with applications to compressed sensing
Mohsen Bayati and Andrea Montanari · 2011
Cited alongside, same era.
Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
Aurelien Decelle, Florent Krzakala, Cristopher Moore, and Lenka Zdeborová · 2011
Cited alongside, same era.
Stochastic blockmodels and community structure in networks
Brian Karrer and Mark EJ Newman · 2011
Cited alongside, same era.
Threshold saturation via spatial coupling: Why convolutional ldpc ensembles perform so well over the bec
Shrinivas Kudekar, Thomas J Richardson, and Rüdiger Urbanke · 2011
Cited alongside, same era.
On consistency and sparsity for principal components analysis in high dimensions
A simple proof of maxwell saturation for coupled scalar recursions
Arvind Yedla, Yung-Yih Jian, Phong S Nguyen, and Henry D Pfister · 2014
Later among the works it cites.
Asymptotic mutual information for the two-groups stochastic block model
Yash Deshpande, Emmanuel Abbe, and Andrea Montanari · 2015
Later among the works it cites.
Submatrix localization via message passing
Bruce Hajek, Yihong Wu, and Jiaming Xu · 2015
Later among the works it cites.
Mmse of probabilistic low-rank matrix estimation: Universality with respect to the output channel
Thibault Lesieur, Florent Krzakala, and Lenka Zdeborová · 2015
Later among the works it cites.
Phase transitions in sparse pca
Thibault Lesieur, Florent Krzakala, and Lenka Zdeborová · 2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Iain M Johnstone and Arthur Yu Lu · 2012
Cited alongside, same era.
Iterative estimation of constrained rank-one matrices in noise
Sundeep Rangan and Alyson K Fletcher · 2012
Cited alongside, same era.
State evolution for general approximate message passing algorithms, with applications to spatial coupling
Adel Javanmard and Andrea Montanari · 2013
Cited alongside, same era.
Low-rank matrix reconstruction and clustering via approximate message passing
Ryosuke Matsushita and Toshiyuki Tanaka · 2013
Cited alongside, same era.
Dynamics and termination cost of spatially coupled mean-field models
Francesco Caltagirone, Silvio Franz, Richard G. Morris, and Lenka Zdeborová · 2014
Cited alongside, same era.
Yudong Chen and Jiaming Xu · 2014
Cited alongside, same era.
Information-theoretically optimal sparse pca
Yash Deshpande and Andrea Montanari · 2014
Cited alongside, same era.
Matrix completion from fewer entries: Spectral detectability and rank estimation
Alaa Saade, Florent Krzakala, and Lenka Zdeborová · 2015
Later among the works it cites.
A nearly tight sum-of-squares lower bound for the planted clique problem
Boaz Barak, Samuel B Hopkins, Jonathan Kelner, Pravesh K Kothari, Ankur Moitra, and Aaron Potechin · 2016
Later among the works it cites.
The mutual information in random linear estimation
Jean Barbier, Mohamad Dia, Nicolas Macris, and Florent Krzakala · 2016
Later among the works it cites.
Spatial coupling as a proof technique and three applications
Andrei Giurgiu, Nicolas Macris, and Rüdiger Urbanke · 2016
Later among the works it cites.
Mutual information in rank-one matrix estimation
Florent Krzakala, Jiaming Xu, and Lenka Zdeborová · 2016
Later among the works it cites.
Performance of a community detection algorithm based on semidefinite programming
Federico Ricci-Tersenghi, Adel Javanmard, and Andrea Montanari · 2016
Later among the works it cites.
Fundamental limits of symmetric low-rank matrix estimation
Marc Lelarge and Léo Miolane · 2017
Later among the works it cites.
High-Dimensional Inference on Dense Graphs with Applications to Coding Theory and Machine Learning
Mohamad Dia · 2018
Closest in time.
The adaptive interpolation method: a simple scheme to prove replica formulas in bayesian inference
Jean Barbier and Nicolas Macris · 2064
Closest in time.