Cleaning large correlation matrices: tools from random matrix theory

25 October 2016

Papers citing "Cleaning large correlation matrices: tools from random matrix theory"

46 / 46 papers shown

Title
Compute-Optimal LLMs Provably Generalize Better With Scale Marc Finzi Sanyam Kapoor Diego Granziol Anming Gu Christopher De Sa J. Zico Kolter Andrew Gordon Wilson 30 0 0 21 Apr 2025
Spectral Analysis of Representational Similarity with Limited Neurons Hyunmo Kang Abdulkadir Canatar SueYeon Chung 66 1 0 27 Feb 2025
A theoretical framework for overfitting in energy-based modeling Giovanni Catania A. Decelle Cyril Furtlehner Beatriz Seoane 57 2 0 31 Jan 2025
Variational Bayes Portfolio Construction Nicolas Nguyen James Ridgway Claire Vernade 31 0 0 09 Nov 2024
On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational invariance Jean Barbier Francesco Camilli Justin Ko Koki Okajima 26 5 0 04 Nov 2024
A Pluggable Common Sense-Enhanced Framework for Knowledge Graph Completion Guanglin Niu Bo Li Siling Feng 29 0 0 06 Oct 2024
Optimal Estimation of Structured Covariance Operators Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 33 3 0 04 Aug 2024
From Zero to Hero: How local curvature at artless initial conditions leads away from bad minima Tony Bonnaire Giulio Biroli C. Cammarota 38 0 0 04 Mar 2024
Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation Markus Gross A. Raulf Christoph Räth 38 0 0 23 Nov 2023
Simultaneous Dimensionality Reduction: A Data Efficient Approach for Multimodal Representations Learning Eslam Abdelaleem Ahmed Roman K. M. Martini I. Nemenman 21 1 0 05 Oct 2023
Quantifying the information lost in optimal covariance matrix cleaning Christian Bongiorno Lamia Lamrani 21 2 0 03 Oct 2023
On the Noise Sensitivity of the Randomized SVD Elad Romanov 22 0 0 27 May 2023
Gradient flow on extensive-rank positive semi-definite matrix denoising A. Bodin N. Macris 34 3 0 16 Mar 2023
Noise-cleaning the precision matrix of fMRI time series Miguel Ibánez-Berganza C. Lucibello Francesca Santucci T. Gili A. Gabrielli 24 1 0 06 Feb 2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien A. Cabannes B. Kiani Randall Balestriero Yann LeCun A. Bietti SSL 11 31 0 06 Feb 2023
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures Antione Bodin N. Macris 34 4 0 13 Dec 2022
Correlation matrix of equi-correlated normal population: fluctuation of the largest eigenvalue, scaling of the bulk eigenvalues, and stock market Y. Akama 16 3 0 11 Dec 2022
Concentration Phenomenon for Random Dynamical Systems: An Operator Theoretic Approach Muhammad Naeem Miroslav Pajic 15 1 0 07 Dec 2022
Boundary between noise and information applied to filtering neural network weight matrices Max Staats M. Thamm B. Rosenow 16 3 0 08 Jun 2022
Random matrix analysis of deep neural network weight matrices M. Thamm Max Staats B. Rosenow 27 12 0 28 Mar 2022
Cleaning large-dimensional covariance matrices for correlated samples Z. Burda A. Jarosz 28 8 0 03 Jul 2021
Large factor model estimation by nuclear norm plus $l_1$ norm penalization M. Farné A. Montanari 22 0 0 06 Apr 2021
Appearance of Random Matrix Theory in Deep Learning Nicholas P. Baskerville Diego Granziol J. Keating 13 11 0 12 Feb 2021
Estimation of Large Financial Covariances: A Cross-Validation Approach Vincent W. C. Tan S. Zohren 19 5 0 10 Dec 2020
Sparse sketches with small inversion bias Michal Derezinski Zhenyu Liao Edgar Dobriban Michael W. Mahoney 15 21 0 21 Nov 2020
A Random Matrix Theory Approach to Damping in Deep Learning Diego Granziol Nicholas P. Baskerville AI4CE ODL 24 2 0 15 Nov 2020
Statistical inference for principal components of spiked covariance matrices Z. Bao Xiucai Ding Jingming Wang Ke Wang 16 50 0 27 Aug 2020
Wigner and Wishart Ensembles for graphical models Hideto Nakashima P. Graczyk 13 2 0 10 Aug 2020
Spectral deconvolution of unitarily invariant matrix models Pierre Tarrago 11 6 0 16 Jun 2020
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training Diego Granziol S. Zohren Stephen J. Roberts ODL 29 48 0 16 Jun 2020
Beyond Random Matrix Theory for Deep Networks Diego Granziol 19 16 0 13 Jun 2020
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data Charles H. Martin Tongsu Peng Peng Michael W. Mahoney 25 101 0 17 Feb 2020
Improved Covariance Matrix Estimator using Shrinkage Transformation and Random Matrix Theory Samruddhi Deshmukh Amartansh Dubey 22 3 0 08 Dec 2019
CorrGAN: Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks Gautier Marti GAN 8 44 0 21 Oct 2019
Asymptotics of empirical eigenvalues for large separable covariance matrices Tiebin Mi Robert C. Qiu 24 0 0 10 Oct 2019
Ridge Regression: Structure, Cross-Validation, and Sketching Sifan Liu Edgar Dobriban CML 25 48 0 06 Oct 2019
Agglomerative Likelihood Clustering Lionel Yelibi Tim Gebbie AI4TS 22 1 0 02 Aug 2019
Learning Clique Forests Guido Previde Massara T. Aste 24 16 0 06 May 2019
Traditional and Heavy-Tailed Self Regularization in Neural Network Models Charles H. Martin Michael W. Mahoney 18 119 0 24 Jan 2019
Optimal cleaning for singular values of cross-covariance matrices Florent Benaych-Georges J. Bouchaud M. Potters 31 7 0 16 Jan 2019
MIXANDMIX: numerical techniques for the computation of empirical spectral distributions of population mixtures Lucilio Cordero-Grande 13 3 0 13 Dec 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 30 190 0 02 Oct 2018
On the overestimation of the largest eigenvalue of a covariance matrix Soufiane Hayou 13 2 0 11 Aug 2017
Cleaning the correlation matrix with a denoising autoencoder Soufiane Hayou 15 0 0 09 Aug 2017
Autoregressive Convolutional Neural Networks for Asynchronous Time Series Mikolaj Binkowski Gautier Marti Philippe Donnat AI4TS BDL 30 149 0 12 Mar 2017
High dimensional deformed rectangular matrices with applications in matrix denoising Xiucai Ding 16 46 0 22 Feb 2017