Yue M. Lu | DeepAI

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Yonina C. Eldar
157 publications
Yuxin Chen
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Florent Krzakala
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Lenka Zdeborová
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Gen Li
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Yuejie Chi
64 publications
Christos Thrampoulidis
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Laura Balzano
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Stanley H. Chan
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Manfred Opper
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Ingrid Daubechies
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∙ 08/04/2022

Spectral Universality of Regularized Linear Regression with Nearly Deterministic Sensing Matrices

It has been observed that the performances of many high-dimensional esti...

0 Rishabh Dudeja, et al. ∙

∙ 05/13/2022

Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime

The generalization performance of kernel ridge regression (KRR) exhibits...

0 Hong Hu, et al. ∙

∙ 05/12/2022

An Equivalence Principle for the Spectrum of Random Inner-Product Kernel Matrices

We consider random matrices whose entries are obtained by applying a (no...

0 Yue M. Lu, et al. ∙

∙ 02/16/2022

Analysis of Random Sequential Message Passing Algorithms for Approximate Inference

We analyze the dynamics of a random sequential message passing algorithm...

0 Burak Çakmak, et al. ∙

∙ 02/15/2021

On the Inherent Regularization Effects of Noise Injection During Training

Randomly perturbing networks during the training process is a commonly u...

0 Oussama Dhifallah, et al. ∙

∙ 01/19/2021

Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles

This paper proposes a new algorithm, named Householder Dice (HD), for si...

0 Yue M. Lu, et al. ∙

∙ 01/06/2021

Phase Transitions in Transfer Learning for High-Dimensional Perceptrons

Transfer learning seeks to improve the generalization performance of a t...

0 Oussama Dhifallah, et al. ∙

∙ 12/08/2020

Construction of optimal spectral methods in phase retrieval

We consider the phase retrieval problem, in which the observer wishes to...

0 Antoine Maillard, et al. ∙

∙ 09/16/2020

Universality Laws for High-Dimensional Learning with Random Features

We prove a universality theorem for learning with random features. Our r...

0 Hong Hu, et al. ∙

∙ 08/27/2020

A Precise Performance Analysis of Learning with Random Features

We study the problem of learning an unknown function using random featur...

0 Oussama Dhifallah, et al. ∙

∙ 06/15/2020

The Limiting Poisson Law of Massive MIMO Detection with Box Relaxation

Estimating a binary vector from noisy linear measurements is a prototypi...

0 Hong Hu, et al. ∙

∙ 06/11/2020

Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization

We consider a commonly studied supervised classification of a synthetic ...

9 Benjamin Aubin, et al. ∙

∙ 02/26/2020

The role of regularization in classification of high-dimensional noisy Gaussian mixture

We consider a high-dimensional mixture of two Gaussians in the noisy reg...

35 Francesca Mignacco, et al. ∙

∙ 05/13/2019

Generalized Approximate Survey Propagation for High-Dimensional Estimation

In Generalized Linear Estimation (GLE) problems, we seek to estimate a s...

0 Luca Saglietti, et al. ∙

∙ 03/27/2019

Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression

In sparse linear regression, the SLOPE estimator generalizes LASSO by as...

0 Hong Hu, et al. ∙

∙ 11/11/2018

Optimal Spectral Initialization for Signal Recovery with Applications to Phase Retrieval

We present the optimal design of a spectral method widely used to initia...

0 Wangyu Luo, et al. ∙

∙ 09/25/2018

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

Substantial progress has been made recently on developing provably accur...

0 Yuejie Chi, et al. ∙

∙ 08/06/2018

Super Resolution Phase Retrieval for Sparse Signals

In a variety of fields, in particular those involving imaging and optics...

0 Gilles Baechler, et al. ∙

∙ 06/12/2018

Streaming PCA and Subspace Tracking: The Missing Data Case

For many modern applications in science and engineering, data are collec...

0 Laura Balzano, et al. ∙

∙ 05/24/2018

Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms

We study algorithms for solving quadratic systems of equations based on ...

0 Oussama Dhifallah, et al. ∙

∙ 05/22/2018

A Solvable High-Dimensional Model of GAN

Despite the remarkable successes of generative adversarial networks (GAN...

0 Chuang Wang, et al. ∙

∙ 05/17/2018

Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis

We present a high-dimensional analysis of three popular algorithms, name...

0 Chuang Wang, et al. ∙

∙ 12/08/2017

Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA

We present a framework for analyzing the exact dynamics of a class of on...

0 Chuang Wang, et al. ∙

∙ 10/15/2017

The Scaling Limit of High-Dimensional Online Independent Component Analysis

We analyze the dynamics of an online algorithm for independent component...

0 Chuang Wang, et al. ∙

∙ 02/21/2017

Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation

We study a spectral initialization method that serves a key role in rece...

0 Yue M. Lu, et al. ∙

∙ 06/04/2016

A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets

We propose an image representation scheme combining the local and nonloc...

0 Rujie Yin, et al. ∙

∙ 01/01/2016

Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective

Many patch-based image denoising algorithms can be formulated as applyin...

0 Stanley H. Chan, et al. ∙

∙ 12/27/2013

Monte Carlo non local means: Random sampling for large-scale image filtering

We propose a randomized version of the non-local means (NLM) algorithm f...

0 Stanley H. Chan, et al. ∙

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