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11/11/2022
Signal-to-noise ratio aware minimaxity and higher-order asymptotics
Since its development, the minimax framework has been one of the corner ...
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11/05/2021
Impact of the Sensing Spectrum on Signal Recovery in Generalized Linear Models
We consider a nonlinear inverse problem 𝐲= f(𝐀𝐱), where observations 𝐲∈ℝ...
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07/31/2021
Compressed sensing in the presence of speckle noise
The problem of recovering a structured signal from its linear measuremen...
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07/10/2020
Mismatched Data Detection in Massive MU-MIMO
We investigate mismatched data detection for massive multi-user (MU) mul...
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03/30/2020
Sharp Concentration Results for Heavy-Tailed Distributions
We obtain concentration and large deviation for the sums of independent ...
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03/03/2020
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
We study the problem of out-of-sample risk estimation in the high dimens...
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10/25/2019
Information Theoretic Limits for Phase Retrieval with Subsampled Haar Sensing Matrices
We study information theoretic limits of recovering an unknown n dimensi...
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09/20/2019
Does SLOPE outperform bridge regression?
A recently proposed SLOPE estimator (arXiv:1407.3824) has been shown to ...
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03/07/2019
Rigorous Analysis of Spectral Methods for Random Orthogonal Matrices
Phase retrieval refers to algorithmic methods for recovering a signal fr...
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03/06/2019
Spectral Method for Phase Retrieval: an Expectation Propagation Perspective
Phase retrieval refers to the problem of recovering a signal x_∈C^n from...
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02/05/2019
Consistent Risk Estimation in High-Dimensional Linear Regression
Risk estimation is at the core of many learning systems. The importance ...
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01/11/2019
Minimax Linear Estimation of the Retargeted Mean
Weighting methods that adjust for observed covariates, such as inverse p...
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11/05/2018
Optimal Data Detection in Large MIMO
Large multiple-input multiple-output (MIMO) appears in massive multi-use...
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10/26/2018
Benefits of over-parameterization with EM
Expectation Maximization (EM) is among the most popular algorithms for m...
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10/04/2018
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Consider the following class of learning schemes: β̂ := β∈C ∑_j=1^n ℓ(x_...
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07/07/2018
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Consider the following class of learning schemes: β̂ := _β ∑_j=1^n ℓ(x_j...
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06/08/2018
Approximate Message Passing for Amplitude Based Optimization
We consider an ℓ_2-regularized non-convex optimization problem for recov...
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01/30/2018
A scalable estimate of the extra-sample prediction error via approximate leave-one-out
We propose a scalable closed-form formula (ALO_λ) to estimate the extra-...
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01/03/2018
Optimization-based AMP for Phase Retrieval: The Impact of Initialization and ℓ_2-regularization
We consider an ℓ_2-regularized non-convex optimization problem for recov...
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12/08/2017
Compressive Phase Retrieval of Structured Signal
Compressive phase retrieval is the problem of recovering a structured ve...
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11/28/2017
VLSI Design of a Nonparametric Equalizer for Massive MU-MIMO
Linear minimum mean-square error (L-MMSE) equalization is among the most...
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08/26/2016
Global analysis of Expectation Maximization for mixtures of two Gaussians
Expectation Maximization (EM) is among the most popular algorithms for e...
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11/03/2015
Consistent Parameter Estimation for LASSO and Approximate Message Passing
We consider the problem of recovering a vector β_o ∈R^p from n random an...
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09/23/2013
Asymptotic Analysis of LASSOs Solution Path with Implications for Approximate Message Passing
This paper concerns the performance of the LASSO (also knows as basis pu...
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11/12/2012
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
The L1-regularized maximum likelihood estimation problem has recently be...
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11/24/2011