
Benefits of overparameterization with EM
Expectation Maximization (EM) is among the most popular algorithms for m...
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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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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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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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Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
The L1regularized maximum likelihood estimation problem has recently be...
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Suboptimality of Nonlocal Means for Images with Sharp Edges
We conduct an asymptotic risk analysis of the nonlocal means image denoi...
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VLSI Design of a Nonparametric Equalizer for Massive MUMIMO
Linear minimum meansquare error (LMMSE) equalization is among the most...
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Optimizationbased AMP for Phase Retrieval: The Impact of Initialization and ℓ_2regularization
We consider an ℓ_2regularized nonconvex optimization problem for recov...
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Compressive Phase Retrieval of Structured Signal
Compressive phase retrieval is the problem of recovering a structured ve...
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A scalable estimate of the extrasample prediction error via approximate leaveoneout
We propose a scalable closedform formula (ALO_λ) to estimate the extra...
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Approximate Message Passing for Amplitude Based Optimization
We consider an ℓ_2regularized nonconvex optimization problem for recov...
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Approximate LeaveOneOut 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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Approximate LeaveOneOut for HighDimensional NonDifferentiable Learning Problems
Consider the following class of learning schemes: β̂ := β∈C ∑_j=1^n ℓ(x_...
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Optimal Data Detection in Large MIMO
Large multipleinput multipleoutput (MIMO) appears in massive multiuse...
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Consistent Risk Estimation in HighDimensional Linear Regression
Risk estimation is at the core of many learning systems. The importance ...
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Minimax Linear Estimation of the Retargeted Mean
Weighting methods that adjust for observed covariates, such as inverse p...
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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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Rigorous Analysis of Spectral Methods for Random Orthogonal Matrices
Phase retrieval refers to algorithmic methods for recovering a signal fr...
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Does SLOPE outperform bridge regression?
A recently proposed SLOPE estimator (arXiv:1407.3824) has been shown to ...
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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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Arian Maleki
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