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08/09/2023
How to induce regularization in generalized linear models: A guide to reparametrizing gradient flow
In this work, we analyze the relation between reparametrizations of grad...
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07/24/2023
Tuning-free one-bit covariance estimation using data-driven dithering
We consider covariance estimation of any subgaussian distribution from f...
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06/08/2023
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
We propose a new algorithm for the problem of recovering data that adher...
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01/11/2023
Plug-in Channel Estimation with Dithered Quantized Signals in Spatially Non-Stationary Massive MIMO Systems
As the array dimension of massive MIMO systems increases to unprecedente...
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09/07/2022
A simple approach for quantizing neural networks
In this short note, we propose a new method for quantizing the weights o...
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07/18/2022
Non-negative Least Squares via Overparametrization
In many applications, solutions of numerical problems are required to be...
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12/21/2021
More is Less: Inducing Sparsity via Overparameterization
In deep learning it is common to overparameterize the neural networks, t...
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06/11/2021
New challenges in covariance estimation: multiple structures and coarse quantization
In this self-contained chapter, we revisit a fundamental problem of mult...
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04/02/2021
Covariance estimation under one-bit quantization
We consider the classical problem of estimating the covariance matrix of...
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03/09/2021
Robust Sensing of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition
We consider the problem of recovering an unknown low-rank matrix X with ...
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03/02/2021
Structural Sparsity in Multiple Measurements
We propose a novel sparsity model for distributed compressed sensing in ...
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11/27/2020
Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank
We provide an explicit analysis of the dynamics of vanilla gradient desc...
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11/18/2019
Quantized Compressed Sensing by Rectified Linear Units
This work is concerned with the problem of recovering high-dimensional s...
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08/07/2019
Linear convergence and support recovery for non-convex multi-penalty regularization
We provide a comprehensive convergence study of the iterative multi-pena...
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07/17/2018
On Recovery Guarantees for One-Bit Compressed Sensing on Manifolds
This paper studies the problem of recovering a signal from one-bit compr...
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05/09/2018
