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09/21/2023
Convergence and Recovery Guarantees of Unsupervised Neural Networks for Inverse Problems
Neural networks have become a prominent approach to solve inverse proble...
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08/18/2023
Geometric characterizations for strong minima with applications to nuclear norm minimization problems
In this paper, we introduce several geometric characterizations for stro...
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03/20/2023
Convergence Guarantees of Overparametrized Wide Deep Inverse Prior
Neural networks have become a prominent approach to solve inverse proble...
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10/17/2022
Provable Phase Retrieval with Mirror Descent
In this paper, we consider the problem of phase retrieval, which consist...
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12/22/2021
A Stochastic Bregman Primal-Dual Splitting Algorithm for Composite Optimization
We study a stochastic first order primal-dual method for solving convex-...
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05/05/2021
Limits and consistency of non-local and graph approximations to the Eikonal equation
In this paper, we study a non-local approximation of the time-dependent ...
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12/24/2020
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms
Lipschitz continuity of the gradient mapping of a continuously different...
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10/17/2020
Continuum limit of p-Laplacian evolution problems on graphs:L^q graphons and sparse graphs
In this paper we study continuum limits of the discretized p-Laplacian e...
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05/11/2020
Inexact and Stochastic Generalized Conditional Gradient with Augmented Lagrangian and Proximal Step
In this paper we propose and analyze inexact and stochastic versions of ...
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02/11/2020
Wasserstein Control of Mirror Langevin Monte Carlo
Discretized Langevin diffusions are efficient Monte Carlo methods for sa...
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02/08/2020
Learning CHARME models with (deep) neural networks
In this paper, we consider a model called CHARME (Conditional Heterosced...
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07/11/2017
Sensitivity Analysis for Mirror-Stratifiable Convex Functions
This paper provides a set of sensitivity analysis and activity identific...
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07/07/2017
Non-smooth Non-convex Bregman Minimization: Unification and new Algorithms
We propose a unifying algorithm for non-smooth non-convex optimization. ...
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04/12/2013
Astronomical Image Denoising Using Dictionary Learning
Astronomical images suffer a constant presence of multiple defects that ...
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05/07/2012
Risk estimation for matrix recovery with spectral regularization
In this paper, we develop an approach to recursively estimate the quadra...
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05/21/2008
Region-based active contour with noise and shape priors
In this paper, we propose to combine formally noise and shape priors in ...
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05/21/2008
