Proximal Gradient Algorithm in the Presence of Adjoint Mismatch

A constrained optimization approach for complex sparse perturbed models

Learning Maximally Monotone Operators for Image Recovery

Deep Unrolled Architecture for Fast and Accurate Gaussian Independent Vector Analysis

A variational approach for joint image recovery and feature extraction based on spatially varying generalised Gaussian models

A Variational Bayesian Approach for Restoring Data Corrupted with Non-Gaussian Noise

A Multi-Parameter Optimization Approach for Complex Continuous Sparse Modelling

Spatio-temporal regularized reconstruction for parallel MRI acquisition systems

A convex variational approach for multiple removal in seismic data

Sparsifying Networks via Subdifferential Inclusion

A Neural Network Approach For Joint Optimization Of Predictors In Lifting-Based Image Coders

A Penalized Subspace Strategy for Solving Large-Scale Constrained Optimization Problems

Adapted Convex Optimization Algorithm for Wavelet-Based Dynamic PET Reconstruction

An Effective Iterative Solution for Independent Vector Analysis with Convergence Guarantees

Vector Lifting Schemes for Stereo Image Coding

Two-dimensional non separable adaptive lifting scheme for still and stereo image coding

A Non-Convex Proximal Approach for Centroid-Based Classification

Fixed Point Strategies in Data Science

A Proximal Approach for Solving Matrix Optimization Problems Involving a Bregman Divergence

Proximal Splitting Adversarial Attack for Semantic Segmentation

Deep Unfolding of the DBFB Algorithm with Application to ROI CT Imaging with Limited Angular Density

Building firmly nonexpansive convolutional neural networks

Efficient Bayes Inference in Neural Networks through Adaptive Importance Sampling

Iterative image deconvolution using overcomplete representations

Procédé de traitement de réflexions multiples

Stochastic Approximations and Perturbations in Forward-Backward Splitting for Monotone Operators

Optimization of Synthesis Oversampled Complex Filter Banks

Majorize-Minimize Adapted Metropolis-Hastings Algorithm

Disparity map estimation under convex constraints using proximal algorithms

Safe Design of Stable Neural Networks for Fault Detection in Small UAVs

Convergence Results for Primal-Dual Algorithms in the Presence of Adjoint Mismatch

Cramer-Rao Bound for a Sparse Complex Model

Hilbert pairs of M-band orthonormal wavelet bases

General risk measures for robust machine learning

Deep Unfolding of the DBFB Algorithm With Application to ROI CT Imaging With Limited Angular Density

Lipschitz Certificates for Layered Network Structures Driven by Averaged Activation Operators

A Nonconvex Variational Approach for Robust Graphical Lasso

A wavelet-based regularized reconstruction algorithm for SENSE parallel MRI with applications to neuroimaging

Learned Image Deblurring by Unfolding a Proximal Interior Point Algorithm

Geometry-Texture Decomposition/Reconstruction Using a Proximal Interior Point Algorithm

Noise Covariance Properties in Dual-Tree Wavelet Decompositions

Playing with Duality: An overview of recent primal-dual approaches for solving large-scale optimization problems

A nonlinear Stein based estimator for multichannel image denoising

A CNC approach for Directional Total Variation

A Forward-Backward View of Some Primal-Dual Optimization Methods in Image Recovery

A proximal approach for a class of matrix optimization problems

Dense disparity map representations for stereo image coding

A Parallel Inertial Proximal Optimization Method

Proximal approaches for matrix optimization problems: Application to robust precision matrix estimation

Efficient Bayes Inference in Neural Networks through Adaptive Importance Sampling