795 citations · 993 across the 20 of their papers we have counts for
22 papers
Smooth over-parameterized solvers for non-smooth structured optimization
Clarice Poon, Gabriel Peyré
Non-smooth optimization is a core ingredient of many imaging or machine learning pipelines. Non-smoothness encodes structural constraints on the solutions, such as sparsity, group…
Smooth Bilevel Programming for Sparse Regularization
Clarice Poon, Gabriel Peyré
Iteratively reweighted least square (IRLS) is a popular approach to solve sparsity-enforcing regression problems in machine learning. State of the art approaches are more efficient…
Screening for Sparse Online Learning
Jingwei Liang, Clarice Poon
Sparsity promoting regularizers are widely used to impose low-complexity structure (e.g. l1-norm for sparsity) to the regression coefficients of supervised learning. In the realm o…
An off-the-grid approach to multi-compartment magnetic resonance fingerprinting
Mohammad Golbabaee, Clarice Poon
We propose a novel numerical approach to separate multiple tissue compartments in image voxels and to estimate quantitatively their nuclear magnetic resonance (NMR) properties and…
Geometry of First-Order Methods and Adaptive Acceleration
Clarice Poon, Jingwei Liang
First-order operator splitting methods are ubiquitous among many fields through science and engineering, such as inverse problems, signal/image processing, statistics, data science…
Degrees of freedom for off-the-grid sparse estimation
Clarice Poon, Gabriel Peyré
A central question in modern machine learning and imaging sciences is to quantify the number of effective parameters of vastly over-parameterized models. The degrees of freedom is…