1.3k citations · 3.8k across the 221 of their papers we have counts for
7 papers · 1 filter
Convex Optimization for Big Data
Volkan Cevher, Stephen Becker, Mark Schmidt
This article reviews recent advances in convex optimization algorithms for Big Data, which aim to reduce the computational, storage, and communications bottlenecks. We provide an o…
A totally unimodular view of structured sparsity
Marwa El Halabi, Volkan Cevher
This paper describes a simple framework for structured sparse recovery based on convex optimization. We show that many structured sparsity models can be naturally represented by li…
Sparsistency of -Regularized -Estimators
Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar +1
We consider the model selection consistency or sparsistency of a broad set of -regularized -estimators for linear and non-linear statistical models in a unified fashion.…
A variational approach to stable principal component pursuit
Aleksandr Aravkin, Stephen Becker, Volkan Cevher +1
We introduce a new convex formulation for stable principal component pursuit (SPCP) to decompose noisy signals into low-rank and sparse representations. For numerical solutions of…
A Primal-Dual Algorithmic Framework for Constrained Convex Minimization
Quoc Tran-Dinh, Volkan Cevher
We present a primal-dual algorithmic framework to obtain approximate solutions to a prototypical constrained convex optimization problem, and rigorously characterize how common str…
Scalable sparse covariance estimation via self-concordance
Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh +1
We consider the class of convex minimization problems, composed of a self-concordant function, such as the metric, a convex data fidelity term and, a regulari…