62 citations · 315 across the 65 of their papers we have counts for
9 papers · 1 filter
Construction and Iteration-Complexity of Primal Sequences in Alternating Minimization Algorithms
Quoc Tran-Dinh
We introduce a new weighted averaging scheme using "Fenchel-type" operators to recover primal solutions in the alternating minimization-type algorithm (AMA) for prototype constrain…
Adaptive Smoothing Algorithms for Nonsmooth Composite Convex Minimization
Quoc Tran-Dinh
We propose an adaptive smoothing algorithm based on Nesterov's smoothing technique in \cite{Nesterov2005c} for solving "fully" nonsmooth composite convex optimization problems. Our…
Structured Sparsity: Discrete and Convex approaches
Anastasios Kyrillidis, Luca Baldassarre, Marwa El-Halabi +2
Compressive sensing (CS) exploits sparsity to recover sparse or compressible signals from dimensionality reducing, non-adaptive sensing mechanisms. Sparsity is also used to enhance…
A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization
Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher
We propose a new first-order primal-dual optimization framework for a convex optimization template with broad applications. Our optimization algorithms feature optimal convergence…
Smooth Alternating Direction Methods for Nonsmooth Constrained Convex Optimization
Quoc Tran-Dinh, Volkan Cevher
We propose two new alternating direction methods to solve "fully" nonsmooth constrained convex problems. Our algorithms have the best known worst-case iteration-complexity guarante…
Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization
Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh
In this paper we analyze several inexact fast augmented Lagrangian methods for solving linearly constrained convex optimization problems. Mainly, our methods rely on the combinatio…
A new splitting method for solving composite monotone inclusions involving parallel-sum operators
Quoc Tran-Dinh, Bang Cong Vu
We propose a new primal-dual splitting method for solving composite inclusions involving Lipschitzian, and parallel-sum-type monotone operators. Our approach extends the framework…
A Universal Primal-Dual Convex Optimization Framework
Alp Yurtsever, Quoc Tran-Dinh, Volkan Cevher
We propose a new primal-dual algorithmic framework for a prototypical constrained convex optimization template. The algorithmic instances of our framework are universal since they…
Composite convex minimization involving self-concordant-like cost functions
Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher
The self-concordant-like property of a smooth convex function is a new analytical structure that generalizes the self-concordant notion. While a wide variety of important applicati…