72 citations · 542 across the 65 of their papers we have counts for
6 papers · 1 filter
On Quantifying Qualitative Geospatial Data: A Probabilistic Approach
Georgios Skoumas, Dieter Pfoser, Anastasios Kyrillidis
Living in the era of data deluge, we have witnessed a web content explosion, largely due to the massive availability of User-Generated Content (UGC). In this work, we specifically…
An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization
Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher
Many scientific and engineering applications feature nonsmooth convex minimization problems over convex sets. In this paper, we address an important instance of this broad class wh…
Composite Self-Concordant Minimization
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex function, endowed with an easily computable proximal op…
Group-Sparse Model Selection: Hardness and Relaxations
Luca Baldassarre, Nirav Bhan, Volkan Cevher +2
Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main pr…
Randomized Low-Memory Singular Value Projection
Stephen Becker, Volkan Cevher, Anastasios Kyrillidis
Affine rank minimization algorithms typically rely on calculating the gradient of a data error followed by a singular value decomposition at every iteration. Because these two step…
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions
Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher
We propose an algorithmic framework for convex minimization problems of a composite function with two terms: a self-concordant function and a possibly nonsmooth regularization term…