21 citations · 67 across the 10 of their papers we have counts for
13 papers
Solution Path of Time-varying Markov Random Fields with Discrete Regularization
Salar Fattahi, Andres Gomez
We study the problem of inferring sparse time-varying Markov random fields (MRFs) with different discrete and temporal regularizations on the parameters. Due to the intractability…
A note on quadratic constraints with indicator variables: Convex hull description and perspective relaxation
Andres Gomez, Weijun Xie
In this paper, we study the mixed-integer nonlinear set given by a separable quadratic constraint on continuous variables, where each continuous variable is controlled by an additi…
Scalable Inference of Sparsely-changing Markov Random Fields with Strong Statistical Guarantees
Salar Fattahi, Andres Gomez
In this paper, we study the problem of inferring time-varying Markov random fields (MRF), where the underlying graphical model is both sparse and changes sparsely over time. Most o…
Supermodularity and valid inequalities for quadratic optimization with indicators
Alper Atamturk, Andres Gomez
We study the minimization of a rank-one quadratic with indicators and show that the underlying set function obtained by projecting out the continuous variables is supermodular. Alt…
Fractional 0-1 programming and submodularity
Shaoning Han, Andres Gomez, Oleg A Prokopyev
In this note we study multiple-ratio fractional 0--1 programs, a broad class of NP-hard combinatorial optimization problems. In particular, under some relatively mild assumptions w…
Ideal formulations for constrained convex optimization problems with indicator variables
Linchuan Wei, Andres Gomez, Simge Kucukyavuz
Motivated by modern regression applications, in this paper, we study the convexification of a class of convex optimization problems with indicator variables and combinatorial const…
Safe Screening Rules for -Regression
Alper Atamtürk, Andrés Gómez
We give safe screening rules to eliminate variables from regression with regularization or cardinality constraint. These rules are based on guarantees that a feature may o…
Learning Optimal Classification Trees: Strong Max-Flow Formulations
Sina Aghaei, Andres Gomez, Phebe Vayanos
We consider the problem of learning optimal binary classification trees. Literature on the topic has burgeoned in recent years, motivated both by the empirical suboptimality of heu…
Rank-one Convexification for Sparse Regression
Alper Atamturk, Andres Gomez
Sparse regression models are increasingly prevalent due to their ease of interpretability and superior out-of-sample performance. However, the exact model of sparse regression with…
Sparse and Smooth Signal Estimation: Convexification of L0 Formulations
Alper Atamturk, Andres Gomez, Shaoning Han
Signal estimation problems with smoothness and sparsity priors can be naturally modeled as quadratic optimization with -"norm" constraints. Since such problems are non-conv…
Simplex QP-based methods for minimizing a conic quadratic objective over polyhedra
Alper Atamturk, Andres Gomez
We consider minimizing a conic quadratic objective over a polyhedron. Such problems arise in parametric value-at-risk minimization, portfolio optimization, and robust optimization…
Submodularity in conic quadratic mixed 0-1 optimization
Alper Atamturk, Andres Gomez
We describe strong convex valid inequalities for conic quadratic mixed 0-1 optimization. These inequalities can be utilized for solving numerous practical nonlinear discrete optimi…
Intrusion Prevention and Detection in Grid Computing - The ALICE Case
Andres Gomez, Camilo Lara, Udo Kebschull
Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is use…