activity
20182021
most citedSupermodularity and valid inequalities for quadratic optimization with indicators

2 citations · 3 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG20211 cited

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…

math.OC20202 cited

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…

math.OC2020

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…

stat.ML2020

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…

stat.ML2020

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…

stat.ML2019

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…