15 citations · 20 across the 9 of their papers we have counts for
7 papers · 1 filter
The equivalence of optimal perspective formulation and Shor's SDP for quadratic programs with indicator variables
Shaoning Han, Andrés Gómez, Alper Atamtürk
In this paper, we compare the strength of the optimal perspective reformulation and Shor's SDP relaxation. We prove these two formulations are equivalent for quadratic optimization…
A Graph-based Decomposition Method for Convex Quadratic Optimization with Indicators
Peijing Liu, Salar Fattahi, Andrés Gómez +1
In this paper, we consider convex quadratic optimization problems with indicator variables when the matrix defining the quadratic term in the objective is sparse. We use a grap…
Compact extended formulations for low-rank functions with indicator variables
Shaoning Han, Andrés Gómez
We study the mixed-integer epigraph of a special class of convex functions with non-convex indicator constraints, which are often used to impose logical constraints on the support…
Learning Optimal Prescriptive Trees from Observational Data
Nathanael Jo, Sina Aghaei, Andrés Gómez +1
We consider the problem of learning an optimal prescriptive tree (i.e., an interpretable treatment assignment policy in the form of a binary tree) of moderate depth, from observati…
Dynamic and Static Object Detection Considering Fusion Regions and Point-wise Features
Andrés Gómez, Thomas Genevois, Jerome Lussereau +1
Object detection is a critical problem for the safe interaction between autonomous vehicles and road users. Deep-learning methodologies allowed the development of object detection…
The Axial Anomaly in Lorentz Violating Theories: Towards the Electromagnetic Response of Weakly Tilted Weyl Semimetals
Andrés Gómez, Luis Urrutia
Using the path integral formulation in Euclidean space, we extended the calculation of the abelian chiral anomalies in the case of Lorentz violating theories by considering a new f…
Strong Optimal Classification Trees
Sina Aghaei, Andrés Gómez, Phebe Vayanos
Decision trees are among the most popular machine learning models and are used routinely in applications ranging from revenue management and medicine to bioinformatics. In this pap…