Decision trees are highly interpretable models for solving classificatio...
In recent years, the integration of Machine Learning (ML) models with
Op...
In this tutorial, we present a computational overview on computing Nash
...
Cloud networks are the backbone of the modern distributed internet
infra...
This paper presents a methodology for integrating machine learning techn...
In the last years, there has been a great interest in machine-learning-b...
We address interactive panoptic annotation, where one segment all object...
Motivated by recent progress on online linear programming (OLP), we stud...
Branch-and-bound approaches in integer programming require ordering port...
Extensive research has been conducted, over recent years, on various way...
A NOtice To AirMen (NOTAM) contains important flight route related
infor...
The expressive and computationally inexpensive bipartite Graph Neural
Ne...
In Machine Learning, Artificial Neural Networks (ANNs) are a very powerf...
We consider the problem of training a deep neural network with nonsmooth...
Mixed-integer programming (MIP) technology offers a generic way of
formu...
State-of-the-art Mixed Integer Linear Program (MILP) solvers combine
sys...
The many-to-one stable matching problem provides the fundamental abstrac...
We propose a methodology at the nexus of operations research and machine...
Combinatorial optimization is a well-established area in operations rese...
Column generation is an iterative method used to solve a variety of
opti...
Finding high-quality solutions to mixed-integer linear programming probl...
In this paper, we consider both first- and second-order techniques to ad...
We present ZERO, a modular and extensible C++ library interfacing
Mathem...
The concept of Nash equilibrium enlightens the structure of rational beh...
The college admission problem plays a fundamental role in several real-w...
Despite the extensive research efforts and the remarkable results obtain...
The Random Utility Maximization model is by far the most adopted framewo...
We survey optimization problems that involve the cardinality of variable...
In this paper we describe Ecole (Extensible Combinatorial Optimization
L...
Primal heuristics play a crucial role in exact solvers for Mixed Integer...
Combinatorial optimization is a well-established area in operations rese...
An important aspect of the quality of a public transport service is its
...
Revenue management is important for carriers (e.g., airlines and railroa...
Airlines have been making use of highly complex Revenue Management Syste...
The recently defined class of integer programming games (IPG) models
sit...
We propose a new stochastic variance-reduced damped L-BFGS algorithm, wh...
We present Ecole, a new library to simplify machine learning research fo...
Many offline unsupervised change point detection algorithms rely on
mini...
Microgrids (MGs) are small-scale power systems which interconnect distri...
A recent Graph Neural Network (GNN) approach for learning to branch has ...
Two-sided markets have become increasingly more important during the las...
Branch and Bound (B B) is the exact tree search method typically used ...
We propose a novel approach using supervised learning to obtain near-opt...
Business research practice is witnessing a surge in the integration of
p...
The goal of a kidney exchange program (KEP) is to maximize number of
tra...
A highly influential ingredient of many techniques designed to exploit
s...
We analyze Nash games played among leaders of Stackelberg games (), and
...
We analyze Nash games played among leaders of Stackelberg games (NASP). ...
We present an approach to couple the resolution of Combinatorial Optimiz...
Combinatorial optimization problems are typically tackled by the
branch-...