118 citations · 152 across the 16 of their papers we have counts for
4 papers · 1 filter
End-to-end Learning for Fair Ranking Systems
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck +1
The learning-to-rank problem aims at ranking items to maximize exposure of those most relevant to a user query. A desirable property of such ranking systems is to guarantee some no…
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
The Jobs shop Scheduling Problem (JSP) is a canonical combinatorial optimization problem that is routinely solved for a variety of industrial purposes. It models the optimal schedu…
Learning Hard Optimization Problems: A Data Generation Perspective
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
Optimization problems are ubiquitous in our societies and are present in almost every segment of the economy. Most of these optimization problems are NP-hard and computationally de…
End-to-End Constrained Optimization Learning: A Survey
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck +1
This paper surveys the recent attempts at leveraging machine learning to solve constrained optimization problems. It focuses on surveying the work on integrating combinatorial solv…