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Learning Hard Optimization Problems: A Data Generation Perspective
4 June 2021
James Kotary
Ferdinando Fioretto
Pascal Van Hentenryck
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Papers citing
"Learning Hard Optimization Problems: A Data Generation Perspective"
7 / 7 papers shown
Title
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework
Mitchell Keegan
Mahdi Abolghasemi
92
1
0
06 Dec 2023
Optimization-based Learning for Dynamic Load Planning in Trucking Service Networks
Ritesh Ojha
Wenbo Chen
Hanyu Zhang
Reem Khir
A. Erera
Pascal Van Hentenryck
100
2
0
08 Jul 2023
Self-Supervised Primal-Dual Learning for Constrained Optimization
Seonho Park
Pascal Van Hentenryck
81
51
0
18 Aug 2022
Fast Continuous and Integer L-shaped Heuristics Through Supervised Learning
Eric Larsen
Emma Frejinger
B. Gendron
Andrea Lodi
59
19
0
02 May 2022
Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problems
Tianyu Zhao
Xiang Pan
Minghua Chen
S. Low
84
10
0
15 Dec 2021
Towards Understanding the Unreasonable Effectiveness of Learning AC-OPF Solutions
M. H. Dinh
Ferdinando Fioretto
M. Mohammadian
K. Baker
26
1
0
22 Nov 2021
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method
James Kotary
Ferdinando Fioretto
Pascal Van Hentenryck
100
20
0
12 Oct 2021
1