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How to effectively use machine learning models to predict the solutions
  for optimization problems: lessons from loss function

How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function

14 May 2021
M. Abolghasemi
B. Abbasi
Toktam Babaei
S. Z. Hosseinifard
    AI4CE
ArXivPDFHTML

Papers citing "How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function"

4 / 4 papers shown
Title
Digital Twins for forecasting and decision optimisation with machine
  learning: applications in wastewater treatment
Digital Twins for forecasting and decision optimisation with machine learning: applications in wastewater treatment
Matthew Colwell
Mahdi Abolghasemi
AI4CE
11
0
0
23 Apr 2024
Approximating Solutions to the Knapsack Problem using the Lagrangian
  Dual Framework
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework
Mitchell Keegan
Mahdi Abolghasemi
59
0
0
06 Dec 2023
The intersection of machine learning with forecasting and optimisation:
  theory and applications
The intersection of machine learning with forecasting and optimisation: theory and applications
M. Abolghasemi
26
1
0
24 Nov 2022
Predicting Tactical Solutions to Operational Planning Problems under
  Imperfect Information
Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
Eric Larsen
Sébastien Lachapelle
Yoshua Bengio
Emma Frejinger
Simon Lacoste-Julien
Andrea Lodi
25
46
0
31 Jul 2018
1