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Learn-n-Route: Learning implicit preferences for vehicle routing
We investigate a learning decision support system for vehicle routing, w...
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Discrete solution pools and noise-contrastive estimation for predict-and-optimize
Numerous real-life decision-making processes involve solving a combinato...
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Interior Point Solving for LP-based prediction+optimisation
Solving optimization problems is the key to decision making in many real...
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A framework for step-wise explaining how to solve constraint satisfaction problems
We explore the problem of step-wise explaining how to solve constraint s...
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Hybrid Classification and Reasoning for Image-based Constraint Solving
There is an increased interest in solving complex constrained problems w...
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Learning to rank for uplift modeling
Uplift modeling has effectively been used in fields such as marketing an...
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Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems
Combinatorial optimization assumes that all parameters of the optimizati...
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Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining
Finding interesting patterns is a challenging task in data mining. Const...
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Vehicle routing by learning from historical solutions
The goal of this paper is to investigate a decision support system for v...
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Learning Relational Representations with Auto-encoding Logic Programs
Deep learning methods capable of handling relational data have prolifera...
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Solution Dominance over Constraint Satisfaction Problems
Constraint Satisfaction Problems (CSPs) typically have many solutions th...
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An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming
The main advantage of Constraint Programming (CP) approaches for sequent...
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The Inductive Constraint Programming Loop
Constraint programming is used for a variety of real-world optimisation ...
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