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08/03/2023
Holy Grail 2.0: From Natural Language to Constraint Models
Twenty-seven years ago, E. Freuder highlighted that "Constraint programm...
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07/12/2023
Guided Bottom-Up Interactive Constraint Acquisition
Constraint Acquisition (CA) systems can be used to assist in the modelin...
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07/11/2023
Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning
Many real-world optimization problems contain unknown parameters that mu...
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03/21/2023
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization (extended algorithms and examples)
We build on a recently proposed method for stepwise explaining solutions...
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01/08/2023
A Divide-Align-Conquer Strategy for Program Synthesis
A major bottleneck in search-based program synthesis is the exponentiall...
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05/20/2022
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens
It is increasingly common to solve combinatorial optimisation problems t...
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01/25/2022
Probability estimation and structured output prediction for learning preferences in last mile delivery
We study the problem of learning the preferences of drivers and planners...
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12/07/2021
Predict and Optimize: Through the Lens of Learning to Rank
In the last years predict-and-optimize approaches (Elmachtoub and Grigas...
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08/10/2021
Data Driven VRP: A Neural Network Model to Learn Hidden Preferences for VRP
The traditional Capacitated Vehicle Routing Problem (CVRP) minimizes the...
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05/25/2021
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization
We build on a recently proposed method for explaining solutions of const...
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01/11/2021
Learn-n-Route: Learning implicit preferences for vehicle routing
We investigate a learning decision support system for vehicle routing, w...
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11/10/2020
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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10/26/2020
Interior Point Solving for LP-based prediction+optimisation
Solving optimization problems is the key to decision making in many real...
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06/11/2020
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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03/24/2020
Hybrid Classification and Reasoning for Image-based Constraint Solving
There is an increased interest in solving complex constrained problems w...
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02/14/2020
Learning to rank for uplift modeling
Uplift modeling has effectively been used in fields such as marketing an...
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11/22/2019
Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems
Combinatorial optimization assumes that all parameters of the optimizati...
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10/01/2019
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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09/17/2019
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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03/29/2019
Learning Relational Representations with Auto-encoding Logic Programs
Deep learning methods capable of handling relational data have prolifera...
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12/21/2018
Solution Dominance over Constraint Satisfaction Problems
Constraint Satisfaction Problems (CSPs) typically have many solutions th...
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04/05/2016
An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming
The main advantage of Constraint Programming (CP) approaches for sequent...
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10/12/2015
