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2020 – today
- 2023
[j3]Mohit Kumar
, Samuel Kolb, Stefano Teso, Luc De Raedt:
Learning MAX-SAT from contextual examples for combinatorial optimisation. Artif. Intell. 314: 103794 (2023)- [i5]Vincent Derkinderen, Pedro Zuidberg Dos Martires, Samuel Kolb, Paolo Morettin:
Top-Down Knowledge Compilation for Counting Modulo Theories. CoRR abs/2306.04541 (2023) - 2022
- [c17]Senne Berden, Mohit Kumar, Samuel Kolb, Tias Guns:
Learning MAX-SAT Models from Examples Using Genetic Algorithms and Knowledge Compilation. CP 2022: 8:1-8:17 - [c16]Mohit Kumar, Samuel Kolb, Tias Guns:
Learning Constraint Programming Models from Data Using Generate-And-Aggregate. CP 2022: 29:1-29:16 - [p1]Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt:
Human-Machine Collaboration for Democratizing Data Science. Human-Like Machine Intelligence 2022: 379-402 - [i4]Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt:
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation. CoRR abs/2202.03888 (2022) - 2021
- [c15]Mohit Kumar, Samuel Kolb, Clément Gautrais, Luc De Raedt:
Democratizing Constraint Satisfaction Problems through Machine Learning. AAAI 2021: 16057-16059 - [c14]Paolo Morettin, Pedro Zuidberg Dos Martires, Samuel Kolb, Andrea Passerini:
Hybrid Probabilistic Inference with Logical and Algebraic Constraints: a Survey. IJCAI 2021: 4533-4542 - [c13]Samuel Kolb, Harold Tiemessen, Peter Wermuth, Jörg Forrer:
Optimization of the Patient Flow in a Forensic Psychiatric Hospital with Discrete Event Simulation. OR 2021: 403-408 - [i3]Mohit Kumar, Samuel Kolb, Luc De Raedt, Stefano Teso:
Learning Mixed-Integer Linear Programs from Contextual Examples. CoRR abs/2107.07136 (2021) - 2020
- [j2]Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt:
Predictive spreadsheet autocompletion with constraints. Mach. Learn. 109(2): 307-325 (2020) - [c12]Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt:
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation. AAAI 2020: 4493-4500 - [c11]Paolo Morettin, Samuel Kolb, Stefano Teso, Andrea Passerini:
Learning Weighted Model Integration Distributions. AAAI 2020: 5224-5231 - [c10]Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt:
VisualSynth: Democratizing Data Science in Spreadsheets. ECML/PKDD (5) 2020: 550-554 - [c9]Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt:
Ordering Variables for Weighted Model Integration. UAI 2020: 879-888 - [i2]Pedro Zuidberg Dos Martires, Samuel Kolb:
Monte Carlo Anti-Differentiation for Approximate Weighted Model Integration. CoRR abs/2001.04566 (2020) - [i1]Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt:
Human-Machine Collaboration for Democratizing Data Science. CoRR abs/2004.11113 (2020)
2010 – 2019
- 2019
- [c8]Elias Arnold Schede, Samuel Kolb, Stefano Teso:
Learning Linear Programs from Data. ICTAI 2019: 1019-1026 - [c7]Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Francesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt:
The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration. IJCAI 2019: 6530-6532 - [c6]Yann Dauxais, Clément Gautrais, Anton Dries, Arcchit Jain, Samuel Kolb, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt:
SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract). PKDD/ECML Workshops (1) 2019: 102-110 - [c5]Samuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt:
How to Exploit Structure while Solving Weighted Model Integration Problems. UAI 2019: 744-754 - 2018
- [c4]Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen:
Elements of an Automatic Data Scientist. IDA 2018: 3-14 - [c3]Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt:
Learning SMT(LRA) Constraints using SMT Solvers. IJCAI 2018: 2333-2340 - [c2]Samuel Kolb, Martin Mladenov, Scott Sanner, Vaishak Belle, Kristian Kersting:
Efficient Symbolic Integration for Probabilistic Inference. IJCAI 2018: 5031-5037 - 2017
- [j1]Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt:
Learning constraints in spreadsheets and tabular data. Mach. Learn. 106(9-10): 1441-1468 (2017) - [c1]Sergey Paramonov, Samuel Kolb, Tias Guns, Luc De Raedt:
TaCLe: Learning Constraints in Tabular Data. CIKM 2017: 2511-2514
Coauthor Index
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