Samuel Kolb
Samuel Kolb
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Learning SMT (LRA) Constraints using SMT Solvers.
S Kolb, S Teso, A Passerini, L De Raedt
IJCAI 18, 2333-2340, 2018
342018
Learning constraints in spreadsheets and tabular data
S Kolb, S Paramonov, T Guns, L De Raedt
Machine Learning 106 (9), 1441-1468, 2017
292017
Efficient Symbolic Integration for Probabilistic Inference.
S Kolb, M Mladenov, S Sanner, V Belle, K Kersting
IJCAI, 5031-5037, 2018
212018
Learning constraints and optimization criteria
SM Kolb
Workshops at the Thirtieth AAAI Conference on Artificial Intelligence, 2016
152016
Elements of an automatic data scientist
L De Raedt, H Blockeel, S Kolb, S Teso, G Verbruggen
International symposium on intelligent data analysis, 3-14, 2018
112018
How to exploit structure while solving weighted model integration problems
S Kolb, PZ Dos Martires, L De Raedt
Uncertainty in Artificial Intelligence, 744-754, 2020
8*2020
The pywmi framework and toolbox for probabilistic inference using weighted model integration
S Kolb, P Morettin, P Zuidberg Dos Martires, F Sommavilla, A Passerini, ...
https://www. ijcai. org/proceedings/2019/, 2019
82019
Learning linear programs from data
EA Schede, S Kolb, S Teso
2019 IEEE 31st International Conference on Tools with Artificial …, 2019
72019
Zuidberg Dos Martires, P., and De Raedt, L.(2019b). How to exploit structure while solving weighted model integration problems
S Kolb
Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence …, 0
6
Learning weighted model integration distributions
P Morettin, S Kolb, S Teso, A Passerini
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5224-5231, 2020
52020
Predictive spreadsheet autocompletion with constraints
S Kolb, S Teso, A Dries, L De Raedt
Machine Learning 109 (2), 307-325, 2020
52020
TaCLe: learning constraints in tabular data
S Paramonov, S Kolb, T Guns, L De Raedt
Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017
52017
Learning MAX-SAT from contextual examples for combinatorial optimisation
M Kumar, S Kolb, S Teso, L De Raedt
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4493-4500, 2020
42020
Human-machine collaboration for democratizing data science
C Gautrais, Y Dauxais, S Teso, S Kolb, G Verbruggen, L De Raedt
arXiv preprint arXiv:2004.11113, 2020
32020
Ordering variables for weighted model integration
V Derkinderen, E Heylen, PZ Dos Martires, S Kolb, L Raedt
Conference on Uncertainty in Artificial Intelligence, 879-888, 2020
22020
Hybrid probabilistic inference with logical and algebraic constraints: a survey
P Morettin, P Zuidberg Dos Martires, S Kolb, A Passerini
Proceedings of the 30th International Joint Conference on Artificial …, 2021
12021
Monte Carlo Anti-Differentiation for Approximate Weighted Model Integration
PZD Martires, S Kolb
arXiv preprint arXiv:2001.04566, 2020
12020
Learning Mixed-Integer Linear Programs from Contextual Examples
M Kumar, S Kolb, L De Raedt, S Teso
arXiv preprint arXiv:2107.07136, 2021
2021
Democratizing Constraint Satisfaction Problems through Machine Learning
M Kumar, S Kolb, C Gautrais, L De Raedt
European Conference on Operational Research, Date: 2021/07/11-2021/07/14 …, 2021
2021
for Democratizing Data Science
C Gautrais, Y Dauxais, S Teso, S Kolb, G Verbruggen, L De Raedt
Oxford University Press, 2021
2021
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