Synthesising Inductive Data Models

Learning Linear Programs from Data

Autorzy: Elias Arnold Schede, Samuel Kolb,Stefano Teso
Opublikowane w: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), 2020, ISBN 978-1-7281-3798-8
Wydawca: IEEE

DeepStochLog: Neural Stochastic Logic Programming

Autorzy: Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt
Opublikowane w: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Wydawca: AAAI press

Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation

Autorzy: Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
Opublikowane w: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, Numer 34(04), 2020, Strona(/y) 4493-4500, ISBN 978-1-57735-835-0
Wydawca: AAAI

Democratizing Constraint Satisfaction Problems through Machine Learning

Autorzy: Kumar, Mohit; Kolb, Samuel; Gautrais, Clement; De Raedt, Luc
Opublikowane w: Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, Numer Vol. 35, iss. 18, 2021, Strona(/y) 16057 - 16059, ISBN 978-1-57735-866-4
Wydawca: AAAI Press

Toward Faithful Explanatory Active Learning with Self-explainable Neural Nets

Autorzy: Teso, Stefano
Opublikowane w: Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2019), Numer 17, 2019, Strona(/y) 4 - 16
Wydawca: CEUR Workshop Proceedings

An Automated Engineering Assistant: Learning Parsers for Technical Drawings

Autorzy: Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert,
Opublikowane w: Proceedings of the AAAI Conference on Artificial Intelligence, Numer abs/1909.08552, 2021
Wydawca: AAAI Press

SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints

Autorzy: Dirko Coetsee, Steve Kroon, McElory Hoffmann, Luc De Raedt
Opublikowane w: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021, Proceedings, Numer 12695, 2021, Strona(/y) 402-413, ISBN 978-3-030-74250-8
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-74251-5_32

Ordering Variables for Weighted Model Integration

Autorzy: Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc Raedt
Opublikowane w: Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, Numer 124, 2020, Strona(/y) 879 - 888
Wydawca: MLR Press

Widening for MDL-Based Retail Signature Discovery

Autorzy: Clément Gautrais, Peggy Cellier, Matthijs van Leeuwen, Alexandre Termier
Opublikowane w: Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings, Numer 12080, 2020, Strona(/y) 197-209, ISBN 978-3-030-44583-6
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-44584-3_16

Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions

Autorzy: Yuanhong Wang, Timothy van Bremen, Yuyi Wang, Ondrej Kuzelka
Opublikowane w: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Wydawca: AAAI press

Hybrid probabilistic inference with logical and algebraic constraints: a survey

Autorzy: Paolo Morettin, Pedro Zuidberg Dos Martires, Samuel Kolb, Andrea Passerini
Opublikowane w: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021, Strona(/y) 4533-4542, ISBN 978-0-9992411-9-6
Wydawca: International Joint Conferences on Artificial Intelligence
DOI: 10.24963/ijcai.2021/617

Context-Specific Likelihood Weighting

Autorzy: Nitesh Kumar, Ondrej Kuzelka
Opublikowane w: Proceedings of Machine Learning Research from the 24th International Conference on Artificial Intelligence and Statistics, 2021
Wydawca: MLresearch Press

Transforming Probabilistic Programs into Algebraic Circuits for Inference and Learning

Autorzy: Pedro Miguel Zuidberg Dos Martires, Vincent Derkinderen, Robin Manhaeve, Wannes Meert, Angelika Kimmig, Luc De Raedt
Opublikowane w: Program Transformations for Machine Learning Workshop at NeurIPS, 2019
Wydawca: OpenReview.net

Anomaly Detection for CERN Beam Transfer Installations Using Machine Learning

Autorzy: Dewitte, Thiebout; Meert, Wannes; Van Wolputte, Elia; Van Trappen, Pieter
Opublikowane w: International Conference on Accelerator and Large Experimental Physics Control Systems (17th), 2019, Strona(/y) 1066-1070, ISBN 978-3-95450-209-7
Wydawca: JACoW Publishing
DOI: 10.18429/jacow-icalepcs2019-wempr010

Co-creating Platformer Levels with Constrained Adversarial Networks

Autorzy: Paolo Morettin, Andrea Passerini, Stefano Teso
Opublikowane w: Proceedings of the 2nd Workshop on Human-AI Co-Creation with Generative, 2021
Wydawca: CEUR Workshop Proceedings

From Statistical Relational to Neuro-Symbolic Artificial Intelligence

Autorzy: Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra
Opublikowane w: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020, Strona(/y) 4943-4950, ISBN 978-0-9992411-6-5
Wydawca: International Joint Conferences on Artificial Intelligence

avatar—Automated Feature Wrangling for Machine Learning

Autorzy: Gust Verbruggen, Elia Van Wolputte, Sebastijan Dumančić, Luc De Raedt
Opublikowane w: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021, Proceedings, Numer 12695, 2021, Strona(/y) 235-247, ISBN 978-3-030-74250-8
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-74251-5_19

Missing Value Imputation with MERCS: A Faster Alternative to MissForest

Autorzy: Elia Van Wolputte, Hendrik Blockeel
Opublikowane w: Discovery Science - 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19–21, 2020, Proceedings, Numer 12323, 2020, Strona(/y) 502-516, ISBN 978-3-030-61526-0
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-61527-7_33

Muppets: Multipurpose Table Segmentation

Autorzy: Gust Verbruggen, Lidia Contreras-Ochando, Cèsar Ferri, José Hernández-Orallo, Luc De Raedt
Opublikowane w: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021, Proceedings, Numer 12695, 2021, Strona(/y) 389-401, ISBN 978-3-030-74250-8
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-74251-5_31

Inference and Learning with Model Uncertainty in Probabilistic Logic Programs

Autorzy: Victor Verreet, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
Opublikowane w: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Wydawca: AAAI press

Approximate Inference for Neural Probabilistic Logic Programming

Autorzy: Robin Manhaeve, Giuseppe Marra, Luc De Raedt
Opublikowane w: Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021, Strona(/y) 475–486, ISBN 978-1-956792-99-7
Wydawca: IJCAI Organization
DOI: 10.24963/kr.2021/45

TaCLe - Learning Constraints in Tabular Data

Autorzy: Sergey Paramonov, Samuel Kolb, Tias Guns, Luc De Raedt
Opublikowane w: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management - CIKM '17, 2017, Strona(/y) 2511-2514, ISBN 9781-450349185
Wydawca: ACM Press
DOI: 10.1145/3132847.3133193

MERCS: Multi-directional Ensembles of Regression and Classification Trees

Autorzy: Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel
Opublikowane w: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Wydawca: AAAI Press

Learning constraints from examples

Autorzy: Luc De Raedt, Andrea Passerini, Stefano Teso
Opublikowane w: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Wydawca: AAAI Press

Constructive Preference Elicitation over Hybrid Combinatorial Spaces

Autorzy: Paolo Dragone, Stefano Teso, Andrea Passerini
Opublikowane w: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Wydawca: AAAI Press

Decomposition strategies for constructive preference elicitation

Autorzy: Paolo Dragone, Stefano Teso, Mohit Kumar, Andrea Passerini
Opublikowane w: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Wydawca: AAAI press

Constructive Preference Elicitation for Multiple Users with Setwise Max-margin

Autorzy: Stefano Teso, Andrea Passerini, Paolo Viappiani
Opublikowane w: Algorithmic Decision Theory. ADT 2017. Lecture Notes in Computer Science, vol 10576., 2017, Strona(/y) 3-17
Wydawca: Springer

Sketched Answer Set Programming

Autorzy: Sergey Paramonov, Christian Bessiere, Anton Dries, Luc De Raedt
Opublikowane w: 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI), 2018, Strona(/y) 694-701, ISBN 978-1-5386-7449-9
Wydawca: IEEE
DOI: 10.1109/ictai.2018.00110

Towards Resource-Efficient Classifiers for Always-On Monitoring

Autorzy: Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Opublikowane w: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III, Numer 11053, 2019, Strona(/y) 305-321, ISBN 978-3-030-10996-7
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-10997-4_19

COBRAS: Interactive Clustering with Pairwise Queries

Autorzy: Toon Van Craenendonck, Sebastijan Dumančić, Elia Van Wolputte, Hendrik Blockeel
Opublikowane w: Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Numer 11191, 2018, Strona(/y) 353-366, ISBN 978-3-030-01767-5
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-01768-2_29

Automatically Wrangling Spreadsheets into Machine Learning Data Formats

Autorzy: Gust Verbruggen, Luc De Raedt
Opublikowane w: Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Numer 11191, 2018, Strona(/y) 367-379, ISBN 978-3-030-01767-5
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-01768-2_30

Learning SMT(LRA) Constraints using SMT Solvers

Autorzy: Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt
Opublikowane w: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, Strona(/y) 2333-2340, ISBN 9780-999241127
Wydawca: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2018/323

Elements of an Automatic Data Scientist

Autorzy: Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen
Opublikowane w: Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Numer 11191, 2018, Strona(/y) 3-14, ISBN 978-3-030-01767-5
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-01768-2_1

Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge

Autorzy: Pedro Miguel Zuidberg Dos Martires, Anton Dries, Luc De Raedt
Opublikowane w: Proceedings of the 30th AAAI Conference on Artificial Intelligence, 2019
Wydawca: AAAI Press

Automating Layout Synthesis with Constructive Preference Elicitation

Autorzy: Luca Erculiani, Paolo Dragone, Stefano Teso, Andrea Passerini
Opublikowane w: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III, Numer 11053, 2019, Strona(/y) 254-270, ISBN 978-3-030-10996-7
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-10997-4_16

Explanatory Interactive Machine Learning

Autorzy: Stefano Teso, Kristian Kersting
Opublikowane w: Proceedings of AAAI/ACM Conference on Artificial Intelligence, Ethics and Society 2019, 2019
Wydawca: AAAI Press

Generic mining of condensed pattern representations under constraints

Autorzy: Sergey Paramonov, Tao Chen, Tias Guns
Opublikowane w: YSIP2 – Proceedings of the Second Young Scientist's International Workshop on Trends in Information Processing, Numer Vol. 1837, 2017, Strona(/y) 168-177
Wydawca: CEUR

Pyconstruct: Constraint Programming Meets Structured Prediction

Autorzy: Paolo Dragone, Stefano Teso, Andrea Passerini
Opublikowane w: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, Strona(/y) 5823-5825, ISBN 9780-999241127
Wydawca: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2018/850

Scalable Rule Learning in Probabilistic Knowledge Bases

Autorzy: Arcchit Jain; Tal Friedman; Ondrej Kuzelka; Guy Van den Broeck; Luc De Raedt
Opublikowane w: Automated Knowledge Base Construction, 2019
Wydawca: University of Massachusetts Amherst

Acquiring Integer Programs from Data

Autorzy: Mohit Kumar, Stefano Teso, Luc De Raedt
Opublikowane w: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019, Strona(/y) 1130-1136, ISBN 978-0-9992411-4-1
Wydawca: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2019/158

The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration

Autorzy: Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Francesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt
Opublikowane w: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019, Strona(/y) 6530-6532, ISBN 978-0-9992411-4-1
Wydawca: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2019/946

How to Exploit Structure while Solving Weighted Model Integration Problems

Autorzy: Pedro Miguel Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt
Opublikowane w: Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Wydawca: AUAI

Generalized Chronicles for Temporal Sequence Classification

Autorzy: Yann Dauxais, Thomas Guyet
Opublikowane w: Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers, Numer 12588, 2020, Strona(/y) 30-45, ISBN 978-3-030-65741-3
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-65742-0_3

Learning Weighted Model Integration Distributions

Autorzy: Paolo Morettin, Samuel Kolb, Stefano Teso, Andrea Passerini
Opublikowane w: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020, Strona(/y) 5224-5231
Wydawca: AAAI press

Automating Personnel Rostering by Learning Constraints Using Tensors

Autorzy: Mohit Kumar, Stefano Teso, Patrick De Causmaecker, Luc De Raedt
Opublikowane w: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Numer Vol. abs/1805.11375, 2019, Strona(/y) 697-704, ISBN 978-1-7281-3798-8
Wydawca: IEEE
DOI: 10.1109/ictai.2019.00102

The Effect of Hyperparameter Tuning on the Comparative Evaluation of Unsupervised Anomaly Detection Methods

Autorzy: Soenen, Jonas; Van Wolputte, Elia; Perini, Lorenzo; Vercruyssen, Vincent; Meert, Wannes; Davis, Jesse; Blockeel, Hendrik
Opublikowane w: Proceedings of the KDD'21 Workshop on Outlier Detection and Description, 2021
Wydawca: Outlier Detection and Description Organising Committee

VisualSynth: Democratizing Data Science in Spreadsheets

Autorzy: Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
Opublikowane w: Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V, Numer 12461, 2021, Strona(/y) 550-554, ISBN 978-3-030-67669-8
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-67670-4_37

Ontology-Mediated Queries over Probabilistic Data via Probabilistic Logic Programming

Autorzy: Timothy van Bremen, Anton Dries, Jean Christoph Jung
Opublikowane w: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019, Strona(/y) 2437-2440, ISBN 9781450369763
Wydawca: ACM
DOI: 10.1145/3357384.3358168

Learning CNF Theories Using MDL and Predicate Invention

Autorzy: Arcchit Jain; Clément Gautrais; Angelika Kimmig; Luc De Raedt; Luc De Raedt
Opublikowane w: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Numer 10, 2021, Strona(/y) 2599-2605, ISBN 978-0-9992411-9-6
Wydawca: International Joint Conferences on Artificial Intelligence
DOI: 10.24963/ijcai.2021/358

Algebraic Circuits for Decision Theoretic Inference and Learning

Autorzy: Vincent Derkinderen, Luc De Raedt
Opublikowane w: Proceedings of the 24th European Conference on Artificial Intelligence, Numer 325, 2020, Strona(/y) 2569 - 2576, ISBN 978-1-64368-100-9
Wydawca: IOS Press
DOI: 10.3233/faia200392

SandSlide: Automatic Slideshow Normalization

Autorzy: Sieben Bocklandt, Gust Verbruggen,Thomas Winters
Opublikowane w: Proceedings of the 2021 16th International Conference on Document Analysis and Recognition (ICDAR), Numer Lecture Notes in Computer Science, vol 12822, 2021, Strona(/y) 445–461, ISBN 978-3-030-86331-9
Wydawca: SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-030-86331-9_29

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations

Autorzy: Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck
Opublikowane w: Advances in neural information processing systems, Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020
Wydawca: Curran Associates

Neural Markov Logic Networks

Autorzy: Giuseppe Marra, Ondřej Kuželka
Opublikowane w: Proceedings of Machine Learning Research (PMLR), Numer Vol.161, 2021, Strona(/y) 908-917
Wydawca: Machine Learning Research (PMLR

SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract)

Autorzy: Yann Dauxais, Clément Gautrais, Anton Dries, Arcchit Jain, Samuel Kolb, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
Opublikowane w: Machine Learning and Knowledge Discovery in Databases, Numer Vol. 1167, 2019, Strona(/y) 102 - 110, ISBN 978-3-030-43822-7
Wydawca: Springer International Publishing

Efficient Generation of Structured Objects with Constrained Adversarial Networks

Autorzy: Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Paolo Morettin, Stefano Teso, Andrea Passerini
Opublikowane w: Advances in neural information processing systems, Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), Numer abs/2007.13197, 2020
Wydawca: Curran Associates

Semiring programming: A semantic framework for generalized sum product problems

Autorzy: Vaishak Belle, Luc De Raedt
Opublikowane w: International Journal of Approximate Reasoning, Numer 126, 2020, Strona(/y) 181-201, ISSN 0888-613X
Wydawca: Elsevier BV
DOI: 10.1016/j.ijar.2020.08.001

Learning Distributional Programs for Relational Autocompletion

Autorzy: Nitesh Kumar; Ondrej Kuzelka; Luc De Raedt
Opublikowane w: Theory and Practice of Logic Programming, Numer Vol.22, issue 1, 2021, Strona(/y) 81 - 114, ISSN 1471-0684
Wydawca: Cambridge University Press
DOI: 10.1017/s1471068421000144

Neural probabilistic logic programming in DeepProbLog

Autorzy: Robin Manhaeve, Sebastijan Dumančić, Angelika Kimmig, Thomas Demeester, Luc De Raedt
Opublikowane w: Artificial Intelligence, Numer 298, 2021, Strona(/y) 103504, ISSN 0004-3702
Wydawca: Elsevier BV
DOI: 10.1016/j.artint.2021.103504

Constructive Preference Elicitation

Autorzy: Paolo Dragone, Stefano Teso, Andrea Passerini
Opublikowane w: Frontiers in Robotics and AI, Numer 4, 2018, ISSN 2296-9144
Wydawca: Frontiers
DOI: 10.3389/frobt.2017.00071

Learning constraints in spreadsheets and tabular data

Autorzy: Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt
Opublikowane w: Machine Learning, Numer 106/9-10, 2017, Strona(/y) 1441-1468, ISSN 0885-6125
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10994-017-5640-x

Declarative data analysis

Autorzy: Hendrik Blockeel
Opublikowane w: International Journal of Data Science and Analytics, Numer volume 6/3, 2017, Strona(/y) 217-223, ISSN 2364-415X
Wydawca: Springer
DOI: 10.1007/s41060-017-0081-y

Combining learning and constraints for genome-wide protein annotation

Autorzy: Stefano Teso, Luca Masera, Michelangelo Diligenti, Andrea Passerini
Opublikowane w: BMC Bioinformatics, Numer 20/1, 2019, ISSN 1471-2105
Wydawca: BioMed Central
DOI: 10.1186/s12859-019-2875-5

Predictive spreadsheet autocompletion with constraints

Autorzy: Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt
Opublikowane w: Machine Learning, 2019, ISSN 0885-6125
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10994-019-05841-y

onto2problog: A Probabilistic Ontology-Mediated Querying System using Probabilistic Logic Programming

Autorzy: Timothy van Bremen, Anton Dries, Jean Christoph Jung
Opublikowane w: KI - Künstliche Intelligenz, Numer 34/4, 2020, Strona(/y) 501-507, ISSN 0933-1875
Wydawca: Springer
DOI: 10.1007/s13218-020-00670-x

Automating Data Science: Prospects and Challenges

Autorzy: De Bie, Tijl; De Raedt, Luc; Hernández-Orallo, José; Hoos, Holger H.; Smyth, Padhraic; Williams, Christopher K. I.
Opublikowane w: Communications of the ACM, Numer Vol.65, issue 3, 2022, Strona(/y) 76-87, ISSN 0001-0782
Wydawca: Association for Computing Machinary, Inc.
DOI: 10.1145/3495256

Making deep neural networks right for the right scientific reasons by interacting with their explanations

Autorzy: Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Franziska Herbert, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting
Opublikowane w: Nature Machine Intelligence, Numer 2/8, 2020, Strona(/y) 476-486, ISSN 2522-5839
Wydawca: Springer Nature
DOI: 10.1038/s42256-020-0212-3

Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring

Autorzy: Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt
Opublikowane w: Frontiers in Robotics and AI, Numer 7, 2020, ISSN 2296-9144
Wydawca: Frontiers Media
DOI: 10.3389/frobt.2020.00100

Semantic programming by example with pre-trained models

Autorzy: Gust Verbruggen, Vu Le, Sumit Gulwani
Opublikowane w: Proceedings of the ACM on Programming Languages;, Numer Vol. 5; iss. OOPSLA, 2021, Strona(/y) 1–25, ISSN 2475-1421
Wydawca: ACM Digital library
DOI: 10.1145/3485477

Human-Machine Collaboration for Democratizing Data Science

Autorzy: Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt
Opublikowane w: Human-Like Machine Intelligence, Numer Vol. abs/2004.11113, 2021, Strona(/y) 379 - 402, ISBN 9780198862536
Wydawca: Oxford University Press
DOI: 10.1093/oso/9780198862536.003.0019

Hybrid ASP-Based Approach to Pattern Mining

Autorzy: Sergey Paramonov, Daria Stepanova, Pauli Miettinen
Opublikowane w: Rules and Reasoning, Numer 10364, 2017, Strona(/y) 199-214, ISBN 978-3-319-61251-5
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-319-61252-2_14

Constraint Learning: An Appetizer

Autorzy: Stefano Teso
Opublikowane w: Reasoning Web. Explainable Artificial Intelligence - 15th International Summer School 2019, Bolzano, Italy, September 20–24, 2019, Tutorial Lectures, Numer 11810, 2019, Strona(/y) 232-249, ISBN 978-3-030-31422-4
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-31423-1_7

Automating Data Science (Dagstuhl Seminar 18401)

Autorzy: Tijl De Bie; Luc De Raedt, Holger H. Hoos, Padhraic Smyth
Opublikowane w: Dagstuhl Reports, Numer Volume 8, Numer 9, 2019
Wydawca: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
DOI: 10.4230/dagrep.8.9.154

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