Synthesising Inductive Data Models

Learning Linear Programs from Data

Autori: Elias Arnold Schede, Samuel Kolb,Stefano Teso
Pubblicato in: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), 2020, ISBN 978-1-7281-3798-8
Editore: IEEE

DeepStochLog: Neural Stochastic Logic Programming

Autori: Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt
Pubblicato in: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Editore: AAAI press

Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation

Autori: Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
Pubblicato in: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, Numero 34(04), 2020, Pagina/e 4493-4500, ISBN 978-1-57735-835-0
Editore: AAAI

Democratizing Constraint Satisfaction Problems through Machine Learning

Autori: Kumar, Mohit; Kolb, Samuel; Gautrais, Clement; De Raedt, Luc
Pubblicato in: Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, Numero Vol. 35, iss. 18, 2021, Pagina/e 16057 - 16059, ISBN 978-1-57735-866-4
Editore: AAAI Press

Toward Faithful Explanatory Active Learning with Self-explainable Neural Nets

Autori: Teso, Stefano
Pubblicato in: Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2019), Numero 17, 2019, Pagina/e 4 - 16
Editore: CEUR Workshop Proceedings

An Automated Engineering Assistant: Learning Parsers for Technical Drawings

Autori: Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert,
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero abs/1909.08552, 2021
Editore: AAAI Press

SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints

Autori: Dirko Coetsee, Steve Kroon, McElory Hoffmann, Luc De Raedt
Pubblicato in: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021, Proceedings, Numero 12695, 2021, Pagina/e 402-413, ISBN 978-3-030-74250-8
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-74251-5_32

Ordering Variables for Weighted Model Integration

Autori: Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc Raedt
Pubblicato in: Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, Numero 124, 2020, Pagina/e 879 - 888
Editore: MLR Press

Widening for MDL-Based Retail Signature Discovery

Autori: Clément Gautrais, Peggy Cellier, Matthijs van Leeuwen, Alexandre Termier
Pubblicato in: Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings, Numero 12080, 2020, Pagina/e 197-209, ISBN 978-3-030-44583-6
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-44584-3_16

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

Autori: Yuanhong Wang, Timothy van Bremen, Yuyi Wang, Ondrej Kuzelka
Pubblicato in: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Editore: AAAI press

Hybrid probabilistic inference with logical and algebraic constraints: a survey

Autori: Paolo Morettin, Pedro Zuidberg Dos Martires, Samuel Kolb, Andrea Passerini
Pubblicato in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021, Pagina/e 4533-4542, ISBN 978-0-9992411-9-6
Editore: International Joint Conferences on Artificial Intelligence
DOI: 10.24963/ijcai.2021/617

Context-Specific Likelihood Weighting

Autori: Nitesh Kumar, Ondrej Kuzelka
Pubblicato in: Proceedings of Machine Learning Research from the 24th International Conference on Artificial Intelligence and Statistics, 2021
Editore: MLresearch Press

Transforming Probabilistic Programs into Algebraic Circuits for Inference and Learning

Autori: Pedro Miguel Zuidberg Dos Martires, Vincent Derkinderen, Robin Manhaeve, Wannes Meert, Angelika Kimmig, Luc De Raedt
Pubblicato in: Program Transformations for Machine Learning Workshop at NeurIPS, 2019
Editore: OpenReview.net

Anomaly Detection for CERN Beam Transfer Installations Using Machine Learning

Autori: Dewitte, Thiebout; Meert, Wannes; Van Wolputte, Elia; Van Trappen, Pieter
Pubblicato in: International Conference on Accelerator and Large Experimental Physics Control Systems (17th), 2019, Pagina/e 1066-1070, ISBN 978-3-95450-209-7
Editore: JACoW Publishing
DOI: 10.18429/jacow-icalepcs2019-wempr010

Co-creating Platformer Levels with Constrained Adversarial Networks

Autori: Paolo Morettin, Andrea Passerini, Stefano Teso
Pubblicato in: Proceedings of the 2nd Workshop on Human-AI Co-Creation with Generative, 2021
Editore: CEUR Workshop Proceedings

From Statistical Relational to Neuro-Symbolic Artificial Intelligence

Autori: Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra
Pubblicato in: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020, Pagina/e 4943-4950, ISBN 978-0-9992411-6-5
Editore: International Joint Conferences on Artificial Intelligence

avatar—Automated Feature Wrangling for Machine Learning

Autori: Gust Verbruggen, Elia Van Wolputte, Sebastijan Dumančić, Luc De Raedt
Pubblicato in: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021, Proceedings, Numero 12695, 2021, Pagina/e 235-247, ISBN 978-3-030-74250-8
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-74251-5_19

Missing Value Imputation with MERCS: A Faster Alternative to MissForest

Autori: Elia Van Wolputte, Hendrik Blockeel
Pubblicato in: Discovery Science - 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19–21, 2020, Proceedings, Numero 12323, 2020, Pagina/e 502-516, ISBN 978-3-030-61526-0
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-61527-7_33

Muppets: Multipurpose Table Segmentation

Autori: Gust Verbruggen, Lidia Contreras-Ochando, Cèsar Ferri, José Hernández-Orallo, Luc De Raedt
Pubblicato in: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021, Proceedings, Numero 12695, 2021, Pagina/e 389-401, ISBN 978-3-030-74250-8
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-74251-5_31

Inference and Learning with Model Uncertainty in Probabilistic Logic Programs

Autori: Victor Verreet, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
Pubblicato in: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Editore: AAAI press

Approximate Inference for Neural Probabilistic Logic Programming

Autori: Robin Manhaeve, Giuseppe Marra, Luc De Raedt
Pubblicato in: Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021, Pagina/e 475–486, ISBN 978-1-956792-99-7
Editore: IJCAI Organization
DOI: 10.24963/kr.2021/45

TaCLe - Learning Constraints in Tabular Data

Autori: Sergey Paramonov, Samuel Kolb, Tias Guns, Luc De Raedt
Pubblicato in: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management - CIKM '17, 2017, Pagina/e 2511-2514, ISBN 9781-450349185
Editore: ACM Press
DOI: 10.1145/3132847.3133193

MERCS: Multi-directional Ensembles of Regression and Classification Trees

Autori: Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel
Pubblicato in: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Editore: AAAI Press

Learning constraints from examples

Autori: Luc De Raedt, Andrea Passerini, Stefano Teso
Pubblicato in: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Editore: AAAI Press

Constructive Preference Elicitation over Hybrid Combinatorial Spaces

Autori: Paolo Dragone, Stefano Teso, Andrea Passerini
Pubblicato in: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Editore: AAAI Press

Decomposition strategies for constructive preference elicitation

Autori: Paolo Dragone, Stefano Teso, Mohit Kumar, Andrea Passerini
Pubblicato in: Proceedings Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Editore: AAAI press

Constructive Preference Elicitation for Multiple Users with Setwise Max-margin

Autori: Stefano Teso, Andrea Passerini, Paolo Viappiani
Pubblicato in: Algorithmic Decision Theory. ADT 2017. Lecture Notes in Computer Science, vol 10576., 2017, Pagina/e 3-17
Editore: Springer

Sketched Answer Set Programming

Autori: Sergey Paramonov, Christian Bessiere, Anton Dries, Luc De Raedt
Pubblicato in: 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI), 2018, Pagina/e 694-701, ISBN 978-1-5386-7449-9
Editore: IEEE
DOI: 10.1109/ictai.2018.00110

Towards Resource-Efficient Classifiers for Always-On Monitoring

Autori: Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Pubblicato in: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III, Numero 11053, 2019, Pagina/e 305-321, ISBN 978-3-030-10996-7
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-10997-4_19

COBRAS: Interactive Clustering with Pairwise Queries

Autori: Toon Van Craenendonck, Sebastijan Dumančić, Elia Van Wolputte, Hendrik Blockeel
Pubblicato in: Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Numero 11191, 2018, Pagina/e 353-366, ISBN 978-3-030-01767-5
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-01768-2_29

Automatically Wrangling Spreadsheets into Machine Learning Data Formats

Autori: Gust Verbruggen, Luc De Raedt
Pubblicato in: Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Numero 11191, 2018, Pagina/e 367-379, ISBN 978-3-030-01767-5
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-01768-2_30

Learning SMT(LRA) Constraints using SMT Solvers

Autori: Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt
Pubblicato in: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, Pagina/e 2333-2340, ISBN 9780-999241127
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2018/323

Elements of an Automatic Data Scientist

Autori: Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen
Pubblicato in: Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings, Numero 11191, 2018, Pagina/e 3-14, ISBN 978-3-030-01767-5
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-01768-2_1

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

Autori: Pedro Miguel Zuidberg Dos Martires, Anton Dries, Luc De Raedt
Pubblicato in: Proceedings of the 30th AAAI Conference on Artificial Intelligence, 2019
Editore: AAAI Press

Automating Layout Synthesis with Constructive Preference Elicitation

Autori: Luca Erculiani, Paolo Dragone, Stefano Teso, Andrea Passerini
Pubblicato in: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III, Numero 11053, 2019, Pagina/e 254-270, ISBN 978-3-030-10996-7
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-10997-4_16

Explanatory Interactive Machine Learning

Autori: Stefano Teso, Kristian Kersting
Pubblicato in: Proceedings of AAAI/ACM Conference on Artificial Intelligence, Ethics and Society 2019, 2019
Editore: AAAI Press

Generic mining of condensed pattern representations under constraints

Autori: Sergey Paramonov, Tao Chen, Tias Guns
Pubblicato in: YSIP2 – Proceedings of the Second Young Scientist's International Workshop on Trends in Information Processing, Numero Vol. 1837, 2017, Pagina/e 168-177
Editore: CEUR

Pyconstruct: Constraint Programming Meets Structured Prediction

Autori: Paolo Dragone, Stefano Teso, Andrea Passerini
Pubblicato in: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, Pagina/e 5823-5825, ISBN 9780-999241127
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2018/850

Scalable Rule Learning in Probabilistic Knowledge Bases

Autori: Arcchit Jain; Tal Friedman; Ondrej Kuzelka; Guy Van den Broeck; Luc De Raedt
Pubblicato in: Automated Knowledge Base Construction, 2019
Editore: University of Massachusetts Amherst

Acquiring Integer Programs from Data

Autori: Mohit Kumar, Stefano Teso, Luc De Raedt
Pubblicato in: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019, Pagina/e 1130-1136, ISBN 978-0-9992411-4-1
Editore: 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

Autori: Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Francesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt
Pubblicato in: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019, Pagina/e 6530-6532, ISBN 978-0-9992411-4-1
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2019/946

How to Exploit Structure while Solving Weighted Model Integration Problems

Autori: Pedro Miguel Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt
Pubblicato in: Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Editore: AUAI

Generalized Chronicles for Temporal Sequence Classification

Autori: Yann Dauxais, Thomas Guyet
Pubblicato in: Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers, Numero 12588, 2020, Pagina/e 30-45, ISBN 978-3-030-65741-3
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-65742-0_3

Learning Weighted Model Integration Distributions

Autori: Paolo Morettin, Samuel Kolb, Stefano Teso, Andrea Passerini
Pubblicato in: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020, Pagina/e 5224-5231
Editore: AAAI press

Automating Personnel Rostering by Learning Constraints Using Tensors

Autori: Mohit Kumar, Stefano Teso, Patrick De Causmaecker, Luc De Raedt
Pubblicato in: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Numero Vol. abs/1805.11375, 2019, Pagina/e 697-704, ISBN 978-1-7281-3798-8
Editore: IEEE
DOI: 10.1109/ictai.2019.00102

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

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

VisualSynth: Democratizing Data Science in Spreadsheets

Autori: Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
Pubblicato in: 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, Numero 12461, 2021, Pagina/e 550-554, ISBN 978-3-030-67669-8
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-67670-4_37

Ontology-Mediated Queries over Probabilistic Data via Probabilistic Logic Programming

Autori: Timothy van Bremen, Anton Dries, Jean Christoph Jung
Pubblicato in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019, Pagina/e 2437-2440, ISBN 9781450369763
Editore: ACM
DOI: 10.1145/3357384.3358168

Learning CNF Theories Using MDL and Predicate Invention

Autori: Arcchit Jain; Clément Gautrais; Angelika Kimmig; Luc De Raedt; Luc De Raedt
Pubblicato in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Numero 10, 2021, Pagina/e 2599-2605, ISBN 978-0-9992411-9-6
Editore: International Joint Conferences on Artificial Intelligence
DOI: 10.24963/ijcai.2021/358

Algebraic Circuits for Decision Theoretic Inference and Learning

Autori: Vincent Derkinderen, Luc De Raedt
Pubblicato in: Proceedings of the 24th European Conference on Artificial Intelligence, Numero 325, 2020, Pagina/e 2569 - 2576, ISBN 978-1-64368-100-9
Editore: IOS Press
DOI: 10.3233/faia200392

SandSlide: Automatic Slideshow Normalization

Autori: Sieben Bocklandt, Gust Verbruggen,Thomas Winters
Pubblicato in: Proceedings of the 2021 16th International Conference on Document Analysis and Recognition (ICDAR), Numero Lecture Notes in Computer Science, vol 12822, 2021, Pagina/e 445–461, ISBN 978-3-030-86331-9
Editore: SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-030-86331-9_29

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations

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

Neural Markov Logic Networks

Autori: Giuseppe Marra, Ondřej Kuželka
Pubblicato in: Proceedings of Machine Learning Research (PMLR), Numero Vol.161, 2021, Pagina/e 908-917
Editore: Machine Learning Research (PMLR

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

Autori: Yann Dauxais, Clément Gautrais, Anton Dries, Arcchit Jain, Samuel Kolb, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
Pubblicato in: Machine Learning and Knowledge Discovery in Databases, Numero Vol. 1167, 2019, Pagina/e 102 - 110, ISBN 978-3-030-43822-7
Editore: Springer International Publishing

Efficient Generation of Structured Objects with Constrained Adversarial Networks

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

Semiring programming: A semantic framework for generalized sum product problems

Autori: Vaishak Belle, Luc De Raedt
Pubblicato in: International Journal of Approximate Reasoning, Numero 126, 2020, Pagina/e 181-201, ISSN 0888-613X
Editore: Elsevier BV
DOI: 10.1016/j.ijar.2020.08.001

Learning Distributional Programs for Relational Autocompletion

Autori: Nitesh Kumar; Ondrej Kuzelka; Luc De Raedt
Pubblicato in: Theory and Practice of Logic Programming, Numero Vol.22, issue 1, 2021, Pagina/e 81 - 114, ISSN 1471-0684
Editore: Cambridge University Press
DOI: 10.1017/s1471068421000144

Neural probabilistic logic programming in DeepProbLog

Autori: Robin Manhaeve, Sebastijan Dumančić, Angelika Kimmig, Thomas Demeester, Luc De Raedt
Pubblicato in: Artificial Intelligence, Numero 298, 2021, Pagina/e 103504, ISSN 0004-3702
Editore: Elsevier BV
DOI: 10.1016/j.artint.2021.103504

Constructive Preference Elicitation

Autori: Paolo Dragone, Stefano Teso, Andrea Passerini
Pubblicato in: Frontiers in Robotics and AI, Numero 4, 2018, ISSN 2296-9144
Editore: Frontiers
DOI: 10.3389/frobt.2017.00071

Learning constraints in spreadsheets and tabular data

Autori: Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt
Pubblicato in: Machine Learning, Numero 106/9-10, 2017, Pagina/e 1441-1468, ISSN 0885-6125
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10994-017-5640-x

Declarative data analysis

Autori: Hendrik Blockeel
Pubblicato in: International Journal of Data Science and Analytics, Numero volume 6/3, 2017, Pagina/e 217-223, ISSN 2364-415X
Editore: Springer
DOI: 10.1007/s41060-017-0081-y

Combining learning and constraints for genome-wide protein annotation

Autori: Stefano Teso, Luca Masera, Michelangelo Diligenti, Andrea Passerini
Pubblicato in: BMC Bioinformatics, Numero 20/1, 2019, ISSN 1471-2105
Editore: BioMed Central
DOI: 10.1186/s12859-019-2875-5

Predictive spreadsheet autocompletion with constraints

Autori: Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt
Pubblicato in: Machine Learning, 2019, ISSN 0885-6125
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10994-019-05841-y

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

Autori: Timothy van Bremen, Anton Dries, Jean Christoph Jung
Pubblicato in: KI - Künstliche Intelligenz, Numero 34/4, 2020, Pagina/e 501-507, ISSN 0933-1875
Editore: Springer
DOI: 10.1007/s13218-020-00670-x

Automating Data Science: Prospects and Challenges

Autori: De Bie, Tijl; De Raedt, Luc; Hernández-Orallo, José; Hoos, Holger H.; Smyth, Padhraic; Williams, Christopher K. I.
Pubblicato in: Communications of the ACM, Numero Vol.65, issue 3, 2022, Pagina/e 76-87, ISSN 0001-0782
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3495256

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

Autori: Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Franziska Herbert, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting
Pubblicato in: Nature Machine Intelligence, Numero 2/8, 2020, Pagina/e 476-486, ISSN 2522-5839
Editore: Springer Nature
DOI: 10.1038/s42256-020-0212-3

Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring

Autori: Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt
Pubblicato in: Frontiers in Robotics and AI, Numero 7, 2020, ISSN 2296-9144
Editore: Frontiers Media
DOI: 10.3389/frobt.2020.00100

Semantic programming by example with pre-trained models

Autori: Gust Verbruggen, Vu Le, Sumit Gulwani
Pubblicato in: Proceedings of the ACM on Programming Languages;, Numero Vol. 5; iss. OOPSLA, 2021, Pagina/e 1–25, ISSN 2475-1421
Editore: ACM Digital library
DOI: 10.1145/3485477

Human-Machine Collaboration for Democratizing Data Science

Autori: Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt
Pubblicato in: Human-Like Machine Intelligence, Numero Vol. abs/2004.11113, 2021, Pagina/e 379 - 402, ISBN 9780198862536
Editore: Oxford University Press
DOI: 10.1093/oso/9780198862536.003.0019

Hybrid ASP-Based Approach to Pattern Mining

Autori: Sergey Paramonov, Daria Stepanova, Pauli Miettinen
Pubblicato in: Rules and Reasoning, Numero 10364, 2017, Pagina/e 199-214, ISBN 978-3-319-61251-5
Editore: Springer International Publishing
DOI: 10.1007/978-3-319-61252-2_14

Constraint Learning: An Appetizer

Autori: Stefano Teso
Pubblicato in: Reasoning Web. Explainable Artificial Intelligence - 15th International Summer School 2019, Bolzano, Italy, September 20–24, 2019, Tutorial Lectures, Numero 11810, 2019, Pagina/e 232-249, ISBN 978-3-030-31422-4
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-31423-1_7

Automating Data Science (Dagstuhl Seminar 18401)

Autori: Tijl De Bie; Luc De Raedt, Holger H. Hoos, Padhraic Smyth
Pubblicato in: Dagstuhl Reports, Numero Volume 8, Numero 9, 2019
Editore: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
DOI: 10.4230/dagrep.8.9.154

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