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Researcher
Hendrik Blockeel
- Disciplines:Data mining, Machine learning and decision making
Affiliations
- Declarative Languages and Artificial Intelligence (DTAI) (Division)
Responsible
From1 Aug 2020 → Today - Declarative Languages and Artificial Intelligence (DTAI) (Division)
Member
From1 Aug 2020 → Today - Informatics Section (Division)
Member
From1 Oct 1999 → 30 Apr 2020
Projects
11 - 20 of 38
- AI in Industry: Learning and Reasoning for AutomationFrom1 Jan 2021 → TodayFunding: IOF - mandates
- Optimisation and Deep LearningFrom1 Jan 2020 → 30 Jul 2023Funding: BOF - doctoral mandates
- Semi-Supervised and Explainable Machine Learning with an Application to the Low-Voltage GridFrom1 Oct 2019 → 9 Sep 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Verifying Learning Artificial Intelligence SystemsFrom1 Jan 2018 → 31 Dec 2021Funding: FWO EOS
- Scalable, interpretable and versatile models of relational data: Design, induction and inferenceFrom1 Oct 2017 → 30 Sep 2021Funding: BOF - Concerted Research Project from 1994
- Efficient and Versatile Methods for Relational Machine LearningFrom20 Sep 2017 → 14 Jun 2022Funding: Own budget, for example: patrimony, inscription fees, gifts
- MERCS: Efficient Modeling of Big Data with Multidirectional Ensembles of Decision TreesFrom4 Oct 2016 → 4 Oct 2020Funding: Own budget, for example: patrimony, inscription fees, gifts
- Induction of multi-directional ensembles of decision treesFrom4 Oct 2016 → 4 Oct 2020Funding: Own budget, for example: patrimony, inscription fees, gifts
- MERCS: Efficient modeling of big data with multidirectional ensembles of decision treesFrom1 Jan 2016 → 31 Dec 2019Funding: FWO research project (including WEAVE projects)
- Modeling, automatisation and optimisation of experimental processes in network-structured domains.From1 Jan 2015 → 13 Dec 2016Funding: Own budget, for example: patrimony, inscription fees, gifts
Publications
1 - 10 of 174
- Semi-Supervised and Explainable Machine Learning with an Application to the Low-Voltage Grid(2023)
Authors: Jonas Soenen, Hendrik Blockeel
- Estimating Dynamic Time Warping Distance Between Time Series with Missing Data(2023)
Authors: Aras Yurtman, Jonas Soenen, Wannes Meert, Hendrik Blockeel
Pages: 221 - 237Number of pages: 17 - Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming(2023)
Authors: Kshitij Goyal, Wannes Meert, Hendrik Blockeel
Pages: 47 - 64Number of pages: 17 - Decision trees: from efficient prediction to responsible AI(2023)
Authors: Hendrik Blockeel, Laurens Devos
- Machine Learning with Constraints: Towards Trustworthy AI(2023)
Authors: Kshitij Goyal, Hendrik Blockeel
- Scenario Generation of Residential Electricity Consumption Through Sampling Of Historical Data(2023)
Authors: Jonas Soenen, Aras Yurtman, Wannes Meert, Hendrik Blockeel
- FeaBI: A Feature Selection-Based Framework for Interpreting KG Embeddings(2023)
Authors: Hendrik Blockeel
Pages: 599 - 617Number of pages: 19 - A scalable ensemble approach to forecast the electricity consumption of households(2022)
Authors: Lola Botman, Jonas Soenen, Konstantinos Theodorakos, Aras Yurtman, Jessa Bekker, Hendrik Blockeel, Bart De Moor
Pages: 757 - 768 - Efficient and Versatile Methods for Relational Machine Learning(2022)
Authors: Jonas Schouterden, Hendrik Blockeel, Jesse Davis
- COBRAS+: Reusing Previously Obtained Constraints in Active Semi-Supervised Clustering(2021)
Authors: Aras Yurtman, Wannes Meert, Hendrik Blockeel
Pages: 184 - 202Number of pages: 19