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Jessa Bekker
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2020 – today
- 2024
- [j4]Victor Verreet
, Luc De Raedt
, Jessa Bekker
:
Modeling PU learning using probabilistic logic programming. Mach. Learn. 113(3): 1351-1372 (2024) - 2023
- [j3]Vincent Derkinderen
, Jessa Bekker
, Pieter Smet
:
Optimizing workforce allocation under uncertain activity duration. Comput. Ind. Eng. 179: 109228 (2023) - [j2]Lola Botman
, Jonas Soenen
, Konstantinos Theodorakos
, Aras Yurtman
, Jessa Bekker
, Koen Vanthournout
, Hendrik Blockeel
, Bart De Moor
, Jesus Lago
:
A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households. IEEE Trans. Smart Grid 14(1): 757-768 (2023) - 2022
- [c9]Jonas Schouterden, Jessa Bekker
, Jesse Davis
, Hendrik Blockeel
:
Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias. AAAI 2022: 4137-4145 - [c8]Tobias Cornille, Fengna Wang, Jessa Bekker
:
Interactive Multi-Level Prosody Control for Expressive Speech Synthesis. ICASSP 2022: 8312-8316 - [c7]Sander De Block, Jessa Bekker:
Bagging Propensity Weighting: A Robust method for biased PU Learning. LIDTA 2022: 23-37 - 2020
- [j1]Jessa Bekker
, Jesse Davis
:
Learning from positive and unlabeled data: a survey. Mach. Learn. 109(4): 719-760 (2020)
2010 – 2019
- 2019
- [c6]Jessa Bekker
, Pieter Robberechts
, Jesse Davis
:
Beyond the Selected Completely at Random Assumption for Learning from Positive and Unlabeled Data. ECML/PKDD (2) 2019: 71-85 - 2018
- [c5]Jessa Bekker, Jesse Davis:
Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction. AAAI 2018: 2712-2719 - [c4]Jessa Bekker, Jesse Davis:
Learning from Positive and Unlabeled Data under the Selected At Random Assumption. LIDTA@ECML/PKDD 2018: 8-22 - [i4]Jessa Bekker, Jesse Davis:
Learning from Positive and Unlabeled Data under the Selected At Random Assumption. CoRR abs/1808.08755 (2018) - [i3]Jessa Bekker, Jesse Davis:
Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data. CoRR abs/1809.03207 (2018) - [i2]Jessa Bekker, Jesse Davis:
Learning From Positive and Unlabeled Data: A Survey. CoRR abs/1811.04820 (2018) - 2017
- [c3]Jessa Bekker
, Jesse Davis
:
Positive and Unlabeled Relational Classification Through Label Frequency Estimation. ILP 2017: 16-30 - [c2]Yitao Liang, Jessa Bekker, Guy Van den Broeck:
Learning the Structure of Probabilistic Sentential Decision Diagrams. UAI 2017 - 2016
- [i1]Jessa Bekker, Arjen Hommersom, Martijn Lappenschaar, Jesse Davis:
Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks. CoRR abs/1612.03055 (2016) - 2015
- [c1]Jessa Bekker, Jesse Davis, Arthur Choi, Adnan Darwiche, Guy Van den Broeck:
Tractable Learning for Complex Probability Queries. NIPS 2015: 2242-2250
Coauthor Index

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