Jessa Bekker

According to our database, Jessa Bekker authored at least 15 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Modeling PU learning using probabilistic logic programming.

Victor Verreet, Luc De Raedt, Jessa Bekker

Mach. Learn., 2024

2023

Optimizing workforce allocation under uncertain activity duration.

Vincent Derkinderen, Jessa Bekker, Pieter Smet

Comput. Ind. Eng., May, 2023

A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households.

Lola Botman, Jonas Soenen, Konstantinos Theodorakos, Aras Yurtman, Jessa Bekker, Koen Vanthournout, Hendrik Blockeel, Bart De Moor, Jesus Lago

IEEE Trans. Smart Grid, 2023

2022

Bagging Propensity Weighting: A Robust method for biased PU Learning.

Sander De Block, Jessa Bekker

Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2022

Interactive Multi-Level Prosody Control for Expressive Speech Synthesis.

Tobias Cornille, Fengna Wang, Jessa Bekker

Proceedings of the IEEE International Conference on Acoustics, 2022

Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias.

Jonas Schouterden, Jessa Bekker, Jesse Davis, Hendrik Blockeel

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2020

Learning from positive and unlabeled data: a survey.

Jessa Bekker, Jesse Davis

Mach. Learn., 2020

2019

Beyond the Selected Completely at Random Assumption for Learning from Positive and Unlabeled Data.

Jessa Bekker, Pieter Robberechts, Jesse Davis

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018

Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data.

Jessa Bekker, Jesse Davis

CoRR, 2018

Learning from Positive and Unlabeled Data under the Selected At Random Assumption.

Jessa Bekker, Jesse Davis

Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction.

Jessa Bekker, Jesse Davis

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Learning the Structure of Probabilistic Sentential Decision Diagrams.

Yitao Liang, Jessa Bekker, Guy Van den Broeck

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Positive and Unlabeled Relational Classification Through Label Frequency Estimation.

Jessa Bekker, Jesse Davis

Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

2016

Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks.

Jessa Bekker, Arjen Hommersom, Martijn Lappenschaar, Jesse Davis

CoRR, 2016

2015

Tractable Learning for Complex Probability Queries.

Jessa Bekker, Jesse Davis, Arthur Choi, Adnan Darwiche, Guy Van den Broeck

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015