Celine Vens

92 papers A* 2B 10C 1Journal 51Unranked 23
YearRankTypeTitle / Venue / Authors
2026 A* conf
Oxytrees: Model Trees for Bipartite Learning.
AAAI
Pedro Ilídio, Felipe Kenji Nakano, Alireza Gharahighehi, Robbe D'hondt, Ricardo Cerri, Celine Vens
2025 B conf
Active semi-supervised learning for multi-target regression.
IJCNN
Maira Farias Andrade Lira, Luisa Cavalcante, Celine Vens, Ricardo B. C. Prudêncio, Felipe Kenji Nakano
2025 — conf
BellatrExplorer: An Interactive Random Forest Local Explainability Dashboard.
ECML/PKDD (10)
Robbe D'hondt, Celine Vens
2025 J jnl
Enhancing Collaborative Filtering-Based Course Recommendations by Exploiting Time-to-Event Information with Survival Analysis.
CoRR
Alireza Gharahighehi, Achilleas Ghinis, Michela Venturini, Frederik Cornillie, Celine Vens
2025 J jnl
Explainable time-to-progression predictions in multiple sclerosis.
Comput. Methods Programs Biomed.
Robbe D'hondt, Klest Dedja, Sofie Aerts, Bart Van Wijmeersch, Tomas Kalincik, Stephen Reddel, Eva Kubala Havrdova, Alessandra Lugaresi, Bianca Weinstock-Guttman, Saloua Mrabet, Patrice Lalive, Allan G. Kermode, Serkan Ozakbas, Francesco Patti, Alexandre Prat, Valentina Tomassini, Izanne Roos, Raed Alroughani, Oliver Gerlach, Samia J. Khoury, Vincent Van Pesch, Maria Jose Sa, Julie Prevost, Daniele Spitaleri, Pamela McCombe, Claudio Solaro, Anneke van der Walt, Helmut Butzkueven, Guy Laureys, Jose Luis Sanchez-Menoyo, Koen de Gans, Abdullah Al-Asmi, Norma Deri, Tunde Csepany, Talal Al-Harbi, William M. Carroll, Csilla Rozsa, Bhim Singhal, Todd A. Hardy, Sudarshini Ramanathan, Liesbet M. Peeters, Celine Vens
2025 C conf
Inductive models for structured output prediction of lncRNA-disease associations.
CIBCB
Felipe Kenji Nakano, Livia Bertoni, Ricardo Cerri, Celine Vens
2025 — conf
Integrating Expert Knowledge in Matrix Factorization.
LAK Workshops
Changsheng Chen, Robbe D'hondt, Alireza Gharahighehi, Celine Vens, Wim Van Den Noortgate
2025 — conf
Multi-Event Survival-Informed Clustering for Time-to-Worsening in Multiple Sclerosis.
AIME (1)
Robbe D'hondt, Jasper de Boer, Celine Vens
2025 J jnl
Oxytrees: Model Trees for Bipartite Learning.
CoRR
Pedro Ilídio, Felipe Kenji Nakano, Alireza Gharahighehi, Robbe D'hondt, Ricardo Cerri, Celine Vens
2025 J jnl
Pairwise and Attribute-Aware Decision Tree-Based Preference Elicitation for Cold-Start Recommendation.
CoRR
Alireza Gharahighehi, Felipe Kenji Nakano, Xuehua Yang, Wenhan Cu, Celine Vens
2025 — conf
Sequential Rule Analysis of ICU Patient Vital Signals and Alarms.
ECML/PKDD (9)
Michela Venturini, Len Feremans, Wouter De Corte, Celine Vens
2024 — conf
Course recommendations in MOOCs using collaborative filtering and survival analysis (Invited Paper).
ALL@AIED
Alireza Gharahighehi, Michela Venturini, Celine Vens
2024 B conf
Deep forests with tree-embeddings and label imputation for weak-label learning.
IJCNN
Pedro Ilídio, Ricardo Cerri, Celine Vens, Felipe Kenji Nakano
2024 J jnl
Improving 1-Year Mortality Prediction After Pediatric Heart Transplantation Using Hypothetical Donor-Recipient Matches.
IEEE Access
Michela Venturini, Fateme Nateghi Haredasht, Frantisek Sabovcik, Robert J. H. Miller, Tatiana Kuznetsova, Celine Vens
2024 — conf
Personalized Learning in K-12 Education: Exploring Weak-Labels for a Random Forest-based Collaborative Filtering Approach.
ALL@AIED
Pedro Ilídio, Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
2024 J jnl
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission.
Comput. Methods Programs Biomed.
Felipe Kenji Nakano, Karolijn Dulfer, Ilse Vanhorebeek, Pieter J. Wouters, Sascha C. Verbruggen, Koen F. Joosten, Fabian Güiza Grandas, Celine Vens, Greet Van den Berghe
2024 J jnl
Predicting time-to-intubation after critical care admission using machine learning and cured fraction information.
Artif. Intell. Medicine
Michela Venturini, Ingrid Van Keilegom, Wouter De Corte, Celine Vens
2024 J jnl
SurvivalLVQ: Interpretable supervised clustering and prediction in survival analysis via Learning Vector Quantization.
Pattern Recognit.
Jasper de Boer, Klest Dedja, Celine Vens
2024 — conf
Using Machine Learning to Predict the Number of Latent Skills in Online Learning Environments.
ALL@AIED
Changsheng Chen, Robbe D'hondt, Celine Vens, Wim Van Den Noortgate
2023 B conf
A Binning Approach for Predicting Long-Term Prognosis in Multiple Sclerosis.
AIME
Robbe D'hondt, Sinead Moylett, An Goris, Celine Vens
2023 — conf
Active Learning for Survival Analysis with Incrementally Disclosed Label Information.
IAL@PKDD/ECML
Klest Dedja, Felipe Kenji Nakano, Celine Vens
2023 — ed.
Artificial Intelligence and Machine Learning - 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7-9, 2022, Revised Selected Papers
BNAIC/BENELEARN
Toon Calders, Celine Vens, Jefrey Lijffijt, Bart Goethals
2023 J jnl
BELLATREX: Building Explanations Through a LocaLly AccuraTe Rule EXtractor.
IEEE Access
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
2023 J jnl
Diversification in session-based news recommender systems.
Pers. Ubiquitous Comput.
Alireza Gharahighehi, Celine Vens
2023 J jnl
Exploiting Censored Information in Self-Training for Time-to-Event Prediction.
IEEE Access
Fateme Nateghi Haredasht, Kazeem Adesina Dauda, Celine Vens
2023 — conf
Extending Bayesian Personalized Ranking with Survival Analysis for MOOC Recommendation.
UMAP (Adjunct Publication)
Alireza Gharahighehi, Michela Venturini, Achilleas Ghinis, Frederik Cornillie, Celine Vens
2023 J jnl
HypeRS: Building a Hypergraph-driven ensemble Recommender System.
CoRR
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
2023 J jnl
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification.
Comput. Biol. Medicine
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
2023 J jnl
Online Extra Trees Regressor.
IEEE Trans. Neural Networks Learn. Syst.
Saulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, André Carlos Ponce de Leon Ferreira de Carvalho
2022 B conf
A Novel Survival Analysis Approach to Predict the Need for Intubation in Intensive Care Units.
AIME
Michela Venturini, Ingrid Van Keilegom, Wouter De Corte, Celine Vens
2022 J jnl
Addressing the Cold-Start Problem in Collaborative Filtering Through Positive-Unlabeled Learning and Multi-Target Prediction.
IEEE Access
Alireza Gharahighehi, Konstantinos Pliakos, Celine Vens
2022 — conf
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering.
IntelliSys (1)
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
2022 J jnl
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering.
CoRR
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
2022 J jnl
Deep tree-ensembles for multi-output prediction.
Pattern Recognit.
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
2022 J jnl
Drug-target interaction prediction via an ensemble of weighted nearest neighbors with interaction recovery.
Appl. Intell.
Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas
2022 J jnl
Explaining random forest prediction through diverse rulesets.
CoRR
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
2022 J jnl
Hierarchy exploitation to detect missing annotations on hierarchical multi-label classification.
CoRR
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
2022 J jnl
Predicting Survival Outcomes in the Presence of Unlabeled Data.
CoRR
Fateme Nateghi Haredasht, Celine Vens
2022 J jnl
Predicting Survival Outcomes in the Presence of Unlabeled Data.
Mach. Learn.
Fateme Nateghi Haredasht, Celine Vens
2022 J jnl
Survival analysis with semi-supervised predictive clustering trees.
Comput. Biol. Medicine
Bijit Roy, Tomaz Stepisnik, Pooled Resource Open-Access A. L. S. Clinical Trials Consortium, Celine Vens, Saso Dzeroski
2021 B conf
An Ensemble Hypergraph Learning Framework for Recommendation.
DS
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
2021 J jnl
Beyond global and local multi-target learning.
Inf. Sci.
Márcio P. Basgalupp, Ricardo Cerri, Leander Schietgat, Isaac Triguero, Celine Vens
2021 J jnl
Diversification in Session-based News Recommender Systems.
CoRR
Alireza Gharahighehi, Celine Vens
2021 — conf
Explaining a Random Survival Forest by Extracting Prototype Rules.
PKDD/ECML Workshops (2)
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
2021 J jnl
Fair multi-stakeholder news recommender system with hypergraph ranking.
Inf. Process. Manag.
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
2021 J jnl
Personalizing Diversity Versus Accuracy in Session-Based Recommender Systems.
SN Comput. Sci.
Alireza Gharahighehi, Celine Vens
2021 J jnl
Predicting Drug-Target Interactions With Multi-Label Classification and Label Partitioning.
IEEE ACM Trans. Comput. Biol. Bioinform.
Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas
2020 J jnl
Active learning for hierarchical multi-label classification.
Data Min. Knowl. Discov.
Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
2020 J jnl
Combining instance and feature neighbours for extreme multi-label classification.
Int. J. Data Sci. Anal.
Len Feremans, Boris Cule, Celine Vens, Bart Goethals
2020 J jnl
Deep tree-ensembles for multi-output prediction.
CoRR
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
2020 J jnl
Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery.
CoRR
Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas
2020 J jnl
Drug-target interaction prediction with tree-ensemble learning and output space reconstruction.
BMC Bioinform.
Konstantinos Pliakos, Celine Vens
2020 J jnl
Fair Multi-Stakeholder News Recommender System with Hypergraph ranking.
CoRR
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
2020 — conf
Making Session-based News Recommenders Diversity-aware.
OHARS@RecSys
Alireza Gharahighehi, Celine Vens
2020 — conf
Multi-stakeholder News Recommendation Using Hypergraph Learning.
PKDD/ECML Workshops
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
2020 — conf
Predictive Bi-clustering Trees for Hierarchical Multi-label Classification.
ECML/PKDD (3)
Bruna Zamith Santos, Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
2019 — conf
Extended Bayesian Personalized Ranking Based on Consumption Behavior.
BNAIC/BENELEARN (Selected Papers)
Alireza Gharahighehi, Celine Vens
2019 J jnl
Integrating machine learning into item response theory for addressing the cold start problem in adaptive learning systems.
Comput. Educ.
Konstantinos Pliakos, Seang-Hwane Joo, Jung Yeon Park, Frederik Cornillie, Celine Vens, Wim Van Den Noortgate
2019 J jnl
Machine learning for discovering missing or wrong protein function annotations - A comparison using updated benchmark datasets.
BMC Bioinform.
Felipe Kenji Nakano, Mathias Lietaert, Celine Vens
2019 J jnl
Network inference with ensembles of bi-clustering trees.
BMC Bioinform.
Konstantinos Pliakos, Celine Vens
2019 — conf
News Topic Recommendation Using an Extended Bayesian Personalized Ranking.
BNAIC/BENELEARN
Alireza Gharahighehi, Celine Vens
2018 J jnl
A machine learning based framework to identify and classify long terminal repeat retrotransposons.
PLoS Comput. Biol.
Leander Schietgat, Celine Vens, Ricardo Cerri, Carlos N. Fischer, Eduardo P. Costa, Jan Ramon, Claudia M. A. Carareto, Hendrik Blockeel
2018 J jnl
Global multi-output decision trees for interaction prediction.
Mach. Learn.
Konstantinos Pliakos, Pierre Geurts, Celine Vens
2018 J jnl
Mining features for biomedical data using clustering tree ensembles.
J. Biomed. Informatics
Konstantinos Pliakos, Celine Vens
2018 J jnl
Network representation with clustering tree features.
J. Intell. Inf. Syst.
Konstantinos Pliakos, Celine Vens
2018 — conf
Teaching for Versus Through Problem Solving: Impact on Teaching and Learning.
ICLS
Annelies Raes, Pieter Vanneste, Celine Vens, Fien Depaepe
2017 B conf
Combining Instance and Feature Neighbors for Efficient Multi-label Classification.
DSAA
Len Feremans, Boris Cule, Celine Vens, Bart Goethals
2017 — ed.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I
ECML/PKDD (1)
Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski
2017 — ed.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II
ECML/PKDD (2)
Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski
2016 — conf
Feature Induction and Network Mining with Clustering Tree Ensembles.
NFMCP@PKDD/ECML
Konstantinos Pliakos, Celine Vens
2016 J jnl
Labelling strategies for hierarchical multi-label classification techniques.
Pattern Recognit.
Isaac Triguero, Celine Vens
2015 J jnl
Learning HMMs for nucleotide sequences from amino acid alignments.
Bioinform.
Carlos N. Fischer, Claudia M. A. Carareto, Renato Augusto Corrêa dos Santos, Ricardo Cerri, Eduardo P. Costa, Leander Schietgat, Celine Vens
2014 B conf
Complex Aggregates over Clusters of Elements.
ILP
Celine Vens, Sofie Van Gassen, Tom Dhaene, Yvan Saeys
2013 B conf
Generalizing from Example Clusters.
Discovery Science
Pan Hu, Celine Vens, Bart Verstrynge, Hendrik Blockeel
2013 — conf
Semi-supervised Clustering with Example Clusters.
KDIR/KMIS
Celine Vens, Bart Verstrynge, Hendrik Blockeel
2013 J jnl
Tree ensembles for predicting structured outputs.
Pattern Recognit.
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski
2012 J jnl
Outlier detection in relational data: A case study in geographical information systems.
Expert Syst. Appl.
Joris Maervoet, Celine Vens, Greet Vanden Berghe, Hendrik Blockeel, Patrick De Causmaecker
2011 J jnl
Identifying discriminative classification-based motifs in biological sequences.
Bioinform.
Celine Vens, Marie-Noëlle Rosso, Etienne G. J. Danchin
2011 A* conf
Random Forest Based Feature Induction.
ICDM
Celine Vens, Fabrizio Costa
2010 — ch.
Predicting Gene Function using Predictive Clustering Trees.
Inductive Databases and Constraint-Based Data Mining
Celine Vens, Leander Schietgat, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski
2010 J jnl
Predicting gene function using hierarchical multi-label decision tree ensembles.
BMC Bioinform.
Leander Schietgat, Celine Vens, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski
2010 — conf
Top-Down Induction of Phylogenetic Trees.
EvoBIO
Celine Vens, Eduardo P. Costa, Hendrik Blockeel
2008 J jnl
Complex aggregates in relational learning.
AI Commun.
Celine Vens
2008 J jnl
Decision trees for hierarchical multi-label classification.
Mach. Learn.
Celine Vens, Jan Struyf, Leander Schietgat, Saso Dzeroski, Hendrik Blockeel
2007 — —
Complex aggregates in relational learning ; Complexe aggregaten in relationeel leren.
Celine Vens
2007 — conf
Ensembles of Multi-Objective Decision Trees.
ECML
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski
2007 — conf
Studying the Presence of Genetically Modified Variants in Organic Oilseed Rape by Using Relational Data Mining.
EnviroInfo (1)
Aneta Ivanovska, Celine Vens, Saso Dzeroski, Nathalie Colbach
2006 J jnl
A simple regression based heuristic for learning model trees.
Intell. Data Anal.
Celine Vens, Hendrik Blockeel
2006 J jnl
First order random forests: Learning relational classifiers with complex aggregates.
Mach. Learn.
Anneleen Van Assche, Celine Vens, Hendrik Blockeel, Saso Dzeroski
2006 B conf
ReMauve: A Relational Model Tree Learner.
ILP
Celine Vens, Jan Ramon, Hendrik Blockeel
2006 — conf
Refining Aggregate Conditions in Relational Learning.
PKDD
Celine Vens, Jan Ramon, Hendrik Blockeel
2004 B conf
First Order Random Forests with Complex Aggregates.
ILP
Celine Vens, Anneleen Van Assche, Hendrik Blockeel, Saso Dzeroski