Celine Vens

ORCID

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 50

Top Venues

Katholieke Universiteit Leuven, Belgium (PHD)

Education History

Katholieke Universiteit Leuven, Belgium

PHD

Publications

Alireza Gharahighehi, Celine Vens
Diversification in session-based news recommender systems. Pers. Ubiquitous Comput. 27 (1) (2023)
Robbe D'hondt, Sinead Moylett, An Goris, Celine Vens
A Binning Approach for Predicting Long-Term Prognosis in Multiple Sclerosis. AIME (2023)
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
BELLATREX: Building Explanations Through a LocaLly AccuraTe Rule EXtractor. IEEE Access 11 (2023)
Alireza Gharahighehi, Michela Venturini, Achilleas Ghinis, Frederik Cornillie, Celine Vens
Extending Bayesian Personalized Ranking with Survival Analysis for MOOC Recommendation. UMAP (Adjunct Publication) (2023)
Saulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, André Carlos Ponce de Leon Ferreira de Carvalho
Online Extra Trees Regressor. IEEE Trans. Neural Networks Learn. Syst. 34 (10) (2023)
Fateme Nateghi Haredasht, Kazeem Adesina Dauda, Celine Vens
Exploiting Censored Information in Self-Training for Time-to-Event Prediction. IEEE Access 11 (2023)
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification. Comput. Biol. Medicine 152 (2023)
Klest Dedja, Felipe Kenji Nakano, Celine Vens
Active Learning for Survival Analysis with Incrementally Disclosed Label Information. IAL@PKDD/ECML (2023)
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
HypeRS: Building a Hypergraph-driven ensemble Recommender System. CoRR (2023)
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha, Celine Vens
Hierarchy exploitation to detect missing annotations on hierarchical multi-label classification. CoRR (2022)
Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas
Drug-target interaction prediction via an ensemble of weighted nearest neighbors with interaction recovery. Appl. Intell. 52 (4) (2022)
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Explaining random forest prediction through diverse rulesets. CoRR (2022)
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Deep tree-ensembles for multi-output prediction. Pattern Recognit. 121 (2022)
Bijit Roy, Tomaz Stepisnik, The Pooled Resource Open-Access A. L. S. Clinical Trials Consortium, Celine Vens, Saso Dzeroski
Survival analysis with semi-supervised predictive clustering trees. Comput. Biol. Medicine 141 (2022)
Michela Venturini, Ingrid Van Keilegom, Wouter De Corte, Celine Vens
A Novel Survival Analysis Approach to Predict the Need for Intubation in Intensive Care Units. AIME (2022)
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering. CoRR (2022)
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering. IntelliSys (1) (2022)
Fateme Nateghi Haredasht, Celine Vens
Predicting Survival Outcomes in the Presence of Unlabeled Data. Mach. Learn. 111 (11) (2022)
Fateme Nateghi Haredasht, Celine Vens
Predicting Survival Outcomes in the Presence of Unlabeled Data. CoRR (2022)
Alireza Gharahighehi, Konstantinos Pliakos, Celine Vens
Addressing the Cold-Start Problem in Collaborative Filtering Through Positive-Unlabeled Learning and Multi-Target Prediction. IEEE Access 10 (2022)
Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas
Predicting Drug-Target Interactions With Multi-Label Classification and Label Partitioning. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (4) (2021)
Alireza Gharahighehi, Celine Vens
Diversification in Session-based News Recommender Systems. CoRR (2021)
Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Explaining a Random Survival Forest by Extracting Prototype Rules. PKDD/ECML Workshops (2) (2021)
Alireza Gharahighehi, Celine Vens
Personalizing Diversity Versus Accuracy in Session-Based Recommender Systems. SN Comput. Sci. 2 (1) (2021)
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
Fair multi-stakeholder news recommender system with hypergraph ranking. Inf. Process. Manag. 58 (5) (2021)
Márcio P. Basgalupp, Ricardo Cerri, Leander Schietgat, Isaac Triguero, Celine Vens
Beyond global and local multi-target learning. Inf. Sci. 579 (2021)
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
An Ensemble Hypergraph Learning Framework for Recommendation. DS (2021)
Konstantinos Pliakos, Celine Vens
Drug-target interaction prediction with tree-ensemble learning and output space reconstruction. BMC Bioinform. 21 (1) (2020)
Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens
Deep tree-ensembles for multi-output prediction. CoRR (2020)
Alireza Gharahighehi, Celine Vens
Making Session-based News Recommenders Diversity-aware. OHARS@RecSys (2020)
Len Feremans, Boris Cule, Celine Vens, Bart Goethals
Combining instance and feature neighbours for extreme multi-label classification. Int. J. Data Sci. Anal. 10 (3) (2020)
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
Multi-stakeholder News Recommendation Using Hypergraph Learning. PKDD/ECML Workshops (2020)
Bruna Zamith Santos, Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
Predictive Bi-clustering Trees for Hierarchical Multi-label Classification. ECML/PKDD (3) (2020)
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
Fair Multi-Stakeholder News Recommender System with Hypergraph ranking. CoRR (2020)
Felipe Kenji Nakano, Ricardo Cerri, Celine Vens
Active learning for hierarchical multi-label classification. Data Min. Knowl. Discov. 34 (5) (2020)
Bin Liu, Konstantinos Pliakos, Celine Vens, Grigorios Tsoumakas
Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery. CoRR (2020)
Felipe Kenji Nakano, Mathias Lietaert, Celine Vens
Machine learning for discovering missing or wrong protein function annotations - A comparison using updated benchmark datasets. BMC Bioinform. 20 (1) (2019)
Alireza Gharahighehi, Celine Vens
Extended Bayesian Personalized Ranking Based on Consumption Behavior. BNAIC/BENELEARN (Selected Papers) (2019)
Konstantinos Pliakos, Celine Vens
Network inference with ensembles of bi-clustering trees. BMC Bioinform. 20 (1) (2019)
Konstantinos Pliakos, Seang-Hwane Joo, Jung Yeon Park, Frederik Cornillie, Celine Vens, Wim van den Noortgate
Integrating machine learning into item response theory for addressing the cold start problem in adaptive learning systems. Comput. Educ. 137 (2019)
Alireza Gharahighehi, Celine Vens
News Topic Recommendation Using an Extended Bayesian Personalized Ranking. BNAIC/BENELEARN (2019)
Konstantinos Pliakos, Celine Vens
Network representation with clustering tree features. J. Intell. Inf. Syst. 51 (2) (2018)
Leander Schietgat, Celine Vens, Ricardo Cerri, Carlos N. Fischer, Eduardo P. Costa, Jan Ramon, Claudia M. A. Carareto, Hendrik Blockeel
A machine learning based framework to identify and classify long terminal repeat retrotransposons. PLoS Comput. Biol. 14 (4) (2018)
Annelies Raes, Pieter Vanneste, Celine Vens, Fien Depaepe
Teaching for Versus Through Problem Solving: Impact on Teaching and Learning. ICLS (2018)
Konstantinos Pliakos, Pierre Geurts, Celine Vens
Global multi-output decision trees for interaction prediction. Mach. Learn. 107 (8-10) (2018)
Konstantinos Pliakos, Celine Vens
Mining features for biomedical data using clustering tree ensembles. J. Biomed. Informatics 85 (2018)
Len Feremans, Boris Cule, Celine Vens, Bart Goethals
Combining Instance and Feature Neighbors for Efficient Multi-label Classification. DSAA (2017)
Konstantinos Pliakos, Celine Vens
Feature Induction and Network Mining with Clustering Tree Ensembles. NFMCP@PKDD/ECML (2016)
Isaac Triguero, Celine Vens
Labelling strategies for hierarchical multi-label classification techniques. Pattern Recognit. 56 (2016)
Carlos N. Fischer, Claudia M. A. Carareto, Renato A. C. dos Santos, Ricardo Cerri, Eduardo P. Costa, Leander Schietgat, Celine Vens
Learning HMMs for nucleotide sequences from amino acid alignments. Bioinform. 31 (11) (2015)
Celine Vens, Sofie Van Gassen, Tom Dhaene, Yvan Saeys
Complex Aggregates over Clusters of Elements. ILP (2014)
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski
Tree ensembles for predicting structured outputs. Pattern Recognit. 46 (3) (2013)
Pan Hu, Celine Vens, Bart Verstrynge, Hendrik Blockeel
Generalizing from Example Clusters. Discovery Science (2013)
Celine Vens, Bart Verstrynge, Hendrik Blockeel
Semi-supervised Clustering with Example Clusters. KDIR/KMIS (2013)
Joris Maervoet, Celine Vens, Greet Vanden Berghe, Hendrik Blockeel, Patrick De Causmaecker
Outlier detection in relational data: A case study in geographical information systems. Expert Syst. Appl. 39 (5) (2012)
Celine Vens, Marie-Noëlle Rosso, Etienne G. J. Danchin
Identifying discriminative classification-based motifs in biological sequences. Bioinform. 27 (9) (2011)
Celine Vens, Fabrizio Costa
Random Forest Based Feature Induction. ICDM (2011)
Celine Vens, Eduardo P. Costa, Hendrik Blockeel
Top-Down Induction of Phylogenetic Trees. EvoBIO (2010)
Leander Schietgat, Celine Vens, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski
Predicting gene function using hierarchical multi-label decision tree ensembles. BMC Bioinform. 11 (2010)
Celine Vens
Complex aggregates in relational learning. AI Commun. 21 (2-3) (2008)
Celine Vens, Jan Struyf, Leander Schietgat, Saso Dzeroski, Hendrik Blockeel
Decision trees for hierarchical multi-label classification. Mach. Learn. 73 (2) (2008)
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski
Ensembles of Multi-Objective Decision Trees. ECML (2007)
Aneta Ivanovska, Celine Vens, Saso Dzeroski, Nathalie Colbach
Studying the Presence of Genetically Modified Variants in Organic Oilseed Rape by Using Relational Data Mining. EnviroInfo (1) (2007)
Celine Vens, Hendrik Blockeel
A simple regression based heuristic for learning model trees. Intell. Data Anal. 10 (3) (2006)
Celine Vens, Jan Ramon, Hendrik Blockeel
Refining Aggregate Conditions in Relational Learning. PKDD (2006)
Anneleen Van Assche, Celine Vens, Hendrik Blockeel, Saso Dzeroski
First order random forests: Learning relational classifiers with complex aggregates. Mach. Learn. 64 (1-3) (2006)
Celine Vens, Jan Ramon, Hendrik Blockeel
ReMauve: A Relational Model Tree Learner. ILP (2006)
Celine Vens, Anneleen Van Assche, Hendrik Blockeel, Saso Dzeroski
First Order Random Forests with Complex Aggregates. ILP (2004)

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Publication Activity (10 Years)

Top Topics

Top Venues

Celine Vens