Jesse Davis - RankMe

214 papers A* 41A 16B 14C 3Misc 1Journal 76Unranked 44

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bounded-Abstention Multi-horizon Time-series Forecasting. CoRR Luca Stradiotti, Laurens Devos, Anna Monreale, Jesse Davis, Andrea Pugnana
2026	J	`jnl`	Correction: TSelect: selecting relevant and non-redundant channels for multivariate time series classification. Data Min. Knowl. Discov. Loren Nuyts, Lorenzo Perini, Jesse Davis
2026	J	`jnl`	Dealing with Uncertainty in Contextual Anomaly Detection. Trans. Mach. Learn. Res. Luca Bindini, Lorenzo Perini, Stefano Nistri, Jesse Davis, Paolo Frasconi
2026	J	`jnl`	Temporal Graph Network Framework for Quantifying Pass Reception Probabilities Against Defensive Structures. Mach. Learn. Pegah Rahimian, Jesse Davis, László Toka
2025	B	`conf`	Anomaly Detection Under Contaminated Data: A Weighted Iterative Refinement Framework for Health Monitoring. DSAA Stefano Donné, Jesse Davis, Filip Van Utterbeeck, Mathias Verbeke
2025	J	`jnl`	Common Data Format (CDF): A Standardized Format for Match-Data in Football (Soccer). CoRR Gabriel Anzer, Kilian Arnsmeyer, Pascal Bauer, Joris Bekkers, Ulf Brefeld, Jesse Davis, Nicolas Evans, Matthias Kempe, Samuel J. Robertson, Joshua Wyatt Smith, Jan Van Haaren
2025	A*	`conf`	Compressing tree ensembles through Level-wise Optimization and Pruning. ICML Laurens Devos, Timo Martens, Deniz Can Oruc, Wannes Meert, Hendrik Blockeel, Jesse Davis
2025	J	`jnl`	Dealing with Uncertainty in Contextual Anomaly Detection. CoRR Luca Bindini, Lorenzo Perini, Stefano Nistri, Jesse Davis, Paolo Frasconi
2025	J	`jnl`	Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidence. ACM Trans. Comput. Heal. Wei Sun, Mingxiao Li, Damien Sileo, Jesse Davis, Marie-Francine Moens
2025	J	`jnl`	Guest editorial: special issue on machine learning in soccer. Mach. Learn. Daniel Berrar, Jesse Davis, Philippe Lopes, Werner Dubitzky
2025	A	`conf`	Learning from biased positive-unlabeled data via threshold calibration. AISTATS Pawel Teisseyre, Timo Martens, Jessa Bekker, Jesse Davis
2025	J	`jnl`	Learning to Reject Low-Quality Explanations via User Feedback. CoRR Luca Stradiotti, Dario Pesenti, Stefano Teso, Jesse Davis
2025	—	`conf`	Mitigating Negative Interference in Multilingual Knowledge Editing through Null-Space Constraints. ACL (Findings) Wei Sun, Tingyu Qu, Mingxiao Li, Jesse Davis, Marie-Francine Moens
2025	J	`jnl`	Mitigating Negative Interference in Multilingual Sequential Knowledge Editing through Null-Space Constraints. CoRR Wei Sun, Tingyu Qu, Mingxiao Li, Jesse Davis, Marie-Francine Moens
2025	A	`conf`	Policy Safety Testing in Non-Deterministic Planning: Fuzzing, Test Oracles, Fault Analysis. ECAI Chaahat Jain, Daniel Sherbakov, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
2025	—	`conf`	RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations. KDD (2) Thomas Daniels, Maarten Bosteels, Pieter Robberechts, Jesse Davis
2025	J	`jnl`	Stop Guessing: Optimizing Goalkeeper Policies for Soccer Penalty Kicks. CoRR Lotte Bransen, Tim Janssen, Jesse Davis
2025	J	`jnl`	TSelect: selecting relevant and non-redundant channels for multivariate time series classification. Data Min. Knowl. Discov. Loren Nuyts, Lorenzo Perini, Jesse Davis
2025	B	`conf`	The When and How of Target Variable Transformations. IDA Loren Nuyts, Jesse Davis
2025	J	`jnl`	The When and How of Target Variable Transformations. CoRR Loren Nuyts, Jesse Davis
2025	J	`jnl`	What Makes a Dribble Successful? Insights From 3D Pose Tracking Data. CoRR Michiel Schepers, Pieter Robberechts, Jan Van Haaren, Jesse Davis
2024	J	`jnl`	Biases in Expected Goals Models Confound Finishing Ability. CoRR Jesse Davis, Pieter Robberechts
2024	A	`conf`	Combining Active Learning and Learning to Reject for Anomaly Detection. ECAI Luca Stradiotti, Lorenzo Perini, Jesse Davis
2024	J	`jnl`	Computational Approaches to Strategy and Tactics in Sports (Dagstuhl Seminar 24081). Dagstuhl Reports Ulf Brefeld, Jesse Davis, Laura de Jong, Stephanie Kovalchik
2024	—	`conf`	DMON: A Simple Yet Effective Approach for Argument Structure Learning. LREC/COLING Wei Sun, Mingxiao Li, Jingyuan Sun, Jesse Davis, Marie-Francine Moens
2024	J	`jnl`	DMON: A Simple yet Effective Approach for Argument Structure Learning. CoRR Wei Sun, Mingxiao Li, Jingyuan Sun, Jesse Davis, Marie-Francine Moens
2024	J	`jnl`	Deep Neural Network Benchmarks for Selective Classification. CoRR Andrea Pugnana, Lorenzo Perini, Jesse Davis, Salvatore Ruggieri
2024	J	`jnl`	Deep Neural Network Benchmarks for Selective Classification. J. Data-centric Mach. Learn. Res. Andrea Pugnana, Lorenzo Perini, Jesse Davis, Salvatore Ruggieri
2024	J	`jnl`	Detecting Epileptic Seizures Using Hand-Crafted and Automatically Constructed EEG Features. IEEE Trans. Biomed. Eng. Arne De Brabandere, Christos Chatzichristos, Wim Van Paesschen, Maarten De Vos, Jesse Davis
2024	A*	`conf`	Faster Repeated Evasion Attacks in Tree Ensembles. NeurIPS Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis
2024	J	`jnl`	Faster Repeated Evasion Attacks in Tree Ensembles. CoRR Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I ECML/PKDD (1) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part II ECML/PKDD (2) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III ECML/PKDD (3) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV ECML/PKDD (4) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V ECML/PKDD (5) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI ECML/PKDD (6) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII ECML/PKDD (7) Albert Bifet, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite
2024	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII ECML/PKDD (8) Albert Bifet, Povilas Daniusis, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Kai Puolamäki, Indre Zliobaite
2024	J	`jnl`	Machine learning with a reject option: a survey. Mach. Learn. Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
2024	J	`jnl`	Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned. Mach. Learn. Jesse Davis, Lotte Bransen, Laurens Devos, Arne Jaspers, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy
2024	A*	`conf`	Robustness Verification of Multi-Class Tree Ensembles. AAAI Laurens Devos, Lorenzo Cascioli, Jesse Davis
2024	A	`conf`	Safety Verification of Tree-Ensemble Policies via Predicate Abstraction. ECAI Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
2024	A	`conf`	Semi-Supervised Isolation Forest for Anomaly Detection. SDM Luca Stradiotti, Lorenzo Perini, Jesse Davis
2024	J	`jnl`	TSFuse: automated feature construction for multiple time series data. Mach. Learn. Arne De Brabandere, Tim Op De Beéck, Kilian Hendrickx, Wannes Meert, Jesse Davis
2024	J	`jnl`	Time-Shifted Transformers for Driver Identification Using Vehicle Data. IEEE Trans. Intell. Transp. Syst. Wim Govers, Aras Yurtman, Turgay Aslandere, Nicole Eikelenberg, Wannes Meert, Jesse Davis
2023	J	`jnl`	A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer. J. Artif. Intell. Res. Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
2023	A	`conf`	A novel reject option applied to sleep stage scoring. SDM Dries Van der Plas, Wannes Meert, Johan Verbraecken, Jesse Davis
2023	—	`conf`	Detecting Evasion Attacks in Deployed Tree Ensembles. ECML/PKDD (5) Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
2023	J	`jnl`	Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidence. CoRR Wei Sun, Mingxiao Li, Damien Sileo, Jesse Davis, Marie-Francine Moens
2023	J	`jnl`	How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection. CoRR Lorenzo Perini, Daniele Giannuzzi, Jesse Davis
2023	A*	`conf`	Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection. KDD Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2023	J	`jnl`	Lifted Reasoning for Combinatorial Counting. J. Artif. Intell. Res. Pietro Totis, Jesse Davis, Luc De Raedt, Angelika Kimmig
2023	—	`ed.`	Machine Learning and Data Mining for Sports Analytics - 9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised Selected Papers MLSA@PKDD/ECML Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
2023	—	`conf`	Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection. ECML/PKDD (1) Timo Martens, Lorenzo Perini, Jesse Davis
2023	A*	`conf`	Unsupervised Anomaly Detection with Rejection. NeurIPS Lorenzo Perini, Jesse Davis
2023	J	`jnl`	Unsupervised Anomaly Detection with Rejection. CoRR Lorenzo Perini, Jesse Davis
2023	A*	`conf`	un-xPass: Measuring Soccer Player's Creativity. KDD Pieter Robberechts, Maaike Van Roy, Jesse Davis
2022	J	`jnl`	Adversarial Example Detection in Deployed Tree Ensembles. CoRR Laurens Devos, Wannes Meert, Jesse Davis
2022	—	`conf`	Bitpaths: Compressing Datasets Without Decreasing Predictive Performance. PKDD/ECML Workshops (1) Loren Nuyts, Laurens Devos, Wannes Meert, Jesse Davis
2022	J	`jnl`	Can the Output of a Learned Classification Model Monitor a Person's Functional Recovery Status Post-Total Knee Arthroplasty? Sensors Jill Emmerzaal, Arne De Brabandere, Rob van der Straaten, Johan Bellemans, Liesbet De Baets, Jesse Davis, Ilse Jonkers, Annick Timmermans, Benedicte Vanwanseele
2022	B	`conf`	Elastic Product Quantization for Time Series. DS Pieter Robberechts, Wannes Meert, Jesse Davis
2022	J	`jnl`	Elastic Product Quantization for Time Series. CoRR Pieter Robberechts, Wannes Meert, Jesse Davis
2022	—	`conf`	Evaluating Sports Analytics Models: Challenges, Approaches, and Lessons Learned. EBeM@IJCAI Jesse Davis, Lotte Bransen, Laurens Devos, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy
2022	J	`jnl`	Impact of Gender and Feature Set on Machine-Learning-Based Prediction of Lower-Limb Overuse Injuries Using a Single Trunk-Mounted Accelerometer. Sensors Sieglinde Bogaert, Jesse Davis, Sam Van Rossom, Benedicte Vanwanseele
2022	—	`conf`	Looking Beyond the Past: Analyzing the Intrinsic Playing Style of Soccer Teams. ECML/PKDD (6) Jeroen Clijmans, Maaike Van Roy, Jesse Davis
2022	—	`ed.`	Machine Learning and Data Mining for Sports Analytics - 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected Papers MLSA@PKDD/ECML Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
2022	—	`conf`	Multi-domain Active Learning for Semi-supervised Anomaly Detection. ECML/PKDD (4) Vincent Vercruyssen, Lorenzo Perini, Wannes Meert, Jesse Davis
2022	B	`conf`	Semi-supervised Change Point Detection Using Active Learning. DS Arne De Brabandere, Zhenxiang Cao, Maarten De Vos, Alexander Bertrand, Jesse Davis
2022	—	`conf`	Systematic Evaluation of CASH Search Strategies for Unsupervised Anomaly Detection. LIDTA Ioannis Antoniadis, Vincent Vercruyssen, Jesse Davis
2022	—	`conf`	Towards Data-Driven Volatility Modeling with Variational Autoencoders. PKDD/ECML Workshops (2) Thomas Dierckx, Jesse Davis, Wim Schoutens
2022	A*	`conf`	Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity. AAAI Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2022	A*	`conf`	Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias. AAAI Jonas Schouterden, Jessa Bekker, Jesse Davis, Hendrik Blockeel
2021	A*	`conf`	A Bayesian Approach to In-Game Win Probability in Soccer. KDD Pieter Robberechts, Jan Van Haaren, Jesse Davis
2021	J	`jnl`	Evaluation of Automated Hypnogram Analysis on Multi-Scored Polysomnographies. Frontiers Digit. Health Dries Van der Plas, Johan Verbraecken, Marc Willemen, Wannes Meert, Jesse Davis
2021	C	`conf`	Know Your Limits: Machine Learning with Rejection for Vehicle Engineering. ADMA Kilian Hendrickx, Wannes Meert, Bram Cornelis, Jesse Davis
2021	J	`jnl`	Leaving Goals on the Pitch: Evaluating Decision Making in Soccer. CoRR Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
2021	J	`jnl`	Machine Learning in Sports (Dagstuhl Seminar 21411). Dagstuhl Reports Ulf Brefeld, Jesse Davis, Martin Lames, James J. Little
2021	J	`jnl`	Machine Learning with a Reject Option: A survey. CoRR Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
2021	—	`conf`	Mapping probability word problems to executable representations. EMNLP (1) Simon Suster, Pieter Fivez, Pietro Totis, Angelika Kimmig, Jesse Davis, Luc De Raedt, Walter Daelemans
2021	J	`jnl`	Motion Sensor-Based Detection of Outlier Days Supporting Continuous Health Assessment for Single Older Adults. Sensors Marc Mertens, Glen Debard, Jesse Davis, Els Devriendt, Koen Milisen, Jos Tournoy, Tom Croonenborghs, Bart Vanrumste
2021	A	`conf`	Verifying Tree Ensembles by Reasoning about Potential Instances. SDM Laurens Devos, Wannes Meert, Jesse Davis
2021	A*	`conf`	Versatile Verification of Tree Ensembles. ICML Laurens Devos, Wannes Meert, Jesse Davis
2020	A	`conf`	"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series. SDM Vincent Vercruyssen, Wannes Meert, Jesse Davis
2020	J	`jnl`	Additive Tree Ensembles: Reasoning About Potential Instances. CoRR Laurens Devos, Wannes Meert, Jesse Davis
2020	A*	`conf`	Class Prior Estimation in Active Positive and Unlabeled Learning. IJCAI Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2020	J	`jnl`	Fast Distance-based Anomaly Detection in Images Using an Inception-like Autoencoder. CoRR Natasa Sarafijanovic-Djukic, Jesse Davis
2020	—	`conf`	How Data Availability Affects the Ability to Learn Good xG Models. MLSA@PKDD/ECML Pieter Robberechts, Jesse Davis
2020	J	`jnl`	Learning from positive and unlabeled data: a survey. Mach. Learn. Jessa Bekker, Jesse Davis
2020	—	`ed.`	Machine Learning and Data Mining for Sports Analytics - 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings MLSA@PKDD/ECML Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
2020	B	`conf`	Multi-directional Rule Set Learning. DS Jonas Schouterden, Jesse Davis, Hendrik Blockeel
2020	—	`conf`	Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions. ECML/PKDD (3) Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
2020	A	`conf`	STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment. ECAI Martin Svatos, Steven Schockaert, Jesse Davis, Ondrej Kuzelka
2020	—	`ed.`	Scalable Uncertainty Management - 14th International Conference, SUM 2020, Bozen-Bolzano, Italy, September 23-25, 2020, Proceedings SUM Jesse Davis, Karim Tabia
2020	—	`conf`	SoccerMix: Representing Soccer Actions with Mixture Models. ECML/PKDD (5) Tom Decroos, Maaike Van Roy, Jesse Davis
2020	J	`jnl`	Towards the Monitoring of Functional Status in a Free-Living Environment for People with Hip or Knee Osteoarthritis: Design and Evaluation of the JOLO Blended Care App. Sensors Jill Emmerzaal, Arne De Brabandere, Yves Vanrompay, Julie Vranken, Valerie Storms, Liesbet De Baets, Kristoff Corten, Jesse Davis, Ilse Jonkers, Benedicte Vanwanseele, Annick Timmermans
2020	A*	`conf`	Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection. AAAI Vincent Vercruyssen, Wannes Meert, Jesse Davis
2020	A*	`conf`	VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract). IJCAI Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis
2020	J	`jnl`	Versatile Verification of Tree Ensembles. CoRR Laurens Devos, Wannes Meert, Jesse Davis
2019	J	`jnl`	A general anomaly detection framework for fleet-based condition monitoring of machines. CoRR Kilian Hendrickx, Wannes Meert, Yves Mollet, Johan Gyselinck, Bram Cornelis, Konstantinos C. Gryllias, Jesse Davis
2019	A*	`conf`	Actions Speak Louder than Goals: Valuing Player Actions in Soccer. KDD Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis
2019	—	`conf`	Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods. PKDD/ECML Workshops (2) Kenneth Verstraete, Tom Decroos, Bruno Coussement, Nick Vannieuwenhoven, Jesse Davis
2019	—	`conf`	Beyond the Selected Completely at Random Assumption for Learning from Positive and Unlabeled Data. ECML/PKDD (2) Jessa Bekker, Pieter Robberechts, Jesse Davis
2019	B	`conf`	Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder. DS Natasa Sarafijanovic-Djukic, Jesse Davis
2019	—	`conf`	Fast Gradient Boosting Decision Trees with Bit-Level Data Structures. ECML/PKDD (1) Laurens Devos, Wannes Meert, Jesse Davis
2019	J	`jnl`	Gait Event Detection in Tibial Acceleration Profiles: a Structured Learning Approach. CoRR Pieter Robberechts, Rud Derie, Pieter Van den Berghe, Joeri Gerlo, Dirk De Clercq, Veerle Segers, Jesse Davis
2019	J	`jnl`	Guest editorial: special issue on machine learning for soccer. Mach. Learn. Daniel Berrar, Philippe Lopes, Jesse Davis, Werner Dubitzky
2019	B	`conf`	LazyBum: Decision Tree Learning Using Lazy Propositionalization. ILP Jonas Schouterden, Jesse Davis, Hendrik Blockeel
2019	J	`jnl`	LazyBum: Decision tree learning using lazy propositionalization. CoRR Jonas Schouterden, Jesse Davis, Hendrik Blockeel
2019	—	`ed.`	Machine Learning and Data Mining for Sports Analytics - 5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings MLSA@PKDD/ECML Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
2019	A	`conf`	Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption. UAI Ondrej Kuzelka, Jesse Davis
2019	—	`conf`	Player Vectors: Characterizing Soccer Players' Playing Style from Match Event Streams. ECML/PKDD (3) Tom Decroos, Jesse Davis
2019	J	`jnl`	The Open International Soccer Database for machine learning. Mach. Learn. Werner Dubitzky, Philippe Lopes, Jesse Davis, Daniel Berrar
2019	—	`conf`	Use of wearable technology to quantify fall risk in psychogeriatric environments: a feasability study. EMBC Marc Mertens, Julie Raepsaet, Glen Debard, Mieke Mondelaers, Bart Vanrumste, Jesse Davis
2019	J	`jnl`	Who Will Win It? An In-game Win Probability Model for Football. CoRR Pieter Robberechts, Jan Van Haaren, Jesse Davis
2018	—	`conf`	AMIE: Automatic Monitoring of Indoor Exercises. ECML/PKDD (3) Tom Decroos, Kurt Schütte, Tim Op De Beéck, Benedicte Vanwanseele, Jesse Davis
2018	A*	`conf`	Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data. KDD Tom Decroos, Jan Van Haaren, Jesse Davis
2018	J	`jnl`	Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data. CoRR Jessa Bekker, Jesse Davis
2018	A*	`conf`	Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption. WWW Kaja Zupanc, Jesse Davis
2018	A*	`conf`	Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction. AAAI Jessa Bekker, Jesse Davis
2018	A*	`conf`	Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion. KDD Tim Op De Beéck, Wannes Meert, Kurt Schütte, Benedicte Vanwanseele, Jesse Davis
2018	—	`conf`	Forecasting the FIFA World Cup - Combining Result- and Goal-Based Team Ability Parameters. MLSA@PKDD/ECML Pieter Robberechts, Jesse Davis
2018	J	`jnl`	Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model. Data Min. Knowl. Discov. Irma Ravkic, Martin Znidarsic, Jan Ramon, Jesse Davis
2018	J	`jnl`	Guest editors introduction to the special issue for the ECML PKDD 2018 journal track. Mach. Learn. Jesse Davis, Björn Bringmann, Élisa Fromont, Derek Greene
2018	J	`jnl`	Introduction to the special issue for the ECML PKDD 2018 journal track. Data Min. Knowl. Discov. Derek Greene, Björn Bringmann, Élisa Fromont, Jesse Davis
2018	J	`jnl`	Learning From Positive and Unlabeled Data: A Survey. CoRR Jessa Bekker, Jesse Davis
2018	—	`conf`	Learning from Positive and Unlabeled Data under the Selected At Random Assumption. LIDTA@ECML/PKDD Jessa Bekker, Jesse Davis
2018	J	`jnl`	Learning from Positive and Unlabeled Data under the Selected At Random Assumption. CoRR Jessa Bekker, Jesse Davis
2018	A	`conf`	PAC-Reasoning in Relational Domains. UAI Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert
2018	J	`jnl`	PAC-Reasoning in Relational Domains. CoRR Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert
2018	—	`conf`	Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver. DMLE/IOTSTREAMING@PKDD/ECML Pieter Robberechts, Maarten Bosteels, Jesse Davis, Wannes Meert
2018	A*	`conf`	Relational Marginal Problems: Theory and Estimation. AAAI Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert
2018	A*	`conf`	Semi-Supervised Anomaly Detection with an Application to Water Analytics. ICDM Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Baumer, Jesse Davis
2017	A*	`conf`	Induction of Interpretable Possibilistic Logic Theories from Relational Data. IJCAI Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2017	J	`jnl`	Induction of Interpretable Possibilistic Logic Theories from Relational Data. CoRR Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2017	B	`conf`	Positive and Unlabeled Relational Classification Through Label Frequency Estimation. ILP Jessa Bekker, Jesse Davis
2017	A*	`conf`	Predicting Soccer Highlights from Spatio-Temporal Match Event Streams. AAAI Tom Decroos, Vladimir Dzyuba, Jan Van Haaren, Jesse Davis
2017	—	`conf`	Predicting the Potential of Professional Soccer Players. MLSA@PKDD/ECML Ruben Vroonen, Tom Decroos, Jan Van Haaren, Jesse Davis
2017	—	`ed.`	Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2015 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), Porto, Portugal, September 11th, 2015. MLSA@PKDD/ECML Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
2017	—	`ed.`	Proceedings of the 4th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18th, 2017. MLSA@PKDD/ECML Jesse Davis, Mehdi Kaytoue, Albrecht Zimmermann
2017	—	`ed.`	Proceedings of the Workshop on Machine Learning and Data Mining for Sports Analytics 2016 co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, MLSA@PKDD/ECML 2016, Riva del Garda, Italy, September 19, 2016. MLSA@PKDD/ECML Jan Van Haaren, Mehdi Kaytoue, Jesse Davis
2017	J	`jnl`	Relational Marginal Problems: Theory and Estimation. CoRR Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert
2017	—	`conf`	STARSS: A Spatio-Temporal Action Rating System for Soccer. MLSA@PKDD/ECML Tom Decroos, Jan Van Haaren, Vladimir Dzyuba, Jesse Davis
2017	A*	`conf`	Solving Probability Problems in Natural Language. IJCAI Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle, Luc De Raedt
2017	—	`conf`	Transfer Learning for Time Series Anomaly Detection. IAL@PKDD/ECML Vincent Vercruyssen, Wannes Meert, Jesse Davis
2016	—	`conf`	A Comprehensive Comparison of Two MEDLINE Annotators for Disease and Gene Linkage: Sometimes Less is More. IWBBIO Sarah ElShal, Jaak Simm, Adam Arany, Pooya Zakeri, Jesse Davis, Yves Moreau
2016	A*	`conf`	Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques. KDD Jan Van Haaren, Horesh Ben Shitrit, Jesse Davis, Pascal Fua
2016	A*	`conf`	Dynamic Early Stopping for Naive Bayes. IJCAI Aäron Verachtert, Hendrik Blockeel, Jesse Davis
2016	J	`jnl`	Guest editors introduction: special issue on inductive logic programming. Mach. Learn. Jesse Davis, Jan Ramon
2016	A	`conf`	Interpretable Encoding of Densities Using Possibilistic Logic. ECAI Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2016	A*	`conf`	Learning Possibilistic Logic Theories from Default Rules. IJCAI Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2016	J	`jnl`	Learning Possibilistic Logic Theories from Default Rules. CoRR Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2016	A	`conf`	Learning the Structure of Dynamic Hybrid Relational Models. ECAI Davide Nitti, Irma Ravkic, Jesse Davis, Luc De Raedt
2016	J	`jnl`	Lifted generative learning of Markov logic networks. Mach. Learn. Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis
2016	J	`jnl`	Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks. CoRR Jessa Bekker, Arjen Hommersom, Martijn Lappenschaar, Jesse Davis
2016	—	`conf`	Qualitative Spatial Reasoning for Soccer Pass Prediction. MLSA@PKDD/ECML Vincent Vercruyssen, Luc De Raedt, Jesse Davis
2016	J	`jnl`	Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract). CoRR Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2016	C	`conf`	Student perspectives on application of game-based learning within a graduate-level engineering course. FIE Cheryl A. Bodnar, Renee M. Clark, Jesse Davis, Tom Congedo, Daniel Cole
2016	—	`conf`	Topic modeling of biomedical text. BIBM Sarah ElShal, Mithila Mathad, Jaak Simm, Jesse Davis, Yves Moreau
2015	—	`conf`	A Note on the Evaluation of Mutation Prioritization Algorithms. SSCI Dusan Popovic, Jesse Davis, Alejandro Sifrim, Bart De Moor
2015	J	`jnl`	Assessing binary classifiers using only positive and unlabeled data. CoRR Marc Claesen, Jesse Davis, Frank De Smet, Bart De Moor
2015	B	`conf`	Automatically Discovering Offensive Patterns in Soccer Match Data. IDA Jan Van Haaren, Vladimir Dzyuba, Siebe Hannosset, Jesse Davis
2015	B	`conf`	Constructing Markov Logic Networks from First-Order Default Rules. ILP Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2015	J	`jnl`	Encoding Markov Logic Networks in Possibilistic Logic. CoRR Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2015	A	`conf`	Encoding Markov logic networks in Possibilistic Logic. UAI Ondrej Kuzelka, Jesse Davis, Steven Schockaert
2015	B	`ed.`	Inductive Logic Programming - 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers ILP Jesse Davis, Jan Ramon
2015	J	`jnl`	Learning relational dependency networks in hybrid domains. Mach. Learn. Irma Ravkic, Jan Ramon, Jesse Davis
2015	B	`conf`	Mining Hierarchical Pathology Data Using Inductive Logic Programming. AIME Tim Op De Beéck, Arjen Hommersom, Jan Van Haaren, Maarten van der Heijden, Jesse Davis, Peter J. F. Lucas, Lucy Overbeek, Iris Nagtegaal
2015	—	`ch.`	Predicting Adverse Drug Events from Electronic Medical Records. Foundations of Biomedical Knowledge Representation Jesse Davis, Vítor Santos Costa, Peggy L. Peissig, Michael Caldwell, David Page
2015	J	`jnl`	Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case. BMC Bioinform. Dusan Popovic, Alejandro Sifrim, Jesse Davis, Yves Moreau, Bart De Moor
2015	A*	`conf`	TODTLER: Two-Order-Deep Transfer Learning. AAAI Jan Van Haaren, Andrey Kolobov, Jesse Davis
2015	—	`conf`	Tractable Learning for Complex Probability Queries. NIPS Jessa Bekker, Jesse Davis, Arthur Choi, Adnan Darwiche, Guy Van den Broeck
2015	—	`ch.`	Treatment of Disease: The Role of Knowledge Representation for Treatment Selection. Foundations of Biomedical Knowledge Representation Jesse Davis, Luis Enrique Sucar, Felipe Orihuela-Espina
2015	A*	`conf`	Unsupervised Learning of an IS-A Taxonomy from a Limited Domain-Specific Corpus. IJCAI Daniele Alfarone, Jesse Davis
2014	—	`conf`	Automatically Detecting and Rating Product Aspects from Textual Customer Reviews. DMNLP@PKDD/ECML Wouter Bancken, Daniele Alfarone, Jesse Davis
2014	J	`jnl`	Improving Markov network structure learning using decision trees. J. Mach. Learn. Res. Daniel Lowd, Jesse Davis
2014	J	`jnl`	Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. CoRR Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel
2014	—	`conf`	Repairing Inconsistent Taxonomies Using MAP Inference and Rules of Thumb. Web-KRM@CIKM Elie Merhej, Steven Schockaert, Martine De Cock, Marjon Blondeel, Daniele Alfarone, Jesse Davis
2013	A	`conf`	Completeness Results for Lifted Variable Elimination. AISTATS Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel
2013	J	`jnl`	First-Order Decomposition Trees. CoRR Nima Taghipour, Jesse Davis, Hendrik Blockeel
2013	—	`conf`	First-order Decomposition Trees. NIPS Nima Taghipour, Jesse Davis, Hendrik Blockeel
2013	B	`conf`	Generalized Counting for Lifted Variable Elimination. ILP Nima Taghipour, Jesse Davis, Hendrik Blockeel
2013	—	`conf`	Lifted Generative Parameter Learning. StarAI@AAAI Guy Van den Broeck, Wannes Meert, Jesse Davis
2013	J	`jnl`	Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. J. Artif. Intell. Res. Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel
2013	C	`conf`	MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages. ECSQARU Bogdan Moldovan, Ingo Thon, Jesse Davis, Luc De Raedt
2013	—	`conf`	On the Completeness of Lifted Variable Elimination. StarAI@AAAI Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel
2013	—	`ed.`	Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2013 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2013), Prague, Czech Republic, September 27th, 2013. MLSA Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
2012	—	`conf`	A Text Mining Approach as Baseline for QA4MRE'12. CLEF (Online Working Notes/Labs/Workshop) Mathias Verbeke, Jesse Davis
2012	A*	`conf`	Conditioning in First-Order Knowledge Compilation and Lifted Probabilistic Inference. AAAI Guy Van den Broeck, Jesse Davis
2012	A*	`conf`	Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events. ICML Jesse Davis, Vítor Santos Costa, Elizabeth Berg, David Page, Peggy L. Peissig, Michael Caldwell
2012	—	`conf`	Generalized Counting for Lifted Variable Elimination. StarAI@UAI Nima Taghipour, Jesse Davis
2012	—	`conf`	Hybrid Logical Bayesian Networks. ILP (Late Breaking Papers) Irma Ravkic, Jan Ramon, Jesse Davis
2012	A	`conf`	Lifted Variable Elimination with Arbitrary Constraints. AISTATS Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel
2012	J	`jnl`	Lifted Variable Elimination: A Novel Operator and Completeness Results CoRR Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel
2012	A*	`conf`	Markov Network Structure Learning: A Randomized Feature Generation Approach. AAAI Jan Van Haaren, Jesse Davis
2012	B	`conf`	Pairwise Markov Logic. ILP Daan Fierens, Kristian Kersting, Jesse Davis, Jian Chen, Martin Mladenov
2012	J	`jnl`	Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation CoRR Kendrick Boyd, Vítor Santos Costa, Jesse Davis, David Page
2012	A*	`conf`	Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. ICML Kendrick Boyd, Jesse Davis, David Page, Vítor Santos Costa
2011	J	`jnl`	Deep Transfer: A Markov Logic Approach. AI Mag. Jesse Davis, Pedro M. Domingos
2011	A*	`conf`	Lifted Probabilistic Inference by First-Order Knowledge Compilation. IJCAI Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt
2010	A*	`conf`	Bottom-Up Learning of Markov Network Structure. ICML Jesse Davis, Pedro M. Domingos
2010	A*	`conf`	Learning First-Order Horn Clauses from Web Text. EMNLP Stefan Schoenmackers, Jesse Davis, Oren Etzioni, Daniel S. Weld
2010	A*	`conf`	Learning Markov Network Structure with Decision Trees. ICDM Daniel Lowd, Jesse Davis
2009	A*	`conf`	Deep transfer via second-order Markov logic. ICML Jesse Davis, Pedro M. Domingos
2007	A*	`conf`	An integrated approach to feature invention and model construction for drug activity prediction. ICML Jesse Davis, Vítor Santos Costa, Soumya Ray, David Page
2007	A*	`conf`	Change of Representation for Statistical Relational Learning. IJCAI Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vítor Santos Costa
2006	—	`conf`	An Efficient Approximation to Lookahead in Relational Learners. ECML Jan Struyf, Jesse Davis, C. David Page Jr.
2006	A*	`conf`	The relationship between Precision-Recall and ROC curves. ICML Jesse Davis, Mark H. Goadrich
2005	—	`conf`	An Integrated Approach to Learning Bayesian Networks of Rules. ECML Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Vítor Santos Costa
2005	Misc	`conf`	Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. AMIA Elizabeth S. Burnside, Jesse Davis, Vítor Santos Costa, Inês de Castro Dutra, Charles E. Kahn Jr., Jason Fine, David Page
2005	—	`conf`	Mass: modular architecture for sensor systems. IPSN Nicholas Gerard Edmonds, Douglas Stark, Jesse Davis
2005	J	`jnl`	Method Of Interaction In A Modular Architecture For Sensor Systems (Mass). Int. J. Softw. Eng. Knowl. Eng. Jesse Davis, Douglas Stark, Nicholas Gerard Edmonds
2005	A*	`conf`	View Learning for Statistical Relational Learning: With an Application to Mammography. IJCAI Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik
2004	—	`conf`	Friendly Object Tracking and Foreign Object Detection and Localization with an SDAC Wireless Sensor Network. FTDCS Douglas Stark, Jesse Davis