Jesse Davis

Orcid: 0000-0002-3748-9263

Affiliations:
  • Katholieke Universiteit Leuven, Department of Computer Science, Belgium
  • University of Washington, Department of Computer Science and Engineering, Seattle, WA, USA


According to our database1, Jesse Davis authored at least 157 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Online presence:

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Bibliography

2024
Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned.
Mach. Learn., September, 2024

TSFuse: automated feature construction for multiple time series data.
Mach. Learn., July, 2024

Time-Shifted Transformers for Driver Identification Using Vehicle Data.
IEEE Trans. Intell. Transp. Syst., May, 2024

Machine learning with a reject option: a survey.
Mach. Learn., May, 2024

Detecting Epileptic Seizures Using Hand-Crafted and Automatically Constructed EEG Features.
IEEE Trans. Biomed. Eng., January, 2024

Computational Approaches to Strategy and Tactics in Sports (Dagstuhl Seminar 24081).
Dagstuhl Reports, 2024

Faster Repeated Evasion Attacks in Tree Ensembles.
CoRR, 2024

Deep Neural Network Benchmarks for Selective Classification.
CoRR, 2024

Biases in Expected Goals Models Confound Finishing Ability.
CoRR, 2024

Semi-Supervised Isolation Forest for Anomaly Detection.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Combining Active Learning and Learning to Reject for Anomaly Detection.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

DMON: A Simple Yet Effective Approach for Argument Structure Learning.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Robustness Verification of Multi-Class Tree Ensembles.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Lifted Reasoning for Combinatorial Counting.
J. Artif. Intell. Res., 2023

A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer.
J. Artif. Intell. Res., 2023

Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidence.
CoRR, 2023

How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection.
CoRR, 2023

A novel reject option applied to sleep stage scoring.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Detecting Evasion Attacks in Deployed Tree Ensembles.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Unsupervised Anomaly Detection with Rejection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

un-xPass: Measuring Soccer Player's Creativity.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Can the Output of a Learned Classification Model Monitor a Person's Functional Recovery Status Post-Total Knee Arthroplasty?
Sensors, 2022

Impact of Gender and Feature Set on Machine-Learning-Based Prediction of Lower-Limb Overuse Injuries Using a Single Trunk-Mounted Accelerometer.
Sensors, 2022

Adversarial Example Detection in Deployed Tree Ensembles.
CoRR, 2022

Multi-domain Active Learning for Semi-supervised Anomaly Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Bitpaths: Compressing Datasets Without Decreasing Predictive Performance.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Towards Data-Driven Volatility Modeling with Variational Autoencoders.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Looking Beyond the Past: Analyzing the Intrinsic Playing Style of Soccer Teams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Systematic Evaluation of CASH Search Strategies for Unsupervised Anomaly Detection.
Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2022

Evaluating Sports Analytics Models: Challenges, Approaches, and Lessons Learned.
Proceedings of the Workshop on AI Evaluation Beyond Metrics co-located with the 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2022), 2022

Elastic Product Quantization for Time Series.
Proceedings of the Discovery Science - 25th International Conference, 2022

Semi-supervised Change Point Detection Using Active Learning.
Proceedings of the Discovery Science - 25th International Conference, 2022

Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Motion Sensor-Based Detection of Outlier Days Supporting Continuous Health Assessment for Single Older Adults.
Sensors, 2021

Evaluation of Automated Hypnogram Analysis on Multi-Scored Polysomnographies.
Frontiers Digit. Health, 2021

Machine Learning in Sports (Dagstuhl Seminar 21411).
Dagstuhl Reports, 2021

Leaving Goals on the Pitch: Evaluating Decision Making in Soccer.
CoRR, 2021

Verifying Tree Ensembles by Reasoning about Potential Instances.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

A Bayesian Approach to In-Game Win Probability in Soccer.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Versatile Verification of Tree Ensembles.
Proceedings of the 38th International Conference on Machine Learning, 2021

Mapping probability word problems to executable representations.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Know Your Limits: Machine Learning with Rejection for Vehicle Engineering.
Proceedings of the Advanced Data Mining and Applications - 17th International Conference, 2021

2020

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, 2020

Learning from positive and unlabeled data: a survey.
Mach. Learn., 2020

Additive Tree Ensembles: Reasoning About Potential Instances.
CoRR, 2020

"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

How Data Availability Affects the Ability to Learn Good xG Models.
Proceedings of the Machine Learning and Data Mining for Sports Analytics, 2020

Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

SoccerMix: Representing Soccer Actions with Mixture Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Class Prior Estimation in Active Positive and Unlabeled Learning.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract).
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Multi-directional Rule Set Learning.
Proceedings of the Discovery Science - 23rd International Conference, 2020

Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
The Open International Soccer Database for machine learning.
Mach. Learn., 2019

Guest editorial: special issue on machine learning for soccer.
Mach. Learn., 2019

A general anomaly detection framework for fleet-based condition monitoring of machines.
CoRR, 2019

Gait Event Detection in Tibial Acceleration Profiles: a Structured Learning Approach.
CoRR, 2019

Who Will Win It? An In-game Win Probability Model for Football.
CoRR, 2019

Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Fast Gradient Boosting Decision Trees with Bit-Level Data Structures.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Player Vectors: Characterizing Soccer Players' Playing Style from Match Event Streams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Beyond the Selected Completely at Random Assumption for Learning from Positive and Unlabeled Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Actions Speak Louder than Goals: Valuing Player Actions in Soccer.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

LazyBum: Decision Tree Learning Using Lazy Propositionalization.
Proceedings of the Inductive Logic Programming - 29th International Conference, 2019

Use of wearable technology to quantify fall risk in psychogeriatric environments: a feasability study.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder.
Proceedings of the Discovery Science - 22nd International Conference, 2019

2018
Guest editors introduction to the special issue for the ECML PKDD 2018 journal track.
Mach. Learn., 2018

Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model.
Data Min. Knowl. Discov., 2018

Introduction to the special issue for the ECML PKDD 2018 journal track.
Data Min. Knowl. Discov., 2018

Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data.
CoRR, 2018

Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

PAC-Reasoning in Relational Domains.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Forecasting the FIFA World Cup - Combining Result- and Goal-Based Team Ability Parameters.
Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018), 2018

Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver.
Proceedings of the ECML PKDD 2018 Workshops, 2018

AMIE: Automatic Monitoring of Indoor Exercises.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Learning from Positive and Unlabeled Data under the Selected At Random Assumption.
Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Semi-Supervised Anomaly Detection with an Application to Water Analytics.
Proceedings of the IEEE International Conference on Data Mining, 2018

Relational Marginal Problems: Theory and Estimation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Predicting the Potential of Professional Soccer Players.
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), 2017

Transfer Learning for Time Series Anomaly Detection.
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), 2017

STARSS: A Spatio-Temporal Action Rating System for Soccer.
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), 2017

Positive and Unlabeled Relational Classification Through Label Frequency Estimation.
Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

Induction of Interpretable Possibilistic Logic Theories from Relational Data.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Solving Probability Problems in Natural Language.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Predicting Soccer Highlights from Spatio-Temporal Match Event Streams.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Lifted generative learning of Markov logic networks.
Mach. Learn., 2016

Guest editors introduction: special issue on inductive logic programming.
Mach. Learn., 2016

Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract).
CoRR, 2016

Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks.
CoRR, 2016

Qualitative Spatial Reasoning for Soccer Pass Prediction.
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, 2016

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

A Comprehensive Comparison of Two MEDLINE Annotators for Disease and Gene Linkage: Sometimes Less is More.
Proceedings of the Bioinformatics and Biomedical Engineering, 2016

Dynamic Early Stopping for Naive Bayes.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning Possibilistic Logic Theories from Default Rules.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Student perspectives on application of game-based learning within a graduate-level engineering course.
Proceedings of the 2016 IEEE Frontiers in Education Conference, 2016

Learning the Structure of Dynamic Hybrid Relational Models.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Interpretable Encoding of Densities Using Possibilistic Logic.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Topic modeling of biomedical text.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015
Learning relational dependency networks in hybrid domains.
Mach. Learn., 2015

Assessing binary classifiers using only positive and unlabeled data.
CoRR, 2015

Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case.
BMC Bioinform., 2015

Encoding Markov logic networks in Possibilistic Logic.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

A Note on the Evaluation of Mutation Prioritization Algorithms.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Tractable Learning for Complex Probability Queries.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Constructing Markov Logic Networks from First-Order Default Rules.
Proceedings of the Inductive Logic Programming - 25th International Conference, 2015

Unsupervised Learning of an IS-A Taxonomy from a Limited Domain-Specific Corpus.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Automatically Discovering Offensive Patterns in Soccer Match Data.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Mining Hierarchical Pathology Data Using Inductive Logic Programming.
Proceedings of the Artificial Intelligence in Medicine, 2015

TODTLER: Two-Order-Deep Transfer Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Treatment of Disease: The Role of Knowledge Representation for Treatment Selection.
Proceedings of the Foundations of Biomedical Knowledge Representation, 2015

Predicting Adverse Drug Events from Electronic Medical Records.
Proceedings of the Foundations of Biomedical Knowledge Representation, 2015

2014
Improving Markov network structure learning using decision trees.
J. Mach. Learn. Res., 2014

Automatically Detecting and Rating Product Aspects from Textual Customer Reviews.
Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014

Repairing Inconsistent Taxonomies Using MAP Inference and Rules of Thumb.
Proceedings of the 5th International Workshop on Web-scale Knowledge Representation Retrieval & Reasoning, 2014

2013
Lifted Variable Elimination: Decoupling the Operators from the Constraint Language.
J. Artif. Intell. Res., 2013

First-order Decomposition Trees.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Generalized Counting for Lifted Variable Elimination.
Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2013

Completeness Results for Lifted Variable Elimination.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

On the Completeness of Lifted Variable Elimination.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

Lifted Generative Parameter Learning.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

2012
Lifted Variable Elimination with Arbitrary Constraints.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Lifted Variable Elimination: A Novel Operator and Completeness Results
CoRR, 2012

Generalized Counting for Lifted Variable Elimination.
Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Hybrid Logical Bayesian Networks.
Proceedings of the Late Breaking Papers of the 22nd International Conference on Inductive Logic Programming, 2012

Pairwise Markov Logic.
Proceedings of the Inductive Logic Programming - 22nd International Conference, 2012

Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events.
Proceedings of the 29th International Conference on Machine Learning, 2012

Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation.
Proceedings of the 29th International Conference on Machine Learning, 2012

A Text Mining Approach as Baseline for QA4MRE'12.
Proceedings of the CLEF 2012 Evaluation Labs and Workshop, 2012

Markov Network Structure Learning: A Randomized Feature Generation Approach.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

Conditioning in First-Order Knowledge Compilation and Lifted Probabilistic Inference.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Deep Transfer: A Markov Logic Approach.
AI Mag., 2011

Lifted Probabilistic Inference by First-Order Knowledge Compilation.
Proceedings of the IJCAI 2011, 2011

2010
Bottom-Up Learning of Markov Network Structure.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Learning Markov Network Structure with Decision Trees.
Proceedings of the ICDM 2010, 2010

Learning First-Order Horn Clauses from Web Text.
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, 2010

2009
Deep transfer via second-order Markov logic.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2007
Change of Representation for Statistical Relational Learning.
Proceedings of the IJCAI 2007, 2007

An integrated approach to feature invention and model construction for drug activity prediction.
Proceedings of the Machine Learning, 2007

2006
The relationship between Precision-Recall and ROC curves.
Proceedings of the Machine Learning, 2006

An Efficient Approximation to Lookahead in Relational Learners.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
Method Of Interaction In A Modular Architecture For Sensor Systems (Mass).
Int. J. Softw. Eng. Knowl. Eng., 2005

Mass: modular architecture for sensor systems.
Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks, 2005

View Learning for Statistical Relational Learning: With an Application to Mammography.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

An Integrated Approach to Learning Bayesian Networks of Rules.
Proceedings of the Machine Learning: ECML 2005, 2005

Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming.
Proceedings of the AMIA 2005, 2005

2004
Friendly Object Tracking and Foreign Object Detection and Localization with an SDAC Wireless Sensor Network.
Proceedings of the 10th IEEE International Workshop on Future Trends of Distributed Computing Systems (FTDCS 2004), 2004


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