Jesse Davis

发表

Fast Gradient Boosting Decision Trees with Bit-Level Data Structures

Wannes Meert, Laurens Devos, Jesse Davis, 2019, ECML/PKDD.

Transfer Learning for Time Series Anomaly Detection

Vincent Vercruyssen, Wannes Meert, Jesse Davis, 2017, IAL@PKDD/ECML.

Predicting the final league tables of domestic football leagues

Jesse Davis, Jan Van Haaren, 2015 .

Choke or Shine? Quantifying Soccer Players' Abilities to Perform Under Mental Pressure

Jesse Davis, Lotte Bransen, Jan Van Haaren, 2019 .

MASS: modular architecture for sensor systems

Jesse Davis, Nicholas Gerard Edmonds, Douglas Stark, 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

A Note on the Evaluation of Mutation Prioritization Algorithms

Bart De Moor, Jesse Davis, Dusan Popovic, 2015, 2015 IEEE Symposium Series on Computational Intelligence.

Wireless sensor network applications and impacts in MOUT

Jesse Davis, Nina M. Berry, N. Berry, 2004, SPIE Defense + Commercial Sensing.

MLSA15 - Proceedings of "Machine Learning and Data Mining for Sports Analytics", workshop @ ECML/PKDD 2015

Jesse Davis, Albrecht Zimmermann, Jan Van Haaren, 2016 .

Stratified knowledge bases as interpretable probabilistic models

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2016 .

Accelerometer Based Data Can Provide a Better Estimate of Cumulative Load During Running Compared to GPS Based Parameters

Jesse Davis, Benedicte Vanwanseele, Tim Op De Beéck, 2020, Frontiers in Sports and Active Living.

Topic modeling of biomedical text

Jesse Davis, Yves Moreau, Jaak Simm, 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A Text Mining Approach as Baseline for QA4MRE'12

Jesse Davis, Mathias Verbeke, 2012, CLEF.

A Machine Learning Approach to Estimate Hip and Knee Joint Loading Using a Mobile Phone-Embedded IMU

Ilse Jonkers, Jesse Davis, Annick Timmermans, 2020, Frontiers in Bioengineering and Biotechnology.

Pairwise Markov Logic

Kristian Kersting, Jesse Davis, Jian Chen, 2012, ILP.

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

Jesse Davis, Jessa Bekker, Jesse Davis, 2018, ECML/PKDD.

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques

Pascal Fua, Jesse Davis, Jan Van Haaren, 2016, KDD.

Tightly Integrating Relational Learning and Multiple-Instance Regression for Real-Valued Drug Activity Prediction

Jesse Davis, Soumya Ray, David L. Page, 2007 .

Machine Learning and Data Mining for Sports Analytics

Guy Van den Broeck, Wannes Meert, Jesse Davis, 2013, Lecture Notes in Computer Science.

A general anomaly detection framework for fleet-based condition monitoring of machines pdf

Wannes Meert, Konstantinos Gryllias, Jesse Davis, 2019, Mechanical Systems and Signal Processing.

Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver

Wannes Meert, Jesse Davis, Pieter Robberechts, 2018, DMLE/IOTSTREAMING@PKDD/ECML.

Change of Representation for Statistical Relational Learning

Jesse Davis, David Page, Vítor Santos Costa, 2007, IJCAI.

Solving Probability Problems in Natural Language

Luc De Raedt, Jesse Davis, Anton Dries, 2017, IJCAI.

Dynamic Early Stopping for Naive Bayes

Jesse Davis, Hendrik Blockeel, Aäron Verachtert, 2016, IJCAI.

DESCRIPTION AND ANALYSIS OF A FLEXIBLE HARDWARE ARCHITECTURE FOR EVENT-DRIVEN DISTRIBUTED SENSOR NETWORK NODES

Jesse Davis, Nina M. Berry, Ron Kyker, 2003 .

Induction of Interpretable Possibilistic Logic Theories from Relational Data

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2017, IJCAI.

Predicting Adverse Drug Events from Electronic Medical Records

Jesse Davis, David Page, Vítor Santos Costa, 2015, Foundations of Biomedical Knowledge Representation.

Wireless sensor systems for sense/decide/act/communicate.

Jesse Davis, Ronald C. Pate, Ronald D. Kyker, 2003 .

Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project

Luc De Raedt, Alessandro Saffiotti, Deniz Yuret, 2017 .

Learning the Structure of Dynamic Hybrid Relational Models

Luc De Raedt, Jesse Davis, Irma Ravkic, 2016, ECAI.

Predicting the Potential of Professional Soccer Players

Jesse Davis, Jan Van Haaren, Ruben Vroonen, 2017, MLSA@PKDD/ECML.

Establishing Identity Equivalence in Multi-Relational Domains

Jesse Davis, Vítor Santos Costa, Inês Dutra, 2005 .

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

Jesse Davis, Jessa Bekker, Jesse Davis, 2018, AAAI.

Monitoring the crus for physical therapy

Wannes Meert, Jesse Davis, Benedicte Vanwanseele, 2014 .

Towards automatic monitoring of activities using contactless sensors

Bart Vanrumste, Jesse Davis, Toon Goedemé, 2011 .

Class Prior Estimation in Active Positive and Unlabeled Learning

Vincent Vercruyssen, Jesse Davis, Lorenzo Perini, 2020, IJCAI.

Hybrid Logical Bayesian Networks

Jesse Davis, Jan Ramon, Irma Ravkic, 2012, ILP.

Biomedical text mining for disease-gene discovery (poster)

Jesse Davis, Yves Moreau, Sarah Elshal, 2013 .

Semi-Supervised Anomaly Detection with an Application to Water Analytics

Vincent Vercruyssen, Wannes Meert, Jesse Davis, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages

Luc De Raedt, Jesse Davis, Ingo Thon, 2013, ECSQARU.

Learning First-Order Horn Clauses from Web Text

Oren Etzioni, Jesse Davis, Daniel S. Weld, 2010, EMNLP.

Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption

Jesse Davis, Ondrej Kuzelka, Jesse Davis, 2019, UAI.

Biomedical Text Mining for Disease Gene Discovery

Jesse Davis, Yves Moreau, Sarah Elshal, 2012 .

Modular Architecture for Sensor Systems (MASS) : description, analysis, simulation, and implementation.

Jesse Davis, Nicholas Edmonds, Douglas P. Stark, 2004 .

Improving Markov network structure learning using decision trees

Jesse Davis, Daniel Lowd, Daniel Lowd, 2014, J. Mach. Learn. Res..

Additive Tree Ensembles: Reasoning About Potential Instances pdf

Wannes Meert, Laurens Devos, Jesse Davis, 2020, ArXiv.

First-order Decomposition Trees

Jesse Davis, Hendrik Blockeel, Nima Taghipour, 2013, NIPS.

Forecasting the FIFA World Cup - Combining Result- and goal-based Team Ability Parameters

Jesse Davis, Pieter Robberechts, Jesse Davis, 2018, MLSA@PKDD/ECML.

Generalized Counting for Lifted Variable Elimination

Jesse Davis, Hendrik Blockeel, Nima Taghipour, 2012, ILP.

Unsupervised Learning of an IS-A Taxonomy from a Limited Domain-Specific Corpus

Jesse Davis, Daniele Alfarone, 2015, IJCAI.

An Efficient Approximation to Lookahead in Relational Learners

Jesse Davis, David Page, Jan Struyf, 2006, ECML.

Part 5: Containment Measures for Slope Hazards: Evaluation of the Effectiveness of Catchment Ditches Along Ohio Roadways

Jesse Davis, Abdul Shakoor, 2005 .

Assessing binary classifiers using only positive and unlabeled data pdf

Bart De Moor, Jesse Davis, Marc Claesen, 2015, ArXiv.

Strategy discovery in professional soccer match data

Jesse Davis, Jan Van Haaren, Siebe Hannosset, 2016, KDD 2016.

Constructing Markov Logic Networks from First-Order Default Rules

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2015, ILP.

The 2017 Soccer Prediction Challenge

Jesse Davis, Werner Dubitzky, Daniel Berrar, 2017 .

Discovering latent structure in clinical databases

Jesse Davis, Vítor Santos Costa, Peggy L. Peissig, 2011, NIPS 2011.

Learning relational dependency networks in hybrid domains

Jesse Davis, Jan Ramon, Irma Ravkic, 2015, Machine Learning.

A Fleet-Wide Approach for Condition Monitoring of Similar Machines Using Time-Series Clustering

Wannes Meert, Konstantinos Gryllias, Jesse Davis, 2018, Applied Condition Monitoring.

Bottom-Up Learning of Markov Network Structure

Pedro M. Domingos, Jesse Davis, Jesse Davis, 2010, ICML.

Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion

Wannes Meert, Jesse Davis, Benedicte Vanwanseele, 2018, KDD.

The Open International Soccer Database for machine learning

Jesse Davis, Werner Dubitzky, Daniel Berrar, 2018, Machine Learning.

Systems assessment of water savings impact of controlled environment agriculture (CEA) utilizing wirelessly networked Sense•Decide•Act•Communicate (SDAC) systems.

Carlos Aguirre, Jesse Davis, Phillip I. Pohl, 2005 .

Encoding Markov logic networks in Possibilistic Logic

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2015, UAI.

Automatically Detecting and Rating Product Aspects from Textual Customer Reviews

Jesse Davis, Daniele Alfarone, Wouter Bancken, 2014, DMNLP@PKDD/ECML.

PAC-Reasoning in Relational Domains pdf

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2018, UAI.

Predicting Soccer Highlights from Spatio-Temporal Match Event Streams

Jesse Davis, Jan Van Haaren, Tom Decroos, 2017, AAAI.

A modular architecture for wireless sensor network nodes

Jesse Davis, Nina M. Berry, 2004, SPIE Defense + Commercial Sensing.

Ordering-based search for tractable Bayesian networks

Guy Van den Broeck, Jesse Davis, Jessa Bekker, 2015 .

Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events

Jesse Davis, David Page, Vítor Santos Costa, 2012, ICML.

Mid-South Megaregion Freight Planning Meeting and Workshop; Memphis, Tennessee; December 8th, 2016

Jesse Davis, Terry Regan, 2017 .

Treatment of Disease: The Role of Knowledge Representation for Treatment Selection

Jesse Davis, Luis Enrique Sucar, Felipe Orihuela-Espina, 2015, Foundations of Biomedical Knowledge Representation.

Multi-directional Rule Set Learning

Jesse Davis, Hendrik Blockeel, Jonas Schouterden, 2020, DS.

Qualitative Spatial Reasoning for Soccer Pass Prediction

Luc De Raedt, Vincent Vercruyssen, Jesse Davis, 2016, MLSA@PKDD/ECML.

Scalable Uncertainty Management: 14th International Conference, SUM 2020, Bozen-Bolzano, Italy, September 23–25, 2020, Proceedings

Jesse Davis, Karim Tabia, K. Tabia, 2020, SUM.

Predicting gait retraining strategies for knee osteoarthritis

Wannes Meert, Jesse Davis, Benedicte Vanwanseele, 2015 .

Who Will Win It? An In-game Win Probability Model for Football pdf

Jesse Davis, Jan Van Haaren, Pieter Robberechts, 2019, ArXiv.

Lifted Variable Elimination: Decoupling the Operators from the Constraint Language pdf

Jesse Davis, Hendrik Blockeel, Nima Taghipour, 2013, J. Artif. Intell. Res..

Actions Speak Louder than Goals: Valuing Player Actions in Soccer

Jesse Davis, Lotte Bransen, Jan Van Haaren, 2018, KDD.

STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2020, ECAI.

Guest editorial: special issue on machine learning for soccer

Jesse Davis, Werner Dubitzky, Daniel Berrar, 2018, Machine Learning.

Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption

Jesse Davis, Kaja Zupanc, Jesse Davis, 2018, WWW.

"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series

Vincent Vercruyssen, Wannes Meert, Jesse Davis, 2020, SDM.

Repairing Inconsistent Taxonomies Using MAP Inference and Rules of Thumb

Martine De Cock, Steven Schockaert, Jesse Davis, 2014, Web-KR '14.

Production of primary mirror segments for the Giant Magellan Telescope

Warren B. Davison, Hubert M. Martin, James H. Burge, 2014, Astronomical Telescopes and Instrumentation.

Learning Markov Network Structure with Decision Trees

Jesse Davis, Daniel Lowd, Daniel Lowd, 2010, 2010 IEEE International Conference on Data Mining.

Improving performance of the eXtasy model by hierarchical sampling

Jesse Davis, Bart De Moor, Yves Moreau, 2014 .

Guest editors introduction: special issue on inductive logic programming

Jesse Davis, Jan Ramon, 2016, Machine Learning.

Introduction to the special issue for the ECML PKDD 2018 journal track

Derek Greene, Jesse Davis, Élisa Fromont, 2018, Data Mining and Knowledge Discovery.

Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks pdf

Jesse Davis, Arjen Hommersom, Jessa Bekker, 2016, ArXiv.

Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection

Vincent Vercruyssen, Wannes Meert, Jesse Davis, 2020, AAAI.

Learning Possibilistic Logic Theories from Default Rules pdf

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2016, IJCAI.

Revised Selected Papers of the 24th International Conference on Inductive Logic Programming - Volume 9046

Jesse Davis, Jan Ramon, 2014 .

STARSS: A Spatio-Temporal Action Rating System for Soccer

Jesse Davis, Jan Van Haaren, Tom Decroos, 2017, MLSA@PKDD/ECML.

Open International Soccer Database

Jesse Davis, Werner Dubitzky, Daniel Berrar, 2017 .

Learning from positive and unlabeled data: a survey

Jesse Davis, Jessa Bekker, Jesse Davis, 2018, Machine Learning.

An integrated approach to feature invention and model construction for drug activity prediction

Jesse Davis, David Page, Vítor Santos Costa, 2007, ICML '07.

An Integrated Approach to Feature Construction and Model Building for Drug Activity Prediction

Jesse Davis, Vítor Santos Costa, Soumya Ray, 2007, ICML 2007.

Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data

Jesse Davis, Jan Van Haaren, Tom Decroos, 2018, KDD.

Markov Network Structure Learning: A Randomized Feature Generation Approach

Jesse Davis, Jan Van Haaren, Jesse Davis, 2012, AAAI.

Method for module interaction in a Modular Architecture for Sensor Systems (MASS).

Jesse Davis, Nicholas Edmonds, Douglas P. Stark, 2005 .

Characterizing Soccer Players' Playing Style from Match Event Streams

Jesse Davis, Tom Decroos, Aron Geerts, 2019, MLSA@PKDD/ECML.

Deep transfer via second-order Markov logic

Pedro M. Domingos, Jesse Davis, Jesse Davis, 2009, ICML '09.

Lifted Variable Elimination with Arbitrary Constraints

Jesse Davis, Hendrik Blockeel, Nima Taghipour, 2012, AISTATS.

VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract)

Jesse Davis, Lotte Bransen, Jan Van Haaren, 2020, IJCAI.

Relational Marginal Problems: Theory and Estimation

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2017, AAAI.

Inductive Logic Programming: 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers

Jesse Davis, Jan Ramon, 2016 .

Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods

Jesse Davis, Nick Vannieuwenhoven, Tom Decroos, 2019, PKDD/ECML Workshops.

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

Jesse Davis, Jessa Bekker, Jesse Davis, 2018, LIDTA@ECML/PKDD.

Sense, decide, act, communicate (SDAC): next generation of smart sensor systems

Jesse Davis, Teresa H. Ko, Ron Kyker, 2004, SPIE Defense + Commercial Sensing.

Lifted inference for probabilistic programming

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2012, NIPS 2012.

Machine learning as a tool to predict impact loading during over-ground distance running

Jesse Davis, Dirk De Clercq, Joeri Gerlo, 2019 .

TODTLER: Two-Order-Deep Transfer Learning

Jesse Davis, Andrey Kolobov, Jan Van Haaren, 2015, AAAI.

Deep Transfer: A Markov Logic Approach

Pedro M. Domingos, Jesse Davis, 2011, AI Mag..

Guest editors introduction to the special issue for the ECML PKDD 2018 journal track

Derek Greene, Jesse Davis, Élisa Fromont, 2018, Machine Learning.

MLSA13 - Proceedings of "Machine Learning and Data Mining for Sports Analytics", workshop @ ECML/PKDD 2013

Jesse Davis, Albrecht Zimmermann, 2013 .

Automatically Discovering Offensive Patterns in Soccer Match Data

Jesse Davis, Jan Van Haaren, Vladimir Dzyuba, 2015, IDA.

View Learning for Statistical Relational Learning: With an Application to Mammography

Jesse Davis, Raghu Ramakrishnan, David Page, 2005, IJCAI.

Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract) pdf

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2016, ArXiv.

Using Machine Learning and Alternative Data to Predict Movements in Market Risk

Jesse Davis, Thomas Dierckx, Wim Schoutens, 2020, 2009.07947.

Architectural and operational tradeoffs in wireless sensor networks

Jesse Davis, Nina M. Berry, 2004, SPIE Defense + Commercial Sensing.

LazyBum: Decision tree learning using lazy propositionalization pdf

Jesse Davis, Hendrik Blockeel, Jonas Schouterden, 2019, ILP.

Interpretable Encoding of Densities Using Possibilistic Logic

Steven Schockaert, Jesse Davis, Ondrej Kuzelka, 2016, ECAI.

Topic modeling of biomedical text: from words and topics to disease and gene links

Jesse Davis, Jaak Simm, Sarah Elshal, 2016 .

Learning a New View of a Database: With an Application to Mammography

Jesse Davis, Raghu Ramakrishnan, Vítor Santos Costa, 2007 .

Student perspectives on application of game-based learning within a graduate-level engineering course

Jesse Davis, Renee M. Clark, Cheryl A. Bodnar, 2016, 2016 IEEE Frontiers in Education Conference (FIE).

Assessing the Performances of Soccer Players

Jesse Davis, Lotte Bransen, Jan Van Haaren, 2019 .

Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation

Jesse Davis, David Page, Vítor Santos Costa, 2012, ICML.

Positive and Unlabeled Relational Classification Through Label Frequency Estimation

Jesse Davis, Jessa Bekker, 2017, ILP.

Versatile Verification of Tree Ensembles pdf

Wannes Meert, Laurens Devos, Jesse Davis, 2020, ArXiv.

Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case

Bart De Moor, Jesse Davis, Yves Moreau, 2015, BMC Bioinformatics.

A Comprehensive Comparison of Two MEDLINE Annotators for Disease and Gene Linkage: Sometimes Less is More

Jesse Davis, Yves Moreau, Jaak Simm, 2016, IWBBIO.

Friendly object tracking and foreign object detection and localization with an SDAC wireless sensor network

Jesse Davis, Douglas Stark, Jesse M. Davis, 2004, Proceedings. 10th IEEE International Workshop on Future Trends of Distributed Computing Systems, 2004. FTDCS 2004..

Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model

Jesse Davis, Jan Ramon, Martin Znidarsic, 2018, Data Mining and Knowledge Discovery.

Mining Hierarchical Pathology Data Using Inductive Logic Programming

Peter Lucas, Jesse Davis, Arjen Hommersom, 2015, AIME.

AMIE: Automatic Monitoring of Indoor Exercises

Jesse Davis, Benedicte Vanwanseele, Kurt Schütte, 2018, ECML/PKDD.

Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach.

Jesse Davis, Dirk De Clercq, Joeri Gerlo, 2020, Gait & posture.

Wannes Meert, Konstantinos Gryllias, Jesse Davis, 2020 .

An Integrated Approach to Learning Bayesian Networks of Rules

Jesse Davis, David Page, Vítor Santos Costa, 2005, ECML.

Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming