David Page

Affiliations:
  • Duke University, Durham, NC, USA
  • University of Wisconsin-Madison, Madison, USA (former)


According to our database1, David Page authored at least 157 papers between 1990 and 2024.

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Bibliography

2024
Closing the Water Balance with a Precision Small-Scale Field Lysimeter.
Sensors, April, 2024

Soft phenotyping for sepsis via EHR time-aware soft clustering.
J. Biomed. Informatics, 2024

MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance.
CoRR, 2024

Differentially Private Multi-Site Treatment Effect Estimation.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

2023
Neural Markov Prolog.
CoRR, 2023

On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models.
CoRR, 2023

From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference.
CoRR, 2023

Variable importance matching for causal inference.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022
Advancing artificial intelligence-assisted pre-screening for fragile X syndrome.
BMC Medical Informatics Decis. Mak., 2022

2021
E-Pedigrees: a large-scale automatic family pedigree prediction application.
Bioinform., 2021

Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach.
Proceedings of the Artificial Intelligence in Medicine, 2021

2020
Troubleshooting deep-learner training data problems using an evolutionary algorithm on Summit.
IBM J. Res. Dev., 2020

KinderMiner Web: a simple web tool for ranking pairwise associations in biomedical applications.
F1000Research, 2020

High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records.
CoRR, 2020

AutoBlock: A Hands-off Blocking Framework for Entity Matching.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods.
Proceedings of the 37th International Conference on Machine Learning, 2020

Adverse drug reaction discovery from electronic health records with deep neural networks.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

2019
Machine learning for phenotyping opioid overdose events.
J. Biomed. Informatics, 2019

Predicting Drug-Drug Interactions from Molecular Structure Images.
CoRR, 2019

High-Throughput Machine Learning from Electronic Health Records.
CoRR, 2019

Machine Learning to Predict Developmental Neurotoxicity with High-Throughput Data from 2D Bio-Engineered Tissues.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

AUCμ: A Performance Metric for Multi-Class Machine Learning Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Privacy-Preserving Collaborative Prediction using Random Forests.
CoRR, 2018

Applying family analyses to electronic health records to facilitate genetic research.
Bioinform., 2018

Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Causal Structure Learning via Temporal Markov Networks.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Quantifying predictive capability of electronic health records for the most harmful breast cancer.
Proceedings of the Medical Imaging 2018: Image Perception, 2018

Recursive Feature Elimination by Sensitivity Testing.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Temporal Poisson Square Root Graphical Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

Use of Electronic Health Record to Predict Family Relationships for Phenome-wide Research.
Proceedings of the AMIA 2018, 2018

Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants.
Proceedings of the AMIA 2018, 2018

2017
Biomedical Informatics.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Markov logic networks for adverse drug event extraction from text.
Knowl. Inf. Syst., 2017

Privacy-Preserving Ridge Regression on Distributed Data.
IACR Cryptol. ePrint Arch., 2017

Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption.
IACR Cryptol. ePrint Arch., 2017

Supporting evidence-based analysis for modified risk tobacco products through a toxicology data-sharing infrastructure.
F1000Research, 2017

A Screening Rule for l1-Regularized Ising Model Estimation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data.
Proceedings of the Machine Learning for Health Care Conference, 2017

Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Employing spaceborne multispectral stereo pairs and pedestrian flow modeling to support disaster response activities in urban environments.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

Breast Cancer Risk Prediction Using Electronic Health Records.
Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017

A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications.
Proceedings of the Summit on Clinical Research Informatics, 2017

SCCS for Detection of Differences in Brand and Generic Adverse Drug Events.
Proceedings of the Summit on Clinical Research Informatics, 2017

bigNN: An open-source big data toolkit focused on biomedical sentence classification.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Identifying Parkinson's Patients: A Functional Gradient Boosting Approach.
Proceedings of the Artificial Intelligence in Medicine, 2017

2016
Relational Learning for Sustainable Health.
Proceedings of the Computational Sustainability, 2016

Structure-Leveraged Methods in Breast Cancer Risk Prediction.
J. Mach. Learn. Res., 2016

Computational Drug Repositioning Using Continuous Self-Controlled Case Series.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
Sparse modeling of spatial environmental variables associated with asthma.
J. Biomed. Informatics, 2015

Big Data in Healthcare: Opportunities and Challenges.
Big Data, 2015

Subsampled Exponential Mechanism: Differential Privacy in Large Output Spaces.
Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security, 2015

Differential Privacy for Classifier Evaluation.
Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security, 2015

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.
Proceedings of the AMIA 2015, 2015

Extracting Adverse Drug Events from Text Using Human Advice.
Proceedings of the Artificial Intelligence in Medicine, 2015

Learning to Reject Sequential Importance Steps for Continuous-Time Bayesian Networks.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

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

2014
QuickFOIL: Scalable Inductive Logic Programming.
Proc. VLDB Endow., 2014

Relational machine learning for electronic health record-driven phenotyping.
J. Biomed. Informatics, 2014

Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.
Proceedings of the 23rd USENIX Security Symposium, San Diego, CA, USA, August 20-22, 2014., 2014

Support Vector Machines for Differential Prediction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Multiple Testing under Dependence via Semiparametric Graphical Models.
Proceedings of the 31th International Conference on Machine Learning, 2014

Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction.
Proceedings of the AMIA 2014, 2014

Learning Heterogeneous Hidden Markov Random Fields.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Forest-Based Point Process for Event Prediction from Electronic Health Records.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Erratum: Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models.
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

On Differentially Private Inductive Logic Programming.
Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms.
Proceedings of the AMIA 2013, 2013

Learning When to Reject an Importance Sample.
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

2012
High-Dimensional Structured Feature Screening Using Binary Markov Random Fields.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.
BMC Bioinform., 2012

Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records.
AI Mag., 2012

Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Relational Differential Prediction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Multiplicative Forests for Continuous-Time Processes.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 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

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records.
Proceedings of the Twenty-Fourth Conference on Innovative Applications of Artificial Intelligence, 2012

Predicting atrial fibrillation and flutter using Electronic Health Records.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Extracting BI-RADS features from Portuguese clinical texts.
Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012

A collective ranking method for genome-wide association studies.
Proceedings of the ACM International Conference on Bioinformatics, 2012

Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women.
Proceedings of the AMIA 2012, 2012

Identifying Adverse Drug Events by Relational Learning.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Integrating knowledge capture and supervised learning through a human-computer interface.
Proceedings of the 6th International Conference on Knowledge Capture (K-CAP 2011), 2011

2010
Biomedical Informatics.
Proceedings of the Encyclopedia of Machine Learning, 2010

Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer.
J. Digit. Imaging, 2010

Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge.
Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming.
Proceedings of the ACM International Health Informatics Symposium, 2010

2009
Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions.
J. Mach. Learn. Res., 2009

An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.
Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Information Extraction for Clinical Data Mining: A Mammography Case Study.
Proceedings of the ICDM Workshops 2009, 2009

2008
A logic-based diagram of signalling pathways central to macrophage activation.
BMC Syst. Biol., 2008

Matching isotopic distributions from metabolically labeled samples.
Proceedings of the Proceedings 16th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2008

CLP(<i>BN</i>): Constraint Logic Programming for Probabilistic Knowledge.
Proceedings of the Probabilistic Inductive Logic Programming - Theory and Applications, 2008

2007
Learning Bayesian Network Structure from Correlation-Immune Data.
Proceedings of the UAI 2007, 2007

Using dynamic programming to create isotopic distribution maps from mass spectra.
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 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
Randomised restarted search in ILP.
Mach. Learn., 2006

Quantitative pharmacophore models with inductive logic programming.
Mach. Learn., 2006

Experimental Design of Time Series Data for Learning from Dynamic Bayesian Networks.
Proceedings of the Biocomputing 2006, 2006

ILP Through Propositionalization and Stochastic k-Term DNF Learning.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

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

2005
Predicting cancer susceptibility from single-nucleotide polymorphism data: a case study in multiple myeloma.
Proceedings of the 5th international workshop on Bioinformatics, 2005

A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment.
Proceedings of the Inductive Logic Programming, 15th International Conference, 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

Why skewing works: learning difficult Boolean functions with greedy tree learners.
Proceedings of the Machine Learning, 2005

Generalized skewing for functions with continuous and nominal attributes.
Proceedings of the Machine Learning, 2005

Multi-instance tree learning.
Proceedings of the Machine Learning, 2005

Mode Directed Path Finding.
Proceedings of the Machine Learning: ECML 2005, 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
Using Machine Learning to Design and Interpret Gene-Expression Microarrays.
AI Mag., 2004

A Monte Carlo Study of Randomised Restarted Search in ILP.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

Sequential skewing: an improved skewing algorithm.
Proceedings of the Machine Learning, 2004

2003
Biological applications of multi-relational data mining.
SIGKDD Explor., 2003

ILP: A Short Look Back and a Longer Look Forward.
J. Mach. Learn. Res., 2003

A Parallel Inductive Logic Programming Data Mining System for Drug Discovery.
Int. J. Comput. Their Appl., 2003

A Bayesian Network Approach to Operon Prediction.
Bioinform., 2003

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge.
Proceedings of the UAI '03, 2003

The Role of Declarative Languages in Mining Biological Databases.
Proceedings of the Practical Aspects of Declarative Languages, 5th International Symposium, 2003

Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction.
Proceedings of the IJCAI-03, 2003

Toward Automatic Management of Embarrassingly Parallel Applications.
Proceedings of the Euro-Par 2003. Parallel Processing, 2003

Accelerating the Drug Design Process through Parallel Inductive Logic Programming Data Mining.
Proceedings of the 2nd IEEE Computer Society Bioinformatics Conference, 2003

2002
KDD Cup 2001 Report.
SIGKDD Explor., 2002

Modelling regulatory pathways in E. coli from time series expression profiles.
Proceedings of the Tenth International Conference on Intelligent Systems for Molecular Biology, 2002

Lattice-Search Runtime Distributions May Be Heavy-Tailed.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

An Empirical Evaluation of Bagging in Inductive Logic Programming.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

2001
Guest Editor's Introduction.
Int. J. Comput. Their Appl., 2001

Multiple Instance Regression.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

An Approach to Parallel Data Mining for Pharmacophore Discovery.
Proceedings of the ISCA 10th International Conference on Intelligent Systems, 2001

2000
Parallel data mining for pharmacophore discovery.
Proceedings of the IEEE International Conference on Systems, 2000

A Probabilistic Learning Approach to Whole-Genome Operon Prediction.
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, 2000

Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

ILP: Just Do It.
Proceedings of the Computational Logic, 2000

1999
Guest Editors' Introduction: Inductive Logic Programming.
J. Log. Program., 1999

1998
Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL.
Mach. Learn., 1998

The Design of the Client User Interface for a Meta Object-Oriented CASE Tool.
Proceedings of the TOOLS 1998: 28th International Conference on Technology of Object-Oriented Languages and Systems, 1998

1997
Guest Editors' Introduction.
Mach. Learn., 1997

1996
Meta-Modelling and Methodology Support in Object-Oriented CASE Tools.
Proceedings of the 1996 International Conference on Object Oriented Information Systems, 1996

An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming.
Proceedings of the Inductive Logic Programming, 6th International Workshop, 1996

1995
Polynomial Learnability and Inductive Logic Programming: Methods and Results.
New Gener. Comput., 1995

Template Generator for a Methodology Independent Object-Oriented Case Tool.
Proceedings of the 1995 International Conference on Object Oriented Information Systems, 1995

A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees.
Proceedings of the Machine Intelligence 15, 1995

Building Theories into Instantiation.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

1994
Prefix Grammars: An Alternative Characterization of the Regular Languages.
Inf. Process. Lett., 1994

An Abstract Definition of Graphical Notations for Object-Oriented Information Systems.
Proceedings of the 1994 International Conference on Object Oriented Information Systems, 1994

Development of an Intelligent Object-Oriented CASE Tool.
Proceedings of the 1994 International Conference on Object Oriented Information Systems, 1994

1993
Object-oriented development of expert systems.
Proceedings of the First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 1993

Learnability in Inductive Logic Programrning: Some Basic Results and Techniques.
Proceedings of the 11th National Conference on Artificial Intelligence. Washington, 1993

1991
Generalizing Atoms in Constraint Logic.
Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning (KR'91). Cambridge, 1991

Learning Constrained Atoms.
Proceedings of the Eighth International Workshop (ML91), 1991

1990
Generalization with Taxonomic Information.
Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, USA, July 29, 1990


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