David Page

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 52

Top Venues

CoRR

AMIA

ICML

AIME

Publications

Tatsuki Koga, Kamalika Chaudhuri, David Page
Differentially Private Multi-Site Treatment Effect Estimation. SaTML (2024)
Brad F. Lyles, Brad D. Sion, David Page, Jackson B. Crews, Eric V. McDonald, Mark B. Hausner
Closing the Water Balance with a Precision Small-Scale Field Lysimeter. Sensors 24 (7) (2024)
Alexander Thomson, David Page
Neural Markov Prolog. CoRR (2023)
Tatsuki Koga, Kamalika Chaudhuri, David Page
Differentially Private Multi-Site Treatment Effect Estimation. CoRR (2023)
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. CoRR (2023)
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
Variable importance matching for causal inference. UAI (2023)
Boyao Li, Alexandar J. Thomson, Matthew M. Engelhard, David Page
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. CoRR (2023)
Arezoo Movaghar, David Page, Murray H. Brilliant, Marsha Mailick
Advancing artificial intelligence-assisted pre-screening for fragile X syndrome. BMC Medical Informatics Decis. Mak. 22 (1) (2022)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. AIME (2021)
Xiayuan Huang, Nicholas Tatonetti, Katie Larow, Brooke Delgoffee, John Mayer, David Page, Scott J. Hebbring
E-Pedigrees: a large-scale automatic family pedigree prediction application. Bioinform. 37 (21) (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. CoRR (2021)
Mark Coletti, Alex Fafard, David Page
Troubleshooting deep-learner training data problems using an evolutionary algorithm on Summit. IBM J. Res. Dev. 64 (3/4) (2020)
Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page
Adverse drug reaction discovery from electronic health records with deep neural networks. CHIL (2020)
Finn Kuusisto, Daniel Ng, John W. Steill, Ian Ross, Miron Livny, James A. Thomson, David Page, Ron M. Stewart
KinderMiner Web: a simple web tool for ranking pairwise associations in biomedical applications. F1000Research 9 (2020)
Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. CoRR (2020)
Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
Temporal Poisson Square Root Graphical Models. CoRR (2020)
Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. ICML (2020)
Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. CoRR (2020)
Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page
AutoBlock: A Hands-off Blocking Framework for Entity Matching. WSDM (2020)
Alex Taylor, Ross Kleiman, Scott J. Hebbring, Peggy L. Peissig, David Page
High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records. CoRR (2020)
Finn Kuusisto, Vítor Santos Costa, Zhonggang Hou, James A. Thomson, David Page, Ron M. Stewart
Machine Learning to Predict Developmental Neurotoxicity with High-Throughput Data from 2D Bio-Engineered Tissues. ICMLA (2019)
Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page
High-Throughput Machine Learning from Electronic Health Records. CoRR (2019)
Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CoRR (2019)
Finn Kuusisto, Vítor Santos Costa, Zhonggang Hou, James A. Thomson, David Page, Ron M. Stewart
Machine Learning to Predict Developmental Neurotoxicity with High-throughput Data from 2D Bio-engineered Tissues. CoRR (2019)
Ross Kleiman, David Page
AUCμ: A Performance Metric for Multi-Class Machine Learning Models. ICML (2019)
Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page
AutoBlock: A Hands-off Blocking Framework for Entity Matching. CoRR (2019)
Jonathan C. Badger, Eric LaRose, John Mayer, Fereshteh S. Bashiri, David Page, Peggy L. Peissig
Machine learning for phenotyping opioid overdose events. J. Biomed. Informatics 94 (2019)
Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Molecular Structure Images. CoRR (2019)
Irene Giacomelli, Somesh Jha, Ross Kleiman, David Page, Kyonghwan Yoon
Privacy-Preserving Collaborative Prediction using Random Forests. CoRR (2018)
Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page
Recursive Feature Elimination by Sensitivity Testing. ICMLA (2018)
Shara Feld, Kaitlin M. Woo, Roxana Alexandridis, Yirong Wu, Jie Liu, Peggy L. Peissig, Adedayo A. Onitilo, Jennifer Cox, David Page, Elizabeth S. Burnside
Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants. AMIA (2018)
Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
Temporal Poisson Square Root Graphical Models. ICML (2018)
Aubrey Barnard, David Page
Causal Structure Learning via Temporal Markov Networks. PGM (2018)
Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI (2018)
Xiayuan Huang, Robert C. Elston, John Mayer, Zhan Ye, Yuqi He, David Page, Scott J. Hebbring
Use of Electronic Health Record to Predict Family Relationships for Phenome-wide Research. AMIA (2018)
Yirong Wu, Jun Fan, Peggy L. Peissig, Richard L. Berg, Ahmad Pahlavan Tafti, Jie Yin, Ming Yuan, David Page, Jennifer Cox, Elizabeth S. Burnside
Quantifying predictive capability of electronic health records for the most harmful breast cancer. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2018)
Xiayuan Huang, Robert C. Elston, Guilherme J. Rosa, John Mayer, Zhan Ye, Terrie E. Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring
Applying family analyses to electronic health records to facilitate genetic research. Bioinform. 34 (4) (2018)
Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. CoRR (2018)
Zhaobin Kuang, Sinong Geng, David Page
A Screening Rule for l1-Regularized Ising Model Estimation. NIPS (2017)
Yirong Wu, Elizabeth S. Burnside, Jennifer Cox, Jun Fan, Ming Yuan, Jie Yin, Peggy L. Peissig, Alexander G. Cobian, David Page, Mark W. Craven
Breast Cancer Risk Prediction Using Electronic Health Records. ICHI (2017)
Stéphanie Boué, Thomas E. Exner, Samik Ghosh, Vincenzo Belcastro, Joh Dokler, David Page, Akash R. Boda, Filipe Bonjour, Barry J. Hardy, Patrick Vanscheeuwijck, Julia Hoeng, Manuel C. Peitsch
Supporting evidence-based analysis for modified risk tobacco products through a toxicology data-sharing infrastructure. F1000Research 6 (2017)
Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC (2017)
Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CRI (2017)
Jonathan C. Badger, Eric R. LaRose, Ross Kleiman, Richard L. Berg, James G. Linneman, Richard Hansen, David Page, Peggy L. Peissig
SCCS for Detection of Differences in Brand and Generic Adverse Drug Events. CRI (2017)
Ahmad Pahlavan Tafti, Ehsun Behravesh, Mehdi Assefi, Eric LaRose, Jonathan C. Badger, John Mayer, AnHai Doan, David Page, Peggy L. Peissig
bigNN: An open-source big data toolkit focused on biomedical sentence classification. IEEE BigData (2017)
Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan
Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. AIME (2017)
Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page
Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. KDD (2017)
Dave Kelbe, Devin White, David Page, Kristin Safi, Andrew Hardin, Amy N. Rose
Employing spaceborne multispectral stereo pairs and pedestrian flow modeling to support disaster response activities in urban environments. IGARSS (2017)
Sriraam Natarajan, Vishal Bangera, Tushar Khot, Jose Picado, Anurag Wazalwar, Vítor Santos Costa, David Page, Michael Caldwell
Markov logic networks for adverse drug event extraction from text. Knowl. Inf. Syst. 51 (2) (2017)
Jun Fan, Yirong Wu, Ming Yuan, David Page, Jie Liu, Irene M. Ong, Peggy L. Peissig, Elizabeth S. Burnside
Structure-Leveraged Methods in Breast Cancer Risk Prediction. J. Mach. Learn. Res. 17 (2016)
Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data. IJCAI (2016)
Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
Computational Drug Repositioning Using Continuous Self-Controlled Case Series. KDD (2016)
Jeremy C. Weiss, Finn Kuusisto, Kendrick Boyd, Jie Liu, David Page
Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. AMIA (2015)
Kendrick Boyd, Eric Lantz, David Page
Differential Privacy for Classifier Evaluation. AISec@CCS (2015)
Phillip Odom, Vishal Bangera, Tushar Khot, David Page, Sriraam Natarajan
Extracting Adverse Drug Events from Text Using Human Advice. AIME (2015)
Eric Lantz, Kendrick Boyd, David Page
Subsampled Exponential Mechanism: Differential Privacy in Large Output Spaces. AISec@CCS (2015)
Matthew Fredrikson, Eric Lantz, Somesh Jha, Simon M. Lin, David Page, Thomas Ristenpart
Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing. USENIX Security Symposium (2014)
Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page
Multiple Testing under Dependence via Semiparametric Graphical Models. ICML (2014)
Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page
Learning Heterogeneous Hidden Markov Random Fields. AISTATS (2014)
Yirong Wu, Jie Liu, David Page, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside
Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction. AMIA (2014)
Qiang Zeng, Jignesh M. Patel, David Page
QuickFOIL: Scalable Inductive Logic Programming. Proc. VLDB Endow. 8 (3) (2014)
Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik
Support Vector Machines for Differential Prediction. ECML/PKDD (2) (2014)
Peggy L. Peissig, Vítor Santos Costa, Michael Caldwell, Carla Rottscheit, Richard L. Berg, Eneida A. Mendonça, David Page
Relational machine learning for electronic health record-driven phenotyping. J. Biomed. Informatics 52 (2014)
Jeremy C. Weiss, David Page
Forest-Based Point Process for Event Prediction from Electronic Health Records. ECML/PKDD (3) (2013)
Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside
Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. AMIA (2013)
Jie Liu, David Page
Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models. NIPS (2013)
Chen Zeng, Eric Lantz, Jeffrey F. Naughton, David Page
On Differentially Private Inductive Logic Programming. ILP (2013)
Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa
Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling. ECML/PKDD (3) (2013)
Jie Liu, Elizabeth S. Burnside, Humberto J. Vidaillet, David Page
A collective ranking method for genome-wide association studies. BCB (2012)
Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page
Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies CoRR (2012)
Eric Lantz, Soumya Ray, David Page
Learning Bayesian Network Structure from Correlation-Immune Data CoRR (2012)
Kendrick Boyd, Jesse Davis, David Page, Vítor Santos Costa
Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. ICML (2012)
José Carlos Almeida Santos, Houssam Nassif, David Page, Stephen H. Muggleton, Michael J. E. Sternberg
Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study. BMC Bioinform. 13 (2012)
Jeremy C. Weiss, Sriraam Natarajan, Peggy L. Peissig, Catherine A. McCarty, David Page
Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records. AI Mag. 33 (4) (2012)
Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge CoRR (2012)
Houssam Nassif, Yirong Wu, David Page, Elizabeth S. Burnside
Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women. AMIA (2012)
Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page
Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies. UAI (2012)
Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page
Relational Differential Prediction. ECML/PKDD (1) (2012)
Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page
High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. AISTATS (2012)
Houssam Nassif, Filipe Cunha, Inês C. Moreira, Ricardo Cruz-Correia, Eliana Sousa, David Page, Elizabeth S. Burnside, Inês de Castro Dutra
Extracting BI-RADS features from Portuguese clinical texts. BIBM (2012)
Jeremy C. Weiss, Sriraam Natarajan, Peggy L. Peissig, Catherine A. McCarty, David Page
Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records. IAAI (2012)
Kendrick Boyd, Vítor Santos Costa, Jesse Davis, David Page
Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation CoRR (2012)
Jeremy C. Weiss, Sriraam Natarajan, David Page
Multiplicative Forests for Continuous-Time Processes. NIPS (2012)
David Page, Vítor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell
Identifying Adverse Drug Events by Relational Learning. AAAI (2012)
Jesse Davis, Vítor Santos Costa, Elizabeth Berg, David Page, Peggy L. Peissig, Michael Caldwell
Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events. ICML (2012)
Trevor Walker, Gautam Kunapuli, Noah Larsen, David Page, Jude W. Shavlik
Integrating knowledge capture and supervised learning through a human-computer interface. K-CAP (2011)
Ryan W. Woods, Louis Oliphant, Kazuhiko Shinki, David Page, Jude W. Shavlik, Elizabeth S. Burnside
Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer. J. Digit. Imaging 23 (5) (2010)
Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside
Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. IHI (2010)
Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik
Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. ILP (2010)
Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. ILP (2009)
Lisa Hellerstein, Bernard Rosell, Eric Bach, Soumya Ray, David Page
Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions. J. Mach. Learn. Res. 10 (2009)
Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page
Information Extraction for Clinical Data Mining: A Mammography Case Study. ICDM Workshops (2009)
Sobia Raza, Kevin A. Robertson, Paul A. Lacaze, David Page, Anton J. Enright, Peter Ghazal, Tom C. Freeman
A logic-based diagram of signalling pathways central to macrophage activation. BMC Syst. Biol. 2 (2008)
Sean McIlwain, David Page, Edward L. Huttlin, Michael R. Sussman
Matching isotopic distributions from metabolically labeled samples. ISMB (2008)
Sean McIlwain, David Page, Edward L. Huttlin, Michael R. Sussman
Using dynamic programming to create isotopic distribution maps from mass spectra. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Eric Lantz, Soumya Ray, David Page
Learning Bayesian Network Structure from Correlation-Immune Data. UAI (2007)
Jesse Davis, Vítor Santos Costa, Soumya Ray, David Page
An integrated approach to feature invention and model construction for drug activity prediction. ICML (2007)
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vítor Santos Costa
Change of Representation for Statistical Relational Learning. IJCAI (2007)
Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King
Quantitative pharmacophore models with inductive logic programming. Mach. Learn. 64 (1-3) (2006)
Elizabeth S. Burnside, Jesse Davis, Vítor Santos Costa, Inês de Castro Dutra, Charles E. Kahn Jr., Jason Fine, David Page
Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. AMIA (2005)

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Publication Activity (10 Years)

Top Topics

Top Venues

David Page