David Page - RankMe

151 papers A* 22A 11B 14C 4Misc 7Journal 52Unranked 37

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Cosmos World Foundation Model Platform for Physical AI. CoRR Niket Agarwal, Arslan Ali, Maciej Bala, Yogesh Balaji, Erik Barker, Tiffany Cai, Prithvijit Chattopadhyay, Yongxin Chen, Yin Cui, Yifan Ding, Daniel Dworakowski, Jiaojiao Fan, Michele Fenzi, Francesco Ferroni, Sanja Fidler, Dieter Fox, Songwei Ge, Yunhao Ge, Jinwei Gu, Siddharth Gururani, Ethan He, Jiahui Huang, Jacob Samuel Huffman, Pooya Jannaty, Jingyi Jin, Seung Wook Kim, Gergely Klár, Grace Lam, Shiyi Lan, Laura Leal-Taixé, Anqi Li, Zhaoshuo Li, Chen-Hsuan Lin, Tsung-Yi Lin, Huan Ling, Ming-Yu Liu, Xian Liu, Alice Luo, Qianli Ma, Hanzi Mao, Kaichun Mo, Arsalan Mousavian, Seungjun Nah, Sriharsha Niverty, David Page, Despoina Paschalidou, Zeeshan Patel, Lindsey Pavao, Morteza Ramezanali, Fitsum Reda, Xiaowei Ren, Vasanth Rao Naik Sabavat, Ed Schmerling, Stella Shi, Bartosz Stefaniak, Shitao Tang, Lyne Tchapmi, Przemek Tredak, Wei-Cheng Tseng, Jibin Varghese, Hao Wang, Haoxiang Wang, Heng Wang, Ting-Chun Wang, Fangyin Wei, Xinyue Wei, Jay Zhangjie Wu, Jiashu Xu, Wei Yang, Yen-Chen Lin, Xiaohui Zeng, Yu Zeng, Jing Zhang, Qinsheng Zhang, Yuxuan Zhang, Qingqing Zhao, Artur Zólkowski
2025	J	`jnl`	MPAC: a computational framework for inferring pathway activities from multi-omic data. Bioinform. Peng Liu, David Page, Paul Ahlquist, Irene M. Ong, Anthony Gitter
2025	J	`jnl`	Probably Approximately Correct Causal Discovery. CoRR Mian Wei, Somesh Jha, David Page
2025	—	`conf`	Temporal Inverse Probability Weighting for Causal Discovery in Controlled Before-After Studies: Discovering ADEs in Generics. CLeaR Aubrey Barnard, Peggy L. Peissig, David Page
2025	J	`jnl`	Training Video Foundation Models with NVIDIA NeMo. CoRR Zeeshan Patel, Ethan He, Parth Mannan, Xiaowei Ren, Ryan Wolf, Niket Agarwal, Jacob Samuel Huffman, Zhuoyao Wang, Carl Wang, Jack Chang, Yan Bai, Tommy Huang, Linnan Wang, Sahil Jain, Shanmugam Ramasamy, Joseph Jennings, Ekaterina Sirazitdinova, Oleg Sudakov, Mingyuan Ma, Bobby Chen, Forrest Lin, Hao Wang, Vasanth Rao Naik Sabavat, Sriharsha Niverty, Rong Ou, Pallab Bhattacharya, David Page, Nima Tajbakhsh, Ashwath Aithal
2024	J	`jnl`	Closing the Water Balance with a Precision Small-Scale Field Lysimeter. Sensors Brad F. Lyles, Brad D. Sion, David Page, Jackson B. Crews, Eric V. McDonald, Mark B. Hausner
2024	—	`conf`	Differentially Private Multi-Site Treatment Effect Estimation. SaTML Tatsuki Koga, Kamalika Chaudhuri, David Page
2024	—	`conf`	MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. MLHC Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page
2024	J	`jnl`	MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. CoRR Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page
2024	A*	`conf`	On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. NeurIPS Boyao Li, Alexander Thomson, Houssam Nassif, Matthew Engelhard, David Page
2023	J	`jnl`	Differentially Private Multi-Site Treatment Effect Estimation. CoRR Tatsuki Koga, Kamalika Chaudhuri, David Page
2023	J	`jnl`	From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. CoRR Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
2023	J	`jnl`	Neural Markov Prolog. CoRR Alexander Thomson, David Page
2023	J	`jnl`	On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. CoRR Boyao Li, Alexandar J. Thomson, Matthew M. Engelhard, David Page
2023	A	`conf`	Variable importance matching for causal inference. UAI Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
2022	J	`jnl`	Advancing artificial intelligence-assisted pre-screening for fragile X syndrome. BMC Medical Informatics Decis. Mak. Arezoo Movaghar, David Page, Murray H. Brilliant, Marsha Mailick
2021	J	`jnl`	E-Pedigrees: a large-scale automatic family pedigree prediction application. Bioinform. Xiayuan Huang, Nicholas P. Tatonetti, Katie Larow, Brooke Delgoffe, John Mayer, David Page, Scott J. Hebbring
2021	B	`conf`	Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. AIME Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
2021	J	`jnl`	Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. CoRR Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
2020	—	`conf`	Adverse drug reaction discovery from electronic health records with deep neural networks. CHIL Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page
2020	A	`conf`	AutoBlock: A Hands-off Blocking Framework for Entity Matching. WSDM Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page
2020	A*	`conf`	CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. ICML Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page
2020	J	`jnl`	CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. CoRR Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page
2020	J	`jnl`	High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records. CoRR Alexander K. Taylor, Ross Kleiman, Scott J. Hebbring, Peggy L. Peissig, David Page
2020	J	`jnl`	KinderMiner Web: a simple web tool for ranking pairwise associations in biomedical applications. F1000Research Finn Kuusisto, Daniel Ng, John W. Steill, Ian Ross, Miron Livny, James A. Thomson, David Page, Ron M. Stewart
2020	J	`jnl`	Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. CoRR Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
2020	J	`jnl`	Temporal Poisson Square Root Graphical Models. CoRR Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
2020	J	`jnl`	Troubleshooting deep-learner training data problems using an evolutionary algorithm on Summit. IBM J. Res. Dev. Mark Coletti, Alex Fafard, David Page
2019	J	`jnl`	A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CoRR Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
2019	A*	`conf`	AUCμ: A Performance Metric for Multi-Class Machine Learning Models. ICML Ross Kleiman, David Page
2019	J	`jnl`	AutoBlock: A Hands-off Blocking Framework for Entity Matching. CoRR Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page
2019	J	`jnl`	High-Throughput Machine Learning from Electronic Health Records. CoRR Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page
2019	C	`conf`	Machine Learning to Predict Developmental Neurotoxicity with High-Throughput Data from 2D Bio-Engineered Tissues. ICMLA Finn Kuusisto, Vítor Santos Costa, Zhonggang Hou, James A. Thomson, David Page, Ron M. Stewart
2019	J	`jnl`	Machine Learning to Predict Developmental Neurotoxicity with High-throughput Data from 2D Bio-engineered Tissues. CoRR Finn Kuusisto, Vítor Santos Costa, Zhonggang Hou, James A. Thomson, David Page, Ron M. Stewart
2019	J	`jnl`	Machine learning for phenotyping opioid overdose events. J. Biomed. Informatics Jonathan C. Badger, Eric LaRose, John Mayer, Fereshteh S. Bashiri, David Page, Peggy L. Peissig
2019	J	`jnl`	Predicting Drug-Drug Interactions from Molecular Structure Images. CoRR Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan
2018	J	`jnl`	An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. CoRR Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page
2018	J	`jnl`	Applying family analyses to electronic health records to facilitate genetic research. Bioinform. Xiayuan Huang, Robert C. Elston, Guilherme J. M. Rosa, John Mayer, Zhan Ye, Terrie E. Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring
2018	—	`conf`	Causal Structure Learning via Temporal Markov Networks. PGM Aubrey Barnard, David Page
2018	Misc	`conf`	Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants. AMIA Shara Feld, Kaitlin M. Woo, Roxana Alexandridis, Yirong Wu, Jie Liu, Peggy L. Peissig, Adedayo A. Onitilo, Jennifer Cox, David Page, Elizabeth S. Burnside
2018	J	`jnl`	Privacy-Preserving Collaborative Prediction using Random Forests. CoRR Irene Giacomelli, Somesh Jha, Ross Kleiman, David Page, Kyonghwan Yoon
2018	—	`conf`	Quantifying predictive capability of electronic health records for the most harmful breast cancer. Image Perception, Observer Performance, and Technology Assessment Yirong Wu, Jun Fan, Peggy L. Peissig, Richard L. Berg, Ahmad Pahlavan Tafti, Jie Yin, Ming Yuan, David Page, Jennifer Cox, Elizabeth S. Burnside
2018	C	`conf`	Recursive Feature Elimination by Sensitivity Testing. ICMLA Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page
2018	A	`conf`	Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page
2018	A*	`conf`	Temporal Poisson Square Root Graphical Models. ICML Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page
2018	Misc	`conf`	Use of Electronic Health Record to Predict Family Relationships for Phenome-wide Research. AMIA Xiayuan Huang, Robert C. Elston, John Mayer, Zhan Ye, Yuqi He, David Page, Scott J. Hebbring
2017	—	`conf`	A Screening Rule for l1-Regularized Ising Model Estimation. NIPS Zhaobin Kuang, Sinong Geng, David Page
2017	—	`conf`	A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. CRI Finn Kuusisto, John W. Steill, Zhaobin Kuang, James A. Thomson, David Page, Ron M. Stewart
2017	—	`conf`	Breast Cancer Risk Prediction Using Electronic Health Records. ICHI Yirong Wu, Elizabeth S. Burnside, Jennifer Cox, Jun Fan, Ming Yuan, Jie Yin, Peggy L. Peissig, Alexander G. Cobian, David Page, Mark W. Craven
2017	C	`conf`	Employing spaceborne multispectral stereo pairs and pedestrian flow modeling to support disaster response activities in urban environments. IGARSS Dave Kelbe, Devin White, David Page, Kristin Safi, Andrew Hardin, Amy N. Rose
2017	—	`conf`	Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett
2017	B	`conf`	Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. AIME Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan
2017	J	`jnl`	Markov logic networks for adverse drug event extraction from text. Knowl. Inf. Syst. Sriraam Natarajan, Vishal Bangera, Tushar Khot, Jose Picado, Anurag Wazalwar, Vítor Santos Costa, David Page, Michael Caldwell
2017	A*	`conf`	Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. KDD Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page
2017	—	`conf`	SCCS for Detection of Differences in Brand and Generic Adverse Drug Events. CRI Jonathan C. Badger, Eric R. LaRose, Ross Kleiman, Richard L. Berg, James G. Linneman, Richard Hansen, David Page, Peggy L. Peissig
2017	J	`jnl`	Supporting evidence-based analysis for modified risk tobacco products through a toxicology data-sharing infrastructure. F1000Research 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
2017	—	`conf`	bigNN: An open-source big data toolkit focused on biomedical sentence classification. IEEE BigData Ahmad Pahlavan Tafti, Ehsun Behravesh, Mehdi Assefi, Eric LaRose, Jonathan C. Badger, John Mayer, AnHai Doan, David Page, Peggy L. Peissig
2016	A*	`conf`	Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data. IJCAI Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
2016	A*	`conf`	Computational Drug Repositioning Using Continuous Self-Controlled Case Series. KDD Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page
2016	—	`ch.`	Relational Learning for Sustainable Health. Computational Sustainability Sriraam Natarajan, Peggy L. Peissig, David Page
2016	J	`jnl`	Structure-Leveraged Methods in Breast Cancer Risk Prediction. J. Mach. Learn. Res. Jun Fan, Yirong Wu, Ming Yuan, David Page, Jie Liu, Irene M. Ong, Peggy L. Peissig, Elizabeth S. Burnside
2015	—	`conf`	Differential Privacy for Classifier Evaluation. AISec@CCS Kendrick Boyd, Eric Lantz, David Page
2015	B	`conf`	Extracting Adverse Drug Events from Text Using Human Advice. AIME Phillip Odom, Vishal Bangera, Tushar Khot, David Page, Sriraam Natarajan
2015	Misc	`conf`	Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. AMIA Jeremy C. Weiss, Finn Kuusisto, Kendrick Boyd, Jie Liu, David Page
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	—	`conf`	Subsampled Exponential Mechanism: Differential Privacy in Large Output Spaces. AISec@CCS Eric Lantz, Kendrick Boyd, David Page
2014	Misc	`conf`	Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction. AMIA Yirong Wu, Jie Liu, David Page, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside
2014	A	`conf`	Learning Heterogeneous Hidden Markov Random Fields. AISTATS Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page
2014	A*	`conf`	Multiple Testing under Dependence via Semiparametric Graphical Models. ICML Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page
2014	A*	`conf`	Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing. USENIX Security Symposium Matthew Fredrikson, Eric Lantz, Somesh Jha, Simon M. Lin, David Page, Thomas Ristenpart
2014	J	`jnl`	QuickFOIL: Scalable Inductive Logic Programming. Proc. VLDB Endow. Qiang Zeng, Jignesh M. Patel, David Page
2014	J	`jnl`	Relational machine learning for electronic health record-driven phenotyping. J. Biomed. Informatics Peggy L. Peissig, Vítor Santos Costa, Michael Caldwell, Carla Rottscheit, Richard L. Berg, Eneida A. Mendonça, David Page
2014	—	`conf`	Support Vector Machines for Differential Prediction. ECML/PKDD (2) Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik
2013	—	`conf`	Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models. NIPS Jie Liu, David Page
2013	—	`conf`	Forest-Based Point Process for Event Prediction from Electronic Health Records. ECML/PKDD (3) Jeremy C. Weiss, David Page
2013	Misc	`conf`	Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. AMIA Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside
2013	B	`conf`	On Differentially Private Inductive Logic Programming. ILP Chen Zeng, Eric Lantz, Jeffrey F. Naughton, David Page
2013	—	`conf`	Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling. ECML/PKDD (3) Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa
2012	—	`conf`	A collective ranking method for genome-wide association studies. BCB Jie Liu, Elizabeth S. Burnside, Humberto J. Vidaillet, David Page
2012	J	`jnl`	Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study. BMC Bioinform. José Carlos Almeida Santos, Houssam Nassif, David Page, Stephen H. Muggleton, Michael J. E. Sternberg
2012	J	`jnl`	CLP(BN): Constraint Logic Programming for Probabilistic Knowledge CoRR Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
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`	Extracting BI-RADS features from Portuguese clinical texts. BIBM Houssam Nassif, Filipe Cunha, Inês C. Moreira, Ricardo Cruz-Correia, Eliana Sousa, David Page, Elizabeth S. Burnside, Inês de Castro Dutra
2012	J	`jnl`	Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies CoRR Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page
2012	A	`conf`	Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies. UAI Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page
2012	A	`conf`	High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. AISTATS Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page
2012	A*	`conf`	Identifying Adverse Drug Events by Relational Learning. AAAI David Page, Vítor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell
2012	J	`jnl`	Learning Bayesian Network Structure from Correlation-Immune Data CoRR Eric Lantz, Soumya Ray, David Page
2012	Misc	`conf`	Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women. AMIA Houssam Nassif, Yirong Wu, David Page, Elizabeth S. Burnside
2012	J	`jnl`	Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records. AI Mag. Jeremy C. Weiss, Sriraam Natarajan, Peggy L. Peissig, Catherine A. McCarty, David Page
2012	—	`conf`	Multiplicative Forests for Continuous-Time Processes. NIPS Jeremy C. Weiss, Sriraam Natarajan, David Page
2012	—	`conf`	Relational Differential Prediction. ECML/PKDD (1) Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page
2012	C	`conf`	Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records. IAAI Jeremy C. Weiss, Sriraam Natarajan, Peggy L. Peissig, Catherine A. McCarty, David Page
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	B	`conf`	Integrating knowledge capture and supervised learning through a human-computer interface. K-CAP Trevor Walker, Gautam Kunapuli, Noah Larsen, David Page, Jude W. Shavlik
2010	B	`conf`	Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. ILP Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik
2010	—	`conf`	Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. IHI Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside
2010	J	`jnl`	Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer. J. Digit. Imaging Ryan W. Woods, Louis Oliphant, Kazuhiko Shinki, David Page, Jude W. Shavlik, Elizabeth S. Burnside
2009	B	`conf`	An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. ILP Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page
2009	J	`jnl`	Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions. J. Mach. Learn. Res. Lisa Hellerstein, Bernard Rosell, Eric Bach, Soumya Ray, David Page
2009	—	`conf`	Information Extraction for Clinical Data Mining: A Mammography Case Study. ICDM Workshops Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page
2008	J	`jnl`	A logic-based diagram of signalling pathways central to macrophage activation. BMC Syst. Biol. Sobia Raza, Kevin A. Robertson, Paul A. Lacaze, David Page, Anton J. Enright, Peter Ghazal, Tom C. Freeman
2008	—	`ch.`	CLP( Probabilistic Inductive Logic Programming Vítor Santos Costa, David Page, James Cussens
2008	A	`conf`	Matching isotopic distributions from metabolically labeled samples. ISMB Sean McIlwain, David Page, Edward L. Huttlin, Michael R. Sussman
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
2007	A	`conf`	Learning Bayesian Network Structure from Correlation-Immune Data. UAI Eric Lantz, Soumya Ray, David Page
2007	—	`conf`	Using dynamic programming to create isotopic distribution maps from mass spectra. ISMB/ECCB (Supplement of Bioinformatics) Sean McIlwain, David Page, Edward L. Huttlin, Michael R. Sussman
2006	J	`jnl`	Quantitative pharmacophore models with inductive logic programming. Mach. Learn. Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King
2005	B	`conf`	A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment. ILP Héctor Corrada Bravo, David Page, Raghu Ramakrishnan, Jude W. Shavlik, Vítor Santos Costa
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	A*	`conf`	Generalized skewing for functions with continuous and nominal attributes. ICML Soumya Ray, David Page
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`	Mode Directed Path Finding. ECML Irene M. Ong, Inês de Castro Dutra, David Page, Vítor Santos Costa
2005	A*	`conf`	Multi-instance tree learning. ICML Hendrik Blockeel, David Page, Ashwin Srinivasan
2005	—	`conf`	Predicting cancer susceptibility from single-nucleotide polymorphism data: a case study in multiple myeloma. BIOKDD Michael Waddell, David Page, John D. Shaughnessy Jr.
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
2005	A*	`conf`	Why skewing works: learning difficult Boolean functions with greedy tree learners. ICML Bernard Rosell, Lisa Hellerstein, Soumya Ray, David Page
2004	B	`conf`	A Monte Carlo Study of Randomised Restarted Search in ILP. ILP Filip Zelezný, Ashwin Srinivasan, David Page
2004	A*	`conf`	Sequential skewing: an improved skewing algorithm. ICML Soumya Ray, David Page
2004	J	`jnl`	Using Machine Learning to Design and Interpret Gene-Expression Microarrays. AI Mag. Michael Molla, Michael Waddell, David Page, Jude W. Shavlik
2003	J	`jnl`	A Bayesian Network Approach to Operon Prediction. Bioinform. Joseph Bockhorst, Mark W. Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner
2003	J	`jnl`	Biological applications of multi-relational data mining. SIGKDD Explor. David Page, Mark Craven
2003	A	`conf`	CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. UAI Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens
2003	J	`jnl`	ILP: A Short Look Back and a Longer Look Forward. J. Mach. Learn. Res. David Page, Ashwin Srinivasan
2003	A*	`conf`	Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction. IJCAI David Page, Soumya Ray
2003	—	`conf`	Toward Automatic Management of Embarrassingly Parallel Applications. Euro-Par Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik, Michael Waddell
2002	B	`conf`	An Empirical Evaluation of Bagging in Inductive Logic Programming. ILP Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik
2002	J	`jnl`	KDD Cup 2001 Report. SIGKDD Explor. Jie Cheng, Christos Hatzis, Hisashi Hayashi, Mark-A. Krogel, Shinichi Morishita, David Page, Jun Sese
2002	B	`conf`	Lattice-Search Runtime Distributions May Be Heavy-Tailed. ILP Filip Zelezný, Ashwin Srinivasan, David Page
2002	A	`conf`	Modelling regulatory pathways in E. coli from time series expression profiles. ISMB Irene M. Ong, Jeremy D. Glasner, David Page
2001	J	`jnl`	Guest Editor's Introduction. Int. J. Comput. Their Appl. David Page, James H. Graham
2001	A*	`conf`	Multiple Instance Regression. ICML Soumya Ray, David Page
2000	A	`conf`	A Probabilistic Learning Approach to Whole-Genome Operon Prediction. ISMB Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner
2000	—	`conf`	ILP: Just Do It. Computational Logic David Page
2000	B	`conf`	ILP: Just Do It. ILP David Page
2000	—	`ed.`	ISCA 9th International Conference on Intelligent Systems, ICIS 2000, June 15-17, 2000, the Galt House, Louisville, Kentucky, USA IS David Page, James H. Graham
2000	A*	`conf`	Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. ICML Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner
1999	J	`jnl`	Guest Editors' Introduction: Inductive Logic Programming. J. Log. Program. Stephen H. Muggleton, David Page
1998	B	`ed.`	Inductive Logic Programming, 8th International Workshop, ILP-98, Madison, Wisconsin, USA, July 22-24, 1998, Proceedings ILP David Page
1998	J	`jnl`	Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. Mach. Learn. Paul W. Finn, Stephen H. Muggleton, David Page, Ashwin Srinivasan
1998	—	`conf`	The Design of the Client User Interface for a Meta Object-Oriented CASE Tool. TOOLS (28) Chris Phillips, Steven Adams, David Page, Daniela Mehandjiska
1997	J	`jnl`	Guest Editors' Introduction. Mach. Learn. Stephen H. Muggleton, David Page
1996	B	`conf`	An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. Inductive Logic Programming Workshop Stephen H. Muggleton, David Page, Ashwin Srinivasan
1996	—	`conf`	Meta-Modelling and Methodology Support in Object-Oriented CASE Tools. OOIS Daniela Mehandjiska-Stavreva, David Page, Mi Duk Choi
1995	—	`conf`	A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees. Machine Intelligence 15 Stephen H. Muggleton, David Page
1995	—	`conf`	Template Generator for a Methodology Independent Object-Oriented Case Tool. OOIS Daniela Mehandjiska-Stavreva, David Page, Jonanthan Ham
1994	—	`conf`	An Abstract Definition of Graphical Notations for Object-Oriented Information Systems. OOIS David Page, Paul K. Clark, Daniela Mehandjiska-Stavreva
1994	—	`conf`	Development of an Intelligent Object-Oriented CASE Tool. OOIS Daniela Mehandjiska-Stavreva, David Page, Paul K. Clark
1993	—	`conf`	Object-oriented development of expert systems. ANNES Daniela Mehandjiska, David Page