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ORCIDDavid Page
C. David Page Jr. – C. David Page
2020 – today
- 2025
[i27]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, Lin Yen-Chen, Xiaohui Zeng, Yu Zeng, Jing Zhang, Qinsheng Zhang, Yuxuan Zhang, Qingqing Zhao, Artur Zólkowski:
Cosmos World Foundation Model Platform for Physical AI. CoRR abs/2501.03575 (2025)- [i26]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:
Training Video Foundation Models with NVIDIA NeMo. CoRR abs/2503.12964 (2025) - 2024
- [j32]Shiyi Jiang
, Xin Gai, Miriam M. Treggiari, William W. Stead, Yuankang Zhao, C. David Page, Anru R. Zhang:
Soft phenotyping for sepsis via EHR time-aware soft clustering. J. Biomed. Informatics 152: 104615 (2024) - [j31]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): 2039 (2024) - [c111]Boyao Li, Alexander Thomson, Houssam Nassif, Matthew Engelhard, David Page:
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. NeurIPS 2024 - [c110]Tatsuki Koga, Kamalika Chaudhuri, David Page:
Differentially Private Multi-Site Treatment Effect Estimation. SaTML 2024: 472-489 - [i25]Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page:
MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. CoRR abs/2408.01869 (2024) - 2023
- [c109]Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page:
Variable importance matching for causal inference. UAI 2023: 1174-1184 - [i24]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 abs/2302.11715 (2023) - [i23]Boyao Li, Alexandar J. Thomson, Matthew M. Engelhard, David Page:
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. CoRR abs/2305.17583 (2023) - [i22]Tatsuki Koga, Kamalika Chaudhuri, David Page:
Differentially Private Multi-Site Treatment Effect Estimation. CoRR abs/2310.06237 (2023) - [i21]Alexander Thomson, David Page:
Neural Markov Prolog. CoRR abs/2312.01521 (2023) - 2022
- [j30]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): 152 (2022) - 2021
- [j29]Xiayuan Huang, Nicholas P. 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): 3966-3968 (2021) - [c108]Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. AIME 2021: 252-257 - [i20]Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. CoRR abs/2103.10916 (2021) - 2020
- [j28]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): 1-12 (2020) - [c107]Wei Zhang, Zhaobin Kuang, Peggy L. Peissig, David Page:
Adverse drug reaction discovery from electronic health records with deep neural networks. CHIL 2020: 30-39 - [c106]Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page:
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. ICML 2020: 11235-11245 - [c105]Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page:
AutoBlock: A Hands-off Blocking Framework for Entity Matching. WSDM 2020: 744-752 - [i19]Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page:
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. CoRR abs/2002.07906 (2020) - [i18]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 abs/2005.06083 (2020) - [i17]Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page:
Temporal Poisson Square Root Graphical Models. CoRR abs/2005.06462 (2020) - [i16]Alexander K. Taylor, Ross Kleiman, Scott J. Hebbring, Peggy L. Peissig, David Page:
High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records. CoRR abs/2011.09497 (2020) - [i15]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: 832 (2020)
2010 – 2019
- 2019
- [j27]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) - [c104]Ross Kleiman, David Page:
AUCμ: A Performance Metric for Multi-Class Machine Learning Models. ICML 2019: 3439-3447 - [c103]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: 293-298 - [i14]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 abs/1905.02121 (2019) - [i13]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 abs/1906.05255 (2019) - [i12]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 abs/1907.01901 (2019) - [i11]Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Molecular Structure Images. CoRR abs/1911.06356 (2019) - [i10]Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page:
AutoBlock: A Hands-off Blocking Framework for Entity Matching. CoRR abs/1912.03417 (2019) - 2018
- [j26]Xiayuan Huang, Robert C. Elston, Guilherme J. M. 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): 635-642 (2018) - [c102]Irene Giacomelli, Somesh Jha, Marc Joye, C. David Page, Kyonghwan Yoon:
Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption. ACNS 2018: 243-261 - [c101]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 - [c100]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 - [c99]Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page:
Temporal Poisson Square Root Graphical Models. ICML 2018: 1700-1709 - [c98]Nicholas Sean Escanilla, Lisa Hellerstein, Ross Kleiman, Zhaobin Kuang, James Shull, David Page:
Recursive Feature Elimination by Sensitivity Testing. ICMLA 2018: 40-47 - [c97]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. Image Perception, Observer Performance, and Technology Assessment 2018: 105770J - [c96]Aubrey Barnard, David Page:
Causal Structure Learning via Temporal Markov Networks. PGM 2018: 13-24 - [c95]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: 156-166 - [i9]Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page:
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. CoRR abs/1810.04707 (2018) - [i8]Irene Giacomelli, Somesh Jha, Ross Kleiman, David Page, Kyonghwan Yoon:
Privacy-Preserving Collaborative Prediction using Random Forests. CoRR abs/1811.08695 (2018) - 2017
- [j25]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): 435-457 (2017) - [c94]Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan:
Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. AIME 2017: 332-337 - [c93]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: 3888-3896 - [c92]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 - [c91]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 - [c90]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: 224-228 - [c89]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: 2573-2576 - [c88]Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page:
Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. KDD 2017: 1537-1546 - [c87]Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett:
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC 2017: 177-190 - [c86]Zhaobin Kuang, Sinong Geng, David Page:
A Screening Rule for l1-Regularized Ising Model Estimation. NIPS 2017: 720-731 - [r2]C. David Page, Sriraam Natarajan:
Biomedical Informatics. Encyclopedia of Machine Learning and Data Mining 2017: 143-163 - [i7]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: 12- (2017) - [i6]Irene Giacomelli, Somesh Jha, C. David Page, Kyonghwan Yoon:
Privacy-Preserving Ridge Regression on Distributed Data. IACR Cryptol. ePrint Arch. 2017: 707 (2017) - [i5]Irene Giacomelli, Somesh Jha, Marc Joye, C. David Page, Kyonghwan Yoon:
Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption. IACR Cryptol. ePrint Arch. 2017: 979 (2017) - 2016
- [j24]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: 85:1-85:15 (2016) - [c85]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: 2521-2528 - [c84]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: 491-500 - [p3]Sriraam Natarajan, Peggy L. Peissig, David Page:
Relational Learning for Sustainable Health. Computational Sustainability 2016: 245-264 - 2015
- [j23]Mark W. Craven, C. David Page:
Big Data in Healthcare: Opportunities and Challenges. Big Data 3(4): 209-210 (2015) - [j22]Timothy S. Chang, Ronald E. Gangnon, C. David Page, William R. Buckingham, Aman Tandias, Kelly J. Cowan, Carrie D. Tomasallo, Brian G. Arndt, Lawrence P. Hanrahan, Theresa W. Guilbert:
Sparse modeling of spatial environmental variables associated with asthma. J. Biomed. Informatics 53: 320-329 (2015) - [c83]Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr.:
Learning to Reject Sequential Importance Steps for Continuous-Time Bayesian Networks. AAAI 2015: 3628-3634 - [c82]Phillip Odom, Vishal Bangera, Tushar Khot, David Page, Sriraam Natarajan:
Extracting Adverse Drug Events from Text Using Human Advice. AIME 2015: 195-204 - [c81]Jeremy C. Weiss, Finn Kuusisto, Kendrick Boyd, Jie Liu, David Page:
Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. AMIA 2015 - [c80]Kendrick Boyd, Eric Lantz, David Page:
Differential Privacy for Classifier Evaluation. AISec@CCS 2015: 15-23 - [c79]Eric Lantz, Kendrick Boyd, David Page:
Subsampled Exponential Mechanism: Differential Privacy in Large Output Spaces. AISec@CCS 2015: 25-33 - [p2]Jesse Davis, Vítor Santos Costa, Peggy L. Peissig, Michael Caldwell, David Page:
Predicting Adverse Drug Events from Electronic Medical Records. Foundations of Biomedical Knowledge Representation 2015: 243-257 - 2014
- [j21]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: 260-270 (2014) - [j20]Qiang Zeng, Jignesh M. Patel, David Page:
QuickFOIL: Scalable Inductive Logic Programming. Proc. VLDB Endow. 8(3): 197-208 (2014) - [c78]Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page:
Learning Heterogeneous Hidden Markov Random Fields. AISTATS 2014: 576-584 - [c77]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 - [c76]Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page:
Multiple Testing under Dependence via Semiparametric Graphical Models. ICML 2014: 955-963 - [c75]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: 50-65 - [c74]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: 17-32 - 2013
- [c73]Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr.:
Learning When to Reject an Importance Sample. AAAI (Late-Breaking Developments) 2013 - [c72]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 - [c71]Chen Zeng, Eric Lantz, Jeffrey F. Naughton, David Page:
On Differentially Private Inductive Logic Programming. ILP 2013: 18-30 - [c70]Jie Liu, David Page:
Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models. NIPS 2013: 1232-1240 - [c69]Kendrick Boyd, Kevin H. Eng, C. David Page Jr.:
Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals. ECML/PKDD (3) 2013: 451-466 - [c68]Kendrick Boyd, Kevin H. Eng, C. David Page Jr.:
Erratum: Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals. ECML/PKDD (3) 2013 - [c67]Jeremy C. Weiss, David Page:
Forest-Based Point Process for Event Prediction from Electronic Health Records. ECML/PKDD (3) 2013: 547-562 - [c66]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: 595-611 - 2012
- [j19]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): 33-45 (2012) - [j18]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: 162 (2012) - [c65]David Page, Vítor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell:
Identifying Adverse Drug Events by Relational Learning. AAAI 2012: 1599-1605 - [c64]Houssam Nassif, Yirong Wu, David Page, Elizabeth S. Burnside:
Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women. AMIA 2012 - [c63]Jie Liu, Elizabeth S. Burnside, Humberto J. Vidaillet, David Page:
A collective ranking method for genome-wide association studies. BCB 2012: 313-320 - [c62]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: 1-4 - [c61]Shreyas Karnik, Sin Lam Tan, Bess Berg, Ingrid Glurich, Jinfeng Zhang, Humberto J. Vidaillet, C. David Page, Rajesh Chowdhary:
Predicting atrial fibrillation and flutter using Electronic Health Records. EMBC 2012: 5562-5565 - [c60]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: 2341-2347 - [c59]Kendrick Boyd, Jesse Davis, David Page, Vítor Santos Costa:
Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. ICML 2012 - [c58]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 - [c57]Jeremy C. Weiss, Sriraam Natarajan, David Page:
Multiplicative Forests for Continuous-Time Processes. NIPS 2012: 467-475 - [c56]Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page:
Relational Differential Prediction. ECML/PKDD (1) 2012: 617-632 - [c55]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: 511-522 - [c54]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: 712-721 - [i4]Kendrick Boyd, Vítor Santos Costa, Jesse Davis, David Page:
Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. CoRR abs/1206.4667 (2012) - [i3]Eric Lantz, Soumya Ray, David Page:
Learning Bayesian Network Structure from Correlation-Immune Data. CoRR abs/1206.5271 (2012) - [i2]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 abs/1210.4868 (2012) - [i1]Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens:
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. CoRR abs/1212.2519 (2012) - 2011
- [c53]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: 89-96 - 2010
- [j17]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): 554-561 (2010) - [c52]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: 76-82 - [c51]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: 253-268 - [r1]C. David Page Jr., Sriraam Natarajan:
Biomedical Informatics. Encyclopedia of Machine Learning 2010: 132
2000 – 2009
- 2009
- [j16]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: 2374-2411 (2009) - [c50]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: 37-42 - [c49]Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page:
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. ILP 2009: 149-165 - 2008
- [j15]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: 36 (2008) - [c48]Sean McIlwain, David Page, Edward L. Huttlin, Michael R. Sussman:
Matching isotopic distributions from metabolically labeled samples. ISMB 2008: 339-347 - [p1]Vítor Santos Costa, David Page, James Cussens:
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. Probabilistic Inductive Logic Programming 2008: 156-188 - 2007
- [c47]Jesse Davis, Vítor Santos Costa, Soumya Ray, David Page:
An integrated approach to feature invention and model construction for drug activity prediction. ICML 2007: 217-224 - [c46]Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vítor Santos Costa:
Change of Representation for Statistical Relational Learning. IJCAI 2007: 2719-2726 - [c45]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: 328-336 - [c44]Eric Lantz, Soumya Ray, David Page:
Learning Bayesian Network Structure from Correlation-Immune Data. UAI 2007: 235-242 - 2006
- [j14]Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King:
Quantitative pharmacophore models with inductive logic programming. Mach. Learn. 64(1-3): 65-90 (2006) - [j13]Filip Zelezný, Ashwin Srinivasan, C. David Page Jr.:
Randomised restarted search in ILP. Mach. Learn. 64(1-3): 183-208 (2006) - [c43]Jan Struyf, Jesse Davis, C. David Page Jr.:
An Efficient Approximation to Lookahead in Relational Learners. ECML 2006: 775-782 - [c42]Irene M. Ong, Scott E. Topper, C. David Page Jr., Vítor Santos Costa:
Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming. ILP 2006: 366-378 - [c41]Aline Paes, Filip Zelezný, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan:
ILP Through Propositionalization and Stochastic k-Term DNF Learning. ILP 2006: 379-393 - [c40]C. David Page Jr., Irene M. Ong:
Experimental Design of Time Series Data for Learning from Dynamic Bayesian Networks. Pacific Symposium on Biocomputing 2006: 267-278 - 2005
- [c39]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 - [c38]Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Vítor Santos Costa:
An Integrated Approach to Learning Bayesian Networks of Rules. ECML 2005: 84-95 - [c37]Irene M. Ong, Inês de Castro Dutra, David Page, Vítor Santos Costa:
Mode Directed Path Finding. ECML 2005: 673-681 - [c36]Hendrik Blockeel, David Page, Ashwin Srinivasan:
Multi-instance tree learning. ICML 2005: 57-64 - [c35]Soumya Ray, David Page:
Generalized skewing for functions with continuous and nominal attributes. ICML 2005: 705-712 - [c34]Bernard Rosell, Lisa Hellerstein, Soumya Ray, David Page:
Why skewing works: learning difficult Boolean functions with greedy tree learners. ICML 2005: 728-735 - [c33]Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik:
View Learning for Statistical Relational Learning: With an Application to Mammography. IJCAI 2005: 677-683 - [c32]Héctor Corrada Bravo, David Page, Raghu Ramakrishnan, Jude W. Shavlik, Vítor Santos Costa:
A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment. ILP 2005: 69-86 - [c31]Michael Waddell, David Page, John D. Shaughnessy Jr.:
Predicting cancer susceptibility from single-nucleotide polymorphism data: a case study in multiple myeloma. BIOKDD 2005: 21-28 - 2004
- [j12]Michael Molla, Michael Waddell, David Page, Jude W. Shavlik:
Using Machine Learning to Design and Interpret Gene-Expression Microarrays. AI Mag. 25(1): 23-44 (2004) - [c30]Soumya Ray, David Page:
Sequential skewing: an improved skewing algorithm. ICML 2004 - [c29]Filip Zelezný, Ashwin Srinivasan, David Page:
A Monte Carlo Study of Randomised Restarted Search in ILP. ILP 2004: 341-358 - 2003
- [j11]Joseph Bockhorst, Mark W. Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner:
A Bayesian Network Approach to Operon Prediction. Bioinform. 19(10): 1227-1235 (2003) - [j10]Ahmed H. Kamal, James H. Graham, C. David Page Jr.:
A Parallel Inductive Logic Programming Data Mining System for Drug Discovery. Int. J. Comput. Their Appl. 10(3): 161-170 (2003) - [j9]David Page, Ashwin Srinivasan:
ILP: A Short Look Back and a Longer Look Forward. J. Mach. Learn. Res. 4: 415-430 (2003) - [j8]David Page, Mark Craven:
Biological applications of multi-relational data mining. SIGKDD Explor. 5(1): 69-79 (2003) - [c28]James H. Graham, C. David Page Jr., Ahmed H. Kamal:
Accelerating the Drug Design Process through Parallel Inductive Logic Programming Data Mining. CSB 2003: 400-402 - [c27]Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik, Michael Waddell:
Toward Automatic Management of Embarrassingly Parallel Applications. Euro-Par 2003: 509-516 - [c26]David Page, Soumya Ray:
Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction. IJCAI 2003: 601-612 - [c25]C. David Page Jr.:
The Role of Declarative Languages in Mining Biological Databases. PADL 2003: 1 - [c24]Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens:
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. UAI 2003: 517-524 - 2002
- [j7]Jie Cheng, Christos Hatzis, Hisashi Hayashi, Mark-A. Krogel, Shinichi Morishita, David Page, Jun Sese:
KDD Cup 2001 Report. SIGKDD Explor. 3(2): 47-64 (2002) - [c23]Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude W. Shavlik:
An Empirical Evaluation of Bagging in Inductive Logic Programming. ILP 2002: 48-65 - [c22]Filip Zelezný, Ashwin Srinivasan, David Page:
Lattice-Search Runtime Distributions May Be Heavy-Tailed. ILP 2002: 333-345 - [c21]Irene M. Ong, Jeremy D. Glasner, David Page:
Modelling regulatory pathways in E. coli from time series expression profiles. ISMB 2002: 241-248 - 2001
- [j6]David Page, James H. Graham:
Guest Editor's Introduction. Int. J. Comput. Their Appl. 8(2) (2001) - [c20]Ahmed H. Kamal, James H. Graham, C. David Page Jr.:
An Approach to Parallel Data Mining for Pharmacophore Discovery. IS 2001: 100-103 - [c19]Soumya Ray, David Page:
Multiple Instance Regression. ICML 2001: 425-432 - 2000
- [c18]David Page:
ILP: Just Do It. Computational Logic 2000: 25-40 - [c17]Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner:
Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. ICML 2000: 199-206 - [c16]David Page:
ILP: Just Do It. ILP 2000: 3-18 - [c15]Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner:
A Probabilistic Learning Approach to Whole-Genome Operon Prediction. ISMB 2000: 116-127 - [c14]James Graham, C. David Page, Alan Wild:
Parallel data mining for pharmacophore discovery. SMC 2000: 1894-1899 - [e2]David Page, James H. Graham:
ISCA 9th International Conference on Intelligent Systems, ICIS 2000, June 15-17, 2000, the Galt House, Louisville, Kentucky, USA. ISCA 2000, ISBN 1-880843-33-1 [contents]
1990 – 1999
- 1999
- [j5]Stephen H. Muggleton, David Page:
Guest Editors' Introduction: Inductive Logic Programming. J. Log. Program. 40(2-3): 125-126 (1999) - 1998
- [j4]Paul W. Finn, Stephen H. Muggleton, David Page, Ashwin Srinivasan:
Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. Mach. Learn. 30(2-3): 241-270 (1998) - [c13]Chris Phillips, Steven Adams, David Page, Daniela Mehandjiska:
The Design of the Client User Interface for a Meta Object-Oriented CASE Tool. TOOLS (28) 1998: 156-167 - [e1]David Page:
Inductive Logic Programming, 8th International Workshop, ILP-98, Madison, Wisconsin, USA, July 22-24, 1998, Proceedings. Lecture Notes in Computer Science 1446, Springer 1998, ISBN 3-540-64738-4 [contents] - 1997
- [j3]Stephen H. Muggleton, David Page:
Guest Editors' Introduction. Mach. Learn. 26(2-3): 97-98 (1997) - 1996
- [c12]Stephen H. Muggleton, David Page, Ashwin Srinivasan:
An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. Inductive Logic Programming Workshop 1996: 25-40 - [c11]Daniela Mehandjiska-Stavreva, David Page, Mi Duk Choi:
Meta-Modelling and Methodology Support in Object-Oriented CASE Tools. OOIS 1996: 370-386 - 1995
- [j2]William W. Cohen, C. David Page Jr.:
Polynomial Learnability and Inductive Logic Programming: Methods and Results. New Gener. Comput. 13(3&4): 369-409 (1995) - [c10]Alan M. Frisch, C. David Page Jr.:
Building Theories into Instantiation. IJCAI 1995: 1210-1216 - [c9]Stephen H. Muggleton, David Page:
A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees. Machine Intelligence 15 1995: 248-267 - [c8]Daniela Mehandjiska-Stavreva, David Page, Jonanthan Ham:
Template Generator for a Methodology Independent Object-Oriented Case Tool. OOIS 1995: 232-247 - 1994
- [j1]Michael Frazier, C. David Page Jr.:
Prefix Grammars: An Alternative Characterization of the Regular Languages. Inf. Process. Lett. 51(2): 67-71 (1994) - [c7]Daniela Mehandjiska-Stavreva, David Page, Paul K. Clark:
Development of an Intelligent Object-Oriented CASE Tool. OOIS 1994: 215-226 - [c6]David Page, Paul K. Clark, Daniela Mehandjiska-Stavreva:
An Abstract Definition of Graphical Notations for Object-Oriented Information Systems. OOIS 1994: 266-276 - 1993
- [c5]Michael Frazier, C. David Page Jr.:
Learnability in Inductive Logic Programrning: Some Basic Results and Techniques. AAAI 1993: 93-98 - [c4]Daniela Mehandjiska, David Page:
Object-oriented development of expert systems. ANNES 1993: 168-172 - 1991
- [c3]C. David Page Jr., Alan M. Frisch:
Learning Constrained Atoms. ML 1991: 427-431 - [c2]C. David Page Jr., Alan M. Frisch:
Generalizing Atoms in Constraint Logic. KR 1991: 429-440 - 1990
- [c1]Alan M. Frisch, C. David Page Jr.:
Generalization with Taxonomic Information. AAAI 1990: 755-761
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