David Page

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 Magazine 33(4): 33-45 (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 Bioinformatics 13: 162 (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. Journal of Machine Learning Research - Proceedings Track 22: 712-721 (2012)

David Page, Vítor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell: Identifying Adverse Drug Events by Relational Learning. AAAI 2012

Jie Liu, Elizabeth S. Burnside, Humberto Vidaillet, David Page: A collective ranking method for genome-wide association studies. BCB 2012: 313-320

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

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, Jesse Davis, David Page, Vítor Santos Costa: Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. ICML 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

Jeremy C. Weiss, Sriraam Natarajan, David Page: Multiplicative Forests for Continuous-Time Processes. NIPS 2012: 467-475

Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page: Relational Differential Prediction. ECML/PKDD (1) 2012: 617-632

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

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)

Eric Lantz, Soumya Ray, David Page: Learning Bayesian Network Structure from Correlation-Immune Data. CoRR abs/1206.5271 (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 abs/1210.4868 (2012)

Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens: CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. CoRR abs/1212.2519 (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: 89-96

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. Digital Imaging 23(5): 554-561 (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: 76-82

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

C. David Page Jr., Sriraam Natarajan: Biomedical Informatics. Encyclopedia of Machine Learning 2010: 132

Lisa Hellerstein, Bernard Rosell, Eric Bach, Soumya Ray, David Page: Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions. Journal of Machine Learning Research 10: 2374-2411 (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: 37-42

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

Vítor Santos Costa, David Page, James Cussens: CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. Probabilistic Inductive Logic Programming 2008: 156-188

Sean McIlwain, David Page, Edward L. Huttlin, Michael R. Sussman: Matching isotopic distributions from metabolically labeled samples. ISMB 2008: 339-347

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

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

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

Eric Lantz, Soumya Ray, David Page: Learning Bayesian Network Structure from Correlation-Immune Data. UAI 2007: 235-242

Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King: Quantitative pharmacophore models with inductive logic programming. Machine Learning 64(1-3): 65-90 (2006)

Filip Zelezný, Ashwin Srinivasan, C. David Page Jr.: Randomised restarted search in ILP. Machine Learning 64(1-3): 183-208 (2006)

Jan Struyf, Jesse Davis, C. David Page Jr.: An Efficient Approximation to Lookahead in Relational Learners. ECML 2006: 775-782

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

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

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

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

Irene M. Ong, Inês de Castro Dutra, David Page, Vítor Santos Costa: Mode Directed Path Finding. ECML 2005: 673-681

Hendrik Blockeel, David Page, Ashwin Srinivasan: Multi-instance tree learning. ICML 2005: 57-64

Soumya Ray, David Page: Generalized skewing for functions with continuous and nominal attributes. ICML 2005: 705-712

Bernard Rosell, Lisa Hellerstein, Soumya Ray, David Page: Why skewing works: learning difficult Boolean functions with greedy tree learners. ICML 2005: 728-735

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

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

Michael Molla, Michael Waddell, David Page, Jude W. Shavlik: Using Machine Learning to Design and Interpret Gene-Expression Microarrays. AI Magazine 25(1): 23-44 (2004)

Soumya Ray, David Page: Sequential skewing: an improved skewing algorithm. ICML 2004

Filip Zelezný, Ashwin Srinivasan, David Page: A Monte Carlo Study of Randomised Restarted Search in ILP. ILP 2004: 341-358

Joseph Bockhorst, Mark Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner: A Bayesian Network Approach to Operon Prediction. Bioinformatics 19(10): 1227-1235 (2003)

Ahmed H. Kamal, James H. Graham, C. David Page Jr.: A Parallel Inductive Logic Programming Data Mining System for Drug Discovery. I. J. Comput. Appl. 10(3): 161-170 (2003)

David Page, Ashwin Srinivasan: ILP: A Short Look Back and a Longer Look Forward. Journal of Machine Learning Research 4: 415-430 (2003)

David Page, Mark Craven: Biological applications of multi-relational data mining. SIGKDD Explorations 5(1): 69-79 (2003)

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

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

David Page, Soumya Ray: Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction. IJCAI 2003: 601-612

C. David Page Jr.: The Role of Declarative Languages in Mining Biological Databases. PADL 2003: 1

Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens: CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. UAI 2003: 517-524

Jie Cheng, Christor Hatzis, Hisashi Hayashi, Mark-A. Krogel, Shinichi Morishita, David Page, Jun Sese: KDD Cup 2001 Report. SIGKDD Explorations 3(2): 47-64 (2002)

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

Filip Zelezný, Ashwin Srinivasan, David Page: Lattice-Search Runtime Distributions May Be Heavy-Tailed. ILP 2002: 333-345

Irene M. Ong, Jeremy D. Glasner, David Page: Modelling regulatory pathways in E. coli from time series expression profiles. ISMB 2002: 241-248

David Page, James H. Graham: Guest Editor's Introduction. I. J. Comput. Appl. 8(2) (2001)

Ahmed H. Kamal, James H. Graham, C. David Page Jr.: An Approach to Parallel Data Mining for Pharmacophore Discovery. ISCA Conference on Intelligent Systems 2001: 100-103

Soumya Ray, David Page: Multiple Instance Regression. ICML 2001: 425-432

David Page: ILP: Just Do It. Computational Logic 2000: 25-40

Mark 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

David Page: ILP: Just Do It. ILP 2000: 3-18

Mark Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner: A Probabilistic Learning Approach to Whole-Genome Operon Prediction. ISMB 2000: 116-127

David Page, James H. Graham (Eds.): 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

Stephen Muggleton, David Page: Guest Editors' Introduction: Inductive Logic Programming. J. Log. Program. 40(2-3): 125-126 (1999)

Paul W. Finn, Stephen Muggleton, David Page, Ashwin Srinivasan: Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. Machine Learning 30(2-3): 241-270 (1998)

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

David Page (Ed.): 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

Stephen Muggleton, David Page: Guest Editors' Introduction. Machine Learning 26(2-3): 97-98 (1997)

Stephen Muggleton, David Page, Ashwin Srinivasan: An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. Inductive Logic Programming Workshop 1996: 25-40

Daniela Mehandjiska-Stavreva, David Page, Mi Duk Choi: Meta-Modelling and Methodology Support in Object-Oriented CASE Tools. OOIS 1996: 370-

William W. Cohen, C. David Page Jr.: Polynomial Learnability and Inductive Logic Programming: Methods and Results. New Generation Comput. 13(3&4): 369-409 (1995)

Alan M. Frisch, C. David Page Jr.: Building Theories into Instantiation. IJCAI 1995: 1210-1216

Stephen 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

Daniela Mehandjiska-Stavreva, David Page, Jonanthan Ham: Template Generator for a Methodology Independent Object-Oriented Case Tool. OOIS 1995: 232-247

Michael Frazier, C. David Page Jr.: Prefix Grammars: An Alternative Characterization of the Regular Languages. Inf. Process. Lett. 51(2): 67-71 (1994)

Daniela Mehandjiska-Stavreva, David Page, Paul K. Clark: Development of an Intelligent Object-Oriented CASE Tool. OOIS 1994: 215-226

David Page, Paul K. Clark, Daniela Mehandjiska-Stavreva: An Abstract Definition of Graphical Notations for Object-Oriented Information Systems. OOIS 1994: 266-276

Michael Frazier, C. David Page Jr.: Learnability in Inductive Logic Programrning: Some Basic Results and Techniques. AAAI 1993: 93-98

C. David Page Jr., Alan M. Frisch: Learning Constrained Atoms. ML 1991: 427-431

C. David Page Jr., Alan M. Frisch: Generalizing Atoms in Constraint Logic. KR 1991: 429-440

Alan M. Frisch, C. David Page Jr.: Generalization with Taxonomic Information. AAAI 1990: 755-761