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Note: Links lead to the DBLP on the Web. Mark Craven Marios Skounakis , Mark Craven: Evidence combination in biomedical natural-language processing. BIOKDD 2003 : 25-32 Marios Skounakis , Mark Craven, Soumya Ray : Hierarchical Hidden Markov Models for Information Extraction. IJCAI 2003 : 427-433 Joseph Bockhorst , Yu Qiu , Jeremy D. Glasner , Mingzhu Liu , Frederick R. Blattner , Mark Craven: Predicting bacterial transcription units using sequence and expression data. ISMB (Supplement of Bioinformatics) 2003 : 34-43 Joseph Bockhorst , Mark Craven, David Page , Jude W. Shavlik , Jeremy Glasner : A Bayesian Network Approach to Operon Prediction. Bioinformatics 19 (10): 1227-1235 (2003) Joseph Bockhorst , Mark Craven: Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. ICML 2002 : 43-50 Mark Craven: The Genomics of a Signaling Pathway: A KDD Cup Challenge Task. SIGKDD Explorations 4 (2): 97-98 (2002) Soumya Ray , Mark Craven: Representing Sentence Structure in Hidden Markov Models for Information Extraction. IJCAI 2001 : 1273-1279 Joseph Bockhorst , Mark Craven: Refining the Structure of a Stochastic Context-Free Grammar. IJCAI 2001 : 1315-1322 Mark Craven, Seán Slattery : Relational Learning with Statistical Predicate Invention: Better Models for Hypertext. Machine Learning 43 (1/2): 97-119 (2001) 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 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 Mark Craven, Dan DiPasquo , Dayne Freitag , Andrew McCallum , Tom M. Mitchell , Kamal Nigam , Seán Slattery : Learning to construct knowledge bases from the World Wide Web. Artif. Intell. 118 (1-2): 69-113 (2000) Mark Craven, Johan Kumlien : Constructing Biological Knowledge Bases by Extracting Information from Text Sources. ISMB 1999 : 77-86 Mark Craven, Dan DiPasquo , Dayne Freitag , Andrew McCallum , Tom M. Mitchell , Kamal Nigam , Seán Slattery : Learning to Extract Symbolic Knowledge from the World Wide Web. AAAI/IAAI 1998 : 509-516 Mark Craven, Seán Slattery , Kamal Nigam : First-Order Learning for Web Mining. ECML 1998 : 250-255 Seán Slattery , Mark Craven: Combining Statistical and Relational Methods for Learning in Hypertext Domains. ILP 1998 : 38-52 Mark Craven, Richard J. Mural , Loren J. Hauser , Edward C. Uberbacher : Predicting Protein Folding Classes without Overly Relying on Homology. ISMB 1995 : 98-106 Mark Craven, Jude W. Shavlik : Extracting Tree-Structured Representations of Trained Networks. NIPS 1995 : 24-30 Jeffrey C. Jackson , Mark Craven: Learning Sparse Perceptrons. NIPS 1995 : 654-660 Mark Craven, Jude W. Shavlik : Using Sampling and Queries to Extract Rules from Trained Neural Networks. ICML 1994 : 37-45 Mark Craven, Jude W. Shavlik : Machine Learning Approaches to Gene Recognition. IEEE Expert 9 (2): 2-10 (1994) Mark Craven, Jude W. Shavlik : Learning Symbolic Rules Using Artificial Neural Networks. ICML 1993 : 73-80 Mark Craven, Jude W. Shavlik : Learning to Represent Codons: A Challenge Problem for Constructive Induction. IJCAI 1993 : 1319-1324 Geoffrey G. Towell , Mark Craven, Jude W. Shavlik : Constructive Induction in Knowledge-Based Neural Networks. ML 1991 : 213-217 1 [ 22 ] 2 [ 14 ] [ 15 ] [ 17 ] [ 20 ] [ 21 ] [ 22 ] 3 [ 11 ] [ 13 ] 4 [ 11 ] [ 13 ] 5 [ 21 ] 6 [ 14 ] [ 15 ] [ 22 ] 7 [ 8 ] 8 [ 6 ] 9 [ 12 ] 10 [ 22 ] 11 [ 11 ] [ 13 ] 12 [ 11 ] [ 13 ] 13 [ 8 ] 14 [ 10 ] [ 11 ] [ 13 ] 15 [ 14 ] [ 15 ] [ 21 ] 16 [ 22 ] 17 [ 18 ] [ 23 ] 18 [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 7 ] [ 14 ] [ 15 ] [ 21 ] 19 [ 23 ] [ 24 ] 20 [ 9 ] [ 10 ] [ 11 ] [ 13 ] [ 16 ] 21 [ 1 ] 22 [ 8 ]  ©2004 Association for Computing Machinery |
