2008 | ||
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39 | Ana L. C. Bazzan, Mark Craven, Natália F. Martins: Advances in Bioinformatics and Computational Biology, Third Brazilian Symposium on Bioinformatics, BSB 2008, Santo André, Brazil, August 28-30, 2008. Proceedings Springer 2008 | |
38 | EE | Burr Settles, Mark Craven: An Analysis of Active Learning Strategies for Sequence Labeling Tasks. EMNLP 2008: 1070-1079 |
37 | EE | Mark Craven: Learning Expressive Models of Gene Regulation. ILP 2008: 4 |
36 | EE | Keith Noto, Mark Craven: Learning Hidden Markov Models for Regression using Path Aggregation. UAI 2008: 444-451 |
2007 | ||
35 | EE | Yue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven: Connecting quantitative regulatory-network models to the genome. ISMB/ECCB (Supplement of Bioinformatics) 2007: 367-376 |
34 | EE | Burr Settles, Mark Craven, Soumya Ray: Multiple-Instance Active Learning. NIPS 2007 |
33 | EE | Keith Noto, Mark Craven: Learning probabilistic models of cis-regulatory modules that represent logical and spatial aspects. Bioinformatics 23(2): 156-162 (2007) |
2006 | ||
32 | Tina Eliassi-Rad, Lyle H. Ungar, Mark Craven, Dimitrios Gunopulos: Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006 ACM 2006 | |
31 | EE | Andrew B. Goldberg, David Andrzejewski, Jurgen Van Gael, Burr Settles, Xiaojin Zhu, Mark Craven: Ranking Biomedical Passages for Relevance and Diversity: University of Wisconsin, Madison at TREC Genomics 2006. TREC 2006 |
2005 | ||
30 | EE | Soumya Ray, Mark Craven: Supervised versus multiple instance learning: an empirical comparison. ICML 2005: 697-704 |
2004 | ||
29 | EE | Aaron E. Darling, Bob Mau, Mark Craven, Nicole T. Perna: Multiple Alignment of Rearranged Genomes. CSB 2004: 738-739 |
28 | EE | Joseph Bockhorst, Mark Craven: Markov Networks for Detecting Overalpping Elements in Sequence Data. NIPS 2004 |
27 | EE | Keith Noto, Mark Craven: Learning Regulatory Network Models that Represent Regulator States and Roles. Regulatory Genomics 2004: 52-64 |
2003 | ||
26 | EE | Marios Skounakis, Mark Craven: Evidence combination in biomedical natural-language processing. BIOKDD 2003: 25-32 |
25 | Marios Skounakis, Mark Craven, Soumya Ray: Hierarchical Hidden Markov Models for Information Extraction. IJCAI 2003: 427-433 | |
24 | EE | 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 |
23 | 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) | |
22 | EE | David Page, Mark Craven: Biological applications of multi-relational data mining. SIGKDD Explorations 5(1): 69-79 (2003) |
2002 | ||
21 | Joseph Bockhorst, Mark Craven: Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. ICML 2002: 43-50 | |
20 | EE | Mark Craven: The Genomics of a Signaling Pathway: A KDD Cup Challenge Task. SIGKDD Explorations 4(2): 97-98 (2002) |
2001 | ||
19 | Soumya Ray, Mark Craven: Representing Sentence Structure in Hidden Markov Models for Information Extraction. IJCAI 2001: 1273-1279 | |
18 | Joseph Bockhorst, Mark Craven: Refining the Structure of a Stochastic Context-Free Grammar. IJCAI 2001: 1315-1322 | |
17 | Mark Craven, Seán Slattery: Relational Learning with Statistical Predicate Invention: Better Models for Hypertext. Machine Learning 43(1/2): 97-119 (2001) | |
2000 | ||
16 | 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 | |
15 | 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 | |
14 | EE | 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) |
1999 | ||
13 | Mark Craven, Johan Kumlien: Constructing Biological Knowledge Bases by Extracting Information from Text Sources. ISMB 1999: 77-86 | |
1998 | ||
12 | 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 | |
11 | Mark Craven, Seán Slattery, Kamal Nigam: First-Order Learning for Web Mining. ECML 1998: 250-255 | |
10 | Seán Slattery, Mark Craven: Combining Statistical and Relational Methods for Learning in Hypertext Domains. ILP 1998: 38-52 | |
1997 | ||
9 | EE | Mark Craven, Jude W. Shavlik: Understanding Time-Series Networks: A Case Study in Rule Extraction. Int. J. Neural Syst. 8(4): 373-384 (1997) |
1995 | ||
8 | Mark Craven, Richard J. Mural, Loren J. Hauser, Edward C. Uberbacher: Predicting Protein Folding Classes without Overly Relying on Homology. ISMB 1995: 98-106 | |
7 | EE | Mark Craven, Jude W. Shavlik: Extracting Tree-Structured Representations of Trained Networks. NIPS 1995: 24-30 |
6 | EE | Jeffrey C. Jackson, Mark Craven: Learning Sparse Perceptrons. NIPS 1995: 654-660 |
1994 | ||
5 | Mark Craven, Jude W. Shavlik: Using Sampling and Queries to Extract Rules from Trained Neural Networks. ICML 1994: 37-45 | |
4 | EE | Mark Craven, Jude W. Shavlik: Machine Learning Approaches to Gene Recognition. IEEE Expert 9(2): 2-10 (1994) |
1993 | ||
3 | Mark Craven, Jude W. Shavlik: Learning Symbolic Rules Using Artificial Neural Networks. ICML 1993: 73-80 | |
2 | Mark Craven, Jude W. Shavlik: Learning to Represent Codons: A Challenge Problem for Constructive Induction. IJCAI 1993: 1319-1324 | |
1991 | ||
1 | Geoffrey G. Towell, Mark Craven, Jude W. Shavlik: Constructive Induction in Knowledge-Based Neural Networks. ML 1991: 213-217 |