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Mark Craven Vis

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*2009
44EEDavid Andrzejewski, Xiaojin Zhu, Mark Craven: Incorporating domain knowledge into topic modeling via Dirichlet Forest priors. ICML 2009: 4
43EEAdam A. Smith, Aaron Vollrath, Christopher A. Bradfield, Mark Craven: Clustered alignments of gene-expression time series data. Bioinformatics 25(12): (2009)
2008
42 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
41EEBurr Settles, Mark Craven: An Analysis of Active Learning Strategies for Sequence Labeling Tasks. EMNLP 2008: 1070-1079
40EEMark Craven: Learning Expressive Models of Gene Regulation. ILP 2008: 4
39EEKeith Noto, Mark Craven: Learning Hidden Markov Models for Regression using Path Aggregation. UAI 2008: 444-451
2007
38EEYue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven: Connecting quantitative regulatory-network models to the genome. ISMB/ECCB (Supplement of Bioinformatics) 2007: 367-376
37EEBurr Settles, Mark Craven, Soumya Ray: Multiple-Instance Active Learning. NIPS 2007
36EEKeith Noto, Mark Craven: Learning probabilistic models of cis-regulatory modules that represent logical and spatial aspects. Bioinformatics 23(2): 156-162 (2007)
2006
35 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
34EEAndrew 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
33EESoumya Ray, Mark Craven: Supervised versus multiple instance learning: an empirical comparison. ICML 2005: 697-704
32EEThomas Brow, Burr Settles, Mark Craven: Classifying Biomedical Articles by Making Localized Decisions. TREC 2005
31EESoumya Ray, Mark Craven: Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text. BMC Bioinformatics 6(S-1): (2005)
2004
30EEAaron E. Darling, Bob Mau, Mark Craven, Nicole T. Perna: Multiple Alignment of Rearranged Genomes. CSB 2004: 738-739
29EEJoseph Bockhorst, Mark Craven: Markov Networks for Detecting Overalpping Elements in Sequence Data. NIPS 2004
28EEKeith Noto, Mark Craven: Learning Regulatory Network Models that Represent Regulator States and Roles. Regulatory Genomics 2004: 52-64
27EEBurr Settles, Mark Craven: Exploiting Zone Information, Syntactic Rules, and Informative Terms in Gene Ontology Annotation of Biomedical Documents. TREC 2004
2003
26EEMarios 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
24EEJoseph 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)
22EEDavid 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
20EEMark 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
14EEMark 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
11EEMark 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
9EEMark 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
7EEMark Craven, Jude W. Shavlik: Extracting Tree-Structured Representations of Trained Networks. NIPS 1995: 24-30
6EEJeffrey 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
4EEMark 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

Coauthor Index

1David Andrzejewski [34] [44]
2Ana L. C. Bazzan [42]
3Frederick R. Blattner [24]
4Joseph Bockhorst [15] [16] [18] [21] [23] [24] [29] [38]
5Christopher A. Bradfield [43]
6Thomas Brow [32]
7Aaron E. Darling [30]
8Dan DiPasquo [12] [14]
9Tim Durfee [38]
10Tina Eliassi-Rad [35]
11Dayne Freitag [12] [14]
12Jurgen Van Gael [34]
13Jeremy D. Glasner [15] [16] [23] [24]
14Andrew B. Goldberg [34]
15Dimitrios Gunopulos [35]
16Loren J. Hauser [8]
17Jeffrey C. Jackson [6]
18Johan Kumlien [13]
19Mingzhu Liu [24]
20Natália F. Martins [42]
21Bob Mau [30]
22Andrew McCallum [12] [14]
23Tom M. Mitchell [12] [14]
24Richard J. Mural [8]
25Kamal Nigam [11] [12] [14]
26Keith Noto [28] [36] [39]
27C. David Page Jr. (David Page) [15] [16] [22] [23]
28Yue Pan [38]
29Nicole T. Perna [30]
30Yu Qiu [24]
31Soumya Ray [19] [25] [31] [33] [37]
32Burr Settles [27] [32] [34] [37] [41]
33Jude W. Shavlik [1] [2] [3] [4] [5] [7] [9] [15] [16] [23]
34Marios Skounakis [25] [26]
35Seán Slattery [10] [11] [12] [14] [17]
36Adam A. Smith [43]
37Geoffrey G. Towell [1]
38Edward C. Uberbacher [8]
39Lyle H. Ungar [35]
40Aaron Vollrath [43]
41Xiaojin Zhu [34] [44]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)