Mark Craven

	2009
45		David Andrzejewski, Xiaojin Zhu, Mark Craven: Incorporating domain knowledge into topic modeling via Dirichlet Forest priors. ICML 2009: 4
44		Adam A. Smith, Aaron Vollrath, Christopher A. Bradfield, Mark Craven: Clustered alignments of gene-expression time series data. Bioinformatics 25(12): (2009)
	2008
43		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
42		Burr Settles, Mark Craven: An Analysis of Active Learning Strategies for Sequence Labeling Tasks. EMNLP 2008: 1070-1079
41		Mark Craven: Learning Expressive Models of Gene Regulation. ILP 2008: 4
40		Keith Noto, Mark Craven: Learning Hidden Markov Models for Regression using Path Aggregation. UAI 2008: 444-451
	2007
39		Yue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven: Connecting quantitative regulatory-network models to the genome. ISMB/ECCB (Supplement of Bioinformatics) 2007: 367-376
38		Burr Settles, Mark Craven, Soumya Ray: Multiple-Instance Active Learning. NIPS 2007
37		Keith Noto, Mark Craven: Learning probabilistic models of cis-regulatory modules that represent logical and spatial aspects. Bioinformatics 23(2): 156-162 (2007)
	2006
36		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
35		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
34		Keith Noto, Mark Craven: A specialized learner for inferring structured cis-regulatory modules. BMC Bioinformatics 7: 528 (2006)
	2005
33		Soumya Ray, Mark Craven: Supervised versus multiple instance learning: an empirical comparison. ICML 2005: 697-704
32		Thomas Brow, Burr Settles, Mark Craven: Classifying Biomedical Articles by Making Localized Decisions. TREC 2005
31		Soumya Ray, Mark Craven: Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text. BMC Bioinformatics 6(S-1): (2005)
	2004
30		Aaron E. Darling, Bob Mau, Mark Craven, Nicole T. Perna: Multiple Alignment of Rearranged Genomes. CSB 2004: 738-739
29		Joseph Bockhorst, Mark Craven: Markov Networks for Detecting Overalpping Elements in Sequence Data. NIPS 2004
28		Keith Noto, Mark Craven: Learning Regulatory Network Models that Represent Regulator States and Roles. Regulatory Genomics 2004: 52-64
27		Burr Settles, Mark Craven: Exploiting Zone Information, Syntactic Rules, and Informative Terms in Gene Ontology Annotation of Biomedical Documents. TREC 2004
	2003
26		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		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		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		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		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		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		Mark Craven, Jude W. Shavlik: Extracting Tree-Structured Representations of Trained Networks. NIPS 1995: 24-30
6		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		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

Coauthor Index

1	David Andrzejewski	[35] [45]
2	Ana L. C. Bazzan	[43]
3	Frederick R. Blattner	[24]
4	Joseph Bockhorst	[15] [16] [18] [21] [23] [24] [29] [39]
5	Christopher A. Bradfield	[44]
6	Thomas Brow	[32]
7	Aaron E. Darling	[30]
8	Dan DiPasquo	[12] [14]
9	Tim Durfee	[39]
10	Tina Eliassi-Rad	[36]
11	Dayne Freitag	[12] [14]
12	Jurgen Van Gael	[35]
13	Jeremy D. Glasner	[15] [16] [23] [24]
14	Andrew B. Goldberg	[35]
15	Dimitrios Gunopulos	[36]
16	Loren J. Hauser	[8]
17	Jeffrey C. Jackson	[6]
18	Johan Kumlien	[13]
19	Mingzhu Liu	[24]
20	Natália F. Martins	[43]
21	Bob Mau	[30]
22	Andrew McCallum	[12] [14]
23	Tom M. Mitchell	[12] [14]
24	Richard J. Mural	[8]
25	Kamal Nigam	[11] [12] [14]
26	Keith Noto	[28] [34] [37] [40]
27	C. David Page Jr. (David Page)	[15] [16] [22] [23]
28	Yue Pan	[39]
29	Nicole T. Perna	[30]
30	Yu Qiu	[24]
31	Soumya Ray	[19] [25] [31] [33] [38]
32	Burr Settles	[27] [32] [35] [38] [42]
33	Jude W. Shavlik	[1] [2] [3] [4] [5] [7] [9] [15] [16] [23]
34	Marios Skounakis	[25] [26]
35	Seán Slattery	[10] [11] [12] [14] [17]
36	Adam A. Smith	[44]
37	Geoffrey G. Towell	[1]
38	Edward C. Uberbacher	[8]
39	Lyle H. Ungar	[36]
40	Aaron Vollrath	[44]
41	Xiaojin Zhu	[35] [45]

Colors in the list of coauthors