Mark Craven

Publication Activity (10 Years)

Years Active: 1995-2022
Publications (10 Years): 9

Top Topics

False Positives

Genetic Variation

Top Venues

PLoS Comput. Biol.

Publications

Akshay Sood, Mark Craven
Feature Importance Explanations for Temporal Black-Box Models. AAAI (2022)
Akshay Sood, Mark Craven
Feature Importance Explanations for Temporal Black-Box Models. CoRR (2021)
Yuriy Sverchkov, Yi-Hsuan Ho, Audrey P. Gasch, Mark Craven
Context-Specific Nested Effects Models. J. Comput. Biol. 27 (3) (2020)
Sunyoung Shin, Rebecca Hudson, Christopher Harrison, Mark Craven, Sündüz Keles
atSNP Search: a web resource for statistically evaluating influence of human genetic variation on transcription factor binding. Bioinform. 35 (15) (2019)
Kyubin Lee, Akshay Sood, Mark Craven
Understanding Learned Models by Identifying Important Features at the Right Resolution. AAAI (2019)
Sid Kiblawi, Deborah Chasman, Amanda Henning, Eunju Park, Hoifung Poon, Michael Gould, Paul Ahlquist, Mark Craven
Augmenting subnetwork inference with information extracted from the scientific literature. PLoS Comput. Biol. 15 (6) (2019)
Kyubin Lee, Akshay Sood, Mark Craven
Understanding Learned Models by Identifying Important Features at the Right Resolution. CoRR (2018)
Yuriy Sverchkov, Yi-Hsuan Ho, Audrey P. Gasch, Mark Craven
Context-Specific Nested Effects Models. RECOMB (2018)
Yuriy Sverchkov, Mark Craven
A review of active learning approaches to experimental design for uncovering biological networks. PLoS Comput. Biol. 13 (6) (2017)
Deborah Chasman, Brandi Gancarz, Linhui Hao, Michael Ferris, Paul Ahlquist, Mark Craven
Inferring Host Gene Subnetworks Involved in Viral Replication. PLoS Comput. Biol. 10 (5) (2014)
Linhui Hao, Qiuling He, Zhishi Wang, Mark Craven, Michael A. Newton, Paul Ahlquist
Limited Agreement of Independent RNAi Screens for Virus-Required Host Genes Owes More to False-Negative than False-Positive Factors. PLoS Comput. Biol. 9 (9) (2013)
Keith Noto, Mark Craven
Learning Hidden Markov Models for Regression using Path Aggregation CoRR (2012)
Andreas Vlachos, Mark Craven
Biomedical event extraction from abstracts and full papers using search-based structured prediction. BMC Bioinform. 13 (S-11) (2012)
Andreas Vlachos, Mark Craven
Search-based Structured Prediction applied to Biomedical Event Extraction. CoNLL (2011)
David Andrzejewski, Xiaojin Zhu, Mark Craven, Benjamin Recht
A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation Using First-Order Logic. IJCAI (2011)
Andreas Vlachos, Mark Craven
Biomedical Event Extraction from Abstracts and Full Papers using Search-based Structured Prediction. BioNLP@ACL (Shared Task) (2011)
Andreas Vlachos, Mark Craven
Detecting Speculative Language Using Syntactic Dependencies and Logistic Regression. CoNLL Shared Task (2010)
Aaron L. Vollrath, Adam A. Smith, Mark Craven, Christopher A. Bradfield
: A web-based solution for management and analysis of Agilent two color microarray experiments. BMC Bioinform. 10 (2009)
David Andrzejewski, Xiaojin Zhu, Mark Craven
Incorporating domain knowledge into topic modeling via Dirichlet Forest priors. ICML (2009)
Adam A. Smith, Aaron L. Vollrath, Christopher A. Bradfield, Mark Craven
Clustered alignments of gene-expression time series data. Bioinform. 25 (12) (2009)
Burr Settles, Mark Craven
An Analysis of Active Learning Strategies for Sequence Labeling Tasks. EMNLP (2008)
Mark Craven
Learning Expressive Models of Gene Regulation. ILP (2008)
Adam A. Smith, Aaron L. Vollrath, Christopher A. Bradfield, Mark Craven
Similarity Queries for Temporal Toxicogenomic Expression Profiles. PLoS Comput. Biol. 4 (7) (2008)
Keith Noto, Mark Craven
Learning Hidden Markov Models for Regression using Path Aggregation. UAI (2008)
Yue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven
Connecting quantitative regulatory-network models to the genome. ISMB/ECCB (Supplement of Bioinformatics) (2007)
Keith Noto, Mark Craven
-regulatory modules that represent logical and spatial aspects. Bioinform. 23 (2) (2007)
Burr Settles, Mark Craven, Soumya Ray
Multiple-Instance Active Learning. NIPS (2007)
Keith Noto, Mark Craven
A specialized learner for inferring structured cis-regulatory modules. BMC Bioinform. 7 (2006)
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)
Soumya Ray, Mark Craven
Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text. BMC Bioinform. 6 (S-1) (2005)
Soumya Ray, Mark Craven
Supervised versus multiple instance learning: an empirical comparison. ICML (2005)
Thomas Brow, Burr Settles, Mark Craven
Classifying Biomedical Articles by Making Localized Decisions. TREC (2005)
Keith Noto, Mark Craven
Learning Regulatory Network Models that Represent Regulator States and Roles. Regulatory Genomics (2004)
Aaron E. Darling, Bob Mau, Mark Craven, Nicole T. Perna
Multiple Alignment of Rearranged Genomes. CSB (2004)
Burr Settles, Mark Craven
Exploiting Zone Information, Syntactic Rules, and Informative Terms in Gene Ontology Annotation of Biomedical Documents. TREC (2004)
Joseph Bockhorst, Mark Craven
Markov Networks for Detecting Overalpping Elements in Sequence Data. NIPS (2004)
Marios Skounakis, Mark Craven
Evidence combination in biomedical natural-language processing. BIOKDD (2003)
David Page, Mark Craven
Biological applications of multi-relational data mining. SIGKDD Explor. 5 (1) (2003)
Marios Skounakis, Mark Craven, Soumya Ray
Hierarchical Hidden Markov Models for Information Extraction. IJCAI (2003)
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)
Mark Craven
The Genomics of a Signaling Pathway: A KDD Cup Challenge Task. SIGKDD Explor. 4 (2) (2002)
Joseph Bockhorst, Mark Craven
Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. ICML (2002)
Mark Craven, Seán Slattery
Relational Learning with Statistical Predicate Invention: Better Models for Hypertext. Mach. Learn. 43 (1/2) (2001)
Joseph Bockhorst, Mark Craven
Refining the Structure of a Stochastic Context-Free Grammar. IJCAI (2001)
Soumya Ray, Mark Craven
Representing Sentence Structure in Hidden Markov Models for Information Extraction. IJCAI (2001)
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) (2000)
Mark Craven, Johan Kumlien
Constructing Biological Knowledge Bases by Extracting Information from Text Sources. ISMB (1999)
Seán Slattery, Mark Craven
Combining Statistical and Relational Methods for Learning in Hypertext Domains. ILP (1998)
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)
Mark Craven, Seán Slattery, Kamal Nigam
First-Order Learning for Web Mining. ECML (1998)
Mark Craven, Richard J. Mural, Loren J. Hauser, Edward C. Uberbacher
Predicting Protein Folding Classes without Overly Relying on Homology. ISMB (1995)
Jeffrey C. Jackson, Mark Craven
Learning Sparse Perceptrons. NIPS (1995)