Joseph Bockhorst

Joseph Bockhorst, Nebojsa Jojic: Discovering Patterns in Biological Sequences by Optimal Segmentation. CoRR abs/1206.5256 (2012)

Scott Vanderbeck, Joseph Bockhorst, Chad Oldfather: A Machine Learning Approach to Identifying Sections in Legal Briefs. MAICS 2011: 16-22

Chris Barber, Joseph Bockhorst, Paul Roebber: Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting. NIPS 2010: 136-144

Yue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven: Connecting quantitative regulatory-network models to the genome. ISMB/ECCB (Supplement of Bioinformatics) 2007: 367-376

Joseph Bockhorst, Nebojsa Jojic: Discovering Patterns in Biological Sequences by Optimal Segmentation. UAI 2007: 17-24

Joseph Bockhorst, Irene M. Ong: FOIL-D: Efficiently Scaling FOIL for Multi-relational Data Mining of Large Datasets. ILP 2004: 63-79

Joseph Bockhorst, Mark Craven: Markov Networks for Detecting Overalpping Elements in Sequence Data. NIPS 2004

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)

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: Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. ICML 2002: 43-50

Joseph Bockhorst, Mark Craven: Refining the Structure of a Stochastic Context-Free Grammar. IJCAI 2001: 1315-1322

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