Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. - Mark W. Craven; David Page; Jude W. Shavlik; Joseph Bockhorst; Jeremy D. Glasner (ICML, 2000)

A Probabilistic Learning Approach to Whole-Genome Operon Prediction. - Mark W. Craven; David Page; Jude W. Shavlik; Joseph Bockhorst; Jeremy D. Glasner (ISMB, 2000)

Refining the Structure of a Stochastic Context-Free Grammar. - Joseph Bockhorst; Mark Craven (IJCAI, 2001)

Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. - Joseph Bockhorst; Mark Craven (ICML, 2002)

Predicting bacterial transcription units using sequence and expression data. - Joseph Bockhorst; Yu Qiu; Jeremy D. Glasner; Mingzhu Liu; Frederick R. Blattner; Mark Craven (ISMB (Supplement of Bioinformatics), 2003)

A Bayesian Network Approach to Operon Prediction. - Joseph Bockhorst; Mark W. Craven; David Page; Jude W. Shavlik; Jeremy D. Glasner (Bioinform., 2003)

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

Markov Networks for Detecting Overalpping Elements in Sequence Data. - Joseph Bockhorst; Mark Craven (NIPS, 2004)

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

Discovering Patterns in Biological Sequences by Optimal Segmentation. - Joseph Bockhorst; Nebojsa Jojic (UAI, 2007)

Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting. - Chris Barber; Joseph Bockhorst; Paul Roebber (NIPS, 2010)

A Machine Learning Approach to Identifying Sections in Legal Briefs. - Scott Vanderbeck; Joseph Bockhorst; Chad Oldfather (MAICS, 2011)

Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction. - Joe Bockhorst; Yingjian Wang; Sukrat Gupta; Maleeha Qazi; Mingju Sun; Glenn Fung (ICMLA, 2016)

Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center. - Joseph Bockhorst; Shi Yu; Luisa F. Polanía; Glenn Fung (ECML/PKDD (3), 2017)

Using Discriminative Graphical Models for Insurance Recommender Systems. - Teja Kanchinadam; Maleeha Qazi; Joseph Bockhorst; Mary Y. Morell; Katie J. Meissner; Glenn Fung (ICMLA, 2018)

Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces. - Joseph Bockhorst; Devin Conathan; Glenn Moo Fung (AAAI, 2019)

Designing and deploying insurance recommender systems using machine learning. - Maleeha Qazi; Kaya Tollas; Teja Kanchinadam; Joseph Bockhorst; Glenn Fung (WIREs Data Mining Knowl. Discov., 2020)

Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center. - Teja Kanchinadam; Zihang Meng; Joseph Bockhorst; Vikas Singh; Glenn Fung (CoRR, 2021)