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Joseph Bockhorst
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Journal Articles
- 2020
- [j2]Maleeha Qazi, Kaya Tollas, Teja Kanchinadam, Joseph Bockhorst, Glenn Fung:
Designing and deploying insurance recommender systems using machine learning. WIREs Data Mining Knowl. Discov. 10(4) (2020) - 2003
- [j1]Joseph Bockhorst, Mark W. Craven, David Page, Jude W. Shavlik, Jeremy D. Glasner:
A Bayesian Network Approach to Operon Prediction. Bioinform. 19(10): 1227-1235 (2003)
Conference and Workshop Papers
- 2019
- [c15]Joseph Bockhorst, Devin Conathan, Glenn Moo Fung:
Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces. AAAI 2019: 9422-9427 - 2018
- [c14]Teja Kanchinadam, Maleeha Qazi, Joseph Bockhorst, Mary Y. Morell, Katie J. Meissner, Glenn Fung:
Using Discriminative Graphical Models for Insurance Recommender Systems. ICMLA 2018: 421-428 - 2017
- [c13]Joseph Bockhorst, Shi Yu, Luisa F. Polanía, Glenn Fung:
Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center. ECML/PKDD (3) 2017: 179-190 - 2016
- [c12]Joe Bockhorst, Yingjian Wang, Sukrat Gupta, Maleeha Qazi, Mingju Sun, Glenn Fung:
Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction. ICMLA 2016: 846-852 - 2011
- [c11]Scott Vanderbeck, Joseph Bockhorst, Chad Oldfather:
A Machine Learning Approach to Identifying Sections in Legal Briefs. MAICS 2011: 16-22 - 2010
- [c10]Chris Barber, Joseph Bockhorst, Paul Roebber:
Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting. NIPS 2010: 136-144 - 2007
- [c9]Yue Pan, Tim Durfee, Joseph Bockhorst, Mark Craven:
Connecting quantitative regulatory-network models to the genome. ISMB/ECCB (Supplement of Bioinformatics) 2007: 367-376 - [c8]Joseph Bockhorst, Nebojsa Jojic:
Discovering Patterns in Biological Sequences by Optimal Segmentation. UAI 2007: 17-24 - 2004
- [c7]Joseph Bockhorst, Irene M. Ong:
FOIL-D: Efficiently Scaling FOIL for Multi-relational Data Mining of Large Datasets. ILP 2004: 63-79 - [c6]Joseph Bockhorst, Mark Craven:
Markov Networks for Detecting Overalpping Elements in Sequence Data. NIPS 2004: 193-200 - 2003
- [c5]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 - 2002
- [c4]Joseph Bockhorst, Mark Craven:
Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. ICML 2002: 43-50 - 2001
- [c3]Joseph Bockhorst, Mark Craven:
Refining the Structure of a Stochastic Context-Free Grammar. IJCAI 2001: 1315-1322 - 2000
- [c2]Mark W. 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 - [c1]Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner:
A Probabilistic Learning Approach to Whole-Genome Operon Prediction. ISMB 2000: 116-127
Informal and Other Publications
- 2021
- [i2]Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh, Glenn Fung:
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center. CoRR abs/2102.00420 (2021) - 2012
- [i1]Joseph Bockhorst, Nebojsa Jojic:
Discovering Patterns in Biological Sequences by Optimal Segmentation. CoRR abs/1206.5256 (2012)
Coauthor Index
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