- Bayesian Biosurveillance Using Multiple Data Streams Weng-Keen Wong,1
- Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs
- Interacting Meaningfully with Machine Learning Systems: Three Experiments1
- Fixing the Program My Computer Learned: Barriers for End Users, Barriers for the Machine
- Markov Blanket Feature Selection for Support Vector Machines Jianqiang Shen and Lida Li and Weng-Keen Wong
- Integrating Rich User Feedback into Intelligent User Interfaces
- Modeling Clinician Detection Time of a Disease Outbreak Due to Inhalational Anthrax
- The Effect of Inferring Work Location from Home Location in Performing Bayesian Biosurveillance
- Bayesian Biosurveillance of Disease Outbreaks Gregory F. Cooper
- Category Detection Using Hierarchical Mean Shift Pavan Vatturi
- Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks Weng-Keen Wong
- Optimal Reinsertion: A new search operator for accelerated and more accurate Bayesian network structure learning
- A Generalization of the Standard AMOC Curve Yanna Shen, Weng-Keen Wong, Gregory F. Cooper
- End-User Feature Labeling: A Locally-Weighted Regression Approach
- Population-wide Anomaly Detection Weng-Keen Wong,
- Proceedings of the International Conference on Information and Automation, December 15-18, 2005, Colombo, Sri Lanka. Abstract--This paper reviews three successful statistical data
- Structure Refinement in First Order Conditional Influence Language Sriraam Natarajan natarasr@eecs.oregonstate.edu
- Bi-level Optimization for Learning Cost Functions from Demonstration Chris Mills-Price, Weng-Keen Wong, Prasad Tadepalli and Ethan Dereszynski
- End-User Feature Labeling via Locally Weighted Logistic Regression Weng-Keen Wong11
- Multi-label Classification for Species Distribution Modeling Jun Yu, Weng-Keen Wong, Tom Dietterich {yuju,wong,tgd}@eecs.oregonstate.edu
- Mini-Crowdsourcing End-User Assessment of Intelligent Assistants
- Towards Recognizing "Cool": Can End Users Help Computer Vision Recognize
