Phillip Odom
ABSTRACT
Machine learning methods have made significant progress across many application areas. However, the power to utilize these methods has remained out of reach for many domain experts due to the background knowledge required to tune parameters and debug errors. Our HuManIC tool eases this requirement for relational models by 1) providing three different ways of meaningfully displaying the model and 2) by allowing the user to intuitively edit the model.
- Shuo Chang, Peng Dai, Lichan Hong, Cheng Sheng, Tianjiao Zhang, and Ed H. Chi. 2016. AppGrouper: Knowledge-graph-based Interactive Clustering Tool for Mobile App Search Results. In 21<sup>st</sup> International Conference on Intelligent User Interfaces. Google Scholar
Digital Library
- Alexander Hayes, Mayukh Das, Phillip Odom, and Sriraam Natarajan. 2017. User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams. In Knowledge Capture Conference. Google ScholarDigital Library
- Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, and Samuel Kaski. 2017. Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. In 22<sup>nd</sup> International Conference on Intelligent User Interfaces. Google ScholarDigital Library
- Sriraam Natarajan, Kristian Kersting, Tushar Khot, and Jude Shavlik. 2015. Boosted Statistical Relational Learners: From Benchmarks to Data-Driven Medicine. Springer. Google ScholarDigital Library
- Phillip Odom and Sriraam Natarajan. 2016. Actively Interacting with Experts: A Probabilistic Logic Approach. In European Conference on Machine Learning and Principles of Knowledge Discovery in Databases.Google Scholar
- Alexander Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, and Christopher Re. 2016. Data Programming: Creating Large Training Sets, Quickly. In Advances in Neural Information Processing Systems. Google ScholarDigital Library
- Jaeho Shin, Sen Wu, Feiran Wang, Christopher De Sa, Ce Zhang, and Christopher Ré. 2015. Incremental Knowledge Base Construction Using DeepDive. Proc. VLDB Endow. 8 (2015), 1310--1321. Google ScholarDigital Library
Index Terms
- HuManIC: human machine interpretive control
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