Automated reasoning and the applications of decision making
We pursue research on automated reasoning, adaptation, and the theories and applications of decision making and learning. Our research goals include learning from data and data mining. By building software that automatically learns from data, we design applications that have new functions and flexibility. Our research focuses on using statistical methods for the development of more advanced, intelligent computer systems.
Nathan Wiebe, Ashish Kapoor, and Krysta M. Svore, Quantum Nearest-neighbor Algorithms for Machine Learning, in Quantum Information and Computation, vol. 15, no. 3&4, pp. 0318-0358, Rinton Press, March 2015.
Elad Yom-Tov, Ingemar Johansson Cox, and Vasileios Lampos, Learning about health and medicine from Internet data, ACM – Association for Computing Machinery, 2 February 2015.
Lihong Li, Offline Evaluation and Optimization for Interactive Systems, in Proceedings of the 8th ACM International Conference on Web Search and Data Mining, ACM – Association for Computing Machinery, February 2015.
Lihong Li, Jin Young Kim, and Imed Zitouni, Toward Predicting the Outcome of an A/B Experiment for Search Relevance, in Proceedings of the 8th ACM International Conference on Web Search and Data Mining, ACM – Association for Computing Machinery, February 2015.
Asli Celikyilmaz and Dilek Hakkani-Tur, INVESTIGATION OF ENSEMBLE MODELS FOR SEQUENCE LEARNING, IEEE – Institute of Electrical and Electronics Engineers, 1 February 2015.
- FaST-LMM (FActored Spectrally Transformed Linear Mixed Models)
- Team Three Rs
- Fully Articulated Hand Tracking
- ICE: Interative Classification and Entity Extraction
- Learning to be a depth camera for close-range human capture and interaction
- Deep Learning for Natural Language Processing: Theory and Practice (CIKM2014 Tutorial)
- User-Specific Hand Modeling from Monocular Depth Sequences
- Real-Time RGB-D Camera Relocalization
- Microsoft 3-Handpose dataset
- ViiBoard: Vision-enhanced Immersive Interaction with Touch Board
- Alternating Minimization for Non-convex Optimization Problems
- MSR-Bing Image Retrieval Challenge (IRC)
- Urban Air
- Voice Conversion with Neural Network
- Dialog and Conversational Systems Research
- Filter Forests for Learning Data-Dependent Convolutional Kernels
- Spatial Crowdsourcing