Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Proceedings of the 8th international conference on Intelligent user interfaces
a CAPpella: programming by demonstration of context-aware applications
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CueFlik: interactive concept learning in image search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The Journal of Machine Learning Research
Learning to generalize for complex selection tasks
Proceedings of the 14th international conference on Intelligent user interfaces
Active learning with near misses
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Overview based example selection in end user interactive concept learning
Proceedings of the 22nd annual ACM symposium on User interface software and technology
Examining multiple potential models in end-user interactive concept learning
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CueT: human-guided fast and accurate network alarm triage
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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End-user interactive machine learning is a promising tool for enhancing human capabilities with large data. Recent work has shown that we can create end-user interactive machine learning systems for specific applications. However, we still lack a generalized understanding of how to design effective end-user interaction with interactive machine learning systems. My dissertation work aims to advance our understanding of this question by investigating new techniques that move beyond naïve or ad-hoc approaches and balance the needs of both end-users and machine learning algorithms. Although these explorations are grounded in specific applications, we endeavored to design strategies independent of application or domain specific features. As a result, our findings can inform future end-user interaction with machine learning systems.