Optimal Partitioning for Classification and Regression Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Watch what I do: programming by demonstration
Watch what I do: programming by demonstration
Eager: programming repetitive tasks by demonstration
Watch what I do
Building applications using only demonstration
IUI '98 Proceedings of the 3rd international conference on Intelligent user interfaces
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Version Space Algebra and its Application to Programming by Demonstration
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning programs from traces using version space algebra
Proceedings of the 2nd international conference on Knowledge capture
Sheepdog: learning procedures for technical support
Proceedings of the 9th international conference on Intelligent user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Similarity-based alignment and generalization
ECML'05 Proceedings of the 16th European conference on Machine Learning
Input-output HMMs for sequence processing
IEEE Transactions on Neural Networks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Toward harnessing user feedback for machine learning
Proceedings of the 12th international conference on Intelligent user interfaces
Proceedings of the 12th international conference on Intelligent user interfaces
Integrating rich user feedback into intelligent user interfaces
Proceedings of the 13th international conference on Intelligent user interfaces
Recovering from errors during programming by demonstration
Proceedings of the 13th international conference on Intelligent user interfaces
Case-based reasoning for procedure learning by instruction
Proceedings of the 13th international conference on Intelligent user interfaces
Interacting meaningfully with machine learning systems: Three experiments
International Journal of Human-Computer Studies
Learning by combining observations and user edits
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Sheepdog, parallel collaborative programming-by-demonstration
Knowledge-Based Systems
A formal framework for combining natural instruction and demonstration for end-user programming
Proceedings of the 16th international conference on Intelligent user interfaces
How to serve soup: interleaving demonstration and assisted editing to support nonprogrammers
Proceedings of the 16th international conference on Intelligent user interfaces
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In this paper we introduce a new approach to Programming-by-Demonstration in which the user is allowed to explicitly edit the procedure model produced by the learning algorithm while demonstrating the task. We describe a new algorithm, Augmentation-Based Learning, that supports this approach by considering both demonstrations and edits as constraints on the hypothesis space, and resolving con icts in favor of edits.