Embedded Machine Learning: Papers from the AAAI Fall Symposium
Rich Caruana, Tom Dietterich, Dragos Margineantu, Organizers
November 12–14, 2015, Arlington, Virginia
Technical Report FS-15-04
30 pp.
Electronic Version of the Technical Report (Download only): $10.00 (Special Introductory Price)
Softcover version of the technical report: $25.00 softcover
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ISBN 978-1-57735-750-6
The Embedded Machine Learning symposium will study the challenges that arise when machine learning is embedded as a component in large complex systems. Papers in this report include Toward Embedding Bayesian Optimization in the Lab: Reasoning about Resource and Actions; Adaptive Treatment Allocation Using Sub-Sampled Gaussian Processes; and Saul: Towards Declarative Learning Based Programming.