Algorithmic Learning Theory: 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings

by Marcus Hutter (Editor), Rocco A. Servedio (Editor), Eiji Takimoto

This book constitutes the refereed proceedings of the 21th International Conference on Algorithmic Learning Theory, ALT 2010, held in Canberra, Australia, in October 2010, co-located with the 13th International Conference on Discovery Science, DS 2010. The 26 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 44 submissions. The papers are divided into topical sections of papers on statistical learning; grammatical inference and graph learning; probably approximately correct learning; query learning and algorithmic teaching; on-line learning; inductive inference; reinforcement learning; and on-line learning and kernel methods.

424 pages, Paperback

First published September 28, 2008

Reviews

[Jovany Agathe · Rating 4 out of 5]

Deep Learning has started to take over a lot of things in natural language processing, so we’re trying to follow this technology, and we think this will work really well here. We can actually make a conversational engine like Alexa or Siri but one that’s a medical expert that knows all of those articles at a sufficient level. And we’re going to use the medical standards and conventions for understanding the text, so we can ensure sufficient understanding to answer some challenging queries.