Presentation | 2004/10/12 Geometrical Structure of Learning Algorithms Noboru MURATA, |
---|---|
PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In the machine learning, it is quite important how to model target problems, and also how to construct efficient algorithms in order to obtain optimal solutions. The concept of information geometry, in which geometrical structures of stochastic models are considered based on differential geometry, helps us to understand the mechanism of learning algorithms. In this article, geometrical understandings of learning algorithms are discussed, such as EM algorithm, boosting, bagging. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | information geometry / EM algorithm / boosting / bagging |
Paper # | NC2004-77 |
Date of Issue |
Conference Information | |
Committee | NC |
---|---|
Conference Date | 2004/10/12(1days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | |
Vice Chair | |
Secretary | |
Assistant |
Paper Information | |
Registration To | Neurocomputing (NC) |
---|---|
Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Geometrical Structure of Learning Algorithms |
Sub Title (in English) | |
Keyword(1) | information geometry |
Keyword(2) | EM algorithm |
Keyword(3) | boosting |
Keyword(4) | bagging |
1st Author's Name | Noboru MURATA |
1st Author's Affiliation | Waseda University() |
Date | 2004/10/12 |
Paper # | NC2004-77 |
Volume (vol) | vol.104 |
Number (no) | 349 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |