Authors
Thomas G Dietterich
Publication date
2002
Source
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshops SSPR 2002 and SPR 2002 Windsor, Ontario, Canada, August 6–9, 2002 Proceedings
Pages
15-30
Publisher
Springer Berlin Heidelberg
Description
Statistical learning problems in many fields involve sequential data. This paper formalizes the principal learning tasks and describes the methods that have been developed within the machine learning research community for addressing these problems. These methods include sliding window methods, recurrent sliding windows, hidden Markov models, conditional random fields, and graph transformer networks. The paper also discusses some open research issues.
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Scholar articles
TG Dietterich - Structural, Syntactic, and Statistical Pattern Recognition …, 2002