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NLPRS
2001
Springer
15 years 8 months ago
A Maximum Entropy Tagger with Unsupervised Hidden Markov Models
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...
Jun'ichi Kazama, Yusuke Miyao, Jun-ichi Tsujii
BSN
2009
IEEE
140views Sensor Networks» more  BSN 2009»
15 years 11 months ago
A Distributed Hidden Markov Model for Fine-grained Annotation in Body Sensor Networks
—Human movement models often divide movements into parts. In walking the stride can be segmented into four different parts, and in golf and other sports, the swing is divided int...
Eric Guenterberg, Hassan Ghasemzadeh, Roozbeh Jafa...
SIGIR
1999
ACM
15 years 8 months ago
A Hidden Markov Model Information Retrieval System
We present a new method for information retrievalusing hidden Markov models (HMMs). We develop a general framework for incorporating multiple word generation mechanisms within the...
David R. H. Miller, Tim Leek, Richard M. Schwartz
BMCBI
2010
117views more  BMCBI 2010»
15 years 4 months ago
New decoding algorithms for Hidden Markov Models using distance measures on labellings
Background: Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. Results: We give a set of algorithms to com...
Daniel G. Brown 0001, Jakub Truszkowski
ICML
2005
IEEE
16 years 5 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore