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125
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SOCIALCOM
2010
15 years 9 days ago
2010
The typical task of unsupervised learning is to organize data, for example into clusters, typically disjoint clusters (eg. the K-means algorithm). One would expect (for example) a...
148
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ICASSP
2011
IEEE
14 years 6 months ago
2011
IEEE
This paper applies affinity propagation (AP) to develop distributed solutions for routing over networks. AP is a message passing algorithm for unsupervised learning. This paper d...
120
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IDA
2001
Springer
15 years 6 months ago
2001
Springer
Abstract. We propose a new unsupervised training method for acquiring probability models that accurately segment Chinese character sequences into words. By constructing a core lexi...
129
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CORR
2002
Springer
15 years 2 months ago
2002
Springer
This paper describes the results of some experiments exploring statistical methods to infer syntactic categories from a raw corpus in an unsupervised fashion. It shares certain po...
150
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IDA
2006
Springer
15 years 2 months ago
2006
Springer
We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...