1183 search results - page 78 / 237 » Learning Process Models with Missing Data |
125
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ICML
2008
IEEE
16 years 2 months ago
2008
IEEE
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...
117
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NIPS
1998
15 years 2 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
117
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NIPS
2008
15 years 2 months ago
2008
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
108
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TSD
2009
Springer
15 years 8 months ago
2009
Springer
Abstract. The discovery of words by young infants involves two interrelated processes: (a) the detection of recurrent word-like acoustic patterns in the speech signal, and (b) cros...
144
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KDD
2012
ACM
13 years 3 months ago
2012
ACM
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...