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» Learning Probabilistic Models of Link Structure
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MM
2005
ACM
140views Multimedia» more  MM 2005»
15 years 5 months ago
Topic transition detection using hierarchical hidden Markov and semi-Markov models
In this paper we introduce a probabilistic framework to exploit hierarchy, structure sharing and duration information for topic transition detection in videos. Our probabilistic d...
Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hun...
NAACL
2010
14 years 9 months ago
Context-free reordering, finite-state translation
We describe a class of translation model in which a set of input variants encoded as a context-free forest is translated using a finitestate translation model. The forest structur...
Christopher Dyer, Philip Resnik
NIPS
2004
15 years 1 months ago
Assignment of Multiplicative Mixtures in Natural Images
In the analysis of natural images, Gaussian scale mixtures (GSM) have been used to account for the statistics of filter responses, and to inspire hierarchical cortical representat...
Odelia Schwartz, Terrence J. Sejnowski, Peter Daya...
NIPS
2001
15 years 1 months ago
Grammatical Bigrams
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Mark A. Paskin
WIDM
2005
ACM
15 years 5 months ago
Web path recommendations based on page ranking and Markov models
Markov models have been widely used for modelling users' navigational behaviour in the Web graph, using the transitional probabilities between web pages, as recorded in the w...
Magdalini Eirinaki, Michalis Vazirgiannis, Dimitri...