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128
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IJCNLP
2005
Springer
15 years 8 months ago
Automatic Image Annotation Using Maximum Entropy Model
Automatic image annotation is a newly developed and promising technique to provide semantic image retrieval via text descriptions. It concerns a process of automatically labeling t...
Wei Li, Maosong Sun
177
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JMLR
2012
13 years 5 months ago
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
127
Voted
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 2 months ago
A Spectral Algorithm for Learning Hidden Markov Models
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Daniel Hsu, Sham M. Kakade, Tong Zhang
100
Voted
LREC
2010
169views Education» more  LREC 2010»
15 years 4 months ago
Using Comparable Corpora to Adapt a Translation Model to Domains
Statistical machine translation (SMT) requires a large parallel corpus, which is available only for restricted language pairs and domains. To expand the language pairs and domains...
Hiroyuki Kaji, Takashi Tsunakawa, Daisuke Okada
77
Voted
ACL
2006
15 years 4 months ago
Scalable Inference and Training of Context-Rich Syntactic Translation Models
Statistical MT has made great progress in the last few years, but current translation models are weak on re-ordering and target language fluency. Syntactic approaches seek to reme...
Michel Galley, Jonathan Graehl, Kevin Knight, Dani...