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» Constructing Visual Models with a Latent Space Approach
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NIPS
2008
13 years 7 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
JMLR
2010
119views more  JMLR 2010»
13 years 17 days ago
Factorized Orthogonal Latent Spaces
Existing approaches to multi-view learning are particularly effective when the views are either independent (i.e, multi-kernel approaches) or fully dependent (i.e., shared latent ...
Mathieu Salzmann, Carl Henrik Ek, Raquel Urtasun, ...
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
14 years 6 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
PAMI
2012
11 years 8 months ago
Exploring Context and Content Links in Social Media: A Latent Space Method
—Social media networks contain both content and context-specific information. Most existing methods work with either of the two for the purpose of multimedia mining and retrieva...
Guo-Jun Qi, Charu C. Aggarwal, Qi Tian, Heng Ji, T...
SMC
2010
IEEE
202views Control Systems» more  SMC 2010»
13 years 4 months ago
Evaluating the performance of nonnegative matrix factorization for constructing semantic spaces: Comparison to latent semantic a
—This study examines the ability of nonnegative matrix factorization (NMF) as a method for constructing semantic spaces, in which the meaning of each word is represented by a hig...
Akira Utsumi