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MM
2005
ACM
209views Multimedia» more  MM 2005»
13 years 11 months ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang
ICML
2008
IEEE
14 years 6 months ago
Topologically-constrained latent variable models
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...
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jo...
MM
2004
ACM
154views Multimedia» more  MM 2004»
13 years 11 months ago
PLSA-based image auto-annotation: constraining the latent space
We address the problem of unsupervised image auto-annotation with probabilistic latent space models. Unlike most previous works, which build latent space representations assuming ...
Florent Monay, Daniel Gatica-Perez
HUMO
2007
Springer
14 years 6 days ago
Modeling Human Locomotion with Topologically Constrained Latent Variable Models
Abstract. Learned, activity-specific motion models are useful for human pose and motion estimation. Nevertheless, while the use of activityspecific models simplifies monocular t...
Raquel Urtasun, David J. Fleet, Neil D. Lawrence
ACL
2012
11 years 8 months ago
Fine Granular Aspect Analysis using Latent Structural Models
In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify ...
Lei Fang, Minlie Huang