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» Learning Probabilistic Models of Word Sense Disambiguation
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134
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MM
2005
ACM
209views Multimedia» more  MM 2005»
15 years 9 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
162
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JIIS
2002
168views more  JIIS 2002»
15 years 3 months ago
Hidden Markov Models for Text Categorization in Multi-Page Documents
In the traditional setting, text categorization is formulated as a concept learning problem where each instance is a single isolated document. However, this perspective is not appr...
Paolo Frasconi, Giovanni Soda, Alessandro Vullo
135
Voted
CRV
2008
IEEE
295views Robotics» more  CRV 2008»
15 years 10 months ago
3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
Kooksang Moon, Vladimir Pavlovic
135
Voted
EMNLP
2010
15 years 1 months ago
Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification
This paper addresses the problem of learning to map sentences to logical form, given training data consisting of natural language sentences paired with logical representations of ...
Tom Kwiatkowksi, Luke S. Zettlemoyer, Sharon Goldw...
143
Voted
MLMI
2007
Springer
15 years 9 months ago
Using Prosodic Features in Language Models for Meetings
Abstract. Prosody has been actively studied as an important knowledge source for speech recognition and understanding. In this paper, we are concerned with the question of exploiti...
Songfang Huang, Steve Renals