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ICPR
2006
IEEE
14 years 9 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
CIKM
2010
Springer
13 years 7 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
ICA
2007
Springer
14 years 2 months ago
Supervised and Semi-supervised Separation of Sounds from Single-Channel Mixtures
In this paper we describe a methodology for model-based single channel separation of sounds. We present a sparse latent variable model that can learn sounds based on their distribu...
Paris Smaragdis, Bhiksha Raj, Madhusudana V. S. Sh...
LREC
2008
153views Education» more  LREC 2008»
13 years 10 months ago
Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis
We present results from using Random Indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. We compare Latent Semantic Analysis, Random ...
Linus Sellberg, Arne Jönsson
PAMI
2012
11 years 11 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...