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» Subspace Analysis Using Random Mixture Models
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ICA
2010
Springer
13 years 6 months ago
Second Order Subspace Analysis and Simple Decompositions
Abstract. The recovery of the mixture of an N-dimensional signal generated by N independent processes is a well studied problem (see e.g. [1,10]) and robust algorithms that solve t...
Harold W. Gutch, Takanori Maehara, Fabian J. Theis
CVPR
2004
IEEE
14 years 9 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Vladimir Pavlovic
PAKDD
2005
ACM
184views Data Mining» more  PAKDD 2005»
14 years 29 days ago
Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Luo Si, Rong Jin
ICCV
1999
IEEE
13 years 11 months ago
Multi-Frame Optical Flow Estimation using Subspace Constraints
We show that the set of all ow- elds in a sequence of frames imaging a rigid scene resides in a lowdimensional linear subspace. Based on this observation, we develop a method for ...
Michal Irani
TMI
2010
182views more  TMI 2010»
13 years 5 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern