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UAI
2004
15 years 8 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
ML
2010
ACM
193views Machine Learning» more  ML 2010»
15 years 2 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
ICML
2006
IEEE
16 years 8 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade
ISBI
2007
IEEE
16 years 1 months ago
Dicovery of "biomarkers" for Alzheimer's Disease Prediction from Structural MR Images
We propose a computational framework for learning predictive image features as “biomarkers” for Alzheimer’s Disease discrimination using high-resolutionMagnetic Resonance (M...
Yanxi Liu, Leonid Teverovskiy, Oscar L. Lopez, How...
CVPR
2010
IEEE
15 years 10 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu