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NIPS
2008
11 years 2 months ago
Supervised Exponential Family Principal Component Analysis via Convex Optimization
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
Yuhong Guo
ICML
2009
IEEE
12 years 2 months ago
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
Linli Xu, Martha White, Dale Schuurmans
GECCO
2008
Springer
139views Optimization» more  GECCO 2008»
11 years 2 months ago
Coordinate change operators for genetic algorithms
This paper studies the issue of space coordinate change in genetic algorithms, based on two methods: convex quadratic approximations, and principal component analysis. In both met...
Elizabeth F. Wanner, Eduardo G. Carrano, Ricardo H...
CORR
2010
Springer
189views Education» more  CORR 2010»
10 years 12 months ago
Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and ef´Čüciently computable, it ...
Huan Xu, Constantine Caramanis, Sujay Sanghavi
ICCV
2003
IEEE
12 years 3 months ago
Images as Bags of Pixels
We propose modeling images and related visual objects as bags of pixels or sets of vectors. For instance, gray scale images are modeled as a collection or bag of (X, Y, I) pixel v...
Tony Jebara
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