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192
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JMLR
2010
144views more  JMLR 2010»
15 years 2 months ago
Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
Alexander Ilin, Tapani Raiko
189
Voted
JMLR
2010
101views more  JMLR 2010»
15 years 2 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
194
Voted
TSP
2010
15 years 2 months ago
On entropy rate for the complex domain and its application to i.i.d. sampling
We derive the entropy rate formula for a complex Gaussian random process by using a widely linear model. The resulting expression is general and applicable to both circular and non...
Wei Xiong, Hualiang Li, Tülay Adali, Yi-Ou Li...
CVPR
2012
IEEE
13 years 9 months ago
Background segmentation with feedback: The Pixel-Based Adaptive Segmenter
In this paper we present a novel method for foreground segmentation. Our proposed approach follows a nonparametric background modeling paradigm, thus the background is modeled by ...
Martin Hofmann 0011, Philipp Tiefenbacher, Gerhard...
IJMMS
2006
171views more  IJMMS 2006»
15 years 7 months ago
The role of moderating factors in user technology acceptance
Along with increasing investments in new technologies, user technology acceptance becomes a frequently studied topic in the information systems discipline. The last two decades ha...
Heshan Sun, Ping Zhang 0002