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» Learning the Relative Importance of Features in Image Data
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NIPS
1997
15 years 1 months ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
BMCBI
2011
14 years 3 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
GLOBECOM
2009
IEEE
15 years 6 months ago
Movement Recognition Using Body Area Networks
—Significant research has been done on recognizing the daily activities using acceleration data but few works have focused on classifying the movements comprising an activity du...
John Paul Varkey, Dario Pompili
AAAI
2007
15 years 2 months ago
A Randomized String Kernel and Its Application to RNA Interference
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
Shibin Qiu, Terran Lane, Ljubomir J. Buturovic
PR
2010
129views more  PR 2010»
14 years 10 months ago
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne