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» Fast Feature Selection Using Fractal Dimension
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CVPR
2000
IEEE
13 years 12 months ago
A Fast and Robust Approach to Recovering Structure and Motion from Live Video Frames
This paper describes a fast and robust approach to recovering structure and motion from video frames. It rst describes a robust recursive factorization method for ane projection...
Takeshi Kurata, Jun Fujiki, Masakatsu Kourogi, Kat...
ICCV
2009
IEEE
15 years 12 days ago
Efficient subset selection based on the Renyi entropy
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
CCGRID
2004
IEEE
13 years 11 months ago
Effective use of reputation in peer-to-peer environments
Peer-to-peer environments have become popular as a framework for exchange of services. In these environments, certain peers may fail to provide their services. Reputation can be a...
Thanasis G. Papaioannou, George D. Stamoulis
PAKM
2008
13 years 8 months ago
Classifying Digital Resources in a Practical and Coherent Way with Easy-to-Get Features
With a rich variety of forms and types, digital resources are complex data objects. They grows fast in volume on the Web, but hard to be classified efficiently. The paper presents ...
Chong Chen, Hongfei Yan, Xiaoming Li
ECML
2007
Springer
14 years 1 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales