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CORR
2010
Springer
128views Education» more  CORR 2010»
15 years 6 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
NN
2006
Springer
15 years 6 months ago
Machine learning in sedimentation modelling
The paper presents machine learning (ML) models that predict sedimentation in the harbour basin of the Port of Rotterdam. The important factors affecting the sedimentation process...
Biswanath Bhattacharya, Dimitri P. Solomatine
SIAMJO
2008
104views more  SIAMJO 2008»
15 years 6 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd
CANDC
2005
ACM
15 years 6 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
ICCV
2009
IEEE
15 years 4 months ago
Learning image similarity from Flickr groups using Stochastic Intersection Kernel MAchines
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if th...
Gang Wang, Derek Hoiem, David A. Forsyth