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ICML
2007
IEEE
14 years 8 months ago
Multiclass multiple kernel learning
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Alexander Zien, Cheng Soon Ong
SSPR
2004
Springer
14 years 25 days ago
Optimizing Classification Ensembles via a Genetic Algorithm for a Web-Based Educational System
Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost ...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
COLT
2010
Springer
13 years 5 months ago
Hedging Structured Concepts
We develop an online algorithm called Component Hedge for learning structured concept classes when the loss of a structured concept sums over its components. Example classes inclu...
Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivine...
VIS
2009
IEEE
399views Visualization» more  VIS 2009»
14 years 8 months ago
Visual Human+Machine Learning
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combine...
Raphael Fuchs, Jürgen Waser, Meister Eduard Gr...
CVPR
2012
IEEE
11 years 10 months ago
Beyond spatial pyramids: Receptive field learning for pooled image features
In this paper we examine the effect of receptive field designs on classification accuracy in the commonly adopted pipeline of image classification. While existing algorithms us...
Yangqing Jia, Chang Huang, Trevor Darrell