30 search results - page 2 / 6 » Random Features for Large-Scale Kernel Machines |
BMVC
2010
13 years 3 months ago
2010
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
ALT
2003
Springer
14 years 2 months ago
2003
Springer
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
DAGM
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
SLSFS
2005
Springer
13 years 10 months ago
2005
Springer
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...