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NPL
2008
130views more  NPL 2008»
13 years 7 months ago
Adaptive Inverse Control of Excitation System with Actuator Uncertainty
: - This paper addresses an inverse controller design for excitation system with changing parameters and nonsmooth nonlinearities in the actuator. The existence of such nonlinearit...
Xiaofang Yuan, Yaonan Wang, Liang-Hong Wu
IJCNN
2007
IEEE
14 years 2 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
JMLR
2010
152views more  JMLR 2010»
13 years 2 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
VEE
2012
ACM
322views Virtualization» more  VEE 2012»
12 years 3 months ago
Modeling virtualized applications using machine learning techniques
With the growing adoption of virtualized datacenters and cloud hosting services, the allocation and sizing of resources such as CPU, memory, and I/O bandwidth for virtual machines...
Sajib Kundu, Raju Rangaswami, Ajay Gulati, Ming Zh...
EMNLP
2009
13 years 5 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti