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ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 7 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
COMPUTING
2004
80views more  COMPUTING 2004»
13 years 7 months ago
An Efficient Multigrid Solver based on Distributive Smoothing for Poroelasticity Equations
In this paper, we present a robust distributive smoother in a multigrid method for the system of poroelasticity equations. Within the distributive framework, we deal with a decoup...
R. Wienands, Francisco J. Gaspar, Francisco J. Lis...
ICRA
1999
IEEE
82views Robotics» more  ICRA 1999»
13 years 12 months ago
An Investigation into Non-Smooth Locomotion
We analyze a class of mechanisms that locomote by switching between constraints. Because of the hybrid nature of such systems, most of the existing analysis tools, developed prima...
Milos Zefran, Francesco Bullo, Jim Radford
ICANN
2005
Springer
14 years 1 months ago
Smooth Bayesian Kernel Machines
Abstract. In this paper, we consider the possibility of obtaining a kernel machine that is sparse in feature space and smooth in output space. Smooth in output space implies that t...
Rutger W. ter Borg, Léon J. M. Rothkrantz
CVPR
2008
IEEE
13 years 9 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang