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WEBI
2010
Springer
14 years 9 months ago
DSP: Robust Semi-supervised Dimensionality Reduction Using Dual Subspace Projections
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Su Yan, Sofien Bouaziz, Dongwon Lee
TSMC
2002
144views more  TSMC 2002»
14 years 11 months ago
COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules
This paper introduces a new learning methodology to quickly generate accurate and simple linguistic fuzzy models, the cooperative rules (COR) methodology. It acts on the consequent...
Jorge Casillas, Oscar Cordón, Francisco Her...
ICRA
2005
IEEE
129views Robotics» more  ICRA 2005»
15 years 5 months ago
Fast Computational Methods for Visually Guided Robots
— This paper proposes numerical algorithms for reducing the computational cost of semi-supervised and active learning procedures for visually guided mobile robots from O(M3 ) to ...
Maryam Mahdaviani, Nando de Freitas, Bob Fraser, F...
SIAMJO
2008
139views more  SIAMJO 2008»
14 years 11 months ago
An Augmented Primal-Dual Method for Linear Conic Programs
We propose a new iterative approach for solving linear programs over convex cones. Assuming that Slaters condition is satisfied, the conic problem is transformed to the minimizatio...
Florian Jarre, Franz Rendl
COLT
2010
Springer
14 years 9 months ago
Composite Objective Mirror Descent
We present a new method for regularized convex optimization and analyze it under both online and stochastic optimization settings. In addition to unifying previously known firstor...
John Duchi, Shai Shalev-Shwartz, Yoram Singer, Amb...