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PR
2006
147views more  PR 2006»
13 years 10 months ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung
PR
2006
80views more  PR 2006»
13 years 10 months ago
Neighborhood size selection in the k-nearest-neighbor rule using statistical confidence
The k-nearest-neighbor rule is one of the most attractive pattern classification algorithms. In practice, the choice of k is determined by the cross-validation method. In this wor...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
SIAMJO
2008
66views more  SIAMJO 2008»
13 years 10 months ago
Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization
Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating ...
Zizhuo Wang, Song Zheng, Yinyu Ye, Stephen Boyd
SIAMJO
2008
92views more  SIAMJO 2008»
13 years 10 months ago
An Active-Set Newton Method for Mathematical Programs with Complementarity Constraints
For a mathematical program with complementarity constraints (MPCC), we propose an active-set Newton method, which has the property of local quadratic convergence under the MPCC lin...
Alexey F. Izmailov, Mikhail V. Solodov
SIAMSC
2008
167views more  SIAMSC 2008»
13 years 10 months ago
New Finite Elements for Large-Scale Simulation of Optical Waves
We present a new method to simulate optical waves in large geometries. This method is based on newly developed finite elements, so-called Trigonometric Finite Wave Elements (TFWEs)...
Britta Heubeck, Christoph Pflaum, Gunther Steinle