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SGP
2007
13 years 10 months ago
Data-dependent MLS for faithful surface approximation
In this paper we present a high-fidelity surface approximation technique that aims at a faithful reconstruction of piecewise-smooth surfaces from a scattered point set. The presen...
Yaron Lipman, Daniel Cohen-Or, David Levin
ADCM
2008
136views more  ADCM 2008»
13 years 7 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
STOC
2005
ACM
174views Algorithms» more  STOC 2005»
14 years 7 months ago
On the average case performance of some greedy approximation algorithms for the uncapacitated facility location problem
In combinatorial optimization, a popular approach to NP-hard problems is the design of approximation algorithms. These algorithms typically run in polynomial time and are guarante...
Abraham Flaxman, Alan M. Frieze, Juan Carlos Vera
SDM
2007
SIAM
106views Data Mining» more  SDM 2007»
13 years 9 months ago
Approximating Representations for Large Numerical Databases
The paper introduces a notion of support for realvalued functions. It is shown how to approximate supports of a large class of functions based on supports of so called polynomial ...
Szymon Jaroszewicz, Marcin Korzen