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JMLR
2010
132views more  JMLR 2010»
15 years 1 months ago
On the Impact of Kernel Approximation on Learning Accuracy
Kernel approximation is commonly used to scale kernel-based algorithms to applications containing as many as several million instances. This paper analyzes the effect of such appr...
Corinna Cortes, Mehryar Mohri, Ameet Talwalkar
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 9 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
ECAI
2008
Springer
15 years 8 months ago
An Analysis of Bayesian Network Model-Approximation Techniques
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
Adamo Santana, Gregory M. Provan
CORR
2010
Springer
137views Education» more  CORR 2010»
15 years 6 months ago
Local algorithms in (weakly) coloured graphs
A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum ...
Matti Åstrand, Valentin Polishchuk, Joel Ryb...
IPL
2007
81views more  IPL 2007»
15 years 6 months ago
Linear-time algorithms for problems on planar graphs with fixed disk dimension
The disk dimension of a planar graph G is the least number k for which G embeds in the plane minus k open disks, with every vertex on the boundary of some disk. Useful properties ...
Faisal N. Abu-Khzam, Michael A. Langston