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ISAAC
2005
Springer
122views Algorithms» more  ISAAC 2005»
14 years 2 months ago
Fast k-Means Algorithms with Constant Approximation
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...
Mingjun Song, Sanguthevar Rajasekaran
IWANN
2009
Springer
14 years 1 months ago
Lower Bounds for Approximation of Some Classes of Lebesgue Measurable Functions by Sigmoidal Neural Networks
We propose a general method for estimating the distance between a compact subspace K of the space L1 ([0, 1]s ) of Lebesgue measurable functions defined on the hypercube [0, 1]s ,...
José Luis Montaña, Cruz E. Borges
ESA
2006
Springer
103views Algorithms» more  ESA 2006»
14 years 16 days ago
Greedy in Approximation Algorithms
The objective of this paper is to characterize classes of problems for which a greedy algorithm finds solutions provably close to optimum. To that end, we introduce the notion of k...
Julián Mestre
DAGSTUHL
2007
13 years 10 months ago
Approximating Solution Structure
Approximations can aim at having close to optimal value or, alternatively, they can aim at structurally resembling an optimal solution. Whereas value-approximation has been extensi...
Iris van Rooij, Matthew Hamilton, Moritz Müll...
SODA
2008
ACM
122views Algorithms» more  SODA 2008»
13 years 10 months ago
Fast approximation of the permanent for very dense problems
Approximation of the permanent of a matrix with nonnegative entries is a well studied problem. The most successful approach to date for general matrices uses Markov chains to appr...
Mark Huber, Jenny Law