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ESANN
2008
15 years 1 months ago
Approximation of Gaussian process regression models after training
The evaluation of a standard Gaussian process regression model takes time linear in the number of training data points. In this paper, the models are approximated in the feature sp...
Thorsten Suttorp, Christian Igel
CAGD
2006
94views more  CAGD 2006»
14 years 12 months ago
High order approximation of rational curves by polynomial curves
We show that many rational parametric curves can be interpolated, in a Hermite sense, by polynomial curves whose degree, relative to the number of data being interpolated, is lowe...
Michael S. Floater
STOC
2009
ACM
106views Algorithms» more  STOC 2009»
16 years 13 days ago
Max cut and the smallest eigenvalue
We describe a new approximation algorithm for Max Cut. Our algorithm runs in ~O(n2 ) time, where n is the number
Luca Trevisan
SIAMJO
2010
125views more  SIAMJO 2010»
14 years 6 months ago
Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the r...
Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
TCOM
2010
65views more  TCOM 2010»
14 years 6 months ago
Evaluation of the distance spectrum of variable-length finite-state codes
The class of variable-length finite-state joint source-channel codes is defined and a polynomial complexity algorithm for the evaluation of their distance spectrum presented. Issu...
Claudio Weidmann, Michel Kieffer