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» On Unbiased Linear Approximations
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87
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TIT
2002
89views more  TIT 2002»
15 years 2 days ago
Comparison of worst case errors in linear and neural network approximation
Sets of multivariable functions are described for which worst case errors in linear approximation are larger than those in approximation by neural networks. A theoretical framework...
Vera Kurková, Marcello Sanguineti
105
Voted
BMCBI
2005
67views more  BMCBI 2005»
15 years 9 days ago
Sequence signature analysis of chromosome identity in three Drosophila species
Background: All eukaryotic organisms need to distinguish each of their chromosomes. A few protein complexes have been described that recognise entire, specific chromosomes, for in...
Per Stenberg, Fredrik Pettersson, Anja O. Saura, A...
97
Voted
SCL
2008
109views more  SCL 2008»
15 years 10 days ago
A note on linear function approximation using random projections
ABSTRACT: Linear function approximations based on random projections are proposed and justified for a class of fixed point and minimization problems. KEY WORDS: random projections,...
Kishor Barman, Vivek S. Borkar
105
Voted
NCI
2004
141views Neural Networks» more  NCI 2004»
15 years 1 months ago
Estimating the error at given test input points for linear regression
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
Masashi Sugiyama
107
Voted
AAAI
2012
13 years 2 months ago
Generalized Sampling and Variance in Counterfactual Regret Minimization
In large extensive form games with imperfect information, Counterfactual Regret Minimization (CFR) is a popular, iterative algorithm for computing approximate Nash equilibria. Whi...
Richard G. Gibson, Marc Lanctot, Neil Burch, Duane...