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JAIR
2002
163views more  JAIR 2002»
13 years 4 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
SIAMJO
2011
12 years 11 months ago
Minimizing the Condition Number of a Gram Matrix
Abstract. The condition number of a Gram matrix defined by a polynomial basis and a set of points is often used to measure the sensitivity of the least squares polynomial approxim...
Xiaojun Chen, Robert S. Womersley, Jane J. Ye
ISCAS
2008
IEEE
217views Hardware» more  ISCAS 2008»
13 years 11 months ago
Approximate L0 constrained non-negative matrix and tensor factorization
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
Morten Mørup, Kristoffer Hougaard Madsen, L...
TOG
2002
212views more  TOG 2002»
13 years 4 months ago
Least squares conformal maps for automatic texture atlas generation
A Texture Atlas is an efficient color representation for 3D Paint Systems. The model to be textured is decomposed into charts homeomorphic to discs, each chart is parameterized, a...
Bruno Lévy, Sylvain Petitjean, Nicolas Ray,...
STOC
2009
ACM
271views Algorithms» more  STOC 2009»
14 years 5 months ago
A fast and efficient algorithm for low-rank approximation of a matrix
The low-rank matrix approximation problem involves finding of a rank k version of a m ? n matrix AAA, labeled AAAk, such that AAAk is as "close" as possible to the best ...
Nam H. Nguyen, Thong T. Do, Trac D. Tran