Results 11 to 20 of about 2,465,255 (121)

Orthogonal least squares regression with tunable kernels [PDF]

, 2005
A novel technique is proposed to construct sparse regression models based on the orthogonal least squares method with tunable kernels. The proposed technique tunes the centre vector and diagonal covariance matrix of individual regressor by incrementally ...
Wang, X. X., Wang, X.X., Brown, D. J., Chen, S., Brown, D.J.   +4 more
core   +2 more sources

Smarandache mukti-squares [PDF]

, 2007
We have introduced Smarandache quasigroups which are Smarandache non-associative structures. A quasigroup is a groupoid whose composition table is a Latin square.
Muktibodh, Arun S.
core   +1 more source

Completions of ε-Dense Partial Latin Squares [PDF]

, 2013
A classical question in combinatorics is the following: given a partial Latin square $P$, when can we complete $P$ to a Latin square $L$? In this paper, we investigate the class of textbf{$epsilon$-dense partial Latin squares}: partial Latin squares in
Bartlett, Padraic James, Padraic Bartlett, Bartlett, Padraic   +2 more
core   +1 more source

Fully complex-valued radial basis function networks: orthogonal least squares regression and classification [PDF]

, 2008
We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental ...
Harris, C. J., Hong, Xia, Chen, Sheng, Hong, X., Harris, Chris J., Hanzo, Lajos, Hanzo, L., Chen, S.   +7 more
core   +2 more sources

Constructing and embedding mutually orthogonal Latin squares: reviewing both new and existing results [PDF]

, 2020
We review results for the embedding of orthogonal partial Latin squares in orthogonal Latin squares, comparing and contrasting these with results for embedding partial Latin squares in Latin squares.
Grannell, Mike, Yazıcı, Emine Ş., Donovan, Diane M.   +2 more
core   +1 more source

NARX-based nonlinear system identification using orthogonal least squares basis hunting [PDF]

, 2008
An orthogonal least squares technique for basis hunting (OLS-BH) is proposed to construct sparse radial basis function (RBF) models for NARX-type nonlinear systems.
Wang, X.X., Chen, Sheng, Harris, Chris J.   +2 more
core   +1 more source

Sub-latin squares and incomplete orthogonal arrays [PDF]

, 1974
The main result of this paper is that for any pair of orthogonal Latin squares of side k, there will exist for all sufficiently large n a pair of orthogonal Latin squares with the first pair as orthogonal sub-squares.
Horton, J.D, J.D Horton
core   +1 more source

Orthogonal-least-squares regression: A unified approach for data modelling

, 2008
A unified approach is proposed for data modelling that includes supervised regression and classification applications as well as unsupervised probability density function estimation. The orthogonal-least-squares regression based on the leave-one-out test
Harris, C. J., X. Hong, B.L. Luk, Chen, Sheng, C.J. Harris, Chen, S., Luk, Bing L., Hong, Xia, B. L. Luk, S. Chen, Luk, B. L., Hong, X., C. J. Harris, Harris, Chris   +13 more
core   +1 more source

Orthogonal least squares algorithm for training multi-output radial basis function networks [PDF]

, 1991
A constructive learning algorithm for multioutput radial basis function networks is presented. Unlike most network learning algorithms, which require a fixed network structure, this algorithm automatically determines an adequate radial basis function ...
S. Chen, Cowan, C. F. N., Chen, Sheng, Grant, P. M., P.M. Grant, C.F.N. Cowan, Cowan, C.F.N., Grant, P.M., Chen, S.   +8 more
core   +1 more source

Local Regularization Assisted Orthogonal Least Squares Regression

, 2006
A locally regularized orthogonal least squares (LROLS) algorithm is proposed for constructing parsimonious or sparse regression models that generalize well.
Chen, S.
core   +1 more source