This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
Abstract--The ranking problem has become increasingly important in modern applications of statistical methods in automated decision making systems. In particular, we consider a for...
We introduce a receiver-oriented approach to congestion control, demonstrated by an experimental protocol, TCP-Real. The protocol allows for a measurement-based transmission strate...
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...