13 search results - page 2 / 3 » The Importance of Convexity in Learning with Squared Loss |
COLT
2007
Springer
13 years 12 months ago
2007
Springer
In the present paper, we study the problem of aggregation under the squared loss in the model of regression with deterministic design. We obtain sharp oracle inequalities for conve...
ALT
2004
Springer
14 years 2 months ago
2004
Springer
We consider a two-layer network algorithm. The first layer consists of an uncountable number of linear units. Each linear unit is an LMS algorithm whose inputs are first “kerne...
JMLR
2010
13 years 17 days ago
2010
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
ESANN
2004
13 years 7 months ago
2004
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
PR
2010
13 years 4 months ago
2010
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...