87 search results - page 9 / 18 » The regularized least squares algorithm and the problem of l... |
ICMLA
2008
13 years 9 months ago
2008
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
CIKM
2011
Springer
12 years 7 months ago
2011
Springer
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
PRL
2010
13 years 5 months ago
2010
We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually cont...
ACL
2008
13 years 9 months ago
2008
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...