37 search results - page 3 / 8 » Spectral Regression for Efficient Regularized Subspace Learn... |
JMLR
2010
13 years 19 days ago
2010
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
AAAI
2008
13 years 8 months ago
2008
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
In this paper, we present novel ridge regression (RR) and kernel ridge regression (KRR) techniques for multivariate labels and apply the methods to the problem of face recognition...
JMLR
2002
13 years 5 months ago
2002
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...