12 search results - page 1 / 3 » A Direct Formulation for Sparse PCA Using Semidefinite Progr... |
NIPS
2004
13 years 6 months ago
2004
We examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound on the cardinality of its...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
ICASSP
2009
IEEE
13 years 8 months ago
2009
IEEE
In this paper, we solve the problem of detecting the entries of a sparse finite-alphabet signal from a limited amount of data, for instance obtained by compressive sampling. While...
ECML
2004
Springer
13 years 8 months ago
2004
Springer
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...