111 search results - page 1 / 23 » Deploying SDP for machine learning |
ESANN
2007
13 years 6 months ago
2007
We discuss the use in machine learning of a general type of convex optimisation problem known as semi-definite programming (SDP) [1]. We intend to argue that SDP’s arise quite n...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Maximum Margin Matrix Factorization (MMMF) was recently suggested (Srebro et al., 2005) as a convex, infinite dimensional alternative to low-rank approximations and standard facto...
JMLR
2006
13 years 4 months ago
2006
The rise of convex programming has changed the face of many research fields in recent years, machine learning being one of the ones that benefitted the most. A very recent develop...
ACML
2009
Springer
13 years 8 months ago
2009
Springer
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...