10 search results - page 1 / 2 » Max-margin Multiple-Instance Learning via Semidefinite Progr... |
ACML
2009
Springer
13 years 9 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...
NIPS
2003
13 years 6 months ago
2003
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
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...
JMLR
2006
13 years 4 months ago
2006
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
We present a new unsupervised algorithm for training structured predictors that is discriminative, convex, and avoids the use of EM. The idea is to formulate an unsupervised versi...