13 search results - page 2 / 3 » Multi-class Discriminant Kernel Learning via Convex Programm... |
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...
JMLR
2010
12 years 11 months ago
2010
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
IJCNN
2006
IEEE
13 years 10 months ago
2006
IEEE
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
NIPS
2007
13 years 6 months ago
2007
We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...