129 search results - page 1 / 26 » Learning as search optimization: approximate large margin me... |
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
JMLR
2008
13 years 4 months ago
2008
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
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...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
ICMLA
2009
13 years 2 months ago
2009
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...