151 search results - page 10 / 31 » Feature selection for ordinal regression |
SETN
2010
Springer
14 years 2 months ago
2010
Springer
In the present work we address the problem of phone duration modeling for the needs of emotional speech synthesis. Specifically, relying on ten well known machine learning techniqu...
JMLR
2010
13 years 2 months ago
2010
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
IWANN
2009
Springer
14 years 2 months ago
2009
Springer
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
ICML
2000
IEEE
14 years 8 months ago
2000
IEEE
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...