3643 search results - page 28 / 729 » Learning Submodular Functions |
ESANN
2003
14 years 11 months ago
2003
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...
INCDM
2010
Springer
14 years 8 months ago
2010
Springer
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
CIE
2007
Springer
15 years 4 months ago
2007
Springer
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
ICCV
2009
IEEE
14 years 7 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...