495 search results - page 26 / 99 » Approximation algorithms for budgeted learning problems |
TNN
2010
13 years 3 months ago
2010
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
CORR
2012
Springer
12 years 4 months ago
2012
Springer
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
IWANN
1999
Springer
14 years 22 days ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
We introduce a natural generalization of submodular set cover and exact active learning with a finite hypothesis class (query learning). We call this new problem interactive submo...
CDC
2010
IEEE
13 years 3 months ago
2010
IEEE
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...