495 search results - page 18 / 99 » Approximation algorithms for budgeted learning problems |
NIPS
2008
13 years 10 months ago
2008
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
AUSAI
2005
Springer
14 years 2 months ago
2005
Springer
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
SODA
2001
ACM
13 years 9 months ago
2001
ACM
Bin covering takes as input a list of items with sizes in (0 1) and places them into bins of unit demand so as to maximize the number of bins whose demand is satis ed. This is in ...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...