701 search results - page 65 / 141 » Self Bounding Learning Algorithms |
ALT
2011
Springer
12 years 7 months ago
2011
Springer
We consider the problem of learning sparse parities in the presence of noise. For learning parities on r out of n variables, we give an algorithm that runs in time poly log 1 δ , ...
ALT
2010
Springer
13 years 9 months ago
2010
Springer
We consider the problem of inferring the most likely social network given connectivity constraints imposed by observations of outbreaks within the network. Given a set of vertices ...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
LION
2010
Springer
13 years 11 months ago
2010
Springer
Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
COLT
2000
Springer
14 years 2 days ago
2000
Springer
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...