77 search results - page 2 / 16 » Sample Size Lower Bounds in PAC Learning by Algorithmic Comp... |
COLT
2000
Springer
13 years 10 months 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...
ALT
1999
Springer
13 years 10 months ago
1999
Springer
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
JMLR
2012
11 years 8 months ago
2012
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
We consider the general, widely applicable problem of selecting from n real-valued random variables a subset of size m of those with the highest means, based on as few samples as ...
ICML
2006
IEEE
14 years 7 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...