3694 search results - page 1 / 739 » Stochastic complexity in learning |
EUROCOLT
1995
Springer
13 years 9 months ago
1995
Springer
ICAART
2010
INSTICC
14 years 2 months ago
2010
INSTICC
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
ALT
2005
Springer
14 years 2 months ago
2005
Springer
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true ...
JMLR
2010
13 years 10 days ago
2010
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
ATAL
2007
Springer
13 years 11 months ago
2007
Springer
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...