2750 search results - page 75 / 550 » The complexity of learning SUBSEQ(A) |
166
click to vote
KCAP
2009
ACM
16 years 20 days ago
2009
ACM
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
138
click to vote
ICDM
2005
IEEE
15 years 11 months ago
2005
IEEE
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
155
click to vote
NN
2006
Springer
15 years 6 months ago
2006
Springer
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
140
click to vote
ICML
2007
IEEE
16 years 7 months ago
2007
IEEE
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
126
click to vote
ALT
2010
Springer
15 years 7 months ago
2010
Springer
We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...