596 search results - page 9 / 120 » Learning noise |
NIPS
2008
13 years 9 months ago
2008
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for ...
AAAI
2012
11 years 10 months ago
2012
Many noise models do not faithfully reflect the noise processes introduced during data collection in many real-world applications. In particular, we argue that a type of noise re...
FOCS
2006
IEEE
14 years 1 months ago
2006
IEEE
We address well-studied problems concerning the learnability of parities and halfspaces in the presence of classification noise. Learning of parities under the uniform distributi...
STOC
2003
ACM
14 years 7 months ago
2003
ACM
Boosting algorithms are procedures that "boost" low-accuracy weak learning algorithms to achieve arbitrarily high accuracy. Over the past decade boosting has been widely...