187 search results - page 22 / 38 » Bounding the cost of learned rules |
COLT
2004
Springer
14 years 1 months ago
2004
Springer
We give an algorithm for the bandit version of a very general online optimization problem considered by Kalai and Vempala [1], for the case of an adaptive adversary. In this proble...
ILP
2005
Springer
14 years 1 months ago
2005
Springer
Online learning algorithms such as Winnow have received much attention in Machine Learning. Their performance degrades only logarithmically with the input dimension, making them us...
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
We study online learning in an oblivious changing environment. The standard measure of regret bounds the difference between the cost of the online learner and the best decision in...
NCA
2007
IEEE
14 years 2 months ago
2007
IEEE
Developing middleware services for dynamic distributed systems, e.g., ad-hoc networks, is a challenging task given that such services deal with dynamically changing membership and...
ACML
2009
Springer
14 years 1 months ago
2009
Springer
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...