83 search results - page 6 / 17 » Online Learning: Beyond Regret |
COLT
2008
Springer
13 years 9 months ago
2008
Springer
Standard no-internal-regret (NIR) algorithms compute a fixed point of a matrix, and hence typically require O(n3 ) run time per round of learning, where n is the dimensionality of...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We introduce an efficient algorithm for the problem of online linear optimization in the bandit setting which achieves the optimal O ( T) regret. The setting is a natural general...
CORR
2010
Springer
13 years 2 months ago
2010
Springer
We consider an opportunistic spectrum access (OSA) problem where the time-varying condition of each channel (e.g., as a result of random fading or certain primary users' activ...