97 search results - page 9 / 20 » Logarithmic Regret Algorithms for Online Convex Optimization |
ECCC
2007
13 years 7 months ago
2007
We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We study on-line decision problems where the set of actions that are available to the decision algorithm vary over time. With a few notable exceptions, such problems remained larg...
NIPS
2007
13 years 9 months ago
2007
In the online linear optimization problem, a learner must choose, in each round, a decision from a set D ⊂ Rn in order to minimize an (unknown and changing) linear cost function...
CORR
2011
Springer
13 years 2 months ago
2011
Springer
The analysis of online least squares estimation is at the heart of many stochastic sequential decision-making problems. We employ tools from the self-normalized processes to provi...
JMLR
2010
13 years 2 months ago
2010
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...