835 search results - page 3 / 167 » Adaptive Bound Optimization for Online Convex Optimization |
NIPS
2008
13 years 9 months ago
2008
This paper examines the generalization properties of online convex programming algorithms when the loss function is Lipschitz and strongly convex. Our main result is a sharp bound...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
WIOPT
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract—We consider the problem of jointly optimizing random access and subgraph selection in coded wireless packet networks. As opposed to the corresponding scheduling approach...
JMLR
2012
11 years 10 months ago
2012
We prove logarithmic regret bounds that depend on the loss L∗ T of the competitor rather than on the number T of time steps. In the general online convex optimization setting, o...
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...