97 search results - page 1 / 20 » Logarithmic Regret Algorithms for Online Convex Optimization |
COLT
2006
Springer
13 years 8 months ago
2006
Springer
In an online convex optimization problem a decision-maker makes a sequence of decisions, i.e., chooses a sequence of points in Euclidean space, from a fixed feasible set. After ea...
NIPS
2008
13 years 6 months ago
2008
We describe a primal-dual framework for the design and analysis of online strongly convex optimization algorithms. Our framework yields the tightest known logarithmic regret bound...
NIPS
2008
13 years 6 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...
JMLR
2012
11 years 7 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...
ECCC
2006
13 years 4 months ago
2006
We introduce a new algorithm and a new analysis technique that is applicable to a variety of online optimization scenarios, including regret minimization for Lipschitz regret func...