2 search results - page 1 / 1 » Mind the Duality Gap: Logarithmic regret algorithms for onli... |
NIPS
2008
13 years 5 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...
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...