15 search results - page 1 / 3 » The Price of Bandit Information for Online Optimization |
NIPS
2007
13 years 6 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...
COLT
2010
Springer
13 years 2 months ago
2010
Springer
Bandit convex optimization is a special case of online convex optimization with partial information. In this setting, a player attempts to minimize a sequence of adversarially gen...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
We present an on-line learning framework tailored towards real-time learning from observed user behavior in search engines and other information retrieval systems. In particular, ...
LION
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
In the multi-armed bandit (MAB) problem there are k distributions associated with the rewards of playing each of k strategies (slot machine arms). The reward distributions are ini...