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» The Stochastic Machine Replenishment Problem
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COLT
2008
Springer
13 years 11 months ago
Regret Bounds for Sleeping Experts and Bandits
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...
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yo...
HIS
2007
13 years 11 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
UAI
2008
13 years 11 months ago
Multi-View Learning over Structured and Non-Identical Outputs
In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, ea...
Kuzman Ganchev, João Graça, John Bli...
CIKM
2006
Springer
14 years 1 months ago
Coupling feature selection and machine learning methods for navigational query identification
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Yumao Lu, Fuchun Peng, Xin Li, Nawaaz Ahmed
COLT
2008
Springer
13 years 11 months ago
Adapting to a Changing Environment: the Brownian Restless Bandits
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...
Aleksandrs Slivkins, Eli Upfal