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» Efficient Algorithms for Online Decision Problems
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CORR
2011
Springer
202views Education» more  CORR 2011»
13 years 4 months ago
Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems
The analysis of online least squares estimation is at the heart of many stochastic sequential decision-making problems. We employ tools from the self-normalized processes to provi...
Yasin Abbasi-Yadkori, Dávid Pál, Csa...
ICPR
2008
IEEE
14 years 10 months ago
Training sequential on-line boosting classifier for visual tracking
On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...
NIPS
2003
13 years 10 months ago
Online Passive-Aggressive Algorithms
We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yor...
RTSS
2003
IEEE
14 years 2 months ago
Multiple-Resource Periodic Scheduling Problem: how much fairness is necessary?
The Pfair algorithms are optimal for independent periodic real-time tasks executing on a multiple-resource system, however, they incur a high scheduling overhead by making schedul...
Dakai Zhu, Daniel Mossé, Rami G. Melhem
INFORMATICALT
2008
196views more  INFORMATICALT 2008»
13 years 9 months ago
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang