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ICML
2005
IEEE
16 years 7 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
SIGSOFT
2010
ACM
15 years 4 months ago
Supporting human-intensive systems
Executing critical systems often rely on humans to make important and sometimes life-critical decisions. As such systems become more complex, the potential for human error to lead...
Lori A. Clarke, Leon J. Osterweil, George S. Avrun...
MLDM
2005
Springer
15 years 11 months ago
Statistical Supports for Frequent Itemsets on Data Streams
Abstract. A statistical technique is developed for estimating the support of itemsets on data streams, regardless of the size of the data stored. This technique, which is computati...
Pierre-Alain Laur, Jean-Emile Symphor, Richard Noc...
SEMWEB
2004
Springer
15 years 11 months ago
METEOR-S Web Service Annotation Framework with Machine Learning Classification
Researchers have recognized the need for more expressive descriptions of Web services. Most approaches have suggested using ontologies to either describe the Web services or to an...
Nicole Oldham, Christopher Thomas, Amit P. Sheth, ...
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
16 years 3 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic