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» Least Expected Cost Query Optimization: What Can We Expect
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IAT
2010
IEEE
13 years 2 months ago
Selecting Operator Queries Using Expected Myopic Gain
When its human operator cannot continuously supervise (much less teleoperate) an agent, the agent should be able to recognize its limitations and ask for help when it risks making...
Robert Cohn, Michael Maxim, Edmund H. Durfee, Sati...
ICDM
2008
IEEE
172views Data Mining» more  ICDM 2008»
13 years 11 months ago
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference
Selecting promising queries is the key to effective active learning. In this paper, we investigate selection techniques for the task of learning an equivalence relation where the ...
Steffen Rendle, Lars Schmidt-Thieme
WWW
2010
ACM
13 years 11 months ago
Visualizing differences in web search algorithms using the expected weighted hoeffding distance
We introduce a new dissimilarity function for ranked lists, the expected weighted Hoeffding distance, that has several advantages over current dissimilarity measures for ranked s...
Mingxuan Sun, Guy Lebanon, Kevyn Collins-Thompson
ICDCS
2002
IEEE
13 years 9 months ago
Query Optimization to Meet Performance Targets for Wide Area Applications
Recent technology advances have enabled mediated query processing with Internet accessible WebSources. A characteristic of WebSources is that their access costs exhibit transient ...
Vladimir Zadorozhny, Louiqa Raschid
ICML
2004
IEEE
14 years 5 months ago
Predictive automatic relevance determination by expectation propagation
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...