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» Approximating Component Selection
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SIGMOD
2001
ACM
136views Database» more  SIGMOD 2001»
15 years 10 months ago
Selectivity Estimation using Probabilistic Models
Estimating the result size of complex queries that involve selection on multiple attributes and the join of several relations is a difficult but fundamental task in database query...
Lise Getoor, Benjamin Taskar, Daphne Koller
PODS
2000
ACM
179views Database» more  PODS 2000»
15 years 2 months ago
Selectivity Estimation for Boolean Queries
In a variety of applications ranging from optimizing queries on alphanumeric attributes to providing approximate counts of documents containing several query terms, there is an in...
Zhiyuan Chen, Flip Korn, Nick Koudas, S. Muthukris...
FOCS
2009
IEEE
15 years 4 months ago
Local Graph Partitions for Approximation and Testing
—We introduce a new tool for approximation and testing algorithms called partitioning oracles. We develop methods for constructing them for any class of bounded-degree graphs wit...
Avinatan Hassidim, Jonathan A. Kelner, Huy N. Nguy...
NIPS
1998
14 years 11 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
KSEM
2009
Springer
15 years 4 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer