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» Selectivity Estimation using Probabilistic Models
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76
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DATE
2006
IEEE
85views Hardware» more  DATE 2006»
15 years 5 months ago
Test set enrichment using a probabilistic fault model and the theory of output deviations
— We present a probabilistic fault model that allows any number of gates in an integrated circuit to fail probabilistically. Tests for this fault model, determined using the theo...
Zhanglei Wang, Krishnendu Chakrabarty, Michael G&o...
ICASSP
2010
IEEE
14 years 12 months ago
Direct importance estimation with probabilistic principal component analyzers
The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
Makoto Yamada, Masashi Sugiyama, Gordon Wichern
ICANN
2007
Springer
15 years 5 months ago
Structure Learning with Nonparametric Decomposable Models
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
Anton Schwaighofer, Mathäus Dejori, Volker Tr...
105
Voted
CVPR
2005
IEEE
16 years 1 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
ALDT
2011
Springer
200views Algorithms» more  ALDT 2011»
13 years 11 months ago
Vote Elicitation with Probabilistic Preference Models: Empirical Estimation and Cost Tradeoffs
A variety of preference aggregation schemes and voting rules have been developed in social choice to support group decision making. However, the requirement that participants provi...
Tyler Lu, Craig Boutilier