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» Modelling decision making with probabilistic causation
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ICCV
2005
IEEE
14 years 1 months ago
LOCUS: Learning Object Classes with Unsupervised Segmentation
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
John M. Winn, Nebojsa Jojic
COLCOM
2005
IEEE
14 years 1 months ago
Developing a framework for integrating prior problem solving and knowledge sharing histories of a group to predict future group
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
ICDE
2011
IEEE
245views Database» more  ICDE 2011»
12 years 11 months ago
Stochastic skyline operator
— In many applications involving the multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions. As a key feature, t...
Xuemin Lin, Ying Zhang, Wenjie Zhang, Muhammad Aam...
ICCAD
1999
IEEE
81views Hardware» more  ICCAD 1999»
13 years 12 months ago
Modeling design constraints and biasing in simulation using BDDs
Constraining and input biasing are frequently used techniques in functional verification methodologies based on randomized simulation generation. Constraints confine the simulatio...
Jun Yuan, Kurt Shultz, Carl Pixley, Hillel Miller,...
SUM
2007
Springer
14 years 1 months ago
Managing Uncertainty in Schema Matcher Ensembles
Schema matching is the task of matching between concepts describing the meaning of data in various heterogeneous, distributed data sources. With many heuristics to choose from, sev...
Anan Marie, Avigdor Gal