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IDT
2010
124views more  IDT 2010»
14 years 8 months ago
Modelling decision making with probabilistic causation
Humans know how to reason based on cause and effect, but cause and effect is not enough to draw conclusions due to the problem of imperfect information and uncertainty. To resol...
Luís Moniz Pereira, Carroline Kencana Ramli
JSAC
2006
111views more  JSAC 2006»
14 years 9 months ago
On trust models and trust evaluation metrics for ad hoc networks
Within the realm of network security, we interpret the concept of trust as a relation among entities that participate in various protocols. Trust relations are based on evidence cr...
George Theodorakopoulos, John S. Baras
ICDE
2012
IEEE
277views Database» more  ICDE 2012»
13 years 7 days ago
Aggregate Query Answering on Possibilistic Data with Cardinality Constraints
— Uncertainties in data arise for a number of reasons: when the data set is incomplete, contains conflicting information or has been deliberately perturbed or coarsened to remov...
Graham Cormode, Divesh Srivastava, Entong Shen, Ti...
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
15 years 10 months ago
Sampling cube: a framework for statistical olap over sampling data
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Y...
CVPR
2004
IEEE
15 years 11 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...