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» Model Selection and Error Estimation
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CIKM
2011
Springer
14 years 4 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han
ECSQARU
2009
Springer
15 years 9 months ago
Inference from Multinomial Data Based on a MLE-Dominance Criterion
We consider the problem of inference from multinomial data with chances θ, subject to the a-priori information that the true parameter vector θ belongs to a known convex polytope...
Alessio Benavoli, Cassio P. de Campos
ISQED
2009
IEEE
103views Hardware» more  ISQED 2009»
15 years 11 months ago
A systematic approach to modeling and analysis of transient faults in logic circuits
With technology scaling, the occurrence rate of not only single, but also multiple transients resulting from a single hit is increasing. In this work, we consider the effect of th...
Natasa Miskov-Zivanov, Diana Marculescu
SP
2002
IEEE
128views Security Privacy» more  SP 2002»
15 years 4 months ago
Fitting hidden Markov models to psychological data
Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive stat...
Ingmar Visser, Maartje E. J. Raijmakers, Peter C. ...
ICIP
2007
IEEE
16 years 6 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...