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JMLR
2002
90views more  JMLR 2002»
13 years 10 months ago
Machine Learning with Data Dependent Hypothesis Classes
We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
ANCS
2007
ACM
14 years 2 months ago
A programmable message classification engine for session initiation protocol (SIP)
Session Initiation Protocol (SIP) has begun to be widely deployed for multiple services such as VoIP, Instant Messaging and Presence. Each of these services uses different SIP mes...
Arup Acharya, Xiping Wang, Charles Wright
IJCNN
2000
IEEE
14 years 3 months ago
ICA for Noisy Neurobiological Data
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
Shiro Ikeda, Keisuke Toyama
JMLR
2011
145views more  JMLR 2011»
13 years 5 months ago
Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Func
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
Jim C. Huang, Brendan J. Frey
CONCUR
1999
Springer
14 years 3 months ago
Robust Satisfaction
In order to check whether an open system satisfies a desired property, we need to check the behavior of the system with respect to an arbitrary environment. In the most general se...
Orna Kupferman, Moshe Y. Vardi