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TIT
1998
96views more  TIT 1998»
13 years 8 months ago
Sequential Prediction of Individual Sequences Under General Loss Functions
Abstract— We consider adaptive sequential prediction of arbitrary binary sequences when the performance is evaluated using a general loss function. The goal is to predict on each...
David Haussler, Jyrki Kivinen, Manfred K. Warmuth
JCIT
2010
156views more  JCIT 2010»
13 years 3 months ago
Intelligent Monitoring Approach for Pipeline Defect Detection from MFL Inspection
Artificial Neural Networks(ANNS) have top level of capability to progress the estimation of cracks in metal tubes. The aim of this paper is to propose an algorithm to identify mod...
Saeedreza Ehteram, Seyed Zeinolabedin Moussavi, Mo...
KES
2006
Springer
13 years 8 months ago
Spiking Neural Network Based Classification of Task-Evoked EEG Signals
This paper presents an improved technique to detect evoked potentials in continuous EEG recordings using a spiking neural network. Human EEG signals recorded during spell checking,...
Piyush Goel, Honghai Liu, David J. Brown, Avijit D...
ICIAR
2004
Springer
14 years 2 months ago
Neuro-Fuzzy Method for Automated Defect Detection in Aluminium Castings
The automated flaw detection in aluminium castings consists of two steps: a) identification of potential defects using image processing techniques, and b) classification of pote...
Sergio Hernández, Doris Saez, Domingo Mery
CCS
2008
ACM
13 years 10 months ago
HMAC is a randomness extractor and applications to TLS
In this paper, we study the security of a practical randomness extractor and its application in the tls standard. Randomness extraction is the first stage of key derivation functi...
Pierre-Alain Fouque, David Pointcheval, Séb...