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15 years 5 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
CORR
2010
Springer
169views Education» more  CORR 2010»
13 years 7 months ago
Spiking Neurons with ASNN Based-Methods for the Neural Block Cipher
Problem statement: This paper examines Artificial Spiking Neural Network (ASNN) which inter-connects group of artificial neurons that uses a mathematical model with the aid of blo...
Saleh Ali K. Al-Omari, Putra Sumari
ICA
2010
Springer
13 years 6 months ago
Time Series Causality Inference Using Echo State Networks
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
Norbert Michael Mayer, Oliver Obst, Chang Yu-Chen
AAAI
2007
13 years 10 months ago
A Planning Approach for Message-Oriented Semantic Web Service Composition
In this paper, we consider the problem of composing a set of web services, where the requirements are specified in terms of the input and output messages of the composite workfl...
Zhen Liu, Anand Ranganathan, Anton Riabov
CCS
2006
ACM
13 years 11 months ago
A scalable approach to attack graph generation
Attack graphs are important tools for analyzing security vulnerabilities in enterprise networks. Previous work on attack graphs has not provided an account of the scalability of t...
Xinming Ou, Wayne F. Boyer, Miles A. McQueen