Introduction to algorithms
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Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
How good are branching rules in DPLL?
Discrete Applied Mathematics
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
A machine program for theorem-proving
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Machine Learning
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
A Probabilistic 3-SAT Algorithm Further Improved
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
Generating Optimal Repertoire of Antibody Strings in an Artificial Immune System
Proceedings of the IIS'2000 Symposium on Intelligent Information Systems
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
An Immunological Approach to Change Detection: Algorithms, Analysis and Implications
SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
An immunological model of distributed detection and its application to computer security
An immunological model of distributed detection and its application to computer security
A Classification Framework for Anomaly Detection
The Journal of Machine Learning Research
An improved deterministic local search algorithm for 3-SAT
Theoretical Computer Science
A Machine Learning Evaluation of an Artificial Immune System
Evolutionary Computation
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Revisiting LISYS: parameters and normal behavior
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
The effect of binary matching rules in negative selection
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Efficient Algorithms for String-Based Negative Selection
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Negative selection algorithms without generating detectors
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Negative selection algorithms on strings with efficient training and linear-time classification
Theoretical Computer Science
Efficient negative selection algorithms by sampling and approximate counting
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
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Negative selection and the associated r-contiguous matching rule is a popular immune-inspired method for anomaly detection problems. In recent years, however, problems such as scalability and high false positive rate have been empirically noticed. In this article, negative selection and the associated r-contiguous matching rule are investigated from a pattern classification perspective. This includes insights in the generalization capability of negative selection and the computational complexity of finding r-contiguous detectors.