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2010 – 2019
- 2012
[c18]Han Xiao, Thomas Stibor, Claudia Eckert:
Evasion Attack of Multi-class Linear Classifiers. PAKDD (1) 2012: 207-218- 2011
- [e1]Pietro Liò, Giuseppe Nicosia, Thomas Stibor:
Artificial Immune Systems - 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings. Lecture Notes in Computer Science 6825, Springer 2011, ISBN 978-3-642-22370-9 [contents] - 2010
- [c17]Thomas Stibor, Anastasio Salazar-Bañuelos:
On Immunological Memory as a Function of a Recursive Proliferation Process. ICECCS 2010: 269-275 - [c16]Thomas Stibor:
A Study of Detecting Computer Viruses in Real-Infected Files in the n-Gram Representation with Machine Learning Methods. IEA/AIE (1) 2010: 509-519 - [c15]Han Xiao, Thomas Stibor:
Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation. ACML 2010: 63-78
2000 – 2009
- 2009
- [j3]Thomas Stibor:
Foundations of r-contiguous matching in negative selection for anomaly detection. Nat. Comput. 8(3): 613-641 (2009) - [c14]Thomas Stibor, Robert F. Oates, Graham Kendall
, Jonathan M. Garibaldi:
Geometrical insights into the dendritic cell algorithm. GECCO 2009: 1275-1282 - 2008
- [j2]Jonathan Timmis, Andrew Hone, Thomas Stibor, Edward Clark:
Theoretical advances in artificial immune systems. Theor. Comput. Sci. 403(1): 11-32 (2008) - [c13]Thomas Stibor:
Discriminating self from non-self with finite mixtures of multivariate Bernoulli distributions. GECCO 2008: 127-134 - [c12]Thomas Stibor:
An Empirical Study of Self/Non-self Discrimination in Binary Data with a Kernel Estimator. ICARIS 2008: 352-363 - 2007
- [c11]Thomas Stibor, Jonathan Timmis:
Comments on real-valued negative selection vs. real-valued positive selection and one-class SVM. IEEE Congress on Evolutionary Computation 2007: 3727-3734 - [c10]Thomas Stibor, Jonathan Timmis:
An Investigation on the Compression Quality of aiNet. FOCI 2007: 495-502 - [c9]Thomas Stibor:
Phase Transition and the Computational Complexity of Generating r -Contiguous Detectors. ICARIS 2007: 142-155 - 2006
- [b1]Thomas Stibor:
On the appropriateness of negative selection for anomaly detection and network intrusion detection. Darmstadt University of Technology, Germany, 2006, pp. 1-120 - [j1]Thomas Stibor, Claudia Eckert, Jonathan Timmis:
Artificial Immune Systems for IT-Security (Künstliche Immunsysteme für IT-Sicherheit). it Inf. Technol. 48(3): 168-173 (2006) - [c8]Thomas Stibor, Jonathan Timmis, Claudia Eckert:
The Link between r-contiguous Detectors and k-CNF Satisfiability. IEEE Congress on Evolutionary Computation 2006: 491-498 - [c7]Thomas Stibor, Jonathan Timmis, Claudia Eckert:
On Permutation Masks in Hamming Negative Selection. ICARIS 2006: 122-135 - [c6]Thomas Stibor, Jonathan Timmis, Claudia Eckert:
On the Use of Hyperspheres in Artificial Immune Systems as Antibody Recognition Regions. ICARIS 2006: 215-228 - [c5]Thomas Stibor, Jonathan Timmis, Claudia Eckert:
Generalization Regions in Hamming Negative Selection. Intelligent Information Systems 2006: 447-456 - 2005
- [c4]Thomas Stibor, Jonathan Timmis, Claudia Eckert:
On the appropriateness of negative selection defined over Hamming shape-space as a network intrusion detection system. Congress on Evolutionary Computation 2005: 995-1002 - [c3]Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, Claudia Eckert:
Is negative selection appropriate for anomaly detection? GECCO 2005: 321-328 - [c2]Thomas Stibor, Jonathan Timmis, Claudia Eckert:
A Comparative Study of Real-Valued Negative Selection to Statistical Anomaly Detection Techniques. ICARIS 2005: 262-275 - 2004
- [c1]Thomas Stibor, Kpatcha M. Bayarou, Claudia Eckert:
An Investigation of R-Chunk Detector Generation on Higher Alphabets. GECCO (1) 2004: 299-307
Coauthor Index
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