Quantitative Emergence – A Refined Approach Based on Divergence Measures

D. Fisch, M. Jänicke, B. Sick, C. Müller-Schloer; Quantitative Emergence – A Refined Approach Based on Divergence Measures; Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems; pp. 94-103; Budapest, 2010


Novelty-Aware Attack recognition - Intrusion Detection With Organic Computing Techniques

D. Fisch, F. Kastl, B. Sick; Novelty-Aware Attack recognition - Intrusion Detection With Organic Computing Techniques; 3rd IFIP Conference on Biologically-Inspired Collaborative Computing (BICC 2010) at the World Computer Congress (WCC 2010); pp. 242-253; Brisbane, 2010


All for one or one for all? - Combining Heterogeneous Features for Activity Spotting

U. Blanke, B. Schiele, M. Kreil, P. Lukowicz, B. Sick, T. Gruber; All for one or one for all? - Combining Heterogeneous Features for Activity Spotting; 7th IEEE Workshop on Context Modeling and Reasoning (CoMoRea) at the 8th IEEE International Conference on Pervasive Computing and Communication (PerCom 2010); pp. 18-24; Mannheim, 2010


Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems

T. Rabl, A. Lang, T. Hackl, B. Sick, H. Kosch; Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems; in: R. Nambiar, M. Poess (Eds.): Performance Evaluation and Benchmarking; Lecture Notes in Computer Science 5895, Springer Verlag, Berlin, Heidelberg, New York; pp. 116-131; Proceedings of the ”First TPC Technology Conference, TPCTC”; Lyon, 2009


Lower Bound Bayesian Networks – An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks

D. Andrade, B. Sick; Lower Bound Bayesian Networks – An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks; 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009); Montreal, 2009


Training of Radial Basis Function Classifiers With Resilient Propagation and Variational Bayesian Inference

D. Fisch, B. Sick; Training of Radial Basis Function Classifiers With Resilient Propagation and Variational Bayesian Inference; Proceedings of the ”International Joint Conference on Neural Networks (IJCNN 2009)”; pp. 838-847; Atlanta, 2009


Learning by Teaching Versus Learning by Doing: Knowledge Exchange in Organic Agent Systems

D. Fisch, M. Jänicke, E. Kalkowski, B. Sick; Learning by Teaching Versus Learning by Doing: Knowledge Exchange in Organic Agent Systems; in Proceedings of the “IEEE Symposium on Intelligent Agents (IA 2009)”; pp. 31-38; Nashville, 2009


Knowledge Fusion Using Dempster-Shafer Theory and the Imprecise Dirichlet Model

D. Andrade, T. Horeis, B. Sick; Knowledge Fusion Using Dempster-Shafer Theory and the Imprecise Dirichlet Model; in: Proceedings of the ”2008 IEEE Conference on Soft Computing in Industrial Applications (SMCia/08)”; pp. 142-148; Muroran, 2008


Forecasting Financial Time Series with Support Vector Machines Based on Dynamic Kernels

J. Mager, U. Paasche, B. Sick; Forecasting Financial Time Series with Support Vector Machines Based on Dynamic Kernels; in: Proceedings of the ”2008 IEEE Conference on Soft Computing in Industrial Applications (SMCia/08)”; pp. 252-257; Muroran, 2008


A Framework for Large-Scale Simulation of Collaborative Intrusion Detection

D. Fisch, A. Hofmann, V. Hornik, I. Dedinski, B. Sick; A Framework for Large-Scale Simulation of Collaborative Intrusion Detection; in: Proceedings of the ”2008 IEEE Conference on Soft Computing in Industrial Applications (SMCia/08)”; pp. 125-130; Muroran, 2008