Getting to Grips with Support Vector Machines: Application

Ekonomiese En BestuurswetenskappeStatistiek & Aktuariele WetenskapPlease help us populate SUNScholar with the post print version of this article. It can be e-mailed to: [email protected]

Getting to Grips with Support Vector Machines: Theory

Ekonomiese En BestuurswetenskappeStatistiek & Aktuariele WetenskapPlease help us populate SUNScholar with the post print version of this article. It can be e-mailed to: [email protected]

Estimation of trust metrics for MANET using QoS parameter and source routing algorithms

Estimation of trust in ad-hoc networks is an inevitable basis for hybrid networks to inter-operate. The contributions in this paper provide a framework for estimating the trust between nodes in an ad hoc network based on quality of service parameters. Probabilities of transit time variation, deleted, multiplied and inserted packets, processing delays are used to estimate and update trust. Functions which facilitate this are provided and evaluated. It has been shown that only two end nodes need to be involved and thereby achieve reduced overhead. The framework proposed is applicable and useful to estimate trust in covert unobservable and anonymous communications. © 2007 IEEE

Regular Inference on Artificial Neural Networks

Part 5: MAKE Explainable AIInternational audienceThis paper explores the general problem of explaining the behavior of artificial neural networks (ANN). The goal is to construct a representation which enhances human understanding of an ANN as a sequence classifier, with the purpose of providing insight on the rationale behind the classification of a sequence as positive or negative, but also to enable performing further analyses, such as automata-theoretic formal verification. In particular, a probabilistic algorithm for constructing a deterministic finite automaton which is approximately correct with respect to an artificial neural network is proposed