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- A. Pierro, C. Hankin, H. Wiklicky
- Computer ScienceProceedings 15th IEEE Computer Security…
- 24 June 2002
A model in which the notion of non-interference is approximated in the sense that it allows for some exactly quantified leakage of information, characterised via a notion of process similarity which replaces the indistinguishability of processes by a quantitative measure of their behavioural difference.
An operational semantics for probabilistic concurrent constraint programming
The aim is to introduce the possibility to formulate so called "randomised algorithms" within the CCP framework by means of a probabilistic transition system such that the execution of a PCCP program may be seen as a stochastic process, i.e. as a random walk on the transition graph.
On Probabilistic CCP
The operational semantics of probabilistic concurrent constraint programming (PCCP) is deene the operational semantics by means of a Probabilistic transition system such that the execution of a PCCP program may be seen as a stochastic process, i.e. as a random walk on the transition graph.
Concurrent constraint programming: towards probabilistic abstract interpretation
The method resembles the one based on Galois onne tion as developed in the Cousot framework for abstra t interpretation and generates the best approximations to an appropriate notion of pre ision de ned in terms of a norm.
Implementing Randomised Algorithms in Constraint Logic Programming
An extensive treatment of two popular (generic) randomised algorithms, namely Simulated Annealing and Ran-domised Rounding are given, and some instantiations of these algorithms for solving two well-known optimisation problems, namely the travelling salesman and the maximum satisfaction problem are discussed.
Probabilistic Constraint Handling Rules
Tunable Quantum Neural Networks for Boolean Functions
This paper proposes a new approach to quantum neural networks that avoids the use of measurements that usually emulate the non-linear activation functions which are characteristic of the classical neural networks and devised an algorithm that leverages the absence of measurements.
Quantitative Relations and Approximate Process Equivalences
A characterisation of probabilistic transition systems (PTS) in terms of linear operators on some suitably defined vector space representing the set of states is introduced and it is argued that this number can be given a statistical interpretation in Terms of the tests needed to distinguish two behaviours.