Search results for "Algorithm design"
showing 10 items of 63 documents
Ockham's Razor in Memetic Computing: Three Stage Optimal Memetic Exploration
2012
Memetic computing is a subject in computer science which considers complex structures as the combination of simple agents, memes, whose evolutionary interactions lead to intelligent structures capable of problem-solving. This paper focuses on memetic computing optimization algorithms and proposes a counter-tendency approach for algorithmic design. Research in the field tends to go in the direction of improving existing algorithms by combining different methods or through the formulation of more complicated structures. Contrary to this trend, we instead focus on simplicity, proposing a structurally simple algorithm with emphasis on processing only one solution at a time. The proposed algorit…
Bayesian Unification of Gradient and Bandit-based Learning for Accelerated Global Optimisation
2017
Bandit based optimisation has a remarkable advantage over gradient based approaches due to their global perspective, which eliminates the danger of getting stuck at local optima. However, for continuous optimisation problems or problems with a large number of actions, bandit based approaches can be hindered by slow learning. Gradient based approaches, on the other hand, navigate quickly in high-dimensional continuous spaces through local optimisation, following the gradient in fine grained steps. Yet, apart from being susceptible to local optima, these schemes are less suited for online learning due to their reliance on extensive trial-and-error before the optimum can be identified. In this…
Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations.
2014
It is well known that the registration process is a key step for super-resolution reconstruction. In this work, we propose to use a piezoelectric system that is easily adaptable on all microscopes and telescopes for controlling accurately their motion (down to nanometers) and therefore acquiring multiple images of the same scene at different controlled positions. Then a fast super-resolution algorithm \cite{eh01} can be used for efficient super-resolution reconstruction. In this case, the optimal use of $r^2$ images for a resolution enhancement factor $r$ is generally not enough to obtain satisfying results due to the random inaccuracy of the positioning system. Thus we propose to take seve…
Case-studies on average-case analysis for an elementary course on algorithms
1999
Average-case algorithm analysis is usually viewed as a tough subject by students in the first courses in computer science. Traditionally, these topics are fully developed in advanced courses with a clear mathematical orientation. The work presented here is not an alternative to this, rather, it presents the analysis of algorithms (and average-case in particular) adapted to the mathematical background of students in an elementary course on algorithms or programming by using two selected case-studies.
The iconic interface for the PIctorial C language
2003
Iconic environments intend to provide expressive tools to implement, to debug and to execute programs. Moreover its pictorial constructs guide the user to design algorithms in an interactive fashion. Visual interfaces are especially required whenever programs run on an heterogeneous and reconfigurable multiprocessor system oriented to image analysis. Pictorial tools help the user to control the scope of variables, and the distribution of the tasks into the processors. In this paper, the general design, the visual-syntax, and the implementation of the first prototype of an iconic user interface for the PIctorial C Language (PICL) are described. >
Privacy violations in Riga open data public transport system
2016
Over the recent years public transportation systems around the world have been migrating to digital ticketing solutions. This paper investigates security and privacy aspects of the one such system implemented by Riga municipality called e-talons by analysing published open data containing ride registrations.
PGAC: A Parallel Genetic Algorithm for Data Clustering
2005
Cluster analysis is a valuable tool for exploratory pattern analysis, especially when very little a priori knowledge about the data is available. Distributed systems, based on high speed intranet connections, provide new tools in order to design new and faster clustering algorithms. Here, a parallel genetic algorithm for clustering called PGAC is described. The used strategy of parallelization is the island model paradigm where different populations of chromosomes (called demes) evolve locally to each processor and from time to time some individuals are moved from one deme to another. Experiments have been performed for testing the benefits of the parallelisation paradigm in terms of comput…
The Engineering of a Compression Boosting Library: Theory vs Practice in BWT Compression
2006
Data Compression is one of the most challenging arenas both for algorithm design and engineering. This is particularly true for Burrows and Wheeler Compression a technique that is important in itself and for the design of compressed indexes. There has been considerable debate on how to design and engineer compression algorithms based on the BWT paradigm. In particular, Move-to-Front Encoding is generally believed to be an "inefficient " part of the Burrows-Wheeler compression process. However, only recently two theoretically superior alternatives to Move-to-Front have been proposed, namely Compression Boosting and Wavelet Trees. The main contribution of this paper is to provide the first ex…
A Local Selection Algorithm for Switching Function Minimization
1984
The minimization algorithms which do not require any preliminary generation of all the prime implicants (PI's) of a function are the most efficient. In this work a new algorithm is described which follows such an approach. It is based on a local selection of PI's carried out by examining a set of vertices whose number is never greater than the number of PI's of a minimum cost cover. This algorithm takes advantage of a technique which uses numerical equivalents of the function vertices as pointers. For this reason it is well suited for implementation by computer. To illustrate the features of this algorithm a few examples are reported.
A purification algorithm for semi-infinite programming
1992
Abstract In this paper we present a purification algorithm for semi-infinite linear programming. Starting with a feasible point, the algorithm either finds an improved extreme point or concludes with the unboundedness of the problem. The method is based on the solution of a sequence of linear programming problems. The study of some recession conditions has allowed us to establish a weak assumption for the finite convergence of this algorithm. Numerical results illustrating the method are given.