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Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers

Francesc J. Ferri (1998)

Kybernetika

Prototype Selection (PS) techniques have traditionally been applied prior to Nearest Neighbour (NN) classification rules both to improve its accuracy (editing) and to alleviate its computational burden (condensing). Methods based on selecting/discarding prototypes and methods based on adapting prototypes have been separately introduced to deal with this problem. Different approaches to this problem are considered in this paper and their main advantages and drawbacks are pointed out along with some...

Combining constraint Propagation and meta-heuristics for searching a Maximum Weight Hamiltonian Chain

Yves Caseau (2006)

RAIRO - Operations Research

This paper presents the approach that we developed to solve the ROADEF 2003 challenge problem. This work is part of a research program whose aim is to study the benefits and the computer-aided generation of hybrid solutions that mix constraint programming and meta-heuristics, such as large neighborhood search (LNS). This paper focuses on three contributions that were obtained during this project: an improved method for propagating Hamiltonian chain constraints, a fresh look at limited discrepancy...

Combining odometry and visual loop-closure detection for consistent topo-metrical mapping

S. Bazeille, D. Filliat (2010)

RAIRO - Operations Research - Recherche Opérationnelle

We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer, IEEE Transactions On Robotics, Special Issue on Visual SLAM 24 (2008) 1027–1037], which is able to detect when the robot has returned back to a previously visited...

Combining Odometry and Visual Loop-Closure Detection for Consistent Topo-Metrical Mapping

S. Bazeille, D. Filliat (2011)

RAIRO - Operations Research

We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer, IEEE Transactions On Robotics, Special Issue on Visual SLAM24 (2008) 1027–1037], which is able to detect when the robot has returned back to a previously visited...

Communication with www in Czech

Lukáš Svoboda, Luboš Popelínský (2004)

Kybernetika

This paper describes UIO, a multi–domain question–answering system for the Czech language that looks for answers on the web. UIO exploits two fields, namely natural language interface to databases and question answering. In its current version, UIO can be used for asking questions about train and coach timetables, cinema and theatre performances, about currency exchange rates, name–days and on the Diderot Encyclopaedia. Much effort have been made into making addition of a new domain very easy. No...

Comparative analysis of noise robustness of type 2 fuzzy logic controllers

Emanuel Ontiveros-Robles, Patricia Melin, Oscar Castillo (2018)

Kybernetika

Nowadays Fuzzy logic in control applications is a well-recognized alternative, and this is thanks to its inherent advantages as its robustness. However, the Type-2 Fuzzy Logic approach, allows managing uncertainty in the model. Type-2 Fuzzy Logic has recently shown to provide significant improvement in image processing applications, however it is also important to analyze its impact in controller performance. This paper is presenting a comparison in the robustness of Interval Type-2 and Generalized...

Comparing algorithms based on marginal problem

Otakar Kříž (2007)

Kybernetika

The paper deals with practical aspects of decision making under uncertainty on finite sets. The model is based on marginal problem. Numerical behaviour of 10 different algorithms is compared in form of a study case on the data from the field of rheumatology. (Five of the algorithms types were suggested by A. Perez.) The algorithms (expert systems, inference engines) are studied in different situations (combinations of parameters).

Comparison of supervised learning methods for spike time coding in spiking neural networks

Andrzej Kasiński, Filip Ponulak (2006)

International Journal of Applied Mathematics and Computer Science

In this review we focus our attention on supervised learning methods for spike time coding in Spiking Neural Networks (SNNs). This study is motivated by recent experimental results regarding information coding in biological neural systems, which suggest that precise timing of individual spikes may be essential for efficient computation in the brain. We are concerned with the fundamental question: What paradigms of neural temporal coding can be implemented with the recent learning methods? In order...

Comparison of two methods for approximation of probability distributions with prescribed marginals

Albert Pérez, Milan Studený (2007)

Kybernetika

Let P be a discrete multidimensional probability distribution over a finite set of variables N which is only partially specified by the requirement that it has prescribed given marginals { P A ; A ∈ 𝒮 } , where 𝒮 is a class of subsets of N with ⋃ 𝒮 = N . The paper deals with the problem of approximating P on the basis of those given marginals. The divergence of an approximation P ^ from P is measured by the relative entropy H ( P | P ^ ) . Two methods for approximating P are compared. One of them uses formerly introduced concept of...

Completing an uncertainty criterion of classification.

Joaquín Abellán (2005)

Mathware and Soft Computing

We present a variation of a method of classification based in uncertainty on credal set. Similarly to its origin it use the imprecise Dirichlet model to create the credal set and the same uncertainty measures. It take into account sets of two variables to reduce the uncertainty and to seek the direct relations between the variables in the data base and the variable to be classified. The success are equivalent to the success of the first method except in those where there are a direct relations between...

Compositional models, Bayesian models and recursive factorization models

Francesco M. Malvestuto (2016)

Kybernetika

Compositional models are used to construct probability distributions from lower-order probability distributions. On the other hand, Bayesian models are used to represent probability distributions that factorize according to acyclic digraphs. We introduce a class of models, called recursive factorization models, to represent probability distributions that recursively factorize according to sequences of sets of variables, and prove that they have the same representation power as both compositional...

Computing with words with the use of inverse RDM models of membership functions

Andrzej Piegat, Marcin Pluciński (2015)

International Journal of Applied Mathematics and Computer Science

Computing with words is a way to artificial, human-like thinking. The paper shows some new possibilities of solving difficult problems of computing with words which are offered by relative-distance-measure RDM models of fuzzy membership functions. Such models are based on RDM interval arithmetic. The way of calculation with words was shown using a specific problem of flight delay formulated by Lotfi Zadeh. The problem seems easy at first sight, but according to the authors' knowledge it has not...

Concept approximations based on rough sets and similarity measures

Jamil Saquer, Jitender Deogun (2001)

International Journal of Applied Mathematics and Computer Science

The formal concept analysis gives a mathematical definition of a formal concept. However, in many real-life applications, the problem under investigation cannot be described by formal concepts. Such concepts are called the non-definable concepts (Saquer and Deogun, 2000a). The process of finding formal concepts that best describe non-definable concepts is called the concept approximation. In this paper, we present two different approaches to the concept approximation. The first approach is based...

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