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Flexible Moment Invariant Bases for 2D Scalar and Vector Fields
Bujack, R.; Flusser, Jan
2017 - English
Complex moments have been successfully applied to pattern detection tasks in two-dimensional real, complex, and vector valued functions. In this paper, we review the different bases of rotational moment invariants based on the generator approach with complex monomials. We analyze their properties with respect to independence, completeness, and existence and\npresent superior bases that are optimal with respect to all three criteria for both scalar and vector fields.
Keywords:
Pattern detection; moment invariants; scalar fields; vector fields; flow fields; generator; basis; complex; monomial
Fulltext is available at external website.
Flexible Moment Invariant Bases for 2D Scalar and Vector Fields
Complex moments have been successfully applied to pattern detection tasks in two-dimensional real, complex, and vector valued functions. In this paper, we review the different bases of rotational ...
Avoiding overfitting of models: an application to research data on the Internet videos
Jiroušek, Radim; Krejčová, I.
2017 - English
The problem of overfitting is studied from the perspective of information theory. In this context, data-based model learning can be viewed as a transformation process, a process transforming the information contained in data into the information represented by a model. The overfitting of a model often occurs when one considers an unnecessarily complex model, which usually means that the considered model contains more information than the original data. Thus, using one of the basic laws of information theory saying that any transformation cannot increase the amount of information, we get the basic restriction laid on models constructed from data: A model is acceptable if it does not contain more information than the input data file.
Keywords:
data-based learning; probabilistic models; information theory; MDL principle; lossless encoding
Fulltext is available at external website.
Avoiding overfitting of models: an application to research data on the Internet videos
The problem of overfitting is studied from the perspective of information theory. In this context, data-based model learning can be viewed as a transformation process, a process transforming the ...
Causality and Intervention in Business Process Management
Bína, V.; Jiroušek, Radim
2017 - English
The paper presents an algebraic approach to the modeling of causality in systems of stochastic variables. The methodology is based on an operator of a composition that provides the possibility of composing a multidimensional distribution from low-dimensional building blocks taking advantage of the dependence structure of the problem variables. The authors formally define and demonstrate on a hypothetical example a surprisingly elegant unifying approach to conditioning by a single variable and the evaluation of the effect of an intervention. Both operations are realized by the composition with a degenerated distribution and differ only in the sequence in which the operator of the composition is performed.
Keywords:
Compositional model; Operator of composition,; Causality; Conditioning; Intervention
Fulltext is available at external website.
Causality and Intervention in Business Process Management
The paper presents an algebraic approach to the modeling of causality in systems of stochastic variables. The methodology is based on an operator of a composition that provides the possibility of ...
Alternative Formulation of Pay-as-clear Auction in Electricity Markets
Aussel, D.; Červinka, Michal; Henrion, R.; Pištěk, Miroslav
2017 - English
In widely used formulation of pay-as-clear electricity market the clearing price is given by the Lagrange multiplier of the demand sat- isfaction constraint in the problem of the Independent System Operator (ISO). Following this idea, one may usually calculate the market clearing\nprice analytically even for problems of higher dimensions. However, the economic interpretation of such a market setting is in question, since the minimized criterion does not correspond neither to the cost of production nor to the overall payment of consumers. This observation motivated us\nto propose an alternative clearing mechanism where the total payment of consumers is explicitly minimized. We show existence and uniqueness of the clearing price in such a setting.
Keywords:
electricity market; Lagrange multiplier; Independent System Operator
Available at various institutes of the ASCR
Alternative Formulation of Pay-as-clear Auction in Electricity Markets
In widely used formulation of pay-as-clear electricity market the clearing price is given by the Lagrange multiplier of the demand sat- isfaction constraint in the problem of the Independent System ...
Parametric Optimization and Related Topics XI
Červinka, Michal; Kratochvíl, Václav
2017 - English
Parametric Optimization and Related Topics XI was a conference dedicate to Jiří Outrata on the occasion of his seventieth birthday. The programme for 86 participants from 21 countries was composed of five invited and 77 contributed talks, held in 22 sessions.
Keywords:
Parametric Optimization; Optimization; Equilibrium
Fulltext is available at external website.
Parametric Optimization and Related Topics XI
Parametric Optimization and Related Topics XI was a conference dedicate to Jiří Outrata on the occasion of his seventieth birthday. The programme for 86 participants from 21 countries was composed of ...
Hidden Auto-Conflict in the Theory of Belief Functions
Daniel, M.; Kratochvíl, Václav
2017 - English
Hidden conflicts of belief functions in some cases where the sum of all multiples of conflicting belief masses being equal to zero were observed. Relationships of hidden conflicts and auto-conflicts of belief functions are pointed out. We are focused on hidden auto-conflicts here - on hidden conflicts appearing when three or more numerically same belief functions are combined. Hidden auto-conflict is a kind of internal conflict. Degrees of hidden auto-conflicts and full non-conflictness are defined and analysed. Finally, computational issues of hidden auto-conflicts and non-conflictness are presented.
Keywords:
Belief functions; Dempster-Shafer theory; Uncertainty; Conflicting belief masses; Internal conflict; Auto-conflict; Hidden-conflict
Fulltext is available at external website.
Hidden Auto-Conflict in the Theory of Belief Functions
Hidden conflicts of belief functions in some cases where the sum of all multiples of conflicting belief masses being equal to zero were observed. Relationships of hidden conflicts and auto-conflicts ...
Exact Inference In Robust Econometrics under Heteroscedasticity
Kalina, Jan; Peštová, B.
2017 - English
The paper is devoted to the least weighted squares estimator, which is one of highly robust estimators for the linear regression model. Novel permutation tests of heteroscedasticity are proposed. Also the asymptotic behavior of the permutation test statistics of the Goldfeld-Quandt and Breusch-Pagan tests is investigated. A numerical experiment on real economic data is presented, which also shows how to perform a robust prediction model under heteroscedasticity. Theoretical results may be simply extended to the context of multivariate quantiles
Keywords:
heteroscedasticity; robust statistics; regression; diagnostic tools; economic data
Fulltext is available at external website.
Exact Inference In Robust Econometrics under Heteroscedasticity
The paper is devoted to the least weighted squares estimator, which is one of highly robust estimators for the linear regression model. Novel permutation tests of heteroscedasticity are proposed. Also ...
A machine learning method for incomplete and imbalanced medical data
Salman, I.; Vomlel, Jiří
2017 - English
Our research reported in this paper is twofold. In the first part of the paper we use\nstandard statistical methods to analyze medical records of patients suffering myocardial\ninfarction from the third world Syria and a developed country - the Czech Republic.\nOne of our goals is to find whether there are statistically significant differences between\nthe two countries. In the second part of the paper we present an idea how to deal with\nincomplete and imbalanced data for tree-augmented naive Bayesian (TAN). All results\npresented in this paper are based on a real data about 603 patients from a hospital in\nthe Czech Republic and about 184 patients from two hospitals in Syria.
Keywords:
Machine Learning; Data Analysis; Bayesian networks; Imbalanced Data; Acute Myocardial Infarction
Fulltext is available at external website.
A machine learning method for incomplete and imbalanced medical data
Our research reported in this paper is twofold. In the first part of the paper we use\nstandard statistical methods to analyze medical records of patients suffering myocardial\ninfarction from the ...
Optimal Value of Loans via Stochastic Programming
Kaňková, Vlasta
2017 - English
A question of mortgage leads to serious and complicated problems of financial mathematics. On one side is a bank with an aim to have a “good” profit, on the other side is the client trying to invest money safely, with possible “small” risk.Let us suppose that a young married couple is in a position of client. Young people know that an expected and also unexpected unpleasant financial situation can happen. Many unpleasant financial situation can be caused by a random factor. Consequently stochastic methods are suitable to secure against them. The aim of the suggested model is not only to state a maximal reasonable value of loans, but also to endure unpleasant financial period. To this end we employ stochastic optimization theory. A few suitable models will be introduced. The choice of the model depends on environment of the young people. Models will be with “deterministic” constraints, probability constraints, but also with stochastic dominance constraints. The suggested models will be analyzed both from the numerical point of view and from possible method solution based on data. Except static one-objective problem we suggest also multi–objective models.
Keywords:
Loan-debtor; installments; stochastic programming; probability constraints; second order dominance constraints
Fulltext is available at external website.
Optimal Value of Loans via Stochastic Programming
A question of mortgage leads to serious and complicated problems of financial mathematics. On one side is a bank with an aim to have a “good” profit, on the other side is the client trying to invest ...
Feasibility Study of an Interactive Medical Diagnostic Wikipedia
Grim, Jiří
2016 - English
Considering different application possibilities of product distribution mixtures we have proposed three formal tools in the last years, which can be used to accumulate decision-making know-how from particular diagnostic cases. First, we have developed a structural mixture model to estimate multidimensional probability distributions from incomplete and possibly weighted data vectors. Second, we have shown that the estimated product mixture can be used as a knowledge base for the Probabilistic Expert System (PES) to infer conclusions from definite or even uncertain input information. Finally we have shown that, by using product mixtures, we can exactly optimize sequential decision-making by means of the Shannon formula of conditional informativity. We combine the above statistical tools in the framework of an interactive open-access medical diagnostic system with automatic accumulation of decision-making knowledge.
Keywords:
Multivariate statistics; Medical diagnostics; Product mixtures; Incomplete data; Sequential classification; EM algorithm
Fulltext is available at external website.
Feasibility Study of an Interactive Medical Diagnostic Wikipedia
Considering different application possibilities of product distribution mixtures we have proposed three formal tools in the last years, which can be used to accumulate decision-making know-how from ...
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