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Bayesian graphical modeling provides an appealing way to obtain uncertainty estimates when inferring network structures, and much recent progress has been made for Gaussian models. These models have been used extensively in applications to…

Methodology · Statistics 2012-07-06 Michael Finegold , Mathias Drton

Some new survival distributions are introduced based on a generalised exponential function. This class of distributions includes heavy-tailed generalisations of exponential, Weibull and gamma distributions. Properties of the distributions…

Methodology · Statistics 2014-12-03 Rose Baker

The search for life outside the Solar System is an endeavour of astronomers all around the world. With hundreds of exoplanets being discovered due to advances in astronomy, there is a need to classify the habitability of these exoplanets.…

Neural and Evolutionary Computing · Computer Science 2021-01-19 Sriram Krishna , Niharika Pentapati

Loss-based updating, including generalized Bayes, Gibbs, and quasi-posteriors, replaces likelihoods by a user-chosen loss and produces a posterior-like distribution via exponential tilt. We give a decision-theoretic characterization that…

Methodology · Statistics 2026-02-03 Kenichiro McAlinn , Kōsaku Takanashi

In this paper, we have proposed a new method for solving the Gaussian integral. Introducing a parameter that depends on a $n$ index, we have found a general solution for this type of integral inspired by Taylor series of a simple function.…

We propose a general learning algorithm for solving optimization problems, based on a simple strategy of trial and adaptation. The algorithm maintains a probability distribution of possible solutions (configurations), which is updated…

adap-org · Physics 2009-10-30 Kan Chen

Universal induction relies on some general search procedure that is doomed to be inefficient. One possibility to achieve both generality and efficiency is to specialize this procedure w.r.t. any given narrow task. However, complete…

Neural and Evolutionary Computing · Computer Science 2018-09-13 Alexey Potapov , Sergey Rodionov

A unified presentation of the perturbation and variational methods for the generalized statistical mechanics based on Tsallis entropy is given here. In the case of the variational method, the Bogoliubov inequality is generalized in a very…

Statistical Mechanics · Physics 2009-10-31 E. K. Lenzi , L. C. Malacarne , R. S. Mendes

This manuscript contains an outline of lectures course "Evolutionary Algorithms" read by the author. The course covers Canonic Genetic Algorithm and various other genetic algorithms as well as evolutionary strategies, genetic programming,…

Neural and Evolutionary Computing · Computer Science 2022-03-31 Anton V. Eremeev

1 Sharp prediction of extinction times is needed in biodiversity monitoring and conservation management. 2 The Galton-Watson process is a classical stochastic model for describing population dynamics. Its evolution is like the matrix…

Applications · Statistics 2019-01-29 B Cloez , T Daufresne , M Kerioui , B Fontez

Most decision tree induction algorithms are based on a greedy top-down recursive partitioning strategy for tree growth. In this paper, we propose several methods for induction of decision trees and their ensembles based on evolutionary…

Neural and Evolutionary Computing · Computer Science 2020-02-04 Evgeny Dolotov , Nikolai Zolotykh

The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics. The equilibrium distribution…

Statistical Mechanics · Physics 2007-05-23 A. S. Parvan

We show that within classical statistical mechanics without taking the thermodynamic limit, the most general Boltzmann factor for the canonical ensemble is a q-exponential function. The only assumption here is that microcanonical…

Statistical Mechanics · Physics 2009-11-11 Rudolf Hanel , Stefan Thurner

In this paper we introduce the so-called Generalized Naive Bayes structure as an extension of the Naive Bayes structure. We give a new greedy algorithm that finds a good fitting Generalized Naive Bayes (GNB) probability distribution. We…

Machine Learning · Statistics 2024-08-29 Edith Alice Kovács , Anna Ország , Dániel Pfeifer , András Benczúr

We develop the theory of canonical-dissipative systems, based on the assumption that both the conservative and the dissipative elements of the dynamics are determined by invariants of motion. In this case, known solutions for conservative…

Statistical Mechanics · Physics 2009-11-07 Frank Schweitzer , Werner Ebeling , Benno Tilch

We propose new analytical tools for describing growth-rate distributions generated by stationary time-series. Our analysis shows how deviations from normality are not pathological behaviour, as suggested by some traditional views, but…

Data Analysis, Statistics and Probability · Physics 2026-04-01 Edgardo Brigatti

We generalize the usual exponential Boltzmann factor to any reasonable and potentially observable distribution function, $B(E)$. By defining generalized logarithms $\Lambda$ as inverses of these distribution functions, we are led to a…

Statistical Mechanics · Physics 2007-05-23 Rudolf Hanel , Stefan Thurner

An algorithm is described that enables efficient deterministic approximate computation of the bootstrap distribution for any linear bootstrap method $T_n^*$, alleviating the need for repeated resampling from observations (resp.…

Methodology · Statistics 2019-04-10 Thomas Pitschel

Structured evolutionary algorithms have been investigated for some time. However, they have been under-explored specially in the field of multi-objective optimization. Despite their good results, the use of complex dynamics and structures…

Neural and Evolutionary Computing · Computer Science 2019-01-03 Danilo Vasconcellos Vargas , Junichi Murata , Hirotaka Takano , Alexandre Claudio Botazzo Delbem

We discuss the use of Tsallis generalized mechanics in simulated annealing algorithms. For a small peptide it is shown that older implementations are not more effective than regular simulated annealing in finding ground state…

Condensed Matter · Physics 2015-06-25 Ulrich H. E. Hansmann
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