Relevant bibliographies by topics / Algorithmic analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Algorithmic analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 June 2025

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Journal articles on the topic "Algorithmic analysis"

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Prautzsch, H. "Algorithmic Blending." Journal of Approximation Theory 72, no. 1 (1993): 87–102. http://dx.doi.org/10.1006/jath.1993.1008.

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Bailey, Simon, Dean Pierides, Adam Brisley, Clara Weisshaar, and Tom Blakeman. "Dismembering organisation: The coordination of algorithmic work in healthcare." Current Sociology 68, no. 4 (2020): 546–71. http://dx.doi.org/10.1177/0011392120907638.

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Algorithms are increasingly being adopted in healthcare settings, promising increased safety, productivity and efficiency. The growing sociological literature on algorithms in healthcare shares an assumption that algorithms are introduced to ‘support’ decisions within an interactive order that is predominantly human-oriented. This article presents a different argument, calling attention to the manner in which organisations can end up introducing a non-negotiable disjuncture between human-initiated care work and work that supports algorithms, which the authors call algorithmic work. Drawing on an ethnographic study, the authors describe how two hospitals in England implemented an Acute Kidney Injury (AKI) algorithm and analyse ‘interruptions’ to the algorithm’s expected performance. When the coordination of algorithmic work occludes care work, the study finds a ‘dismembered’ organisation that is algorithmically-oriented rather than human-oriented. In the discussion, the authors examine the consequences of coordinating human and non-human work in each hospital and conclude by urging sociologists of organisation to attend to the importance of the formal in algorithmic work. As the use of algorithms becomes widespread, the analysis provides insight into how organisations outside of healthcare can also end up severing tasks from human experience when algorithmic automation is introduced.
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Lu, Chung-Cheng Jason, and Yen-Chun Jim Wu. "Evaluation of Heuristics Using Data Envelopment Analysis." International Journal of Information Technology & Decision Making 13, no. 04 (2014): 795–810. http://dx.doi.org/10.1142/s0219622014500606.

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This paper focuses on identifying relatively efficient configurations of algorithmic operators among a set of configurations in the development of heuristics or meta-heuristics. Each configuration is considered as a decision-making unit with multiple inputs and outputs. Then, data envelopment analysis (DEA) is adopted to evaluate relative and cross-efficiencies of a set of algorithmic configurations. The proposed approach differs from existing methods based on statistical tests in that multiple inputs and outputs are simultaneously considered in an integrated framework for the evaluation of algorithmic efficiency. A case study is presented to demonstrate the application of DEA for determining the efficient configurations of genetic algorithm operators. The evaluation results of two DEA models are also compared. The DEA evaluation results are consistent with those obtained by a commonly used statistical method.
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V'yugin, Vladimir V. "Bayesianism: An Algorithmic Analysis." Information and Computation 127, no. 1 (1996): 1–10. http://dx.doi.org/10.1006/inco.1996.0045.

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Khusainov, B. M. "Algorithmic degree of unars." Algebra and Logic 27, no. 4 (1988): 301–12. http://dx.doi.org/10.1007/bf01978402.

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Ben Gharbia, I., and J. Ch Gilbert. "An Algorithmic Characterization of $P$-Matricity." SIAM Journal on Matrix Analysis and Applications 34, no. 3 (2013): 904–16. http://dx.doi.org/10.1137/120883025.

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Paudyal, Pragya, and B. L. William Wong. "Algorithmic Opacity: Making Algorithmic Processes Transparent through Abstraction Hierarchy." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 192–96. http://dx.doi.org/10.1177/1541931218621046.

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In this paper we introduce the problem of algorithmic opacity and the challenges it presents to ethical decision-making in criminal intelligence analysis. Machine learning algorithms have played important roles in the decision-making process over the past decades. Intelligence analysts are increasingly being presented with smart black box automation that use machine learning algorithms to find patterns or interesting and unusual occurrences in big data sets. Algorithmic opacity is the lack visibility of computational processes such that humans are not able to inspect its inner workings to ascertain for themselves how the results and conclusions were computed. This is a problem that leads to several ethical issues. In the VALCRI project, we developed an abstraction hierarchy and abstraction decomposition space to identify important functional relationships and system invariants in relation to ethical goals. Such explanatory relationships can be valuable for making algorithmic process transparent during the criminal intelligence analysis process.
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Franklin, Johanna N. Y., Timothy H. McNicholl, and Jason Rute. "Algorithmic Randomness and Fourier Analysis." Theory of Computing Systems 63, no. 3 (2018): 567–86. http://dx.doi.org/10.1007/s00224-018-9888-8.

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Bruno, A. D., and V. F. Edneral. "Algorithmic analysis of local integrability." Doklady Mathematics 79, no. 1 (2009): 48–52. http://dx.doi.org/10.1134/s1064562409010141.

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Ventsov, Yu G. "Algorithmic properties of branching models." Algebra and Logic 25, no. 4 (1986): 229–38. http://dx.doi.org/10.1007/bf01979010.

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Dissertations / Theses on the topic "Algorithmic analysis"

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Óbdržálek, Jan. "Algorithmic analysis of parity games." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/25034.

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In this thesis we add to the body of work on parity games. We start by presenting parity games and explaining the concepts behind them, giving a survey of known algorithms, and show their relationship to other problems. In the second part of the thesis we want to answer the following question: Are there classes of graphs on which we can solve parity games in polynomial time? Tree-width has long been considered the most important connectivity measure of (undirected) graphs, and we give a polynomial algorithm for solving parity games on graphs of bounded tree-width. However tree-width is not the most concise measure for directed graphs, on which the parity games are played. We therefore introduce a new measure for directed graphs called DAG-width. We show several properties of this measure, including its relationship to other measures, and give a polynomial-time algorithm for solving parity games on graphs of bounded DAG-width. In the third part we analyze the strategy improvement algorithm of Vöge and Jurdziński, providing some new results and comments on their algorithm. Finally we present a new algorithm for parity games, in part inspired by the strategy improvement algorithm, based on spines. The notion of spine is a new structural way of capturing the (possible) winning sets and counterstrategies. This notion has some interesting properties, which can give a further insight into parity games.
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Nell, Christopher Warren. "Automating meta-algorithmic analysis and design." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/38247.

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Sophisticated empirical methods based upon automated experimental analysis techniques drive the development of high-performance solvers for an increasing range of problems from industry and academia. However, tools implementing these methods are often difficult to develop and to use. This thesis describes work towards addressing this issue. First, we develop a formal description of meta-algorithmic problems, and use it as the basis for a framework supporting the development and application of a broad class of automated algorithm analysis and design techniques. Second, we describe the High-performance Algorithm Laboratory (HAL), an extensible software implementation of this framework that provides developers and users of automated empirical techniques with support for distributed execution, remote monitoring, data management, and statistical analysis of results. We use HAL to construct a suite of interoperable tools that implement a variety of automated empirical techniques, and demonstrate our approach by conducting a sequence of increasingly complex analysis and design tasks on state-of-the-art solvers for Boolean satisfiability and mixed-integer programming problems.
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Anagnostopoulou, Christina. "Algorithmic categorisation in formal music analysis." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/22277.

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A new method of formal music analysis is presented, <i>Similarity and Categorisation Analysis of Music, </i>which is based on Paradigmatic Analysis of music, as devised by Nattiez. The new method, which is independent of musical style, is applied to three pieces of diverse character: a Scottish folk tune, a solo flute piece by Debussy and a piece from a piano sonata by Boulez. As in Paradigmatic Analysis, the analyst produces a classification of the segments of a piece of music. However, the new method is set in a more formal framework in which the individual steps of the analysis are clearly delineated and the criteria for the classification are explicitly defined. Furthermore, in extension to Paradigmatic Analysis, the resulting classification is hierarchical, and new findings from categorisation theory are brought in to enhance the methodology and to act as a bridge to cognitive modelling of categorisation in music analysis. The new method is computationally modelled with an unsupervised neural network algorithm, thereby further formalising the classification process. The rationale behind this new approach is to allow for a formal analysis without restricting the analyst’s freedom of choice: the method acts as a framework for the analysis, making explicit previously intuitive decisions of the analyst, while the analyst remains free to choose his/her own analytical criteria. The thesis is divided into two parts: the first part provides necessary background and describes the new method in detail in musical terms. An example analysis is demonstrated for a Scottish folk tune. The second part describes the computational model of the method. The purpose of the computational analyses is two-fold: first, to produce entirely new analyses, and second, to reproduce human analyses in order to find the criteria on which the analyst based his/her decisions. Two more pieces of different character are analysed using the computational model: <i>Syrinx</i> by Debussy, which has previously been analysed by Nattiez in the framework of Paradigmatic Analyses, and <i>Parenthèse </i>by Boulez. The thesis concludes with an evaluation of the method and a discussion of the extent to which it is possible and useful to be formal in music analysis.
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Rute, Jason. "Topics in algorithmic randomness and computable analysis." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/260.

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This dissertation develops connections between algorithmic randomness and computable analysis. In the first part, it is shown that computable randomness can be defined robustly on all computable probability spaces, and that computable randomness is preserved by a.e. computable isomorphisms between spaces. Further applications are also given. In the second part, a number of almost-everywhere convergence theorems are looked at using computable analysis and algorithmic randomness. These include various martingale convergence theorems and almosteverywhere differentiability theorems. General conditions are given for when the rate of convergence is computable and for when convergence takes place on the Schnorr random points. Examples are provided to show that these almost-everywhere convergence theorems characterize Schnorr randomness.
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Iz, Huseyin Baki. "An algorithmic approach to crustal deformation analysis /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487327695621647.

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Hautphenne, Sophie. "An algorithmic look at phase-controlled branching processes." Doctoral thesis, Universite Libre de Bruxelles, 2009. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210255.

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Branching processes are stochastic processes describing the evolution of populations of individuals which reproduce and die independently of each other according to specific probability laws. We consider a particular class of branching processes, called Markovian binary trees, where the lifetime and birth epochs of individuals are controlled by a Markovian arrival process. <p><p>Our objective is to develop numerical methods to answer several questions about Markovian binary trees. The issue of the extinction probability is the main question addressed in the thesis. We first assume independence between individuals. In this case, the extinction probability is the minimal nonnegative solution of a matrix fixed point equation which can generally not be solved analytically. In order to solve this equation, we develop a linear algorithm based on functional iterations, and a quadratic algorithm, based on Newton's method, and we give their probabilistic interpretation in terms of the tree. <p><p>Next, we look at some transient features for a Markovian binary tree: the distribution of the population size at any given time, of the time until extinction and of the total progeny. These distributions are obtained using the Kolmogorov and the renewal approaches. <p><p>We illustrate the results mentioned above through an example where the Markovian binary tree serves as a model for female families in different countries, for which we use real data provided by the World Health Organization website. <p><p>Finally, we analyze the case where Markovian binary trees evolve under the external influence of a random environment or a catastrophe process. In this case, individuals do not behave independently of each other anymore, and the extinction probability may no longer be expressed as the solution of a fixed point equation, which makes the analysis more complicated. We approach the extinction probability, through the study of the population size distribution, by purely numerical methods of resolution of partial differential equations, and also by probabilistic methods imposing constraints on the external process or on the maximal population size.<p><p>/<p><p>Les processus de branchements sont des processus stochastiques décrivant l'évolution de populations d'individus qui se reproduisent et meurent indépendamment les uns des autres, suivant des lois de probabilités spécifiques. <p><p>Nous considérons une classe particulière de processus de branchement, appelés arbres binaires Markoviens, dans lesquels la vie d'un individu et ses instants de reproduction sont contrôlés par un MAP. Notre objectif est de développer des méthodes numériques pour répondre à plusieurs questions à propos des arbres binaires Markoviens.<p><p>La question de la probabilité d'extinction d'un arbre binaire Markovien est la principale abordée dans la thèse. Nous faisons tout d'abord l'hypothèse d'indépendance entre individus. Dans ce cas, la probabilité d'extinction s'exprime comme la solution minimale non négative d'une équation de point fixe matricielle, qui ne peut être résolue analytiquement. Afin de résoudre cette équation, nous développons un algorithme linéaire, basé sur l'itération fonctionnelle, ainsi que des algorithmes quadratiques, basés sur la méthode de Newton, et nous donnons leur interprétation probabiliste en termes de l'arbre que l'on étudie.<p><p>Nous nous intéressons ensuite à certaines caractéristiques transitoires d'un arbre binaire Markovien: la distribution de la taille de la population à un instant donné, celle du temps jusqu'à l'extinction du processus et celle de la descendance totale. Ces distributions sont obtenues en utilisant l'approche de Kolmogorov ainsi que l'approche de renouvellement.<p><p>Nous illustrons les résultats mentionnés plus haut au travers d'un exemple où l'arbre binaire Markovien sert de modèle pour des populations féminines dans différents pays, et pour lesquelles nous utilisons des données réelles fournies par la World Health Organization.<p><p>Enfin, nous analysons le cas où les arbres binaires Markoviens évoluent sous une influence extérieure aléatoire, comme un environnement Markovien aléatoire ou un processus de catastrophes. Dans ce cas, les individus ne se comportent plus indépendamment les uns des autres, et la probabilité d'extinction ne peut plus s'exprimer comme la solution d'une équation de point fixe, ce qui rend l'analyse plus compliquée. Nous approchons la probabilité d'extinction au travers de l'étude de la distribution de la taille de la population, à la fois par des méthodes purement numériques de résolution d'équations aux dérivées partielles, ainsi que par des méthodes probabilistes en imposant des contraintes sur le processus extérieur ou sur la taille maximale de la population.<br>Doctorat en Sciences<br>info:eu-repo/semantics/nonPublished
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Weingartner, Stephan G. "System development : an algorithmic approach." Virtual Press, 1987. http://liblink.bsu.edu/uhtbin/catkey/483077.

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The subject chosen to develop this thesis project on is developing an algorithm or methodology for system selection. The specific problem studied involves a procedure to determine anion computer system alternative is the best choice for a given user situation.The general problem to be addressed is the need for one to choose computing hardware, software, systems, or services in a -Logical approach from a user perspective, considering cost, performance and human factors. Most existing methods consider only cost and performance factors, combining these factors in ad hoc, subjective fashions to react: a selection decision. By not considering factors treat measure effectiveness and functionality of computer services for a user, existing methods ignore some of the most important measures of value to the user.In this work, a systematic and comprehensive approach to computer system selection has been developed. Also developed were methods for selecting and organizing various criteria.Also ways to assess the importance and value of different service attributes to a end-user are discussed.Finally, the feasibility of a systematic approach to computer system selection has been proven by establishing a general methodology and by proving it through a demonstration of a specific application.
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Simpson, D. P. "Deadlock free algorithmic parallelism : analysis, implementation and performance." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274694.

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Trstanova, Zofia. "Mathematical and algorithmic analysis of modified Langevin dynamics." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM054/document.

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En physique statistique, l’information macroscopique d’intérêt pour les systèmes considérés peut être dé-duite à partir de moyennes sur des configurations microscopiques réparties selon des mesures de probabilitéµ caractérisant l’état thermodynamique du système. En raison de la haute dimensionnalité du système (quiest proportionnelle au nombre de particules), les configurations sont le plus souvent échantillonnées en util-isant des trajectoires d’équations différentielles stochastiques ou des chaînes de Markov ergodiques pourla mesure de Boltzmann-Gibbs µ, qui décrit un système à température constante. Un processus stochas-tique classique permettant d’échantillonner cette mesure est la dynamique de Langevin. En pratique, leséquations de la dynamique de Langevin ne peuvent pas être intégrées analytiquement, la solution est alorsapprochée par un schéma numérique. L’analyse numérique de ces schémas de discrétisation est maintenantbien maîtrisée pour l’énergie cinétique quadratique standard. Une limitation importante des estimateurs desmoyennes sontleurs éventuelles grandes erreurs statistiques.Sous certaines hypothèsessur lesénergies ciné-tique et potentielle, il peut être démontré qu’un théorème de limite central est vrai. La variance asymptotiquepeut être grande en raison de la métastabilité du processus de Langevin, qui se produit dès que la mesure deprobabilité µ est multimodale.Dans cette thèse, nous considérons la discrétisation de la dynamique de Langevin modifiée qui améliorel’échantillonnage de la distribution de Boltzmann-Gibbs en introduisant une fonction cinétique plus généraleà la place de la formulation quadratique standard. Nous avons en fait deux situations en tête : (a) La dy-namique de Langevin Adaptativement Restreinte, où l’énergie cinétique s’annule pour les faibles moments,et correspond à l’énergie cinétique standard pour les forts moments. L’intérêt de cette dynamique est que lesparticules avec une faible énergie sont restreintes. Le gain vient alors du fait que les interactions entre lesparticules restreintes ne doivent pas être mises à jour. En raison de la séparabilité des positions et des mo-ments marginaux de la distribution, les moyennes des observables qui dépendent de la variable de positionsont égales à celles calculées par la dynamique de Langevin standard. L’efficacité de cette méthode résidedans le compromis entre le gain de calcul et la variance asymptotique des moyennes ergodiques qui peutaugmenter par rapport à la dynamique standards car il existe a priori plus des corrélations dans le tempsen raison de particules restreintes. De plus, étant donné que l’énergie cinétique est nulle sur un ouvert, ladynamique de Langevin associé ne parvient pas à être hypoelliptique. La première tâche de cette thèse est deprouver que la dynamique de Langevin avec une telle énergie cinétique est ergodique. L’étape suivante con-siste à présenter une analyse mathématique de la variance asymptotique de la dynamique AR-Langevin. Afinde compléter l’analyse de ce procédé, on estime l’accélération algorithmique du coût d’une seule itération,en fonction des paramètres de la dynamique. (b) Nous considérons aussi la dynamique de Langevin avecdes énergies cinétiques dont la croissance est plus que quadratique à l’infini, dans une tentative de réduire lamétastabilité. La liberté supplémentaire fournie par le choix de l’énergie cinétique doit être utilisée afin deréduire la métastabilité de la dynamique. Dans cette thèse, nous explorons le choix de l’énergie cinétique etnous démontrons une convergence améliorée des moyennes ergodiques sur un exemple de faible dimension.Un des problèmes avec les situations que nous considérons est la stabilité des régimes discrétisés. Afind’obtenir une méthode de discrétisation faiblement cohérente d’ordre 2 (ce qui n’est plus trivial dans le casde l’énergie cinétique générale), nous nous reposons sur les schémas basés sur des méthodes de Metropolis<br>In statistical physics, the macroscopic information of interest for the systems under consideration can beinferred from averages over microscopic configurations distributed according to probability measures µcharacterizing the thermodynamic state of the system. Due to the high dimensionality of the system (whichis proportional to the number of particles), these configurations are most often sampled using trajectories ofstochastic differential equations or Markov chains ergodic for the probability measure µ, which describesa system at constant temperature. One popular stochastic process allowing to sample this measure is theLangevin dynamics. In practice, the Langevin dynamics cannot be analytically integrated, its solution istherefore approximated with a numerical scheme. The numerical analysis of such discretization schemes isby now well-understood when the kinetic energy is the standard quadratic kinetic energy.One important limitation of the estimators of the ergodic averages are their possibly large statisticalerrors.Undercertainassumptionsonpotentialandkineticenergy,itcanbeshownthatacentrallimittheoremholds true. The asymptotic variance may be large due to the metastability of the Langevin process, whichoccurs as soon as the probability measure µ is multimodal.In this thesis, we consider the discretization of modified Langevin dynamics which improve the samplingof the Boltzmann–Gibbs distribution by introducing a more general kinetic energy function U instead of thestandard quadratic one. We have in fact two situations in mind:(a) Adaptively Restrained (AR) Langevin dynamics, where the kinetic energy vanishes for small momenta,while it agrees with the standard kinetic energy for large momenta. The interest of this dynamics isthat particles with low energy are restrained. The computational gain follows from the fact that theinteractions between restrained particles need not be updated. Due to the separability of the positionand momenta marginals of the distribution, the averages of observables which depend on the positionvariable are equal to the ones computed with the standard Langevin dynamics. The efficiency of thismethod lies in the trade-off between the computational gain and the asymptotic variance on ergodic av-erages which may increase compared to the standard dynamics since there are a priori more correlationsin time due to restrained particles. Moreover, since the kinetic energy vanishes on some open set, theassociated Langevin dynamics fails to be hypoelliptic. In fact, a first task of this thesis is to prove thatthe Langevin dynamics with such modified kinetic energy is ergodic. The next step is to present a math-ematical analysis of the asymptotic variance for the AR-Langevin dynamics. In order to complementthe analysis of this method, we estimate the algorithmic speed-up of the cost of a single iteration, as afunction of the parameters of the dynamics.(b) We also consider Langevin dynamics with kinetic energies growing more than quadratically at infinity,in an attempt to reduce metastability. The extra freedom provided by the choice of the kinetic energyshould be used in order to reduce the metastability of the dynamics. In this thesis, we explore thechoice of the kinetic energy and we demonstrate on a simple low-dimensional example an improvedconvergence of ergodic averages.An issue with the situations we consider is the stability of discretized schemes. In order to obtain aweakly consistent method of order 2 (which is no longer trivial for a general kinetic energy), we rely on therecently developped Metropolis schemes
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Schleiermacher, Chris. "Algorithmic support for PCR and genome wide repeat analysis." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=963799495.

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Books on the topic "Algorithmic analysis"

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Bokutʹ, L. A. Algorithmic and combinatorial algebra. Kluwer Academic, 1994.

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Ruhe, Günther. Algorithmic aspects of flows in networks. Kluwer Academic Publishers, 1991.

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Zidong, Wang, and Liu Xiaohui, eds. Microarray image analysis: An algorithmic approach. Chapman & Hall/CRC, 2010.

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Fraser, Karl. Microarray image analysis: An algorithmic approach. Chapman & Hall/CRC, 2010.

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Tsinaslanidis, Prodromos E., and Achilleas D. Zapranis. Technical Analysis for Algorithmic Pattern Recognition. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23636-0.

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Algorithmic algebraic combinatorics and Gröbner bases. Springer, 2009.

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Křivánek, Mirko. Algorithmic and geometric aspects of cluster analysis. Academia nakl. Československé akademie věd, 1991.

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Iz, Huseyin Baki. An algorithmic approach to crustal deformation analysis. Dept. of Geodetic Science and Surveying, Ohio State University, 1987.

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Smart, Nigel P. The algorithmic resolution of diophantine equations. Cambridge University Press, 1998.

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Aronov, Boris. Combinatorial and algorithmic analysis of space decomposition problems. Courant Institute of Mathematical Sciences, New York University, 1989.

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Book chapters on the topic "Algorithmic analysis"

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Leiserson, Charles E. "Algorithmic analysis of multithreaded algorithms." In Algorithms and Computation. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63890-3_15.

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Abramsky, Samson. "Algorithmic Game Semantics and Static Analysis." In Static Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11547662_1.

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Bucio Ramirez, Ariana Guadalupe, Cesar Marco Antonio Robles Gonzalez, Marco Pedro Ramirez Tachiquin, and Rogelio Adrian Hernandez Becerril. "Algorithmic Analysis of the Pseudoanalytic Cryptographic Algorithm." In Transactions on Engineering Technologies. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9115-1_16.

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Gupta, Sushmita, Sanjukta Roy, Saket Saurabh, and Meirav Zehavi. "Group Activity Selection on Graphs: Parameterized Analysis." In Algorithmic Game Theory. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66700-3_9.

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Martinoli, O., F. Masulli, and M. Riani. "Algorithmic Information of Images." In Image Analysis and Processing II. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1007-5_31.

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Tsinaslanidis, Prodromos E., and Achilleas D. Zapranis. "Technical Analysis." In Technical Analysis for Algorithmic Pattern Recognition. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23636-0_1.

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Rios, Jesus, and David Rios Insua. "Adversarial Risk Analysis: Applications to Basic Counterterrorism Models." In Algorithmic Decision Theory. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04428-1_27.

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Lee, Wonchan, Bow-Yaw Wang, and Kwangkeun Yi. "Termination Analysis with Algorithmic Learning." In Computer Aided Verification. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31424-7_12.

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Qadeer, Shaz. "Algorithmic Verification of Systems Software Using SMT Solvers." In Static Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03237-0_2.

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Simakov, Sergey, Iaroslav Ispolatov, Sergei Maslov, and Alexander Nikitin. "Algorithmic Basis for Pathway Visualization." In Pathway Analysis for Drug Discovery. John Wiley & Sons, Inc., 2008. http://dx.doi.org/10.1002/9780470399279.ch4.

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Conference papers on the topic "Algorithmic analysis"

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Alexandrov, Natalia, and Robert Lewis. "Algorithmic perspectives on problem formulations in MDO." In 8th Symposium on Multidisciplinary Analysis and Optimization. American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4719.

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Simon, Jaan-Willem, and Dieter Weichert. "Interior-Point Method for the Computation of Shakedown Loads for Engineering Systems." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25334.

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A new interior-point algorithm for the computation of shakedown loads has recently been developed by the authors. The analytical formulation is based on the statical shakedown theorem by Melan which leads to a nonlinear convex optimization problem. The algorithm’s efficiency results from the close adaption of the solution procedure to the specific problem of shakedown analysis. This paper focuses on algorithmic aspects of the proposed method. A numerical example of practical interest is used for validation purposes.
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Roy, Swapnoneel, Atri Rudra, and Akshat Verma. "Energy Aware Algorithmic Engineering." In 2014 IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS. IEEE, 2014. http://dx.doi.org/10.1109/mascots.2014.47.

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Díaz, R. Durán, and J. Muñoz Masqué. "Algorithmic and Experimental Computation of Higher‐Order Safe Primes." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS: International Conference on Numerical Analysis and Applied Mathematics 2008. American Institute of Physics, 2008. http://dx.doi.org/10.1063/1.2990883.

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Szabo, Jozsef Z., and Peter Bakucz. "Determining Algorithmic Performance with Uncertainty Analysis." In 2019 IEEE 17th International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2019. http://dx.doi.org/10.1109/sisy47553.2019.9111554.

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Kim, Eric P., and Naresh R. Shanbhag. "Statistical analysis of algorithmic noise tolerance." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638153.

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Ghafari, Naghmeh, Arie Gurfinkel, Nils Klarlund, and Richard Trefler. "Algorithmic Analysis of Piecewise FIFO Systems." In Formal Methods in Computer Aided Design (FMCAD'07). IEEE, 2007. http://dx.doi.org/10.1109/fmcad.2007.4401981.

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Ghafari, Nagh, Arie Gurfinkel, Nils Klarlund, and Richard Trefler. "Algorithmic Analysis of Piecewise FIFO Systems." In Formal Methods in Computer Aided Design (FMCAD'07). IEEE, 2007. http://dx.doi.org/10.1109/famcad.2007.18.

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Bassily, Raef, Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, and Jonathan Ullman. "Algorithmic stability for adaptive data analysis." In STOC '16: Symposium on Theory of Computing. ACM, 2016. http://dx.doi.org/10.1145/2897518.2897566.

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Sagebaum, Max, Emre Özkaya, Nicolas R. Gauger, et al. "Efficient Algorithmic Differentiation Techniques for Turbo-machinery Design." In 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. American Institute of Aeronautics and Astronautics, 2017. http://dx.doi.org/10.2514/6.2017-3998.

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Reports on the topic "Algorithmic analysis"

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Acton, S., K. Skadron, S. Ozer, R. Sarkar, and D. Newell. Prototype for Meta-Algorithmic, Content-Aware Image Analysis. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada621858.

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V.A. Mousseau. Architectural and Algorithmic Requirements for a Next-Generation System Analysis Code. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1004279.

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Barry, Matthew, Eric Bush, Doug Smith, et al. Static Analysis Numerical Algorithms. Defense Technical Information Center, 2016. http://dx.doi.org/10.21236/ad1008340.

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McGeoch, Catherine C. Experimental Analysis of Algorithms. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada188528.

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Williamson, William R. Systems Analysis Quality Metrics Algorithms. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada272811.

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Cordeiro de Amorim, Renato. A survey on feature weighting based K-Means algorithms. Web of Open Science, 2020. http://dx.doi.org/10.37686/ser.v1i2.79.

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In a real-world data set there is always the possibility, rather high in our opinion, that different features may have different degrees of relevance. Most machine learning algorithms deal with this fact by either selecting or deselecting features in the data preprocessing phase. However, we maintain that even among relevant features there may be different degrees of relevance, and this should be taken into account during the clustering process. With over 50 years of history, K-Means is arguably the most popular partitional clustering algorithm there is. The first K-Means based clustering algorithm to compute feature weights was designed just over 30 years ago. Various such algorithms have been designed since but there has not been, to our knowledge, a survey integrating empirical evidence of cluster recovery ability, common flaws, and possible directions for future research. This paper elaborates on the concept of feature weighting and addresses these issues by critically analysing some of the most popular, or innovative, feature weighting mechanisms based in K-Means
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De Jong, Wibe A., Chris S. Oehmen, and Douglas J. Baxter. "Greenbook Algorithms and Hardware Needs Analysis". Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/989065.

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Phillips, P. Jonathon, and Elaine M. Newton. Meta-analysis of face recognition algorithms. National Institute of Standards and Technology, 2001. http://dx.doi.org/10.6028/nist.ir.6719.

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Hart, Darren M., and Bion John Merchant. Component evaluation testing and analysis algorithms. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1031883.

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Morris, R. A., and T. Chancellor. Algorithm for dual-energy radiographic analysis. Office of Scientific and Technical Information (OSTI), 1994. http://dx.doi.org/10.2172/10103845.

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