Bibliografías temáticas / Empirical methods

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Literatura académica sobre el tema "Empirical methods"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 22 de febrero de 2025

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Artículos de revistas sobre el tema "Empirical methods"

1

Lindley, D. V., J. S. Maritz y T. Lwin. "Empirical Bayes Methods". Mathematical Gazette 74, n.º 467 (marzo de 1990): 91. http://dx.doi.org/10.2307/3618894.

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Bagghi, Parthasarathy, J. S. Maritz y T. Lwin. "Empirical Bayes Methods." Journal of the American Statistical Association 86, n.º 413 (marzo de 1991): 244. http://dx.doi.org/10.2307/2289739.

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Angus, John E. "Empirical Bayes Methods". Technometrics 33, n.º 2 (mayo de 1991): 243–45. http://dx.doi.org/10.1080/00401706.1991.10484821.

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Stephenson, W. Robert. "Empirical Bayes Methods". Journal of Quality Technology 22, n.º 3 (julio de 1990): 249–50. http://dx.doi.org/10.1080/00224065.1990.11979250.

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Young, Karen, J. Maritz y T. Lwin. "Empirical Bayes Methods." Applied Statistics 41, n.º 3 (1992): 604. http://dx.doi.org/10.2307/2348097.

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Denham, Mike, J. S. Maritz y T. Lwin. "Empirical Bayes Methods." Statistician 39, n.º 1 (1990): 97. http://dx.doi.org/10.2307/2348214.

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Schneider-Mayerson, Matthew, Alexa Weik von Mossner y W. P. Małecki. "Empirical Ecocriticism: Environmental Texts and Empirical Methods". ISLE: Interdisciplinary Studies in Literature and Environment 27, n.º 2 (2020): 327–36. http://dx.doi.org/10.1093/isle/isaa022.

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ter Beek, Maurice H. y Alessio Ferrari. "Empirical Formal Methods: Guidelines for Performing Empirical Studies on Formal Methods". Software 1, n.º 4 (24 de septiembre de 2022): 381–416. http://dx.doi.org/10.3390/software1040017.

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Empirical studies on formal methods and tools are rare. In this paper, we provide guidelines for such studies. We mention their main ingredients and then define nine different study strategies (usability testing, laboratory experiments with software and human subjects, case studies, qualitative studies, surveys, judgement studies, systematic literature reviews, and systematic mapping studies) and discuss for each of them their crucial characteristics, the difficulties of applying them to formal methods and tools, typical threats to validity, their maturity in formal methods, pointers to external guidelines, and pointers to studies in other fields. We conclude with a number of challenges for empirical formal methods.
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Wolstein, Benjamin. "Five Empirical Psychoanalytic Methods". Contemporary Psychoanalysis 26, n.º 2 (abril de 1990): 237–56. http://dx.doi.org/10.1080/00107530.1990.10746657.

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Laird, Nan M. y Thomas A. Louis. "Empirical Bayes Ranking Methods". Journal of Educational Statistics 14, n.º 1 (marzo de 1989): 29–46. http://dx.doi.org/10.3102/10769986014001029.

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Ranking problems arise in setting priorities for investigations, in providing a simple summary of performance, in comparing objects in a manner robust to measurement scale, and in a wide variety of other applications. Commonly, rankings are computed from measurements that depend on the true attribute. Using the Gaussian model, we propose and compare methods for using these measurements to estimate the ranks of the underlying attributes and show that those based on an empirical Bayes model produce estimates that differ from ranking observed data. These differences result both from the effect of shrinking posterior means towards a common value by an amount that depends on the precision of individual measurements and from the Bayes processing of the posterior distribution to produce estimates that account for the uncertainty in the distribution of the ranks. We illustrate different ranking methods using data on school achievement reported by Aitkin and Longford (1986) . Mathematical and empirical results highlight the importance of using appropriate ranking methods and identify issues requiring further research.
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Tesis sobre el tema "Empirical methods"

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Luta, Gheorghe Sen Pranab Kumar Koch Gary G. "Empirical likelihood-based adjustment methods". Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2006. http://dc.lib.unc.edu/u?/etd,502.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2006.
Title from electronic title page (viewed Oct. 10, 2007). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biostatistics." Discipline: Biostatistics; Department/School: Public Health.
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Zawadzki, Erik P. "Multiagent learning and empirical methods". Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2480.

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Many algorithms exist for learning how to act in a repeated game and most have theoretical guarantees associated with their behaviour. However, there are few experimental results about the empirical performance of these algorithms, which is important for any practical application of this work. Most of the empirical claims in the literature to date have been based on small experiments, and this has hampered the development of multiagent learning (MAL) algorithms with good performance properties. In order to rectify this problem, we have developed a suite of tools for running multiagent experiments called the Multiagent Learning Testbed (MALT). These tools are designed to facilitate running larger and more comprehensive experiments by removing the need to code one-off experimental apparatus. MALT also provides a number of public implementations of MAL algorithms—hopefully eliminating or reducing differences between algorithm implementations and increasing the reproducibility of results. Using this test-suite, we ran an experiment that is unprecedented in terms of the number of MAL algorithms used and the number of game instances generated. The results of this experiment were analyzed by using a variety of performance metrics—including reward, maxmin distance, regret, and several types of convergence. Our investigation also draws upon a number of empirical analysis methods. Through this analysis we found some surprising results: the most surprising observation was that a very simple algorithm—one that was intended for single-agent reinforcement problems and not multiagent learning— performed better empirically than more complicated and recent MAL algorithms.
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Fevang, Rune y Arne Bergene Fossaa. "Empirical evaluation of metric indexing methods". Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8902.

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Metric indexing is a branch of search technology that is designed for search non-textual data. Examples of this includes image search (where the search query is an image), document search (finding documents that are roughly equal) to search in high-dimensional Euclidean spaces. Metric indexing is based on the theory of metric spaces, where the only thing known about a set of objects is the distance between them (defined by a metric distance function). A large number of methods have been proposed to solve the metric indexing problem. In this thesis, we have concentrated on new approaches to solving these problems, as well as combining existing methods to create better ones. The methods studied in this thesis include D-Index, GNAT, EMVP-Forest, HC, SA-Tree, SSS-Tree, M-Tree, PM-Tree, M*-Tree and PM*-Tree. These have all been implemented and tested against each other to find strengths and weaknesses. This thesis also studies a group of indexing methods called hybrid methods which combines tree-based methods (like SA-Tree, SSS-tree and M-Tree), with pivoting methods (like AESA and LAESA). The thesis also proposes a method to create hybrid trees from existing trees by using features in the programming language. Hybrid methods have been shown in this thesis to be very promising. While they may have a considerable overhead in construction time,CPU usage and/or memory usage, they show large benefits in reduced number of distance computations. We also propose a new way of calculating the Minimal Spanning Tree of a graph operating on metric objects, and show that it reduces the number of distance computations needed.

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Benhaddou, Rida. "Nonparametric and Empirical Bayes Estimation Methods". Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5765.

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In the present dissertation, we investigate two different nonparametric models; empirical Bayes model and functional deconvolution model. In the case of the nonparametric empirical Bayes estimation, we carried out a complete minimax study. In particular, we derive minimax lower bounds for the risk of the nonparametric empirical Bayes estimator for a general conditional distribution. This result has never been obtained previously. In order to attain optimal convergence rates, we use a wavelet series based empirical Bayes estimator constructed in Pensky and Alotaibi (2005). We propose an adaptive version of this estimator using Lepski's method and show that the estimator attains optimal convergence rates. The theory is supplemented by numerous examples. Our study of the functional deconvolution model expands results of Pensky and Sapatinas (2009, 2010, 2011) to the case of estimating an (r+1)-dimensional function or dependent errors. In both cases, we derive minimax lower bounds for the integrated square risk over a wide set of Besov balls and construct adaptive wavelet estimators that attain those optimal convergence rates. In particular, in the case of estimating a periodic (r+1)-dimensional function, we show that by choosing Besov balls of mixed smoothness, we can avoid the ''curse of dimensionality'' and, hence, obtain higher than usual convergence rates when r is large. The study of deconvolution of a multivariate function is motivated by seismic inversion which can be reduced to solution of noisy two-dimensional convolution equations that allow to draw inference on underground layer structures along the chosen profiles. The common practice in seismology is to recover layer structures separately for each profile and then to combine the derived estimates into a two-dimensional function. By studying the two-dimensional version of the model, we demonstrate that this strategy usually leads to estimators which are less accurate than the ones obtained as two-dimensional functional deconvolutions. Finally, we consider a multichannel deconvolution model with long-range dependent Gaussian errors. We do not limit our consideration to a specific type of long-range dependence, rather we assume that the eigenvalues of the covariance matrix of the errors are bounded above and below. We show that convergence rates of the estimators depend on a balance between the smoothness parameters of the response function, the smoothness of the blurring function, the long memory parameters of the errors, and how the total number of observations is distributed among the channels.
Ph.D.
Doctorate
Mathematics
Sciences
Mathematics
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Reinhardt, Timothy Patrick. "Empirical methods for comparing governance structure". Thesis, [Austin, Tex. : University of Texas, 2009. http://hdl.handle.net/2152/ETD-UT-2009-05-134.

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Nguyen, Viet Hung. "Empirical Methods for Evaluating Vulnerability Models". Doctoral thesis, Università degli studi di Trento, 2014. https://hdl.handle.net/11572/368542.

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This dissertation focuses on the following research question: “how to independently and systematically validate empirical vulnerability models?†. Based on the survey of past studies about the vulnerability discovery process, the dissertation has pointed out several critical issues in the traditional methodology for evaluating the performance of vulnerability discovery models (VDMs). Such issues did impact the conclusions of several studies in the literature. To address such pitfalls, a novel empirical methodology and a data collection infrastructure are proposed to conduct experiments that evaluate the empirical performance of VDMs. The methodology consists of two quantitative analyses, namely quality and predictability analyses, which enable analysts to study the performance of VDMs, and to compare them effectively.The proposed methodology and the data collection infrastructure have been used to assess several existing VDMs on many major versions of the major browsers (i.e., Chrome, Firefox, Internet Explorer, and Safari). The extensive experimental analysis reveals an interesting finding about the VDM performance in terms of quality and predictability: the simplest linear model is the most appropriate one for predicting vulnerability discovery trend within the first twelve months since the release date of browser versions; later than that, logistic models are more appropriate. The analyzed vulnerability data exhibits the phenomenon of after-life vulnerabilities, which have been discovered for the current version, but also attributed to browser versions out of support – dead versions. These vulnerabilities, however, may not actually exist, and may have an impact on past scientific studies, or on compliance assessment. Therefore, this dissertation has proposed a method to identify code evidence for vulnerabilities. The results of the experiments show that a significant amount of vulnerabilities has been systematically over-reported for old versions of browsers. Consequently, old versions of software seem to have less vulnerabilities than reported.
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Nguyen, Viet Hung. "Empirical Methods for Evaluating Vulnerability Models". Doctoral thesis, University of Trento, 2014. http://eprints-phd.biblio.unitn.it/1282/1/nguyen-thesis.pdf.

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This dissertation focuses on the following research question: “how to independently and systematically validate empirical vulnerability models?”. Based on the survey of past studies about the vulnerability discovery process, the dissertation has pointed out several critical issues in the traditional methodology for evaluating the performance of vulnerability discovery models (VDMs). Such issues did impact the conclusions of several studies in the literature. To address such pitfalls, a novel empirical methodology and a data collection infrastructure are proposed to conduct experiments that evaluate the empirical performance of VDMs. The methodology consists of two quantitative analyses, namely quality and predictability analyses, which enable analysts to study the performance of VDMs, and to compare them effectively.The proposed methodology and the data collection infrastructure have been used to assess several existing VDMs on many major versions of the major browsers (i.e., Chrome, Firefox, Internet Explorer, and Safari). The extensive experimental analysis reveals an interesting finding about the VDM performance in terms of quality and predictability: the simplest linear model is the most appropriate one for predicting vulnerability discovery trend within the first twelve months since the release date of browser versions; later than that, logistic models are more appropriate. The analyzed vulnerability data exhibits the phenomenon of after-life vulnerabilities, which have been discovered for the current version, but also attributed to browser versions out of support – dead versions. These vulnerabilities, however, may not actually exist, and may have an impact on past scientific studies, or on compliance assessment. Therefore, this dissertation has proposed a method to identify code evidence for vulnerabilities. The results of the experiments show that a significant amount of vulnerabilities has been systematically over-reported for old versions of browsers. Consequently, old versions of software seem to have less vulnerabilities than reported
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Mikkola, Hennamari. "Empirical studies on Finnish hospital pricing methods /". Helsinki : Helsinki School of Economics, 2002. http://aleph.unisg.ch/hsgscan/hm00068878.pdf.

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Brandel, John. "Empirical Bayes methods for missing data analysis". Thesis, Uppsala University, Department of Mathematics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121408.

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Lönnstedt, Ingrid. "Empirical Bayes Methods for DNA Microarray Data". Doctoral thesis, Uppsala University, Department of Mathematics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5865.

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cDNA microarrays is one of the first high-throughput gene expression technologies that has emerged within molecular biology for the purpose of functional genomics. cDNA microarrays compare the gene expression levels between cell samples, for thousands of genes simultaneously.

The microarray technology offers new challenges when it comes to data analysis, since the thousands of genes are examined in parallel, but with very few replicates, yielding noisy estimation of gene effects and variances. Although careful image analyses and normalisation of the data is applied, traditional methods for inference like the Student t or Fisher’s F-statistic fail to work.

In this thesis, four papers on the topics of empirical Bayes and full Bayesian methods for two-channel microarray data (as e.g. cDNA) are presented. These contribute to proving that empirical Bayes methods are useful to overcome the specific data problems. The sample distributions of all the genes involved in a microarray experiment are summarized into prior distributions and improves the inference of each single gene.

The first part of the thesis includes biological and statistical background of cDNA microarrays, with an overview of the different steps of two-channel microarray analysis, including experimental design, image analysis, normalisation, cluster analysis, discrimination and hypothesis testing. The second part of the thesis consists of the four papers. Paper I presents the empirical Bayes statistic B, which corresponds to a t-statistic. Paper II is based on a version of B that is extended for linear model effects. Paper III assesses the performance of empirical Bayes models by comparisons with full Bayes methods. Paper IV provides extensions of B to what corresponds to F-statistics.

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Libros sobre el tema "Empirical methods"

1

Maritz, J. S. Empirical Bayes methods. 2a ed. London: Chapman and Hall, 1989.

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author, Lwin T., ed. Empirical Bayes Methods. London: Taylor and Francis, 2018.

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Lawless, Robert M. Empirical methods in law. New York: Aspen Publishers, 2010.

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K, Robbennolt Jennifer y Ulen Thomas, eds. Empirical methods in law. New York: Aspen Publishers, 2010.

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Sudhoff, Stefan, Denisa Lenertova, Roland Meyer, Sandra Pappert, Petra Augurzky, Ina Mleinek, Nicole Richter y Johannes Schließer, eds. Methods in Empirical Prosody Research. Berlin, Boston: DE GRUYTER, 2006. http://dx.doi.org/10.1515/9783110914641.

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Cohen, Paul R. Empirical methods for artificial intelligence. Cambridge, Ma: MIT Press, 1995.

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Stefan, Hrsg :. Sudhoff, ed. Methods in empirical prosody research. Berlin: Walter de Gruyter GmbH & Co. KG, 2006.

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Krahmer, Emiel y Mariët Theune, eds. Empirical Methods in Natural Language Generation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15573-4.

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Semmler, Willi, ed. Business Cycles: Theory and Empirical Methods. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1364-9.

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Felderer, Michael y Guilherme Horta Travassos, eds. Contemporary Empirical Methods in Software Engineering. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-32489-6.

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Capítulos de libros sobre el tema "Empirical methods"

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Volponi, Allan J. "Empirical Methods". En Gas Turbine Parameter Corrections, 61–69. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41076-6_7.

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O’Connell, Daniel C. y Sabine Kowal. "Empirical Methods". En Communicating with One Another, 1–14. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-77632-3_2.

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Hult, Henrik, Filip Lindskog, Ola Hammarlid y Carl Johan Rehn. "Empirical Methods". En Risk and Portfolio Analysis, 197–229. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4103-8_7.

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Corami, Alessia, Saeid Eslamian y Eslamian Faezeh. "Empirical Methods". En Fundamentals of Evapotranspiration, 13–24. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003467229-4.

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Häder, Michael. "Survey Methods". En Empirical Social Research, 173–311. Wiesbaden: Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-37907-0_6.

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Patten, Mildred L. y Michelle Newhart. "Empirical Research". En Understanding Research Methods, 5–7. Tenth edition. | New York, NY : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315213033-3.

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Patten, Mildred L. y Michelle Newhart. "Empirical Validity". En Understanding Research Methods, 129–32. Tenth edition. | New York, NY : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315213033-42.

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Newhart, Michelle y Mildred L. Patten. "Empirical Validity". En Understanding Research Methods, 203–7. 11a ed. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003092049-45.

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Wu, Changbao y Mary E. Thompson. "Empirical Likelihood Methods". En ICSA Book Series in Statistics, 161–92. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44246-0_8.

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Cai, Kai-Yuan. "Empirical Regression Methods". En The Kluwer International Series in Software Engineering, 29–68. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5593-3_2.

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Actas de conferencias sobre el tema "Empirical methods"

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Kalogirou, Eleftheria, Michalis Mavrovouniotis, Marios Tzouvaras, Christodoulos Mettas, Evagoras Evagorou y Diofantos Hadjimitsis. "Empirical Analysis of Oil Spill Detection Methods". En IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 3673–77. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642731.

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Vance, Nathan y Patrick Flynn. "Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods". En 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 380–88. IEEE, 2024. http://dx.doi.org/10.1109/cvprw63382.2024.00043.

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Sabir, Umair y Che-Rung Lee. "An Empirical Study on Methods for Abnormal Trajectory Detection". En 2019 IEEE 5th International Conference on Big Data Intelligence and Computing (DATACOM), 242–45. IEEE, 2019. http://dx.doi.org/10.1109/datacom.2019.00044.

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Grendar, M. "Empirical Maximum Entropy Methods". En Bayesian Inference and Maximum Entropy Methods In Science and Engineering. AIP, 2006. http://dx.doi.org/10.1063/1.2423302.

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Pakalnis, Rimas. "Empirical design methods in practice". En International Seminar on Design Methods in Underground Mining. Australian Centre for Geomechanics, Perth, 2015. http://dx.doi.org/10.36487/acg_rep/1511_0.3_pakalnis.

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Tadepalli, Srikanth y Kristin L. Wood. "Adaptive Methods for Non-Linear Empirical Similitude Method". En ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67974.

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Several problems in engineering realm pose modeling and simulation difficulty due to severe non–linear behavior and debilitating singular or stiff conditions that act as additional impediments. In many such instances advanced numerical schemes are employed to either relax or simplify the PDE that defines the physical process to obtain reasonable output from the simulation. Digressing from this traditional approach, we present an experimental similitude method in this paper to analyze non–linear systems. Combined with the use of original mapping algorithms, we discuss the benefits of empirical similarity techniques and present a heat transfer example for exposition.
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Koehn, Philipp y Kevin Knight. "Empirical methods for compound splitting". En the tenth conference. Morristown, NJ, USA: Association for Computational Linguistics, 2003. http://dx.doi.org/10.3115/1067807.1067833.

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Tsumoto, Shusaku. "Empirical Rule Induction Methods Selection". En 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671726.

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Paek, Tim. "Empirical methods for evaluating dialog systems". En the workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2001. http://dx.doi.org/10.3115/1118053.1118054.

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Paek, Tim. "Empirical methods for evaluating dialog systems". En the Second SIGdial Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2001. http://dx.doi.org/10.3115/1118078.1118092.

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Informes sobre el tema "Empirical methods"

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Glaeser, Edward. Researcher Incentives and Empirical Methods. Cambridge, MA: National Bureau of Economic Research, octubre de 2006. http://dx.doi.org/10.3386/t0329.

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Walters, Christopher. Empirical Bayes Methods in Labor Economics. Cambridge, MA: National Bureau of Economic Research, octubre de 2024. http://dx.doi.org/10.3386/w33091.

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Hommel, Nicolas, Augustin Landier y David Thesmar. Corporate Valuation: An Empirical Comparison of Discounting Methods. Cambridge, MA: National Bureau of Economic Research, enero de 2023. http://dx.doi.org/10.3386/w30898.

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Birenzvige, A., L. M. Sturdivan, G. R. Famini, P. N. Krishnan y R. E. Morris. Predicting Polymer Properties by Computational Methods 2: A Comparison of Semi-Empirical Methods. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 1992. http://dx.doi.org/10.21236/ada256856.

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Cain, P. Empirical methods of support design for the Sydney Coalfield. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1985. http://dx.doi.org/10.4095/304789.

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Gu, Jiaying y Roger Koenker. Rebayes: an R package for empirical bayes mixture methods. The IFS, agosto de 2017. http://dx.doi.org/10.1920/wp.cem.2017.3717.

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Rosati, Julie D. Functional Design of Breakwaters for Shore Protection: Empirical Methods. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 1990. http://dx.doi.org/10.21236/ada228024.

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Tetenov, Aleksey y Toru Kitagawa. Who should be treated? Empirical welfare maximization methods for treatment choice. IFS, marzo de 2015. http://dx.doi.org/10.1920/wp.cem.2015.1015.

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Kitagawa, Toru y Aleksey Tetenov. Who should be treated? Empirical welfare maximization methods for treatment choice. The IFS, mayo de 2017. http://dx.doi.org/10.1920/wp.cem.2017.2417.

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Kunsberg, P. Citizen advisory boards: An empirical model for choosing goals and methods. Office of Scientific and Technical Information (OSTI), diciembre de 1994. http://dx.doi.org/10.2172/543603.

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