Literatura científica selecionada sobre o tema "Closeness testing"
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Artigos de revistas sobre o assunto "Closeness testing"
Batu, Tuğkan, Lance Fortnow, Ronitt Rubinfeld, Warren D. Smith e Patrick White. "Testing Closeness of Discrete Distributions". Journal of the ACM 60, n.º 1 (fevereiro de 2013): 1–25. http://dx.doi.org/10.1145/2432622.2432626.
Texto completo da fonteLi, Qi. "Nonparametric testing of closeness between two unknown distribution functions". Econometric Reviews 15, n.º 3 (janeiro de 1996): 261–74. http://dx.doi.org/10.1080/07474939608800355.
Texto completo da fonteMalinovsky, Yaakov, e Shelemyahu Zacks. "Proportional closeness estimation of probability of contamination under group testing". Sequential Analysis 37, n.º 2 (3 de abril de 2018): 145–57. http://dx.doi.org/10.1080/07474946.2018.1466518.
Texto completo da fonteRachman, Rosyidah, e Indri Ariyani. "PERSEPSI KUALITAS LAYANAN DAN KEDEKATAN EMOSIONAL TERHADAP KEPUASAN MASYARAKAT PADA PELAYANAN PUSKESMAS KECAMATAN MOYO HILIR". Samalewa: Jurnal Riset & Kajian Manajemen 4, n.º 1 (16 de julho de 2024): 70–81. http://dx.doi.org/10.58406/samalewa.v4i1.1595.
Texto completo da fonteWang, Hua. "The Effects of School Climate, Parent–Child Closeness, and Peer Relations on the Problematic Internet Use of Chinese Adolescents: Testing the Mediating Role of Self-Esteem and Depression". International Journal of Environmental Research and Public Health 19, n.º 13 (21 de junho de 2022): 7583. http://dx.doi.org/10.3390/ijerph19137583.
Texto completo da fonteCarolus, Astrid, Jens F. Binder, Ricardo Muench, Catharina Schmidt, Florian Schneider e Sarah L. Buglass. "Smartphones as digital companions: Characterizing the relationship between users and their phones". New Media & Society 21, n.º 4 (12 de dezembro de 2018): 914–38. http://dx.doi.org/10.1177/1461444818817074.
Texto completo da fonteBelovs, Aleksandrs, Arturo Castellanos, Francois Le Gall, Guillaume Malod e Alexander A. Sherstov. "Quantum communication complexity of distribution testing". Quantum Information and Computation 21, n.º 15&16 (novembro de 2021): 1261–73. http://dx.doi.org/10.26421/qic21.15-16-1.
Texto completo da fonteTeacher Jiham Salman Allawy e Teacher Rouaa Ali AbdAlsadah. "The Role of Internal Ranking in Job Satisfaction: An Exploratory Research in the General Company for Electrical and Electronic Industries in Baghdad". Economic and Administrative Studies Journal 2, n.º 2 (27 de maio de 2023): 75–96. http://dx.doi.org/10.58564/easj/2.2.2023.5.
Texto completo da fontePesaran, M. Hashem. "Global and Partial Non-Nested Hypotheses and Asymptotic Local Power". Econometric Theory 3, n.º 1 (fevereiro de 1987): 69–97. http://dx.doi.org/10.1017/s0266466600004138.
Texto completo da fonteMazmanian, R. O. "NONCORRALATED DATA ORDERED SAMPLES AS A SINGLE-ELEMENT MULTICHANNEL CONVERTER". Tekhnichna Elektrodynamika 2021, n.º 3 (19 de abril de 2021): 74–82. http://dx.doi.org/10.15407/techned2021.03.074.
Texto completo da fonteTeses / dissertações sobre o assunto "Closeness testing"
Pornsakulvanich, Vikanda. "TESTING A USES AND GRATIFICATIONS MODEL OF ONLINE RELATIONSHIPS". Kent State University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=kent1120752984.
Texto completo da fonteFermanian, Jean-Baptiste. "High dimensional multiple means estimation and testing with applications to machine learning". Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASM035.
Texto completo da fonteIn this thesis, we study the influence of high dimension in testing and estimation problems. We analyze the dimension dependence of the separation rate of a closeness test and of the quadratic risk of multiple vector estimation. We complement existing results by studying these dependencies in the case of non-isotropic distributions. For such distributions, the role of dimension is played by notions of effective dimension defined from the covariance of the distributions. This framework covers infinite-dimensional data such as kernel mean embedding, a machine learning tool we will be seeking to estimate. Using this analysis, we construct methods for simultaneously estimating mean vectors of different distributions from independent samples of each. These estimators perform better theoretically and practically than the empirical mean in unfavorable situations where the (effective) dimension is large. These methods make explicit or implicit use of the relative ease of testing compared with estimation. They are based on the construction of estimators of distances and moments of covariance, for which we provide non-asymptotic concentration bounds. Particular interest is given to the study of bounded data, for which a specific analysis is required. Our methods are accompanied by a minimax analysis justifying their optimality. In a final section, we propose an interpretation of the attention mechanism used in Transformer neural networks as a multiple vector estimation problem. In a simplified framework, this mechanism shares similar ideas with our approaches, and we highlight its denoising effect in high dimension
Trabalhos de conferências sobre o assunto "Closeness testing"
Chan, Siu-On, Ilias Diakonikolas, Paul Valiant e Gregory Valiant. "Optimal Algorithms for Testing Closeness of Discrete Distributions". In Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973402.88.
Texto completo da fonteDiakonikolas, Ilias, Daniel M. Kane e Sihan Liu. "Testing Closeness of Multivariate Distributions via Ramsey Theory". In STOC '24: 56th Annual ACM Symposium on Theory of Computing. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3618260.3649657.
Texto completo da fonteAcharya, Jayadev, Ashkan Jafarpour, Alon Orlitsky e Ananda Theertha Suresh. "Sublinear algorithms for outlier detection and generalized closeness testing". In 2014 IEEE International Symposium on Information Theory (ISIT). IEEE, 2014. http://dx.doi.org/10.1109/isit.2014.6875425.
Texto completo da fonteDiakonikolas, Ilias, Daniel M. Kane e Vladimir Nikishkin. "Optimal Algorithms and Lower Bounds for Testing Closeness of Structured Distributions". In 2015 IEEE 56th Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2015. http://dx.doi.org/10.1109/focs.2015.76.
Texto completo da fonteJohnson, William R., Michael J. Leamy, Washington DeLima e Massimo Ruzzene. "Pulse Shaping in 1D Elastic Waveguides for Shock Testing". In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23280.
Texto completo da fonteAbbasi, Jassem, e Pål Østebø Andersen. "Improved Initialization of Non-Linear Solvers in Numerical Simulation of Flow in Porous Media with a Deep Learning Approach". In SPE EuropEC - Europe Energy Conference featured at the 83rd EAGE Annual Conference & Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209667-ms.
Texto completo da fonteAbbasi, Jassem, e Pål Østebø Andersen. "Improved Initialization of Non-Linear Solvers in Numerical Simulation of Flow in Porous Media with a Deep Learning Approach". In SPE EuropEC - Europe Energy Conference featured at the 83rd EAGE Annual Conference & Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209667-ms.
Texto completo da fonteRelatórios de organizações sobre o assunto "Closeness testing"
Tsidylo, Ivan M., Serhiy O. Semerikov, Tetiana I. Gargula, Hanna V. Solonetska, Yaroslav P. Zamora e Andrey V. Pikilnyak. Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic. CEUR Workshop Proceedings, junho de 2021. http://dx.doi.org/10.31812/123456789/4370.
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