Artigos de revistas sobre o tema "Algorithmie quantique"
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Pavel, Ilarion. "Les défis des technologies quantiques". Annales des Mines - Responsabilité et environnement N° 114, n.º 2 (10 de abril de 2024): 81–90. http://dx.doi.org/10.3917/re1.114.0081.
Texto completo da fonteBlais, A. "Algorithmes et architectures pour ordinateurs quantiques supraconducteurs". Annales de Physique 28, n.º 5 (setembro de 2003): 1–148. http://dx.doi.org/10.1051/anphys:2003008.
Texto completo da fonteRahman, Mohammad Arshad. "Quantile regression using metaheuristic algorithms". International Journal of Computational Economics and Econometrics 3, n.º 3/4 (2013): 205. http://dx.doi.org/10.1504/ijcee.2013.058498.
Texto completo da fonteMOUNT, DAVID M., NATHAN S. NETANYAHU, CHRISTINE D. PIATKO, RUTH SILVERMAN e ANGELA Y. WU. "QUANTILE APPROXIMATION FOR ROBUST STATISTICAL ESTIMATION AND k-ENCLOSING PROBLEMS". International Journal of Computational Geometry & Applications 10, n.º 06 (dezembro de 2000): 593–608. http://dx.doi.org/10.1142/s0218195900000334.
Texto completo da fonteKibzun, A. I. "Parallelization of the quantile function optimization algorithms". Automation and Remote Control 68, n.º 5 (maio de 2007): 799–810. http://dx.doi.org/10.1134/s0005117907050074.
Texto completo da fontePapacharalampous, Georgia, Hristos Tyralis, Andreas Langousis, Amithirigala W. Jayawardena, Bellie Sivakumar, Nikos Mamassis, Alberto Montanari e Demetris Koutsoyiannis. "Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms". Water 11, n.º 10 (14 de outubro de 2019): 2126. http://dx.doi.org/10.3390/w11102126.
Texto completo da fonteZheng, Songfeng. "Gradient descent algorithms for quantile regression with smooth approximation". International Journal of Machine Learning and Cybernetics 2, n.º 3 (22 de julho de 2011): 191–207. http://dx.doi.org/10.1007/s13042-011-0031-2.
Texto completo da fonteMöller, Eva, Gert Grieszbach, Bärbel Schack e Herbert Witte. "Statistical Properties and Control Algorithms of Recursive Quantile Estimators". Biometrical Journal 42, n.º 6 (outubro de 2000): 729–46. http://dx.doi.org/10.1002/1521-4036(200010)42:6<729::aid-bimj729>3.0.co;2-w.
Texto completo da fonteXiang, Dao-Hong, Ting Hu e Ding-Xuan Zhou. "Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression". Journal of Applied Mathematics 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/902139.
Texto completo da fonteCheng, Hao. "Comparison of partial least square algorithms in hierarchical latent variable model with missing data". SIMULATION 96, n.º 10 (30 de julho de 2020): 825–39. http://dx.doi.org/10.1177/0037549720944467.
Texto completo da fonteKoutmos, Dimitrios. "Network Activity and Ethereum Gas Prices". Journal of Risk and Financial Management 16, n.º 10 (30 de setembro de 2023): 431. http://dx.doi.org/10.3390/jrfm16100431.
Texto completo da fonteIvkin, Nikita, Edo Liberty, Kevin Lang, Zohar Karnin e Vladimir Braverman. "Streaming Quantiles Algorithms with Small Space and Update Time". Sensors 22, n.º 24 (8 de dezembro de 2022): 9612. http://dx.doi.org/10.3390/s22249612.
Texto completo da fonteTyralis, Hristos, Georgia Papacharalampous, Andreas Langousis e Simon Michael Papalexiou. "Explanation and Probabilistic Prediction of Hydrological Signatures with Statistical Boosting Algorithms". Remote Sensing 13, n.º 3 (20 de janeiro de 2021): 333. http://dx.doi.org/10.3390/rs13030333.
Texto completo da fonteHuang, Tianbao, Guanglong Ou, Hui Xu, Xiaoli Zhang, Yong Wu, Zihao Liu, Fuyan Zou, Chen Zhang e Can Xu. "Comparing Algorithms for Estimation of Aboveground Biomass in Pinus yunnanensis". Forests 14, n.º 9 (28 de agosto de 2023): 1742. http://dx.doi.org/10.3390/f14091742.
Texto completo da fonteCheng, Hao. "Importance sampling imputation algorithms in quantile regression with their application in CGSS data". Mathematics and Computers in Simulation 188 (outubro de 2021): 498–508. http://dx.doi.org/10.1016/j.matcom.2021.04.014.
Texto completo da fonteArandjelovic, Ognjen, Duc-Son Pham e Svetha Venkatesh. "Two Maximum Entropy-Based Algorithms for Running Quantile Estimation in Nonstationary Data Streams". IEEE Transactions on Circuits and Systems for Video Technology 25, n.º 9 (setembro de 2015): 1469–79. http://dx.doi.org/10.1109/tcsvt.2014.2376137.
Texto completo da fonteChuan, Zun Liang, Wan Nur Syahidah Wan Yusoff, Azlyna Senawi, Mohd Romlay Mohd Akramin, Soo-Fen Fam, Wendy Ling Shinyie e Tan Lit Ken. "A Comparative Effectiveness of Hierarchical and Non-hierarchical Regionalisation Algorithms in Regionalising the Homogeneous Rainfall Regions". Pertanika Journal of Science and Technology 30, n.º 1 (4 de janeiro de 2022): 319–42. http://dx.doi.org/10.47836/pjst.30.1.18.
Texto completo da fonteWatson, Oliver P., Isidro Cortes-Ciriano, Aimee R. Taylor e James A. Watson. "A decision-theoretic approach to the evaluation of machine learning algorithms in computational drug discovery". Bioinformatics 35, n.º 22 (9 de maio de 2019): 4656–63. http://dx.doi.org/10.1093/bioinformatics/btz293.
Texto completo da fonteTyralis, Hristos, Georgia Papacharalampous, Apostolos Burnetas e Andreas Langousis. "Hydrological post-processing using stacked generalization of quantile regression algorithms: Large-scale application over CONUS". Journal of Hydrology 577 (outubro de 2019): 123957. http://dx.doi.org/10.1016/j.jhydrol.2019.123957.
Texto completo da fonteZhang, Hong-Yan, Wei Sun, Xiao Chen, Rui-Jia Lin e Yu Zhou. "Fixed-point algorithms for solving the critical value and upper tail quantile of Kuiper's statistics". Heliyon 10, n.º 7 (abril de 2024): e28274. http://dx.doi.org/10.1016/j.heliyon.2024.e28274.
Texto completo da fonteArunachalam, Srinivasan, Vojtech Havlicek, Giacomo Nannicini, Kristan Temme e Pawel Wocjan. "Simpler (classical) and faster (quantum) algorithms for Gibbs partition functions". Quantum 6 (1 de setembro de 2022): 789. http://dx.doi.org/10.22331/q-2022-09-01-789.
Texto completo da fonteKibzun, Andrey. "Comparison of two algorithms for solving a two-stage bilinear stochastic programming problem with quantile criterion". Applied Stochastic Models in Business and Industry 31, n.º 6 (16 de fevereiro de 2015): 862–74. http://dx.doi.org/10.1002/asmb.2115.
Texto completo da fonteAhsan, Md Manjurul, M. A. Parvez Mahmud, Pritom Kumar Saha, Kishor Datta Gupta e Zahed Siddique. "Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance". Technologies 9, n.º 3 (24 de julho de 2021): 52. http://dx.doi.org/10.3390/technologies9030052.
Texto completo da fonteWu, Xiaofeng. "AHP-BP-Based Algorithms for Teaching Quality Evaluation of Flipped English Classrooms in the Context of New Media Communication". International Journal of Information Technologies and Systems Approach 16, n.º 2 (21 de abril de 2023): 1–12. http://dx.doi.org/10.4018/ijitsa.322096.
Texto completo da fonteChen, Wei, Zhao Wang, Guirong Wang, Zixin Ning, Boxiang Lian, Shangjie Li, Paraskevas Tsangaratos, Ioanna Ilia e Weifeng Xue. "Optimizing Rotation Forest-Based Decision Tree Algorithms for Groundwater Potential Mapping". Water 15, n.º 12 (19 de junho de 2023): 2287. http://dx.doi.org/10.3390/w15122287.
Texto completo da fonteRascon, Caleb, Oscar Ruiz-Espitia e Jose Martinez-Carranza. "On the Use of the AIRA-UAS Corpus to Evaluate Audio Processing Algorithms in Unmanned Aerial Systems". Sensors 19, n.º 18 (10 de setembro de 2019): 3902. http://dx.doi.org/10.3390/s19183902.
Texto completo da fonteRajabi, Amirarsalan, e Ozlem Ozmen Garibay. "TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks". Machine Learning and Knowledge Extraction 4, n.º 2 (16 de maio de 2022): 488–501. http://dx.doi.org/10.3390/make4020022.
Texto completo da fonteIvković, Nikola, Robert Kudelić e Matej Črepinšek. "Probability and Certainty in the Performance of Evolutionary and Swarm Optimization Algorithms". Mathematics 10, n.º 22 (20 de novembro de 2022): 4364. http://dx.doi.org/10.3390/math10224364.
Texto completo da fonteWitkovsky, Viktor. "Numerical inversion of a characteristic function: An alternative tool to form the probability distribution of output quantity in linear measurement models". ACTA IMEKO 5, n.º 3 (4 de novembro de 2016): 32. http://dx.doi.org/10.21014/acta_imeko.v5i3.382.
Texto completo da fonteBeazley, Elizabeth, Anna Bertiger e Kaisa Taipale. "An equivariant rim hook rule for quantum cohomology of Grassmannians". Discrete Mathematics & Theoretical Computer Science DMTCS Proceedings vol. AT,..., Proceedings (1 de janeiro de 2014). http://dx.doi.org/10.46298/dmtcs.2377.
Texto completo da fontePietrosanu, Matthew, Jueyu Gao, Linglong Kong, Bei Jiang e Di Niu. "Advanced algorithms for penalized quantile and composite quantile regression". Computational Statistics, 12 de julho de 2020. http://dx.doi.org/10.1007/s00180-020-01010-1.
Texto completo da fonteCheng, Hao. "Efficient importance sampling imputation algorithms for quantile and composite quantile regression". Statistical Analysis and Data Mining: The ASA Data Science Journal, 29 de novembro de 2021. http://dx.doi.org/10.1002/sam.11565.
Texto completo da fonteDabney, Will, Mark Rowland, Marc Bellemare e Rémi Munos. "Distributional Reinforcement Learning With Quantile Regression". Proceedings of the AAAI Conference on Artificial Intelligence 32, n.º 1 (29 de abril de 2018). http://dx.doi.org/10.1609/aaai.v32i1.11791.
Texto completo da fonteChernozhukov, Victor, Iván Fernández-Val e Blaise Melly. "Fast algorithms for the quantile regression process". Empirical Economics, 12 de julho de 2020. http://dx.doi.org/10.1007/s00181-020-01898-0.
Texto completo da fonteDeng, Yan, Huiwen Jia, Shabbir Ahmed, Jon Lee e Siqian Shen. "Scenario Grouping and Decomposition Algorithms for Chance-Constrained Programs". INFORMS Journal on Computing, 13 de outubro de 2020. http://dx.doi.org/10.1287/ijoc.2020.0970.
Texto completo da fontePapacharalampous, Georgia, e Andreas Langousis. "Probabilistic water demand forecasting using quantile regression algorithms". Water Resources Research, 5 de maio de 2022. http://dx.doi.org/10.1029/2021wr030216.
Texto completo da fonteWen, Jiawei, Songshan Yang, Christina Dan Wang, Yifan Jiang e Runze Li. "Feature-splitting algorithms for ultrahigh dimensional quantile regression". Journal of Econometrics, março de 2023. http://dx.doi.org/10.1016/j.jeconom.2023.01.028.
Texto completo da fonteDolce, Pasquale, Cristina Davino e Domenico Vistocco. "Quantile composite-based path modeling: algorithms, properties and applications". Advances in Data Analysis and Classification, 2 de novembro de 2021. http://dx.doi.org/10.1007/s11634-021-00469-0.
Texto completo da fonteJin, Jun, Shuangzhe Liu e Tiefeng Ma. "Optimal subsampling algorithms for composite quantile regression in massive data". Statistics, 24 de julho de 2023, 1–33. http://dx.doi.org/10.1080/02331888.2023.2239507.
Texto completo da fontePagès, Gilles, e Abass Sagna. "Weak and strong error analysis of recursive quantization: a general approach with an application to jump diffusions". IMA Journal of Numerical Analysis, 30 de setembro de 2020. http://dx.doi.org/10.1093/imanum/draa033.
Texto completo da fonteMoon, Haeseong, e Wen-Xin Zhou. "High-dimensional composite quantile regression: Optimal statistical guarantees and fast algorithms". Electronic Journal of Statistics 17, n.º 2 (1 de janeiro de 2023). http://dx.doi.org/10.1214/23-ejs2147.
Texto completo da fonteSu, Yang, Huang Zhang, Benoit Gabrielle e David Makowski. "Performances of Machine Learning Algorithms in Predicting the Productivity of Conservation Agriculture at a Global Scale". Frontiers in Environmental Science 10 (8 de fevereiro de 2022). http://dx.doi.org/10.3389/fenvs.2022.812648.
Texto completo da fonteKrabichler, Thomas, e Marcus Wunsch. "Hedging goals". Financial Markets and Portfolio Management, 17 de novembro de 2023. http://dx.doi.org/10.1007/s11408-023-00437-y.
Texto completo da fonteGerdt, Vladimir P., e Vladimir V. Kornyak. "An algorithm for analysis of the structure of finitely presented Lie algebras". Discrete Mathematics & Theoretical Computer Science Vol. 1 (1 de janeiro de 1997). http://dx.doi.org/10.46298/dmtcs.243.
Texto completo da fonteGholami, Hamid, Aliakbar Mohammadifar, Dieu Tien Bui e Adrian L. Collins. "Mapping wind erosion hazard with regression-based machine learning algorithms". Scientific Reports 10, n.º 1 (24 de novembro de 2020). http://dx.doi.org/10.1038/s41598-020-77567-0.
Texto completo da fonteVogeti, Rishith Kumar, Bhavesh Rahul Mishra e K. Srinivasa Raju. "Machine learning algorithms for streamflow forecasting of Lower Godavari Basin". H2Open Journal, 1 de novembro de 2022. http://dx.doi.org/10.2166/h2oj.2022.240.
Texto completo da fonteDebbarma, Nilotpal, Parthasarathi Choudhury e Parthajit Roy. "Comparision of performance of multi criteria decision making ensemble-clustering algorithms in rainfall frequency analysis". Water Practice and Technology, 2 de setembro de 2021. http://dx.doi.org/10.2166/wpt.2021.086.
Texto completo da fonteAdler, Jakob, Elina Taneva, Thomas Ansorge e Peter R. Mertens. "CKD prevalence based on real-world data: continuous age-dependent lower reference limits of eGFR with CKD–EPI, FAS and EKFC algorithms". International Urology and Nephrology, 28 de abril de 2022. http://dx.doi.org/10.1007/s11255-022-03210-8.
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