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Privacy-preserving distributed statistical computation to a semi-honest multi-cloud.

, , and . CNS, page 506-514. IEEE, (2015)

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On the Probabilistic and Physical Consistency of Traffic Random Variables and Models., , , and . Comput. Aided Civ. Infrastructure Eng., 29 (7): 496-517 (2014)A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks., , , , and . J. Sensors, (2015)A Markovian-Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors., , , , , , and . Comput. Aided Civ. Infrastructure Eng., 31 (3): 193-218 (2016)Bayesian Networks-Based Probabilistic Safety Analysis for Railway Lines., , and . Comput. Aided Civ. Infrastructure Eng., 31 (9): 681-700 (2016)On Random-Forest-Based Prediction Intervals.. IDEAL (1), volume 12489 of Lecture Notes in Computer Science, page 172-184. Springer, (2020)Privacy-preserving distributed statistical computation to a semi-honest multi-cloud., , and . CNS, page 506-514. IEEE, (2015)A Model for Continuous Dynamic Network Loading Problem with Different Overtaking Class Users., , , , and . J. Intell. Transp. Syst., 17 (4): 328-350 (2013)Robustness of Minimum Density Power Divergence Estimators and Wald-type test statistics in loglinear models with multinomial sampling., , and . J. Comput. Appl. Math., (2021)Factor Analysis for Anonymization., , and . ICDM Workshops, page 984-991. IEEE Computer Society, (2017)