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Wavelet-based dynamic and privacy-preserving similitude data models for edge computing.

, , and . Wirel. Networks, 27 (1): 351-366 (2021)

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Concise essence-preserving big data representation., , , and . IEEE BigData, page 3662-3665. IEEE Computer Society, (2016)Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms., , and . J. Artif. Intell. Res., (2004)Variance Optimized Bagging., , and . ECML, volume 2430 of Lecture Notes in Computer Science, page 60-71. Springer, (2002)Security and privacy aspects in MapReduce on clouds: A survey., , , and . Comput. Sci. Rev., (2016)Wavelet-based dynamic and privacy-preserving similitude data models for edge computing., , and . Wirel. Networks, 27 (1): 351-366 (2021)Efficient and private approximations of distributed databases calculations., , , and . IEEE BigData, page 4487-4496. IEEE Computer Society, (2017)Efficient and Private Approximations of Distributed Databases Calculations., , , and . CoRR, (2016)MLDStore - DNNs as Similitude Models for Sharing Big Data (Brief Announcement)., , and . CSCML, volume 11527 of Lecture Notes in Computer Science, page 93-96. Springer, (2019)Efficient and Privacy Preserving Approximation of Distributed Statistical Queries., , , and . IEEE Trans. Big Data, 8 (5): 1399-1413 (2022)Error Bounds for Transductive Learning via Compression and Clustering., , and . NIPS, page 1085-1092. MIT Press, (2003)