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Blind Inference: An Automated Privacy-Preserving Prediction Service using Secure Multi-Party Computation for Medical Applications.

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TripleBlind: A Privacy-Preserving Framework for Decentralized Data and Algorithms., , , , , , , , , and . NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 343-348. PMLR, (2021)Blind Inference: An Automated Privacy-Preserving Prediction Service using Secure Multi-Party Computation for Medical Applications., , , , , , and . AMIA, AMIA, (2022)ModelKB: towards automated management of the modeling lifecycle in deep learning., , , and . RAISE@ICSE, page 28-34. IEEE / ACM, (2019)Code2graph: automatic generation of static call graphs for Python source code., , and . ASE, page 880-883. ACM, (2018)Defect prediction using deep learning with Network Portrait Divergence for software evolution., , , and . Empir. Softw. Eng., 27 (5): 118 (2022)An Automated Framework for Distributed Deep Learning-A Tool Demo., , , , , , , , and . ICDCS, page 1302-1305. IEEE, (2022)Automatic Hierarchical Clustering of Static Call Graphs for Program Comprehension., , and . IEEE BigData, page 4016-4025. IEEE, (2018)GraphEvo: Characterizing and Understanding Software Evolution using Call Graphs., , , and . IEEE BigData, page 4799-4807. IEEE, (2019)Automated Management of Deep Learning Experiments., , , , and . DEEM@SIGMOD, page 8:1-8:4. ACM, (2019)ArchFeature: A Modeling Environment Integrating Features into Product Line Architecture., and . D&P@MoDELS, volume 1725 of CEUR Workshop Proceedings, page 56-63. CEUR-WS.org, (2016)