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Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis.

, , , , and . IACR Trans. Cryptogr. Hardw. Embed. Syst., 2021 (1): 25-55 (2021)

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Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms., , , , and . CoRR, (2020)Learning Metrics Between Tree Structured Data: Application to Image Recognition., , and . ECML, volume 4701 of Lecture Notes in Computer Science, page 54-66. Springer, (2007)Online Non-linear Gradient Boosting in Multi-latent Spaces., , , , and . IDA, volume 11191 of Lecture Notes in Computer Science, page 99-110. Springer, (2018)Generalized Stochastic Tree Automata for Multi-relational Data Mining., , and . ICGI, volume 2484 of Lecture Notes in Computer Science, page 120-133. Springer, (2002)A Spectral Approach for Probabilistic Grammatical Inference on Trees., , and . ALT, volume 6331 of Lecture Notes in Computer Science, page 74-88. Springer, (2010)Anomaly Detection, Consider Your Dataset First An Illustration on Fraud Detection., , , , , and . ICTAI, page 1351-1355. IEEE, (2019)Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis., , , , and . IACR Trans. Cryptogr. Hardw. Embed. Syst., 2021 (1): 25-55 (2021)Conditional Variational AutoEncoder based on Stochastic Attack., , , , and . IACR Cryptol. ePrint Arch., (2022)A General Framework for the Derandomization of PAC-Bayesian Bounds., , , and . CoRR, (2021)Is My Neural Net Driven by the MDL Principle?, , , , , and . ECML/PKDD (2), volume 14170 of Lecture Notes in Computer Science, page 173-189. Springer, (2023)