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Privacy-Preserving Textual Analysis via Calibrated Perturbations.

, and . PrivateNLP@WSDM, volume 2573 of CEUR Workshop Proceedings, page 41-42. CEUR-WS.org, (2020)

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Hierarchical Methods of Moments., , and . CoRR, (2018)Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison., , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 1386-1394. JMLR.org, (2014)Mnemonist: Locating Model Parameters that Memorize Training Examples., , , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 1879-1888. PMLR, (2023)Learning Predictive State Representations From Non-Uniform Sampling., , , , and . AAAI, page 3061-3068. AAAI Press, (2018)Privacy Amplification via Random Check-Ins., , , , and . NeurIPS, (2020)Spectral Learning of General Weighted Automata via Constrained Matrix Completion., and . NIPS, page 2168-2176. (2012)Privacy-Preserving Textual Analysis via Calibrated Perturbations., and . PrivateNLP@WSDM, volume 2573 of CEUR Workshop Proceedings, page 41-42. CEUR-WS.org, (2020)Beyond the Calibration Point: Mechanism Comparison in Differential Privacy., , , , and . CoRR, (2024)A \FRAMEWORK\ \FOR\ \ROBUSTNESS\ \CERTIFICATION\ ØF\ \SMOOTHED\ \CLASSIFIERS\ \USING\ F-\DIVERGENCES\, , , , , , , , and . International Conference on Learning Representations, (2020)Learning Weighted Automata., and . CAI, volume 9270 of Lecture Notes in Computer Science, page 1-21. Springer, (2015)