"Privacy"的相关文档

标签“Privacy”的相关文档，共16条

Gradient Disaggregation Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix
GradientDisaggregation:BreakingPrivacyinFederatedLearningbyReconstructingtheUserParticipantMatrixMaximilianLam1Gu-YeonWei1DavidBrooks1VijayJanapaReddi1MichaelMitzenmacher1Abstractorwearables,andmai...
Learning Gradient in Breaking Privacy
2023-11-16 18:46:496134.95 MB3
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Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Accuracy,Interpretability,andDifferentialPrivacyviaExplainableBoostingHarshaNori1RichCaruana1ZhiqiBu2JudyHanwenShen3JanardhanKulkarni1AbstractWhileGAMsweretraditionallyﬁtusingsmoothlow-orderspline...
and via Differential Privacy Accuracy
2023-11-16 18:00:221740604.89 KB14
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Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
SharpCompositionBoundsforGaussianDifferentialPrivacyviaEdgeworthExpansionQinqingZheng1JinshuoDong1QiLong1WeijieSu1Abstracttheprioralgorithms’output,anadversarycanadaptivelyanalyzethedatasettocause...
for Gaussian bounds Composition Differential
2023-11-14 21:46:2417412.17 MB9
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Scalable Differential Privacy with Certified Robustness in Adversarial Learning
ScalableDifferentialPrivacywithCertiﬁedRobustnessinAdversarialLearningNhatHaiPhan1MyT.Thai2HanHu1RuomingJin3TongSun4DejingDou56Abstracttrainingdatatoconsistofbenignexamplesandadversar-ialexamplesc...
with in Differential Privacy Robustness
2023-11-14 21:46:171983614.28 KB3
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Reinforcement Learning with Differential Privacy
PrivateReinforcementLearningwithPACandRegretGuaranteesGiuseppeVietri1BorjaBalle2AkshayKrishnamurthy3StevenWu1Abstractingdataisavailablebeforehand.Whilethesetechniquescoveralargenumberofapplications...
Learning with Reinforcement Differential Privacy
2023-11-14 21:46:08534299.45 KB3
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Optimal Differential Privacy Composition for Exponential Mechanisms
OptimalDifferentialPrivacyCompositionforExponentialMechanismsJinshuoDong12DavidDurfee2RyanRogers2Abstractsuchashyperparameterselection(LiuandTalwar,2019),privatePCA(Chaudhurietal.,2013),syntheticda...
for Optimal Composition Differential Privacy
2023-11-14 21:45:4111932.35 MB30
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Context Aware Local Differential Privacy
Context-AwareLocalDifferentialPrivacyJayadevAcharya1K.A.Bonawitz2PeterKairouz2DanielRamage2ZitengSun13Abstractversion,localdifferentialPrivacy(LDP)(Deﬁnition1),pro-videscontext-freePrivacyguarante...
Local Differential Privacy Context Aware
2023-11-14 21:43:3518231.08 MB4
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Bayesian Differential Privacy for Machine Learning
BayesianDifferentialPrivacyforMachineLearningAlekseiTriastcyn1BoiFaltings1AbstractDespitenotableadvances,differentiallyprivateMLstillsuffersfromtwomajorproblems:(a)utilitylossduetoTraditionaldiffer...
Learning for Bayesian Machine Differential
2023-11-14 21:43:121379492.2 KB26
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Alleviating Privacy Attacks via Causal Learning
AlleviatingPrivacyAttacksviaCausalLearningShrutiTople1AmitSharma1AdityaV.Nori1Abstractsuchattackcalledmembershipinferencerevealswhetheradatasamplewaspresentinthetrainingdataset(ShokriMachinelearnin...
Learning via Causal Privacy Attacks
2023-11-14 21:43:0317431.33 MB13
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Poission Subsampled Rényi Differential Privacy
PoissonSubsampledRenyiDifferentialPrivacyYuqingZhu1Yu-XiangWang1Abstract2016)fordifferentiallyprivatedeeplearning.NoisySGDiterativelyupdatesthemodelparametersasfollows:Weconsidertheproblemof"privac...
Differential Privacy Poission Subsampled nyi
2023-11-13 14:48:157271.35 MB2
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Low Latency Privacy Preserving Inference
LowLatencyPrivacyPreservingInferenceAlonBrutzkus1OrenElisha2RanGilad-Bachrach3Abstractdictionservice,whichshouldbecapableofoperatingontheencrypteddatawithouthavingaccesstotherawdata.Whenapplyingmac...
Inference low Privacy Latency Preserving
2023-11-13 14:47:47635403.5 KB29
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Formal Privacy for Functional Data with Gaussian Perturbations
FormalPrivacyforFunctionalDatawithGaussianPerturbationsArdalanMirshani1MatthewReimherr1AleksandraSlavkovic1Abstractdata,withthecorrespondingbranchofstatisticscalledfunc-tionaldataanalysis,FDA.FDAis...
for with Gaussian Data Formal
2023-11-13 14:47:146272.19 MB15
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Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
ImprovingthePrivacyandAccuracyofADMM-BasedDistributedAlgorithmsXueruZhang1MohammadMahdiKhalili1MingyanLiu1Abstractinteractiveprocessoflocalcomputationandmessagepass-ing,whichideallyshouldresultinal...
of and the Improving Privacy
2023-11-13 11:59:47781673.98 KB19
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Improving the Gaussian Mechanism for Differential Privacy Analytical Calibration and Optimal Denoising
ImprovingtheGaussianMechanismforDifferentialPrivacy:AnalyticalCalibrationandOptimalDenoisingBorjaBalle1Yu-XiangWang23AbstracttheGaussianmechanismisthebuildingblockofprivateempiricalriskminimization...
for Gaussian the Improving Differential
2023-11-13 11:59:4712672.39 MB19
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The Price of Differential Privacy for Online Learning
ThePriceofDifferentialPrivacyforOnlineLearningNamanAgarwal1KaranSingh1Abstractthefullinformationandpartialinformation(bandit)set-tings.ThisresultimprovestheknownbestregretboundsWedesigndifferential...
of for Online the Differential
2023-11-12 20:45:23890480.33 KB1
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Pain-Free Random Differential Privacy with Sensitivity Sampling
Pain-FreeRandomDifferentialPrivacywithSensitivitySamplingBenjaminI.P.Rubinstein1FrancescoAlda`2Abstracttentrequirementistheneedtoboundglobalsensitivity—aLipschitzconstantofthetarget,non-privatefun...
Sampling with random Pain-Free Differential
2023-11-12 20:45:001525447.75 KB16
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