Advances and Open Problems in Federated Learning

Peter Kairouz, H. Brendan McMahan, Brendan Avent, +44

Foundations and Trends® in Machine Learning

Differential Privacy: An Economic Method for Choosing Epsilon

Justin Hsu, Marco Gaboardi, Andreas Haeberlen, +4

Linear dependent types for differential privacy

Marco Gaboardi, Andreas Haeberlen, Justin Hsu, +2

Privacy ProtectionEngineeringInformation SecurityFunctional AnalysisSingle Record +14

Data Poisoning against Differentially-Private Learners: Attacks and Defenses

Yuzhe Ma, Xiaojin Zhu, Justin Hsu

Artificial IntelligenceData Poisoning AttacksPrivacy ProtectionEngineeringMachine Learning +16

Proving Differential Privacy via Probabilistic Couplings

Gilles Barthe, Marco Gaboardi, Benjamin Grégoire, +2

Privacy ProtectionEngineeringInformation SecurityPrivacy ServiceVerification +13

Proving Differential Privacy in Hoare Logic

Gilles Barthe, Marco Gaboardi, Emilio Jesús Gallego Arias, +3

Privacy ProtectionEngineeringInformation SecurityVerificationFormal Verification +14

Advanced Probabilistic Couplings for Differential Privacy

Gilles Barthe, Noémie Fong, Marco Gaboardi, +3

Privacy ProtectionEngineeringInformation SecurityVerificationFormal Verification +15

Private matchings and allocations

Justin Hsu, Zhiyi Huang, Aaron Roth, +2

Mathematical ProgrammingEngineeringGame TheoryMarket Equilibrium ComputationMarket Design +18

System FC with explicit kind equality

Stephanie Weirich, Justin Hsu, Richard A. Eisenberg

System FEngineeringBoolean FunctionProgram AnalysisAutomated Reasoning +13

A semantic account of metric preservation

Arthur Azevedo de Amorim, Marco Gaboardi, Justin Hsu, +2