Showing 1–20 of 54 results
/ Date/ Name
Sep 18, 2019Detailed comparison of communication efficiency of split learning and federated learningOct 7, 2025Power Mechanism: Private Tabular Representation Release for Model Agnostic ConsumptionMar 19, 2020Apps Gone Rogue: Maintaining Personal Privacy in an EpidemicJul 8, 2022Private independence testing across two partiesJul 6, 2020Splintering with distributions: A stochastic decoy scheme for private computationAug 19, 2021Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularityJan 3, 2016Supervised Dimensionality Reduction via Distance Correlation MaximizationMar 24, 2026Combinatorial Privacy: Private Multi-Party Bitstream Grand Sum by Hiding in Birkhoff PolytopesAug 20, 2020NoPeek: Information leakage reduction to share activations in distributed deep learningJun 11, 2013DISCOMAX: A Proximity-Preserving Distance Correlation Maximization AlgorithmDec 8, 2018No Peek: A Survey of private distributed deep learningDec 27, 2019Split Learning for collaborative deep learning in healthcareMay 14, 2019Data Markets to support AI for All: Pricing, Valuation and GovernanceFeb 22, 2021PrivateMail: Supervised Manifold Learning of Deep Features With Differential Privacy for Image RetrievalFeb 17, 2017Combinatorics of Distance Covariance: Inclusion-Minimal Maximizers of Quasi-Concave Set Functions for Diverse Variable SelectionSep 27, 2019Maximal adversarial perturbations for obfuscation: Hiding certain attributes while preserving restOct 19, 2021Private measurement of nonlinear correlations between data hosted across multiple partiesJan 25, 2022Effects of Privacy-Inducing Noise on Welfare and Influence of Referendum SystemsDec 3, 2018Split learning for health: Distributed deep learning without sharing raw patient dataDec 28, 2016Optimal bandwidth estimation for a fast manifold learning algorithm to detect circular structure in high-dimensional data