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Greatest papers with code

A generic framework for privacy preserving deep learning

9 Nov 2018OpenMined/PySyft

We detail a new framework for privacy preserving deep learning and discuss its assets.

FEDERATED LEARNING PRIVACY PRESERVING DEEP LEARNING

Fawkes: Protecting Privacy against Unauthorized Deep Learning Models

19 Feb 2020Shawn-Shan/fawkes

In this paper, we propose Fawkes, a system that helps individuals inoculate their images against unauthorized facial recognition models.

FACE RECOGNITION PRIVACY PRESERVING DEEP LEARNING

Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset

12 Jun 2019htwang14/PA-HMDB51

We first discuss an innovative heuristic of cross-dataset training and evaluation, enabling the use of multiple single-task datasets (one with target task labels and the other with privacy labels) in our problem.

ACTION RECOGNITION PRIVACY PRESERVING DEEP LEARNING

Towards Fair and Privacy-Preserving Federated Deep Models

4 Jun 2019lingjuanlv/FPPDL

This problem can be addressed by either a centralized framework that deploys a central server to train a global model on the joint data from all parties, or a distributed framework that leverages a parameter server to aggregate local model updates.

FAIRNESS FEDERATED LEARNING PRIVACY PRESERVING DEEP LEARNING

Locally Private Graph Neural Networks

9 Jun 2020sisaman/lpgnn

As a result and for the first time, in this paper, we study the problem of node data privacy, where graph nodes have potentially sensitive data that is kept private, but they could be beneficial for a central server for training a GNN over the graph.

DENOISING FEDERATED LEARNING NODE CLASSIFICATION PRIVACY PRESERVING DEEP LEARNING