About

Benchmarks

No evaluation results yet. Help compare methods by submit evaluation metrics.

Datasets

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

Generative Models for Effective ML on Private, Decentralized Datasets

ICLR 2020 tensorflow/federated

To improve real-world applications of machine learning, experienced modelers develop intuition about their datasets, their models, and how the two interact.

FEDERATED LEARNING

Federated Learning for Mobile Keyboard Prediction

8 Nov 2018tensorflow/federated

We train a recurrent neural network language model using a distributed, on-device learning framework called federated learning for the purpose of next-word prediction in a virtual keyboard for smartphones.

FEDERATED LEARNING LANGUAGE MODELLING

Label Leakage and Protection in Two-party Split Learning

17 Feb 2021bytedance/fedlearner

We first show that, norm attack, a simple method that uses the norm of the communicated gradients between the parties, can largely reveal the ground-truth labels from the participants.

FEDERATED LEARNING

Advances and Open Problems in Federated Learning

10 Dec 2019FedML-AI/FedML

FL embodies the principles of focused data collection and minimization, and can mitigate many of the systemic privacy risks and costs resulting from traditional, centralized machine learning and data science approaches.

FEDERATED LEARNING

Central Server Free Federated Learning over Single-sided Trust Social Networks

11 Oct 2019FedML-AI/FedML

However, in many social network scenarios, centralized federated learning is not applicable (e. g., a central agent or server connecting all users may not exist, or the communication cost to the central server is not affordable).

FEDERATED LEARNING

Learning Private Neural Language Modeling with Attentive Aggregation

17 Dec 2018shaoxiongji/federated-learning

Federated learning (FL) provides a promising approach to learning private language modeling for intelligent personalized keyboard suggestion by training models in distributed clients rather than training in a central server.

FEDERATED LEARNING LANGUAGE MODELLING

LEAF: A Benchmark for Federated Settings

3 Dec 2018TalwalkarLab/leaf

Modern federated networks, such as those comprised of wearable devices, mobile phones, or autonomous vehicles, generate massive amounts of data each day.

AUTONOMOUS VEHICLES FEDERATED LEARNING META-LEARNING MULTI-TASK LEARNING