A collection of research papers, codes, tutorials and blogs on ML carried out in a federated manner (distributed;decentralized).
Maintainer - Tushar Semwal
Contributors - Shaoxiong Ji
- Online Comic from Google AI on Federated Learning
- Federated Learning: Collaborative Machine Learning without Centralized Training Data
- An Introduction to Federated Learning
- Federated learning: Distributed machine learning with data locality and privacy
- Federated Learning: The Future of Distributed Machine Learning
- Federated Learning for Wake Word Detection
- Advances and Open Problems in Federated Learning, HAL-Inria 2019
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey, preprint 2019
- Federated Machine Learning: Concept and Applications, ACM TIST 2019
- Federated Learning: Challenges, Methods, and Future Directions, 2019
- Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection, 2019
- Convergence of Edge Computing and Deep Learning: A Comprehensive Survey, preprint, 2019
- On the Convergence of FedAvg on Non-IID Data, ICLR 2020
- FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record, NIPS 2018 Workshop
- Federated Learning for Emoji Prediction in a Mobile Keyboard, preprint 2019
- Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems, IEEE RAL 2019
- Decentralized Federated Learning: A Segmented Gossip Approach, FML 2019
- Federated Learning-Based Computation Offloading Optimization in Edge Computing-Supported Internet of Things, IEEE Access
- Federated Learning for Emoji Prediction in a Mobile Keyboard, preprint 2019
- Towards Faster and Better Federated Learning: A Feature Fusion Approach, ICIP 2019
- Decentralized Bayesian Learning over Graphs, preprint 2019
- Federated Multi-task Hierarchical Attention Model for Sensor Analytics, preprint 2019
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection, International Conference on Big Data 2019.
- Federated Learning for Time Series Forecasting Using LSTM Networks: Exploiting Similarities Through Clustering, Student thesis, KTH.
- Adaptive Federated Learning in Resource Constrained Edge Computing Systems, IEEE JSAC.
- Privacy-Preserving Deep Learning via Weight Transmission
- Learning Private Neural Language Modeling with Attentive Aggregation, IJCNN 2019. [Code]
- FFD: A Federated Learning Based Method for Credit Card Fraud Detection, International Conference on Big Data 2019
- On the Convergence of FedAvg on Non-IID Data, preprint 2019
- Federated Learning for Time Series Forecasting Using LSTM Networks: Exploiting Similarities Through Clustering, Student thesis, KTH
- Adaptive Federated Learning in Resource Constrained Edge Computing Systems, IEEE JSAC
- Privacy-Preserving Deep Learning via Weight Transmission, preprint 2019
- Learning Private Neural Language Modeling with Attentive Aggregation, IJCNN 2019 [Code]
- Federated Learning of Out-of-Vocabulary Words
- Towards Federated Learning at Scale: System Design
- Agnostic Federated Learning preprint 2019
- Peer-to-peer Federated Learning on Graphs preprint 2019
- How to backdoor federated learning, preprint, 2018
- Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- Federated Kernelized Multi-Task Learning
- Federated Learning with Non-IID Data
- Distributed Fine-tuning of Language Models on Private Data, ICLR 2018
- Federated Learning Based Proactive Content Caching in Edge Computing, IEEE GLOBECOM 2018
- When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning, IEEE Infocom 2018
- How To Backdoor Federated Learning
- LEAF: A Benchmark for Federated Settings [code]
- Federated Learning for Mobile Keyboard Prediction - Gboard
- Communication-Efficient Learning of Deep Networks from Decentralized Data, AISTATS 2017
- Differentially Private Federated Learning: A Client Level Perspective, NIPS 2017 Workshop. [code]
- Federated Tensor Factorization for Computational Phenotyping, KDD 2017
- Federated Multi-Task Learning, NIPS 2017
- Practical Secure Aggregation for Federated Learning on User-Held Data
- Federated Learning: Strategies for Improving Communication Efficiency
- Privacy-Preserving Deep Learning, ACM SIGSAC 2015
- Paddle Federated Learning - Federated Deep Learning in PaddlePaddle.
- PySyft - Github - The PyTorch based library.
- PySyft-Tensoflow - The TensorFlow bindings for PySyft
- Tensorflow Federated - TFF - A library on top of Tensorflow.
- Industrial Federated Learning Framework, Federated AI Technology Enabler, WeBank AI
- PyTorch Federated Learning - Github