Awesome Federated Computing

A collection of research papers, codes, tutorials and blogs on ML carried out in a federated manner (distributed;decentralized).

Maintainer - Tushar Semwal

Contents

• Blogs
• Survey Papers
• Research Papers
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
• Libraries/Frameworks
• Tutorials
• Datasets
• Projects

Blogs

• Learn to adapt Flower for your use-case
• 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

Survey Papers

• Survey of Personalization Techniques for Federated Learning, preprint 2020
• 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

Research Papers

2021

• FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning, preprint
• A Bayesian Federated Learning Framework with Multivariate Gaussian Product, preprint
• Client Selection for Federated Learning With Non-IID Data in Mobile Edge Computing, IEEE Access
• FedProf: Optimizing Federated Learning with Dynamic Data Profiling, ICML2020
• Toward Resource-Efficient Federated Learning in Mobile Edge Computing, IEEE Network
• Scaling Neuroscience Research using Federated Learning, preprint
• Exploiting Shared Representations for Personalized Federated Learning, preprint
• FedSA: A staleness-aware asynchronous Federated Learning algorithm with non-IID data, FGCS Elsevier
• Blockchained Federated Learning for Threat Defense
• Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning, preprint
• FedBN: Federated Learning on Non-IID Features via Local Batch Normalization, ICLR 2021 [code]
• Federated Learning over Noisy Channels: Convergence Analysis and Design Examples, preprint

2020

• Turn Signal Prediction: A Federated Learning Case Study, preprint
• FedPerf: A Practitioners’ Guide to Performance of Federated Learning Algorithms, preprint
• WAFFLe: Weight Anonymized Factorization for Federated Learning, preprint
• Fed+: A Family of Fusion Algorithms for Federated Learning, preprint
• Fast-Convergent Federated Learning, preprint
• FedML: A Research Library and Benchmark for Federated Machine Learning, preprint [code]
• Federated Visual Classification with Real-World Data Distribution, ECCV 2020 [code]
• Flower: A Friendly Federated Learning Research Framework, preprint [code]
• Federated Deep Reinforcement Learning for Internet of Things with Decentralized Cooperative Edge Caching, IEEE IoT journal
• Three Approaches for Personalization with Applications to Federated Learning, preprint
• Salvaging Federated Learning by Local Adaptation, preprint
• Federated Learning of a Mixture of Global and Local Models, preprint
• Federated Learning with Matched Averaging, ICLR 2020
• On the Convergence of FedAvg on Non-IID Data, ICLR 2020. [code]
• Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning, preprint
• Knowledge Federation: Hierarchy and Unification, preprint
• Decentralized Knowledge Acquisition for Mobile Internet Applications, World Wide Web, Springer journal
• Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach, IEEE Access 2020
• Multi-Participant Multi-Class Vertical Federated Learning, preprint
• Accelerating DNN Training in Wireless Federated Edge Learning System, preprint
• Federated Optimization in Heterogeneous Networks, MLSYS 2020 [code]

2019

• Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints, IEEE Transaction on Neural Nets, [Code]
• Robust and Communication-Efficient Federated Learning from Non-IID Data, preprint. [Code]
• Federated Learning for Ranking Browser History Suggestions, preprint. [Code]
• Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification, preprint
• The Non-IID Data Quagmire of Decentralized Machine Learning, preprint
• Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning, preprint
• Accelerating DNN Training in Wireless Federated Edge Learning System, preprint
• FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record, NIPS 2018 Workshop
• Federated Learning for Emoji Prediction in a Mobile Keyboard, preprint
• 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
• Towards Faster and Better Federated Learning: A Feature Fusion Approach, ICIP 2019
• Decentralized Bayesian Learning over Graphs, preprint
• Federated Multi-task Hierarchical Attention Model for Sensor Analytics, preprint
• 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]
• On the Convergence of FedAvg on Non-IID Data, preprint. [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

2018

• A Performance Evaluation of Federated Learning Algorithms, DIDL 2018
• How to backdoor federated learning, preprint
• Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
• Federated Kernelized Multi-Task Learning
• Federated Learning with Non-IID Data, preprint.
• 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, preprint. [code]
• Federated Learning for Mobile Keyboard Prediction - Gboard

2017

• 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

2016

• Practical Secure Aggregation for Federated Learning on User-Held Data, preprint
• Federated Learning: Strategies for Improving Communication Efficiency, preprint
• Federated Optimization: Distributed Machine Learning for On-Device Intelligence, preprint
• Communication-Efficient Learning of Deep Networks from Decentralized Data, preprint (first FL paper by Google)

2015

• Privacy-Preserving Deep Learning, ACM SIGSAC 2015

Libraries/Frameworks

• PySyft - Github - The PyTorch based library.
• Tensorflow Federated - TFF - A library on top of Tensorflow.
• Industrial Federated Learning Framework, Federated AI Technology Enabler, WeBank AI
• PyTorch Federated Learning - Github
• Paddle Federated Learning - Federated Deep Learning in PaddlePaddle.
• Flower - A friendly federated learning research framework.

Tutorials

• Flower
• PySyft
• TFF

Datasets

• LEAF
• Federated iNaturalist/Landmarks

Projects

• PhotoLabeller by Jose A. Corbacho
  • Client
  • Server
• Ownership Protocol by Qibing Lee
  • DataToken
  • Compute-to-Data