• SCAFFOLD

  • Referenced in 4 articles [sw34100]
  • SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. Federated Averaging (FedAvg) has emerged as the algorithm ... choice for federated learning due to its simplicity and low communication cost. However, in spite...
  • FedML

  • Referenced in 2 articles [sw34090]
  • Research Library and Benchmark for Federated Machine Learning. ederated learning is a rapidly growing research ... field in the machine learning domain. Although considerable research efforts have been made, existing libraries ... that facilitates the development of new federated learning algorithms and fair performance comparisons. FedML supports ... developing and evaluating algorithms for the federated learning research community. We maintain the source code...
  • PySyft

  • Referenced in 3 articles [sw34091]
  • private data from model training, using Federated Learning, Differential Privacy, and Encrypted Computation (like Multi...
  • LEAF

  • Referenced in 2 articles [sw34096]
  • LEAF: A Benchmark for Federated Settings. Modern federated networks, such as those comprised of wearable ... This wealth of data can help to learn models that can improve the user experience ... challenges in research areas such as federated learning, meta-learning, and multi-task learning ... LEAF, a modular benchmarking framework for learning in federated settings. LEAF includes a suite...
  • PaddleFL

  • Referenced in 1 article [sw34097]
  • PaddleFL is an open source federated learning framework based on PaddlePaddle. Researchers can easily replicate ... compare different federated learning algorithms with PaddleFL. Developers can also benefit from PaddleFL in that ... easy to deploy a federated learning system in large scale distributed clusters. In PaddleFL, serveral ... federated learning strategies will be provided with application in computer vision, natural language processing, recommendation...
  • FederatedScope

  • Referenced in 1 article [sw41823]
  • FederatedScope is a comprehensive federated learning platform that provides convenient usage and flexible customization ... various federated learning tasks in both academia and industry. Based on a message-oriented framework ... satisfy the burgeoning demands from federated learning, and aims to build up an easy...
  • Ditto

  • Referenced in 1 article [sw41838]
  • Ditto: Fair and Robust Federated Learning Through Personalization. Fairness and robustness are two important concerns ... federated learning systems. In this work, we identify that robustness to data and model poisoning ... simple, general framework for personalized federated learning, Ditto, that can inherently provide fairness and robustness ... linear problems. Empirically, across a suite of federated datasets, we show that Ditto not only...
  • SAFELearn

  • Referenced in 1 article [sw41614]
  • SAFELearn: secure aggregation for private federated learning. This code provides the implementation of SAFELearn ... scheme for Secure Aggregation for private FEderated Learning. The code allows to securely aggregating model ... SAFELearn: Secure Aggregation for private FEderated Learning.” 2021 IEEE Security and Privacy Workshops (SPW). IEEE...
  • FedNAS

  • Referenced in 1 article [sw40627]
  • Deep Learning via Neural Architecture Search. Federated Learning (FL) has been proved ... costs, and regulatory restrictions. When training deep learning models under an FL setting, people employ ... Thus, we advocate automating federated learning (AutoFL) to improve model accuracy and reduce the manual ... automate the design process. We propose a Federated NAS (FedNAS) algorithm to help scattered workers...
  • Flower

  • Referenced in 1 article [sw41835]
  • Flower: A Friendly Federated Learning Research Framework. Federated Learning (FL) has emerged as a promising...
  • FedGL

  • Referenced in 1 article [sw41836]
  • FedGL: Federated Graph Learning Framework with Global Self-Supervision. Graph data are ubiquitous ... real world. Graph learning (GL) tries to mine and analyze graph data so that valuable ... address this problem, we incorporate federated learning into GL and propose a general Federated Graph ... Learning framework FedGL, which is capable of obtaining a high-quality global graph model while...
  • FLGUARD

  • Referenced in 1 article [sw41617]
  • FLGUARD: Secure and Private Federated Learning. Recently, a number of backdoor attacks against Federated Learning ... adversary injects poisoned model updates into the federated model aggregation process with the goal...
  • FetchSGD

  • Referenced in 1 article [sw34099]
  • FetchSGD: Communication-Efficient Federated Learning with Sketching. Existing approaches to federated learning suffer from...
  • FedHealth

  • Referenced in 1 article [sw34101]
  • FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. With the rapid development of computing ... healthcare achieves great success by training machine learning models on a large quantity of user ... paper, we propose FedHealth, the first federated transfer learning framework for wearable healthcare to tackle ... challenges. FedHealth performs data aggregation through federated learning, and then builds personalized models by transfer...
  • PyVertical

  • Referenced in 1 article [sw41839]
  • PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN. We introduce PyVertical, a framework ... supporting vertical federated learning using split neural networks. The proposed framework allows a data scientist...
  • FedGraphNN

  • Referenced in 1 article [sw41837]
  • FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. Graph Neural Network ... thanks to the capacity of GNNs in learning distributed representations from graph-structured data. However ... concerns, regulation restrictions, and commercial competitions. Federated learning (FL), a trending distributed learning paradigm, provides ... benchmark system that can facilitate research on federated GNNs. FedGraphNN is built on a unified...
  • POSEIDON

  • Referenced in 1 article [sw40779]
  • POSEIDON: Privacy-Preserving Federated Neural Network Learning. In this paper, we address the problem ... neural networks in an N-party, federated learning setting. We propose a novel system, POSEIDON...
  • TFF

  • Referenced in 1 article [sw34092]
  • TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations ... facilitate open research and experimentation with Federated Learning (FL), an approach to machine learning where...
  • SAMBA

  • Referenced in 1 article [sw42123]
  • secure federated multi-armed bandits. The multi-armed bandit is a reinforcement learning model where ... learning agent repeatedly chooses an action (pull a bandit arm) and the environment responds with ... reward maximization problem in a secure federated learning setting, where multiple data owners keep their ... extsc{Samba}, a generic framework for Secure federAted Multi-armed BAndits. Each data owner...
  • Mobyle

  • Referenced in 2 articles [sw36784]
  • federated network of curated bioinformatics portals without the user having to learn complex concepts...