Federated meta-learning
WebApr 13, 2024 · Federated learning (FL) has recently shown the capacity of collaborative artificial intelligence and privacy preservation. Based on these capabilities, we propose a novel approach to solve the few-shot FD problem, which includes a generic framework (i.e., FedMeta-FFD) and an easy-to-implement enhancement technique (i.e., AILR). WebJan 5, 2024 · Our FML-ST framework combines federated learning with meta-learning and introduces a personalized learning mechanism in the process of client local training. The …
Federated meta-learning
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WebApr 11, 2024 · In this paper, we propose an energy-efficient federated meta-learning framework. The objective is to enable learning a meta-model that can be fine-tuned to a … Web2.3 The Federated Meta-Learning Framework. We incorporate meta-learning into the decentralized training process as in federated learning. In this framework, meta-training …
WebJul 19, 2024 · In contrast, our proposed federated meta-learning framework achieves a significant improvement over FedAvg, which indicates that applying the MAML approach to the federated recommender system can effectively improve the model’s adaptability to the user’s local data. In terms of recommendation models, our proposed ISSA-based model … Webwith a Federated Meta-learning framework (FedMeta-FFD), which relies on initialization-based meta-learning and federated learning to solve few-shot FD tasks. (2) Theoretically, we perform a convergence analysis of the proposed FedMeta-FFD algorithm on the non-convex setting. (3) Empirically, we conduct an extensive empirical evaluation
WebApr 10, 2024 · Recent Meta AI research presents their project called “Segment Anything,” which is an effort to “democratize segmentation” by providing a new task, dataset, and … WebJul 7, 2024 · Moreover, federated learning frameworks are usually vulnerable to malicious attacks of the central server and diverse clients. To address these problems, we propose a decentralized federated meta-learning framework (DFMLF) for few-shot multitask learning. In DFMLF, the devices take the rapid adaptation as objective and learn the meta …
Web论文：Zheng W, Yan L, Gou C, et al. Federated Meta-Learning for Fraudulent Credit Card Detection[C], Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Special Track on AI in FinTech. Pages 4654-4660. 2024: 4654-4660.
WebSep 13, 2024 · A federated meta-learning framework is designed for higher convergence speeds to unseen tasks and environments. We distributed learning algorithms in the … truro townshipWebApr 10, 2024 · Recent Meta AI research presents their project called “Segment Anything,” which is an effort to “democratize segmentation” by providing a new task, dataset, and model for image segmentation. Their Segment Anything Model (SAM) and Segment Anything 1-Billion mask dataset (SA-1B), the largest ever segmentation dataset. philippine system of governmentWebJan 1, 2024 · This approach has two problems: first, remote data and model transmission produces high communication overhead; second, uploading user sensitive data to the … philippine system of national accountsWebMeta Federated Learning. ICLR 2024. Watch video. Abstract. Due to its distributed methodology alongside its privacy-preserving features, Federated Learning (FL) is vulnerable to training time backdoor attacks. Contemporary defenses against backdoor attacks in FL require direct access to each individual client's update which is not feasible … truro townhouseWebDec 5, 2024 · Federated meta-learning has emerged as a promising AI framework for today’s mobile computing scenes involving distributed clients. It enables collaborative model training using the data located at distributed mobile clients and accommodates clients that need fast model customization with limited new data. However, federated meta-learning ... philippines youth populationWebApr 14, 2024 · The joint utilization of meta-learning algorithms and federated learning enables quick, personalized, and heterogeneity-supporting training [14,15,39]. … truro township fireWebFeb 10, 2024 · To this end, we propose Meta Federated Learning (Meta-FL), a novel variant of federated learning which not only is compatible with secure aggregation … philippine tamaraw conservation status