Results 51 to 60 of about 34,864,804 (179)
Comparison of FedAvg and LoAdaboost on non-IID data with data-sharing strategy.
, 2020 Comparison of FedAvg and LoAdaboost on non-IID data with data-sharing strategy.
Zeng Fu (8727135) +5 more
core +1 more source
Non-IID Learning for Recommendation, Time Series and Hashing [PDF]
, 2023 University of Technology Sydney. Faculty of Engineering and Information Technology.For several decades, the independent and identically distributed (short for IID) assumption has laid the foundation of data learning, simplifying real-world data's ...
Zhang, Qi
core +1 more source
Agronomy, 2023 Paddy leaf diseases encompass a range of ailments affecting rice plants’ leaves, arising from factors like bacteria, fungi, viruses, and environmental stress.
Meenakshi Aggarwal +6 more
doaj +1 more source
Frontiers in Neurology, 2022 ObjectiveTo analyze the interictal discharge (IID) patterns on pre-operative scalp electroencephalogram (EEG) and compare the changes in IID patterns after removal of epileptogenic tubers in preschool children with tuberous sclerosis complex (TSC ...
Liu Yuan +10 more
doaj +1 more source
DCFL: Non-IID awareness Data Condensation aided Federated Learning [PDF]
, 2023 Federated learning is a decentralized learning paradigm wherein a central server trains a global model iteratively by utilizing clients who possess a certain amount of private datasets. The challenge lies in the fact that the client side private data may
Sun, YaFeng, Sha, Shaohan
core
Federated PAC-Bayesian Learning on Non-IID Data
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Existing research has either adapted the Probably Approximately Correct (PAC) Bayesian framework for federated learning (FL) or used information-theoretic PAC-Bayesian bounds while introducing their theorems, but few considering the non-IID challenges in FL. Our work presents the first non-vacuous federated PAC-Bayesian bound tailored for non-IID local
Zihao Zhao 0001 +3 more
openaire +4 more sources
Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data
CoRR, 2022 Non-independent and identically distributed (non-IID) data is a key challenge in federated learning (FL), which usually hampers the optimization convergence and the performance of FL. Existing data augmentation methods based on federated generative models or raw data sharing strategies for solving the non-IID problem still suffer from low performance ...
Shaoming Duan +5 more
openaire +2 more sources
Non-IID representation learning on complex categorical data [PDF]
, 2019 University of Technology Sydney. Faculty of Engineering and Information Technology.Learning complex categorical data requires proper vector or metric representations of the intricate characteristics of that data.
Zhu, Chengzhang
core
A Distributed Privacy Preserved Federated Learning Approach for Revolutionizing Pneumonia Detection in Isolated Heterogenous Data Silos [PDF]
International Journal of Mathematical, Engineering and Management SciencesPneumonia is a respiratory lung contamination that ranges in severity from mild to lethal outcomes. The analysis of tomographic images is the most significant method of pneumonia detection.
Shagun Sharma, Kalpna Guleria
doaj +1 more source
Privacy Protection in Prosumer Energy Management Based on Federated Learning
IEEE Access, 2021 With the booming development of prosumers, there is an urgent need for a prosumer energy management system to take full advantage of the flexibility of prosumers and take into account the interests of other parties.
Yunfeng Li +3 more
doaj +1 more source