Results 21 to 30 of about 7,049,980 (289)
Analysis and Improvement of Entropy Estimators in NIST SP 800-90B for Non-IID Entropy Sources
IACR Transactions on Symmetric Cryptology, 2017 Random number generators (RNGs) are essential for cryptographic applications. In most practical applications, the randomness of RNGs is provided by entropy sources.
Shuangyi Zhu +4 more
doaj +2 more sources
Federated PAC-Bayesian Learning on Non-IID Data
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 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 +3 more sources
Performance Enhancement in Federated Learning by Reducing Class Imbalance of Non-IID Data. [PDF]
Sensors (Basel), 2023 Seol M, Kim T.
europepmc +2 more sources
Addressing Non-IID with Data Quantity Skew in Federated Learning
InformationNon-IID is one of the key challenges in federated learning. Data heterogeneity may lead to slower convergence, reduced accuracy, and more training rounds.
Narisu Cha, Long Chang
doaj +2 more sources
Federated Data Augmentation Algorithm for Non-independent and Identical Distributed Data [PDF]
Jisuanji kexue, 2022 In federated learning,the local data distribution of users changes with the location and preferences of users,the data under the non-independent and identical distributed(Non-IID) data may lack data of some label categories,which significantly affects ...
QU Xiang-mou, WU Ying-bo, JIANG Xiao-ling
doaj +1 more source
, 2023 Personalized federated learning simulation platform with non-IID and unbalanced ...
Tsing +3 more
core +1 more source
IID-DTH/2019nCov-iSNV: iSNV_figures
, 2021 R scripts for figures in Two-step fitness selection for intra-host variations in SARS-CoV-
IID-DTH
core +1 more source
, 2023 <p>First version of code for benchmarking normalization layers in federated learning for image classification tasks on non-iid data</p ...
Bruno Casella
core +1 more source
A Graph Neural Network Based Decentralized Learning Scheme
Sensors, 2022 As an emerging paradigm considering data privacy and transmission efficiency, decentralized learning aims to acquire a global model using the training data distributed over many user devices.
Huiguo Gao +3 more
doaj +1 more source
Federated Learning Architecture for Non-IID Data [PDF]
Jisuanji gongcheng, 2023 In the scenarios of federated learning involving ultra-large-scale edge devices, the local data of participants are non-Independent Identically Distribution(non-IID) pattern, resulting in an imbalance in overall training data and difficulty in defending ...
Tianchen QIU, Xiaoying ZHENG, Yongxin ZHU, Songlin FENG
doaj +1 more source