Results 61 to 70 of about 33,062,051 (187)
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
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
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
Overcoming Forgetting in Federated Learning on Non-IID Data
CoRR, 2019 We tackle the problem of Federated Learning in the non i.i.d. case, in which local models drift apart, inhibiting learning. Building on an analogy with Lifelong Learning, we adapt a solution for catastrophic forgetting to Federated Learning. We add a penalty term to the loss function, compelling all local models to converge to a shared optimum. We show
Neta Shoham +6 more
openaire +2 more sources
IEEE AccessIn sentiment analysis, data are commonly distributed across many devices, and traditional machine learning requires transferring these data to a central location exposing data to security and privacy risks. Federated Learning (FL) avoids this transfer by
Davoud Gholamiangonabadi +1 more
doaj +1 more source
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
Linear Scalarization for Byzantine-robust learning on non-IID data
, 2022 In this work we study the problem of Byzantine-robust learning when data among clients is heterogeneous. We focus on poisoning attacks targeting the convergence of SGD.
Errami, Latifa, Bergou, El Houcine
core
Balancing Privacy and Performance: A Differential Privacy Approach in Federated Learning
ComputersFederated learning (FL), a decentralized approach to machine learning, facilitates model training across multiple devices, ensuring data privacy. However, achieving a delicate privacy preservation–model convergence balance remains a major problem ...
Huda Kadhim Tayyeh +1 more
doaj +1 more source
Non-IID scenario: 10-fold cross validation results with varying C.
, 2020 Non-IID scenario: 10-fold cross validation results with varying C.
Zeng Fu (8727135) +5 more
core +1 more source
Adding Data Quality to Federated Learning Performance Improvement
IEEE AccessMassive data generation from Internet of Things (IoT) devices increases the demand for efficient data analysis to extract relevant and actionable insights. As a result, Federated Learning (FL) allows IoT devices to collaborate in Artificial Intelligence (
Ernesto Gurgel Valente Neto +4 more
doaj +1 more source