Results 61 to 70 of about 31,221,148 (284)
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
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
Agribusiness, EarlyView.ABSTRACT This paper explores Swedish consumers' protein preferences by estimating the willingness‐to‐pay (WTP) for minced meat and plant‐based proteins in pasta sauce from an in‐store experiment (n = 206) and an online discrete choice experiment (n = 517). On average, the WTP was highest for minced meat.
Emilia Mattsson +3 more
wiley +1 more source
Mitigating non-IID data impact in federated learning with entropy
, 2023 Algoritmos de Machine Learning (ML) possibilitam processar um conjunto de dados de entradas para gerar coeficientes que ajustem a saída a um resultado previamente conhecido, como menor erro possível, fazendo com que seja possível reconhecer e extrair ...
Orlandi, Fernanda Cavalheiro
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Assessing the Impact of Promotions on Consumer Purchasing Behavior During Crises
Agribusiness, EarlyView.ABSTRACT Understanding how households modify their food expenditure decisions during times of crisis is essential because consumer purchasing behavior frequently changes during these times. This study looks at these behavioral shifts during the COVID‐19 pandemic, concentrating on how price sensitivity and response to sales promotions changed over the ...
Wafa Mehaba, José María Gil
wiley +1 more source
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
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
Adaptive Federated Learning on Non-IID Data With Resource Constraint
, 2022 Federated learning (FL) has been widely recognized as a promising approach by enabling individual end-devices to cooperatively train a global model without exposing their own data.
Zhan, Yufeng +6 more
core +1 more source
Agribusiness, EarlyView.ABSTRACT Brazil and the United States account for more than 40% of global poultry exports, with China and South Korea among their major destination markets. This study examines price transmission and market linkages between Brazil and the United States using monthly poultry export price data from January 1990 to December 2024. It also assesses which of
Khondoker Abdul Mottaleb +2 more
wiley +1 more source