Results 51 to 60 of about 14,306 (259)

Improving Accuracy of Federated Learning in Non-IID Settings

CoRR, 2020
Federated Learning (FL) is a decentralized machine learning protocol that allows a set of participating agents to collaboratively train a model without sharing their data. This makes FL particularly suitable for settings where data privacy is desired.
Mustafa Safa Özdayi, Murat Kantarcioglu, Rishabh Iyer   +2 more
openaire   +2 more sources

Decoupled Federated Learning for ASR with Non-IID Data

Interspeech 2022, 2022
Automatic speech recognition (ASR) with federated learning (FL) makes it possible to leverage data from multiple clients without compromising privacy. The quality of FL-based ASR could be measured by recognition performance, communication and computation costs. When data among different clients are not independently and identically distributed (non-IID)
Han Zhu 0004, Jindong Wang 0001, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan 0002   +4 more
openaire   +2 more sources

Swedish Consumers' Willingness‐to‐Pay for Plant‐Based Proteins in Pasta Sauce: Preferences and Policy Scenarios

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, Anna Kristina Edenbrandt, Jens Rommel, Sarah Säll   +3 more
wiley   +1 more source

Federated Learning for Sentiment Analysis in Presence of Non-IID Data: Sensitivity of Deep Learning Models

IEEE Access
In 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, Katarina Grolinger   +1 more
doaj   +1 more source

Multi-Level Coupling Network for Non-IID Sequential Recommendation

IEEE Access, 2019
Sequential recommendation has been recently attracting a lot attention to suggest users with next items to interact. However, most of the traditional studies implicitly assume that users and items are independent and identically distributed (IID) and ...
Yatong Sun, Guibing Guo, Xiaodong He, Xiaohua Liu   +3 more
doaj   +1 more source

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

Nonlinear Distortion-Aware Channel Estimation Strategies for IRS-Aided MIMO Systems

IEEE Access
The article addresses the challenges posed by nonlinear distortions in Intelligent Reflecting Surface (IRS)-assisted Multiple-Input Multiple-Output (MIMO) systems, which are often overlooked in conventional channel estimation strategies.
D. L. Sharini, Ravilla Dilli, M. Kanthi, G. D. Goutham Simha   +3 more
doaj   +1 more source

Price Transmission and Leadership in the Global Poultry Market: Results From Parametric and Nonparametric Approaches

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, Shaikh M. Rahman, Syed Imran Ali Meerza   +2 more
wiley   +1 more source

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, Yang Liu 0165, Wenbo Ding 0001, Xiao-Ping Zhang 0003   +3 more
openaire   +2 more sources

Is There a Market for Organic Milk in Serbia? Insights From Integrated Choice and Latent Variable Model

Agribusiness, EarlyView.
ABSTRACT Past growth in the global organic market has been concentrated in high‐income countries, while in middle‐income countries such as Serbia the organic market remains nascent and characterized by a sparse assortment of organic products, high retail premia and limited evidence on consumer preferences and their drivers.
Milan Tatic, Sanja Dzever, Bojan Matkovski, Danilo Djokic   +3 more
wiley   +1 more source