Essays about: "Non-IID"
Showing result 1 - 5 of 7 essays containing the word Non-IID.
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1. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
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2. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
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3. Federated Self-supervised Learning in Computer Vision
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : With an ever-increasing amount of available image data, self-supervised learning (SSL) circumvents the necessity for annotations in traditional supervised learning methods. SSL methods such as SimSiam have shown excellent results on popular benchmark datasets, even outperforming supervised methods. READ MORE
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4. Personalized Federated Learning for mmWave Beam Prediction Using Non-IID Sub-6 GHz Channels
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : While it is difficult for base stations to estimate the millimeter wave (mmWave) channels and find the optimal mmWave beam for user equipments (UEs) quickly, the sub-6 GHz channels which are usually easier to obtain and more robust to blockages could be used to reduce the time before initial access and enhance the reliability of mmWave communication. Considering that the channel information is collected by a massive number of radio base stations and would be sensitive to privacy and security, Federated Learning (FL) is a match for this use case. READ MORE
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5. Towards Peer-to-Peer Federated Learning: Algorithms and Comparisons to Centralized Federated Learning
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Due to privacy and regulatory reasons, sharing data between institutions can be difficult. Because of this, real-world data are not fully exploited by machine learning (ML). An emerging method is to train ML models with federated learning (FL) which enables clients to collaboratively train ML models without sharing raw training data. READ MORE
