Essays about: "Federerad inlärning"
Showing result 1 - 5 of 13 essays containing the words Federerad inlärning.
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1. Confidential Federated Learning with Homomorphic Encryption
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Federated Learning (FL), one variant of Machine Learning (ML) technology, has emerged as a prevalent method for multiple parties to collaboratively train ML models in a distributed manner with the help of a central server normally supplied by a Cloud Service Provider (CSP). Nevertheless, many existing vulnerabilities pose a threat to the advantages of FL and cause potential risks to data security and privacy, such as data leakage, misuse of the central server, or the threat of eavesdroppers illicitly seeking sensitive information. READ MORE
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2. Unlearn with Your Contribution : A Machine Unlearning Framework in Federated Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recent years have witnessed remarkable advancements in machine learning, but with these advances come concerns about data privacy. Machine learning inherently involves learning functions from data, and this process can potentially lead to information leakage through various attacks on the learned model. READ MORE
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3. 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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4. Federated Learning for Natural Language Processing using Transformers
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The use of Machine Learning (ML) in business has increased significantly over the past years. Creating high quality and robust models requires a lot of data, which is at times infeasible to obtain. As more people are becoming concerned about their data being misused, data privacy is increasingly strengthened. READ MORE
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5. Energy-Efficient Private Forecasting on Health Data using SNNs
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Health monitoring devices, such as Fitbit, are gaining popularity both as wellness tools and as a source of information for healthcare decisions. Predicting such wellness goals accurately is critical for the users to make informed lifestyle choices. READ MORE
