Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Local Differential Privacy"”.
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Local differential privacy in decentralized optimization
Privacy concerns with sensitive data are receiving increasing attention. In this thesis, we study local differential privacy (LDP) in interactive decentralized optimization. Comparing to central differential privacy (DP), where a centralized curator maintains the dataset, LDP is a stronger notion …
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Fair Selective Regression
… a calibration condition for the former, and a local differential privacy condition for the latter. Based on our theoretical results, we design two novel inference algorithms for fair selective regression that enforce their respective feature set constraints via regularization in a neural …
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Privacy-Preserving Data Collection and Sharing in Modern Mobile Internet Systems
… data for improving products and services, data privacy poses a major concern. This dissertation research addresses the problem of privacy-preserving data collection and sharing in the context of both mobile trajectory data and mobile Internet access data. The first contribution of this …
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On the Use of Iterative Feedback in Private Frequency Estimation
… algorithms, specifically the family of Local Differential Privacy (LDP) algorithms. The main contribution is the Iterative LDP Algorithm which uses iterative feedback to outperform generic LDP mechanisms in certain scenarios, including those with low response rates (number of samples). …
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Learning with classical and quantum information constraints
… various information constraints, including privacy and communication constraints on classical computers, and inherent randomness governed by the laws of physics in quantum computers. First, we study distribution learning and testing with local information constraints such as local …
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Privacy-Preserving and Robust Data Analytics under Distributed Settings
… face of exponential data growth and stringent privacy regulations, safeguarding sensitive information within data processing and analytics workflows, especially in distributed systems, has become paramount. High-profile data breaches and privacy regulations like the General Data Protection …
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The fundamental limits of statistical data privacy
… need to share data and the need to preserve the privacy of Internet users. The need for privacy appears in three main contexts: (1) the global privacy context, as in when private companies and public institutions release personal information about individuals to the public; (2) the local privacy …