Private Distributed Computing for Machine Learning Algorithms, M.Sc. Thesis Sharif University of Technology ; Maddah-Ali, Mohammad Ali (Supervisor) ; Mirmohseni, Mahtab (Co-Supervisor)
Abstract
In this thesis, we argue that in many basic algorithms for machine learning, including support vector machine (SVM) for classification, principal component analysis (PCA) for dimensionality reduction, and regression for dependency estimation, we need the inner products of the data samples, rather than the data samples themselves. Motivated by the above observation, we introduce the problem of private inner product retrieval for distributed machine learning, where we have a system including a database of some files, duplicated across some non-colluding servers. A user intends to retrieve a subset of specific size of the inner products of the data files with minimum communication load, without...
Cataloging briefPrivate Distributed Computing for Machine Learning Algorithms, M.Sc. Thesis Sharif University of Technology ; Maddah-Ali, Mohammad Ali (Supervisor) ; Mirmohseni, Mahtab (Co-Supervisor)
Abstract
In this thesis, we argue that in many basic algorithms for machine learning, including support vector machine (SVM) for classification, principal component analysis (PCA) for dimensionality reduction, and regression for dependency estimation, we need the inner products of the data samples, rather than the data samples themselves. Motivated by the above observation, we introduce the problem of private inner product retrieval for distributed machine learning, where we have a system including a database of some files, duplicated across some non-colluding servers. A user intends to retrieve a subset of specific size of the inner products of the data files with minimum communication load, without...
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