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Differentially Private Consensus-Based Distributed Optimization
Consensus-based optimization consists of a set of computational nodes arranged in a graph, each having a local objective that depends on their local data, where in every step nodes take a linear combination of their neighbors' messages, as well as taking a new gradient step.
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise
Data privacy is an important concern in machine learning, and is fundamentally at odds with the task of training useful learning models, which typically require the acquisition of large amounts of private user data.
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