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Convergence Analysis Framework for Fixed-Point Algorithms in Machine Learning and Signal Processing

Creator:

Vu, Trung

Abstract:

Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...

Resource Type:

Dissertation