Stochastic Approximation: A Dynamical Systems Viewpoint

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Focusing on stochastic approximation algorithms, this advanced text offers a thorough exploration through the lens of ordinary differential equations (ODE). The second edition enhances its coverage of classical convergence analysis while incorporating recent advancements like concentration bounds and stability tests. It also addresses distributed and asynchronous schemes, multiple time scales, and general noise models. With a category-wise exposition of significant applications, it serves as an essential resource for graduate students and professionals in probability, statistics, engineering, economics, and machine learning.