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Asynchronous Parallel Computing in Signal Processing and Machine Learning
Convex Optimization & Parsimony of L_p-balls Representation
Introduction to dynamical systems. Linear dynamics, stability, Lyapunov functions, eigenvalue conditions.
Lyapunov equations and inequalities. Duality in convex optimization and systems theory. Linear matrix inequalities (LMIs). S-Procedure and applications (ellipsoid containment, etc.).
Optimal sensor and actuator selection in distributed systems
Optimization methods: First order methods: basic gradient and extensions (accelerated, stochastic, subgradient, and projection).
Optimization Taxonomy and Mathematical Foundations
Revisiting Nesterov€™s Acceleration
Stochastic Dynamical Modeling: Structured Matrix Completion of Partially Available Statistics