Theory of Efficient Optimization Algorithms for Continuous Big Data Analytics. Subjects Will Include: First-Order Methods for Convex and Non-Convex Optimization, Stochastic Optimization Methods for Convex and Non-Convex Problems and Efficient Algorithms for Efficient Algorithms with Rigorous Proofs of Their Computational Efficiency, as Well as the Development of Complementary Lower Bounds. Online at the End of the Course the Student Will Know:
1. to Understand the Principles, and to Implememt a Large Variety of Important and Central Optimization Algorithms in the Field of Machine
2. to Indenpendently Read and Understand Contemporary Litreature in
3. to Embark on Academic Reasearch (Both Theoretical and Practical) in the Field.