Large-Scale Optimization for Machine Learning

Catalog description

Credits 3. 3 Lecture Hours. Fundamental optimization algorithms and their analysis for solving machine learning problems; deterministic and stochastic gradient-based algorithms; adaptive gradient-based methods; momentum-based methods; convergence analysis of selected algorithms; implementation of algorithms and their application to solving of real-world machine learning and artificial intelligence problems. Prerequisites: CSCE 633 or CSCE 636 or approval of instructor; graduate classification.