Large-Scale Optimization for Machine Learning Introduction of optimization algorithms suitable for solving large- scale problems, with a focus on exploring recent advances in the context of machine learning. Students will learn several algorithms for solving smooth and non-smooth problems, compare the efficacy of those methods, and discuss the trade-offs in terms of statistical accuracy, scalability, and algorithmic complexity. Not offered on a regular basis. Credit Hours: 4 Prerequisites: CSCI 4360/6360 or CSCI 4380/6380 or permission of department Level: Graduate
