CS 168: The Modern Algorithmic Toolbox

This course will provide a rigorous and hands-on introduction to the central ideas and algorithms that constitute the core of the modern algorithms toolkit. Emphasis will be on understanding the high-level theoretical intuitions and principles underlying the algorithms we discuss, as well as developing a concrete understanding of when and how to implement and apply the algorithms. The course will be structured as a sequence of one-week investigations; each week will introduce one algorithmic idea, and discuss the motivation, theoretical underpinning, and practical applications of that algorithmic idea. Each topic will be accompanied by a mini-project in which students will be guided through a practical application of the ideas of the week. Topics include modern techniques in hashing, dimension reduction, linear and convex programming, gradient descent and regression, sampling and estimation, compressive sensing, and linear-algebraic techniques (principal components analysis, singular value decomposition, spectral techniques).

CS107 and CS161, or permission from the instructor.