Students choose a topic on their own under the guidance of a faculty adviser who will then grade the final written report

(formerly Exercise Science)

This seminar will explore machine learning and data analytic techniques for the purpose of designing network mechanisms such as cache management algorithms and for exploring and analyzing network data such as traffic traces.

Lecture, discussion. Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2 midterm exams, timed final.