CME 305:
Discrete Mathematics and Algorithms (MS&E 316)
Topics: Basic Algebraic Graph Theory, Matroids and Minimum Spanning Trees, Submodularity and Maximum Flow, NPHardness, Approximation Algorithms, Randomized Algorithms, The Probabilistic Method, and Spectral Sparsification using Effective Resistances. Topics will be illustrated with applications from Distributed Computing, Machine Learning, and largescale Optimization. Prerequisites: CS 261 is highly recommended, although not required.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit