Banach spaces, as complete normed vector spaces, form a central framework in modern functional analysis. Their rich geometric structure underpins much of the theoretical development in approximation ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) ...

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...

This course is available on the MPA in Data Science for Public Policy, MSc in Applicable Mathematics, MSc in Data Science, MSc in Operations Research & Analytics, MSc in Statistics, MSc in Statistics ...

We present a probabilistic greedy search method for combinatorial optimisation problems. This approach is implemented and evaluated for the Set Covering Problem (SCP) and shown to yield a simple, ...