It 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) .

Formulate linear and integer programming problems for solving commonly encountered optimization problems. Understand how approximation algorithms compute solutions that are guaranteed to be within ...

Google is borrowing from Darwin to make a seismic leap in automatic machine learning. It could spell out the end of most human bias.

Thomas J. Hindelang, John F. Muth, A Dynamic Programming Algorithm for Decision CPM Networks, Operations Research, Vol. 27, No. 2 (Mar. - Apr., 1979), pp. 225-241 ...