Linear Programming: Bit Complexity || @ CMU || Lecture 17c of CS Theory Toolkit

It is shown that *if* a Linear Program is feasible, then it has a feasible solution that can be written down with a polynomial of bits. Combined with LP duality, this implies Linear Programming is in NP ∩ coNP. (We will later see it is in P.) Lecture 17c of "CS Theory Toolkit": a semester-long graduate course on math and CS fundamentals for research in theoretical computer science, taught at Carnegie Mellon University.

Resources for this lecture:
"Understanding and Using Linear Programming" by Matoušek and Gärtner
"Geometric Algorithms and Combinatorial Optimization" by Grötschel, Lovász, and Schrijver