Complexity theory is a fundamental branch of theoretical computer science that categorises computational problems according to their inherent difficulty and the resources required to solve them. At ...

This is a preview. Log in through your library . Abstract We apply a potential reduction algorithm to solve the general linear complementarity problem (GLCP) minimize ...

Daniel Lokshtanov’s work explores the limits of what computers can solve, paving the way for advances in artificial intelligence and computational efficiency.

The amount of time it takes for an algorithm to solve a polynomial function, which is a mathematical expression that does not contain fractions or negative numbers. The time is proportional to the ...

We present a general framework whereby analysis of interior-point algorithms for semidefinite programming can be extended verbatim to optimization problems over all classes of symmetric cones ...

In computational complexity theory, P and NP are two classes of problems. P is the class of decision problems that a deterministic Turing machine can solve in polynomial time. In useful terms, any ...

Jie Wang does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...

A diagram showing the relevant complexity classes in the P vs NP problem. “P” problems are solvable in polynomial time; “NP” problems might be solvable in polynomial time, and are checkable in ...

While fully operational Quantum AI systems may still be a long way off, Oman's proactive approach in introducing quantum AI in Oman Vision 2040 places the nation as a regional leader in digital ...