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 ...

Constraint satisfaction problems (CSPs) provide a versatile framework for modelling complex decision-making tasks where a collection of variables must be allocated values that satisfy specific ...

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape. How fundamentally difficult is a problem?

They have a mathematical, analog “solver” that can potentially find the best solution to NP-hard problems. NP-hardness is a theory of computational complexity, with problems that are famous for their ...

The historical pursuit of creating intelligent machines has culminated in the modern era of artificial intelligence. However, the efficacy of AI applications is contingent upon a nuanced understanding ...

Professor Wang's current research interests include text mining algorithms and systems, data modeling and its applications, and combinatorial optimizations. His previous interests included large-scale ...