New research from the University of Waterloo is making inroads on one of the biggest problems in theoretical computer science ...

By default, LibreOffice Calc is free of AI or machine learning features, mainly because its developers focus more on ...

Abstract: Plenty of decision variable grouping-based algorithms have shown satisfactory performance in solving high-dimensional optimization problems. However, most of them are tailored for ...

Annealing processors (APs) are gaining popularity for solving complex optimization problems. Fully-coupled Ising model APs are especially valued for their flexibility, but balancing capacity (number ...

ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

For many, the long-term dream for AI within EDA is the ability to define a set of goals and tell the computer to go design it for them. A short while later, an optimized design will pop out. All of ...

Abstract: Dynamic environments pose great challenges for expensive optimization problems, as the objective functions of these problems change over time and thus require remarkable computational ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a study led by ...