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

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 ...

Abstract: This article presents the development of a technological tool that results in student learning about solving differential calculus optimization problems. This work is framed in a research ...

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 ...

I’ve been away from Substack for a bit due to work, work writing, and work travel. There’s a lot going on in the areas I work on; this is my attempt to connect the dots in particular between the ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

Kubernetes has become the de facto way to schedule and manage services in medium and large enterprises. Coupled with the microservice design pattern, it has proved to be a useful tool for managing ...