When faced with a job offer, a major move, or a difficult personal choice, most people reach for a pros-and-cons list. It ...

There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods should be developed ...

ABSTRACT: This paper addresses a class of numerical solution problems for quaternion quadratic matrix equations arising from practical engineering applications. By transforming it into a special ...

E4620 is typically taught once per year in the Fall semester. The information below is meant to provide a snapshot of the material covered. E4620 is intended to provide students with an introduction ...

Hey there! I'm Aayush Khanna from Noida, Uttar Pradesh, India. I am a third year undergrad pursuing civil engineering at the Indian institute of Technology (BHU), Varanasi. I am interested in all ...

Abstract: For the low-rank matrix recovery problem, algorithms that directly manipulate the low-rank matrix typically require computing the top singular values/vectors of the matrix and thus are ...

Abstract: Factorizing a low-rank matrix into two matrix factors with low dimensions from its noisy observations is a classical but challenging problem arising from real-world applications. This paper ...

Inspired by path integral solutions to the quantum relaxation problem, we develop a numerical method to solve classical stochastic differential equations with multiplicative noise that avoids ...