Quantum walks sound abstract, but they sit at the center of a very concrete race: who will harness quantum mechanics to solve problems that overwhelm today’s most powerful supercomputers. Instead of ...

Abstract: In this paper, we introduce a classical algorithm for random sampling of permutations, drawing inspiration from the Steinhaus-Johnson-Trotter algorithm. Our approach takes a comprehensive ...

Background: Human papillomavirus (HPV) infection is the primary cause of cervical cancer, and HPV self-sampling has emerged as a novel screening method with the potential to increase screening ...

Denoising Diffusion Probabilistic Models (DDPMs) have gained great attention in adversarial purification. Current diffusion-based works focus on designing effective condition-guided mechanisms while ...

Abstract: This paper proposes a new perspective on the relationship between the sampling and aliasing. Unlike the uniform sampling case, where the aliases are simply periodic replicas of the original ...

Before delving into debugging, it is critical to have a solid understanding of the basics of SystemVerilog constraint randomization. Constraints are used to define the valid range of values for ...

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly ...