When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

A mother's health during pregnancy, childbirth and the postpartum period is the foundation of lifelong well-being, directly ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Machine learning (ML) is a complex domain that sits squarely at the convergence of mathematics, computer science, and statistics. Its mastery demands profound knowledge, practical expertise, and a ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

Artificial intelligence and machine learning have transformed how we process information, make decisions, and solve complex problems. Behind every ...