In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

This course introduces the process, methods, and computing tools fundamental to machine learning. Students will work on large real-world datasets to write code to accomplish tasks such as predicting ...

Automated machine learning (autoML) is the process of applying tools to data to apply the machine learning process to a real-world problem. Applying machine learning to a new dataset is a complicated ...

A new research paper featured on the cover of Volume 17, Issue 11 of Aging-US was published on October 30, 2025, titled "SAMP ...

As the election season rampages on, we categorize voters into broad demographics — soccer moms, NASCAR dads, blacks, whites, ALICEs, yuppies — in an attempt to understand and discuss this complex, ...

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 ...

Human-in-the-loop machine learning takes advantage of human feedback to eliminate errors in training data and improve the accuracy of models. Machine learning models are often far from perfect. When ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...