Researchers have developed a powerful computational framework that shows how carefully optimized nanotube shapes can amplify ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...

You’ll often hear plastic pollution referred to as a problem. But the reality is that it’s multiple problems. Depending on the properties we need, we form plastics out of different polymers, each of ...

Abstract: When solving decision-making problems with mathematical optimization, some constraints or objectives may lack analytic expressions but can be approximated from the data. When an ...

Abstract: The exponential growth in Internet-connected devices has escalated the demand for optimized network topologies to ensure high performance. Traditional optimization methods often fall short ...