Many engineering challenges come down to the same headache—too many knobs to turn and too few chances to test them. Whether ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

We had our first taste of the problem with mean-variance optimization at a hedge fund some years back. We loaded the positions into an optimizer, pressed the button, and discovered 25% of the ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

Research and investment in artificial intelligence (AI) have rapidly expanded over the past decade. The International Data Corporation predicts that global spending on cognitive and AI systems will ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...

There are, generally speaking, two types of people in the mathematical optimization software field: • Optimization solver developers: The technical experts who devise and implement the algorithms that ...