A new book, The Structure of Fair Solutions: Achieving Fairness in an Optimization Model, by Özgün Elçi, John Hooker, and Peter Zhang, challenges how people typically think about mathematical decision ...

DUBLIN--(BUSINESS WIRE)--Research and Markets(http://www.researchandmarkets.com/research/799091/deterministic_oper) has announced the addition of John Wiley and Sons ...

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure the ...

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 ...

"What's the difference between mathematical optimization and machine learning?" This is a question that — as the CEO of a mathematical optimization software company — I get asked all the time.

An optimization problem is one where you have to make the best decision (choose the best investments, minimize your company’s costs, find the class schedule with the fewest morning classes, or so on).

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...