Neel Somani points out that while artificial intelligence may look like it runs on data and algorithms, its real engine is ...
We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...
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 ...
Facility location and optimization problems have long been a central focus in operations research and applied mathematics, addressing the challenge of strategically placing facilities to serve a ...
We develop a novel framework, the implicit hitting set approach, for solving a class of combinatorial optimization problems. The explicit hitting set problem is as follows: given a set U and a family ...
Following a spate of deadly wildfires earlier this year, many of us find ourselves asking how we can fight such a powerful ...
A group of researchers at the Massachusetts Institute of Technology have devised a potentially more effective way of helping computers solve some of the toughest optimization problems they face. Their ...
The artificial intelligence start-up said the new system, OpenAI o3, outperformed leading A.I. technologies on tests that rate skills in math, science, coding and logic. By Cade Metz Reporting from ...
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