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 ...

The Journal of the Operational Research Society, Vol. 55, No. 7, Part Special Issue: Local Search (Jul., 2004), pp. 705-716 (12 pages) The Bin Packing Problem and the Cutting Stock Problem are two ...

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 ...

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 ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

This course introduces high-performance computing (“HPC”) systems, software, and methods used to solve large-scale problems in science and engineering. It will focus on the intersection of two ...

In modern computing, solving complex optimization problems has always been a significant challenge. Recently, a research team from Canada developed a new type of photonic Ising machine capable of ...