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 ...

Computer-generated holography (CGH) provides an approach to digitally modulate a given wavefront. This technology, partly inherited from optical holography and partly advanced by the progress of ...

Estimation errors or uncertainities in expected return and risk measures create difficulties for portfolio optimization. The literature deals with the uncertainty using stochastic, fuzzy or ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

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 ...

A recent prototype developed by Microsoft Research is exploring a non-electronic approach to computation by relying on ...

Problem solving is, itself, a problem. With so many proven methods at our disposal, choosing the right one can feel like a long and difficult journey. Today, I’d like to take a look at three methods ...