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 ...
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 ...
Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven ...
Researchers from Zhejiang University and their collaborators have developed Qjump, a hybrid quantum-classical algorithm for ...
At Pittcon 2026 in San Antonio, Texas, USA, LCGC International spoke with 2026 LCGC International Emerging Leader Award ...
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