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During the last decade, the data sizes have grown faster than the speed of processors. In this context, the capabilities of statistical machine learning methods is limited by the computing time rather than the sample siz...

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. ...

Previous article Next article An Algorithm for Least-Squares Estimation of Nonlinear ParametersDonald W. MarquardtDonald W. Marquardthttps://doi.org/10.1137/0111030PDFPDF PLUSBibTexSections ToolsAdd to favoritesExport Ci...

Designing complex, dynamic yet multi-functional materials and devices is challenging because the design spaces for these materials have numerous interdependent and often conflicting constraints. Taking inspiration from a...

Subjects / keywords: nonsmooth analysis, nonsmooth optimization, variational analysis, equilibrium problems, stochastic optimization, bilevel optimization; Science

Subjects / keywords: multi-criteria decision making, socio-technical decision modeling, robust and stochastic optimization, human factors and ergonomics, supply chain and logistics analytics, digital twins and simulation; Technology: Technol...

Subjects / keywords: linear systems, stochastic systems, adaptive control, data analysis, optimization, operations research; Science: Mathematics; Social Sciences: Industries. Land use. Labor: Management. Industrial management: Technological...

Subjects / keywords: Gradient boosting; Parameterized complexity; Mathematics; Robustness (evolution); Boosting (machine learning); Regression; Mathematical optimization; Algorithm; Data point; Computer science; Statistics; Artificial intell...

From the Publisher: The past decade has seen considerable theoretical and applied research on Markov decision processes, as well as the growing use of these models in ecology, economics, communications engineering, and o...

By decision-making in a fuzzy environment is meant a decision process in which the goals and/or the constraints, but not necessarily the system under control, are fuzzy in nature. This means that the goals and/or the con...

Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore ...