Results 11 to 20 of about 5,032 (199)
Reverse Search for Parametric Linear Programming [PDF]
Proceedings of the 45th IEEE Conference on Decision and Control, 2006 This paper introduces a new enumeration technique for (multi) parametric linear programs (pLPs) based on the reverse-search paradigm. We prove that the proposed algorithm has a computational complexity that is linear in the size of the output (number of so-called critical regions) and a constant space complexity.
Colin N. Jones, Jan M. Maciejowski
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CKM substructure from the weak to the Planck scale
Journal of High Energy Physics, 2022 We look for relations among CKM matrix elements that are not consequences of the Wolfenstein parametrization. In particular, we search for products of CKM elements raised to integer powers that approximately equal 1.
Yuval Grossman +3 more
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Non-parametric contextual stochastic search [PDF]
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016 Stochastic search algorithms are black-box optimizer of an objective function. They have recently gained a lot of attention in operations research, machine learning and policy search of robot motor skills due to their ease of use and their generality.
Abbas Abdolmaleki +3 more
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Insights Into Efficient k-Nearest Neighbor Classification With Convolutional Neural Codes
IEEE Access, 2020 The increasing consideration of Convolutional Neural Networks (CNN) has not prevented the use of the k-Nearest Neighbor (kNN) method. In fact, a hybrid CNN-kNN approach is an interesting option in which the network specializes in feature extraction ...
Antonio-Javier Gallego +2 more
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AutoML Approach to Stock Keeping Units Segmentation
Journal of Theoretical and Applied Electronic Commerce Research, 2022 A typical retailer carries 10,000 stock-keeping units (SKUs). However, these numbers may exceed hundreds of millions for giants such as Walmart and Amazon.
Ilya Jackson
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Neighborhood Search Considering Continuous Space Search
Trends in Computational and Applied Mathematics, 2002 The objective of this work is to present and discuss a dynamical optimization procedure based on the algorithm of self-consistent parametric inference, where the movement of one feasible solution to another is implemented in continuous mode. The approach
A.T. Gómez, B.E.J. BODMANN
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Parametric search visualization [PDF]
Proceedings of the 29th annual symposium on Symposuim on computational geometry - SoCG '13, 2013 This video provides a visualization of parametric search using as the underlying application an algorithm for computing a tangent to a level in arrangement proposed by Matousek [2]. The visualization is based on the framework of van~Oostrum and Veltkamp [6], which simplifies considerably the implementation of parametric search algorithms.
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Architecture Students' Search Behavior in Parametric Design
eCAADe proceedings, 2022 Over the last decade, architecture has witnessed a growing popularity for new computational tools such as parametric design environments (PDEs). Given their rapid evolution and development, expertise tends to become increasingly transient, and architects find themselves in a situation where they must constantly re-learn their tools.
Dissaux, Thomas, Jancart, Sylvie
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Научный вестник МГТУ ГА, 2018 The application of hybrid memetic algorithm of global constrained optimization in the search optimal control of nonlinear stochastic systems problem is researched in the paper.
A. V. Panteleev, V. N. Panovskiy
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Energies, 2017 Due to growing worldwide energy demand, the search for diversification of the energy matrix stands out as an important research topic. Bioethanol represents a notable alternative of renewable and environmental-friendly energy sources extracted from ...
Hanniel Ferreira Sarmento de Freitas +2 more
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