Results 1 to 10 of about 691,754 (120)
Flower pollination algorithm parameters tuning [PDF]
Soft Computing, 2021 The flower pollination algorithm (FPA) is a highly efficient metaheuristic optimization algorithm that is inspired by the pollination process of flowering species. FPA is characterised by simplicity in its formulation and high computational performance.
Mergos, P.E., Yang, X-S.
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Tuning Retinex Parameters [PDF]
Journal of Electronic Imaging, 2004 Our goal is to understand how the Retinex parameters affect the predictions of the model. A simplified Retinex computation is specified in the recent MATLAB™ implementation; however, there remain several free parameters that introduce significant variability into the model’s predictions. We extend previous work on specifying these parameters.
Ciurea, Florian, Funt, Brian
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Efficiently Tuned Parameters Are Task Embeddings
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 EMNLP 2022 (main conference)
Zhou, Wangchunshu +2 more
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GEANT4 parameter tuning using Professor
Journal of Instrumentation, 2020 The Geant4 toolkit is used extensively in high energy physics to simulate the passage of particles through matter and to predict effects such as detector efficiencies and smearing. Geant4 uses many underlying models to predict particle interaction kinematics, and uncertainty in these models leads to uncertainty in high energy physics measurements.
Elvira, V. +12 more
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Hierarchical Collaborative Hyper-Parameter Tuning
, 2022 Hyper-parameter Tuning is among the most critical stages in building machine learning solutions. This paper demonstrates how multi-agent systems can be utilized to develop a distributed technique for determining near-optimal values for any arbitrary set of hyper-parameters in a machine learning model.
Ahmad Esmaeili +2 more
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Proceedings of the VLDB Endowment, 2022 The ever-growing demand and complexity of machine learning are putting pressure on hyper-parameter tuning systems: while the evaluation cost of models continues to increase, the scalability of state-of-the-arts starts to become a crucial bottleneck.
Li, Yang +7 more
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On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes [PDF]
, 2012 In this paper, a comparative study is done on the time and frequency domain tuning strategies for fractional order (FO) PID controllers to handle higher order processes. A new fractional order template for reduced parameter modeling of stable minimum/non-
Alomoush +56 more
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A Methodology for Spark Parameter Tuning [PDF]
Big Data Research, 2018 Spark has been established as an attractive platform for big data analysis, since it manages to hide most of the complexities related to parallelism, fault tolerance and cluster setting from developers. However, this comes at the expense of having over 150 configurable parameters, the impact of which cannot be exhaustively examined due to the ...
Gounaris, Anastasios +1 more
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Naturalness and Fine Tuning in the NMSSM: Implications of Early LHC Results [PDF]
, 2011 We study the fine tuning in the parameter space of the semi-constrained NMSSM, where most soft Susy breaking parameters are universal at the GUT scale. We discuss the dependence of the fine tuning on the soft Susy breaking parameters M_1/2 and m0, and on
A Strumia +52 more
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Micro Injection Moulding Process Parameter Tuning [PDF]
Procedia CIRP, 2015 AbstractThis paper focuses on tuning the micro injection moulding process parameters. In this study four process parameters namely, barrel temperature, mould temperature, holding pressure and injection speed were considered. In order to capture their behaviour a L16 Orthogonal Array with two levels for each parameter was employed to produce the design ...
Packianather, Michael Sylvester +2 more
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