Frontier Orbital Engineering in Heteroatom-Doped Prototypical Organic Dyes for Dye-Sensitized Solar Cells. [PDF]
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Clinical Note Generation From Doctor-Patient Conversations Using Parameter-Efficient Fine-Tuning Large Language Models: Comparative Study. [PDF]
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Resolving non-identifiability mitigates systematic errors in simultaneous models of neural tuning and functional coupling. [PDF]
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Response to the Letter by Zhang "The hidden variable in a 'neutral' upgrade: why parameter re-tuning and perceived reliability matter after G6 → G7 in Control-IQ". [PDF]
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Parameter tuning for meta-heuristics
Knowledge-Based Systems, 2020Abstract These days meta-heuristic algorithms are gaining lot of popularity. The performance of the meta-heuristics depends upon the suitable selection of user dependent parameters. Finding the most suitable values for the parameters (fine tuning) is a challenging problem.
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Multiobjectivization for classifier parameter tuning
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, 2013We present a multiobjectivization approach to the parameter tuning of RBF networks and multilayer perceptrons. The approach works by adding two new objectives -- maximization of kappa statistic and minimization of root mean square error -- to the originally single-objective problem of minimizing the classification error of the model.
Martin Pilát, Roman Neruda
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Tuning of 802.11e network parameters
IEEE Communications Letters, 2006This paper introduces a mechanism which dynamically tunes the parameters of the 802.11e contention-based access method.
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Scalable parameter tuning for AVQ
IEEE Communications Letters, 2005This letter proposes a simple, scalable, practical and systematic rule for tuning the control parameter of the adaptive virtual queue (AVQ) active queue management scheme. An explicit stability condition of AVQ is proposed using classical control theory. Theoretical analyses as well as simulation results are used to validate the result.
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When parameter tuning actually is parameter control
Proceedings of the 13th annual conference on Genetic and evolutionary computation, 2011In this paper, we show that sequential parameter optimization (SPO), a method that was designed for (offline) parameter tuning, can be successfully used as a controller for multistart approaches of evolutionary algorithms (EA). We demonstrate this by replacing the restart heuristic of the IPOP-CMA-ES with the SPO algorithm. Experiments on the BBOB 2010
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Parameter Tuning of Stable Fuzzy Controllers
Journal of Intelligent and Robotic Systems, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jean-Yves Dieulot, Pierre Borne
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