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KnitLoRA: bridging low-rank adaptation as interwoven layers for deeper semantic reasoning. [PDF]
Sci RepQiu H +11 more
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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.
Susheel Kumar Joshi +1 more
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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.
Juliana Freitag Borin +2 more
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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.
Liansheng Tan +4 more
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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
Simon Wessing +2 more
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AQM Mechanism with Neuron Tuning Parameters
2020The congestion control is one of the most important questions in modern computer network performance. This article investigates the problem of adaptive neuron based choice of the Active Queue Mechanisms parameters. We evaluate the performance of the AQM mechanism in the presence of self-similar traffic based on the automatic selection of their ...
Szyguła Jakub +5 more
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NEOCOGNITRON'S PARAMETER TUNING BY GENETIC ALGORITHMS
International Journal of Neural Systems, 1999The further study on the sensitivity analysis of Neocognitron is discussed in this paper. Fukushima's Neocognitron is capable of recognizing distorted patterns as well as tolerating positional shift. Supervised learning of the Neocognitron is fulfilled by training patterns layer by layer.
Shi, D., Dong, C., Yeung, D.S.
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Parameters and Parameter Tuning
2015Chapter 3 presented an algorithmic framework that forms the common basis for all evolutionary algorithms. A decision to use an evolutionary algorithm implies that the user adopts the main design decisions behind this framework. Thus, the main algorithm setup follows automatically: the algorithm is based on a population of candidate solutions that is ...
A. E. Eiben, J. E. Smith
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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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