Results 1 - 10 of 143,082

Sensitivity Analysis of the Optimal Parameter Settings of an LTE Packet Scheduler

by I. Fernandez Diaz, R. Litjens, D. C. Dimitrova, K. Spaey
"... Abstract—Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to vari ..."
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Abstract—Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect

Towards Fair Comparisons of Connectionist Algorithms through Automatically Optimized Parameter Sets

by Frank E. Ritter - In Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society , 1991
"... The learning rate and convergence of connectionist learning algorithms are often dependent on their parameters. Most algorithms, if their parameters have been optimized at all, have been optimized by hand. ..."
Abstract - Cited by 15 (6 self) - Add to MetaCart
The learning rate and convergence of connectionist learning algorithms are often dependent on their parameters. Most algorithms, if their parameters have been optimized at all, have been optimized by hand.

A Bi-Level Programming Model and Solution Algorithm on Optimal Parameter Setting in Wireless Sensor Networks

by Zhao Tong, Yang Wen-guo, Guo Tian-de
"... Zhao T, Yang WG, Guo TD. A bi-level programming model and solution algorithm on optimal parameter setting in wireless sensor networks. Journal of Software, 2007,18(12):3124−3130. ..."
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Zhao T, Yang WG, Guo TD. A bi-level programming model and solution algorithm on optimal parameter setting in wireless sensor networks. Journal of Software, 2007,18(12):3124−3130.

Automatically Searching for Optimal Parameter Settings Using a Genetic Algorithm?

by David S. Bolme, J. Ross Beveridge, Bruce A. Draper, P. Jonathon Phillips, Yui Man Lui
"... Abstract. Modern vision systems are often a heterogeneous collection of image processing, machine learning, and pattern recognition tech-niques. One problem with these systems is finding their optimal parame-ter settings, since these systems often have many interacting parameters. This paper propose ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract. Modern vision systems are often a heterogeneous collection of image processing, machine learning, and pattern recognition tech-niques. One problem with these systems is finding their optimal parame-ter settings, since these systems often have many interacting parameters. This paper

Locally Optimal Parameter Settings for Pattern Discovery in Gene Expression Microarray Data

by unknown authors
"... Pattern discovery on gene expression microarray data is an emerging analysis technique. It provides specific advantages over the more commonly used clustering techniques [Rigoutsos, 00]. Due to the NP-Hard nature of pattern discovery, various heuristics are employed in pattern discovery algorithms s ..."
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such as Teiresias. This paper explores the effects of varying parameter settings in Teiresias in terms of the patterns that are discovered in yeast cell cycle data. A metric that relates execution time to proportion of patterns discovered is developed and used to determine that Teiresias is most efficient

Research Article The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan

by Hung-chang Liao, Meng-hao Chen, Ya-huei Wang
"... Copyright © 2014 Hung-Chang Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This study proposed the optimal parameter set ..."
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capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings

Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative

by Donald W. K. Andrews, Werner Ploberger , 1992
"... ..."
Abstract - Cited by 619 (11 self) - Add to MetaCart
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Optimal Brain Damage

by Yann Le Cun, John S. Denker, Sara A. Sola , 1990
"... We have used information-theoretic ideas to derive a class of practical and nearly optimal schemes for adapting the size of a neural network. By removing unimportant weights from a network, several improvements can be expected: better generalization, fewer training examples required, and improved sp ..."
Abstract - Cited by 510 (5 self) - Add to MetaCart
We have used information-theoretic ideas to derive a class of practical and nearly optimal schemes for adapting the size of a neural network. By removing unimportant weights from a network, several improvements can be expected: better generalization, fewer training examples required, and improved

Some optimal inapproximability results

by Johan Håstad , 2002
"... We prove optimal, up to an arbitrary ffl? 0, inapproximability results for Max-Ek-Sat for k * 3, maximizing the number of satisfied linear equations in an over-determined system of linear equations modulo a prime p and Set Splitting. As a consequence of these results we get improved lower bounds for ..."
Abstract - Cited by 751 (11 self) - Add to MetaCart
We prove optimal, up to an arbitrary ffl? 0, inapproximability results for Max-Ek-Sat for k * 3, maximizing the number of satisfied linear equations in an over-determined system of linear equations modulo a prime p and Set Splitting. As a consequence of these results we get improved lower bounds

Global Optimization with Polynomials and the Problem of Moments

by Jean B. Lasserre - SIAM JOURNAL ON OPTIMIZATION , 2001
"... We consider the problem of finding the unconstrained global minimum of a real-valued polynomial p(x) : R R, as well as the global minimum of p(x), in a compact set K defined by polynomial inequalities. It is shown that this problem reduces to solving an (often finite) sequence of convex linear ma ..."
Abstract - Cited by 577 (48 self) - Add to MetaCart
We consider the problem of finding the unconstrained global minimum of a real-valued polynomial p(x) : R R, as well as the global minimum of p(x), in a compact set K defined by polynomial inequalities. It is shown that this problem reduces to solving an (often finite) sequence of convex linear
Results 1 - 10 of 143,082