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Constrained implicit function fitting
[1992] Proceedings. 11th IAPR International Conference on Pattern Recognition, 2003Describes techniques for stabilizing the implicit function fitting process. The key drawback of implicit function fitting methods described in literature thus far has been the stability with respect to outliners in the data. In this paper methods for stabilizing the implicit function fitting using additional constraints in the form of surface (curve ...
G. Taubin, R.M. Bolle, B.C. Vemuri
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2016
This chapter focuses on the fitness-contribution theory of function, which holds, roughly, that the function of a trait consists in its typical contribution to the fitness of the organisms that possess it. I begin by surveying several different theories within this family, and I show why any plausible version must include a statistical element.
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This chapter focuses on the fitness-contribution theory of function, which holds, roughly, that the function of a trait consists in its typical contribution to the fitness of the organisms that possess it. I begin by surveying several different theories within this family, and I show why any plausible version must include a statistical element.
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Measurement and Fitness Function
2015One of the greatest challenges in Evolvable Hardware—in particular when dealing with intrinsic evolution—is to monitor and assess the performance of an (evolving) circuit or system in order to arrive at a solution that ultimately meets the design specifications.
Martin A. Trefzer, Andy M. Tyrrell
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Boolean Functions Fitness Spaces
1999We investigate the distribution of performance of the Boolean functions of 3 Boolean inputs (particularly that of the parity functions), the always-on-6 and even-6 parity functions. We use enumeration, uniform Monte-Carlo random sampling and sampling random full trees. As expected XOR dramatically changes the fitness distributions.
W. B. Langdon, R. Poli
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Fitting of multivariate functions
Proceedings of the IEEE, 1987This research presents a nonparametric algorithm for fitting of a multivariate function from noisy data. Conditions are provided that assure local and global convergence in probability. Suggestions are stated for practical use of the algorithm.
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2011
Institutions of higher education are not like corporations: they have multiple goals, not even limited to the central ones of teaching and research, nor are they organized hierarchically. One class of leading inhabitants, faculty members, are a cross between independent contractors and employees; another class, administrators, are a cross between ...
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Institutions of higher education are not like corporations: they have multiple goals, not even limited to the central ones of teaching and research, nor are they organized hierarchically. One class of leading inhabitants, faculty members, are a cross between independent contractors and employees; another class, administrators, are a cross between ...
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2002
In this paper we define and study a class of functional tests of fit. These smooth tests are associated with projection density estimators. The Pearson’s X2-test belongs to this class since it is associated with the histogram.
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In this paper we define and study a class of functional tests of fit. These smooth tests are associated with projection density estimators. The Pearson’s X2-test belongs to this class since it is associated with the histogram.
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1998
Genetic algorihtms (GA) are supposed to suceed through the use of ‘implicit parallelism’ and ‘building blocks’. Given these properties, we can create rules for constructing GA-optimal fitness functions. Some of these rules are also relevant to evolutionary programming and evolution strategies searches.
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Genetic algorihtms (GA) are supposed to suceed through the use of ‘implicit parallelism’ and ‘building blocks’. Given these properties, we can create rules for constructing GA-optimal fitness functions. Some of these rules are also relevant to evolutionary programming and evolution strategies searches.
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Functional nanoparticles through π-conjugated polymer self-assembly
Nature Reviews Materials, 2020Liam R Macfarlane +2 more
exaly