Learning Curves and the Parameter Maximum Performance
Limitations to maximum running speed on flat curves
... Introduction In nature, evasive maneuvers associated with high-speed predator/prey chases are often a priority in locomotor performance. For example, predators with faster straight-ahead running speeds cannot ...
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Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... three- parameter kappa distribution (K3D) introduced by Meilke ...for parameter estimation by the ME method in the K3D ...its performance com- pared to the ML method is also ...
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Evaluating the Performance of a Successive-Approximations Approach to Parameter Optimization in Maximum-Likelihood Phylogeny Estimation
... Almost all studies that estimate phylogenies from DNA sequence data under the maximum-likelihood (ML) criterion employ an approximate approach. Most commonly, model parameters are estimated on some initial ...
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A Comparison of Algorithms for Maximum Entropy Parameter Estimation
... In this paper, we have described experiments com- paring the performance of a number of different al- gorithms for estimating the parameters of a con- ditional ME model. The results show that vari- ants of ...
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Learning Curves of Harvester Operators
... Throughout the seasons there are also variations based on light, weight of roundwood and driving conditions. But there still are variations without an external influence factor. When a harvester operator starts his ...
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Performance of medical students on a virtual reality simulator for knee arthroscopy: an analysis of learning curves and predictors of performance
... We are aware of the potential limitations of this study. Although this study was prospectively conducted, the limited number of participants (n = 20) was possibly too small to detect subtle differences but did allow to ...
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Performance of medical students on a virtual reality simulator for knee arthroscopy: an analysis of learning curves and predictors of performance
... We are aware of the potential limitations of this study. Although this study was prospectively conducted, the limited number of participants (n = 20) was possibly too small to detect subtle differences but did allow to ...
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Approximating Learning Curves for Active-Learning-Driven Annotation
... trade-off between additional annotation costs and gain in classifier performance is falling below some threshold. For uncertainty-based AL, further stopping criteria employ- ing a confidence estimate of the ...
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Prediction of Learning Curves in Machine Translation
... predicting learning curves in realistic sce- ...modeling learning curves via an extensive empirical ...predict performance on a given test set with a root mean squared error in the ...
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Mixture Modeling of Individual Learning Curves
... and Performance Factors Analysis [16] use logistic regressions that include parameters for each skill involved in some ...by learning per-student initial mastery probabilities ...model performance on ...
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Semidefinite Programming for Approximate Maximum Likelihood Sinusoidal Parameter Estimation
... Figure 19: MSE for ω 2 of multiple complex sinusoids. differences between the lower and upper bounds are small, though equalities are replaced by positive semidefinite (PSD) constraints. While in the periodogram-based ...
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The Effects of Parameter Tuning on Machine Learning Performance in a Software Defect Prediction Context
... the performance of default tunings and the performance of many non-default ...The performance measures of the non-default tunings are somewhat protected by the law of large ...the performance ...
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Parameter Learning and the Carry Trade
... historical performance of the carry trade rules out stories of persistently biased agent ...gain learning means that even though beliefs about the growth rate of the economy are unconditionally unbiased, ...
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Targeted Maximum Likelihood Learning
... the parameter Ψ( p 0 ) for given parameter mappings Ψ : M → IR d ...the parameter of interest ψ 0 = Ψ( p 0 ...the parameter of ...based learning of smooth parameters of a density of a ...
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Designed for Maximum Accelerator Performance
... 1 Source: NVIDIA analysis of GPU-accelerated codes HPC Workloads The CS-Storm system is well suited for HPC workloads in the defense, oil and gas, financial services, life sciences and business intelligence sectors. ...
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Parameter estimation for a computable general equilibrium model: a maximum entropy approach
... Table 4 illustrates measures of goodness of fit for exports and imports by commodity. Performance in terms of correlation and R-squared varies substantially from more than 0.9 to negative values. For the major ...
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Using learning curves to mine student models
... the performance of each individual constraint over ...average performance of the constraint set as a whole over time, for which a learning curve can then be ...the learning curve for the ...
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Technology Learning Curves for Energy Policy Support
... through learning by doing (i.e. opening the ‘black box’ of learning curves) led to better replication of historic ...of learning by doing such as commodity prices; and that learning ...
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Bayesian Network Learning with Parameter Constraints
... their performance in the visual cortex ...the performance of ShHPM starts to degrade because it makes the biased assumption that all voxels in CALC can be described by a single shared hidden process ...in ...
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Four-parameter curves
... arclength [5]. The Euler spiral (or clothoid, as it is nearly universally known in that application domain) is popular in railroad track design. The linear change in curvature is desirably smooth on the interior of the ...
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