Y.-T. Liu, G. Mayer-Kress. and K. M. Newell (2003) fit learning curves to movement time data and suggested 2 new methods for analyzing learning. They claimed that the methods go "beyond curve fitting.' However, in neither their curve fitting nor their new methods is measurement noise accounted for, and therefore they produce inefficient and biased results. Using the data of Liu et al., in which variance caused by learning is small relative to the level of noise for most participants, the present authors demonstrate those problems and provide better alternatives that are more noise tolerant, more powerful, and go beyond curve fitting without displaying the extreme bias produced by the methods of Liu et al
In a recent paper, Flament et al. studied the process of learning to flex the elbow faster. They con...
Three factors enter into analyses of performance curves such as learning curves: the amount of train...
Part 9: Pattern RecognitionInternational audienceThis article describes a Bayesian-based method for ...
Learning-curve models fitted to initial data are used to predict subsequent performance; however, th...
A learning curve displays the measure of accuracy/error on test data of a machine learning algorithm...
Penultimate draft, accepted, BRMIC We examine recent concerns that averaged learning curves can pres...
The learning curve illustrates how the generalization performance of the learner evolves with more t...
Estimation of learning curves is ubiquitously based on proportions of correct responses within movin...
Extrapolation of the learning curve provides an estimation of how much data is needed to achieve the...
Estimation of learning curves is ubiquitously based on proportions of correct responses within movin...
Plotting a learner's generalization performance against the training set size results in a so-called...
Estimation of learning curves is ubiquitously based on proportions of correct responses within movin...
This paper highlights, both analytically and by simulations, some interesting phenomena regarding th...
This is a commentary on Barth and Paladino (2011). Barth and Paladino (2011) argue that changes in n...
Nowadays, the increasing competitiveness inside the markets has ended up in a huge necessity by comp...
In a recent paper, Flament et al. studied the process of learning to flex the elbow faster. They con...
Three factors enter into analyses of performance curves such as learning curves: the amount of train...
Part 9: Pattern RecognitionInternational audienceThis article describes a Bayesian-based method for ...
Learning-curve models fitted to initial data are used to predict subsequent performance; however, th...
A learning curve displays the measure of accuracy/error on test data of a machine learning algorithm...
Penultimate draft, accepted, BRMIC We examine recent concerns that averaged learning curves can pres...
The learning curve illustrates how the generalization performance of the learner evolves with more t...
Estimation of learning curves is ubiquitously based on proportions of correct responses within movin...
Extrapolation of the learning curve provides an estimation of how much data is needed to achieve the...
Estimation of learning curves is ubiquitously based on proportions of correct responses within movin...
Plotting a learner's generalization performance against the training set size results in a so-called...
Estimation of learning curves is ubiquitously based on proportions of correct responses within movin...
This paper highlights, both analytically and by simulations, some interesting phenomena regarding th...
This is a commentary on Barth and Paladino (2011). Barth and Paladino (2011) argue that changes in n...
Nowadays, the increasing competitiveness inside the markets has ended up in a huge necessity by comp...
In a recent paper, Flament et al. studied the process of learning to flex the elbow faster. They con...
Three factors enter into analyses of performance curves such as learning curves: the amount of train...
Part 9: Pattern RecognitionInternational audienceThis article describes a Bayesian-based method for ...