AI Chat AI Image Generator AI Video Text to Speech

A computationally and cognitively plausible model of supervised and unsupervised learning

10/11/2020

∙

by David M. W. Powers, et al.

∙

∙

Both empirical and mathematical demonstrations of the importance of chance-corrected measures are discussed, and a new model of learning is proposed based on empirical psychological results on association learning. Two forms of this model are developed, the Informatron as a chance-corrected Perceptron, and AdaBook as a chance-corrected AdaBoost procedure. Computational results presented show chance correction facilitates learning.

research

∙ 08/17/2022

Convergence of a class of high order corrected trapezoidal rules

We present convergence theory for corrected quadrature rules on uniform ...

0 Federico Izzo, et al. ∙

research

∙ 02/11/2020

A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data

A novel correction algorithm is proposed for multi-class classification ...

0 Jun Hou, et al. ∙

research

∙ 08/26/2020

Improved estimators in beta prime regression models

In this paper, we consider the beta prime regression model recently prop...

0 Francisco M. C. Medeiros, et al. ∙

research

∙ 04/23/2020

Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models

This paper provides general expression for Bartlett and Bartlett-type co...

0 Mariana C. Araújo, et al. ∙

research

∙ 02/26/2020

A corrected decoupled scheme for chemotaxis models

The main purpose of this paper is to present a new corrected decoupled s...

0 M. Akhmouch, et al. ∙

research

∙ 11/09/2017

Toward perfect reads

We propose a new method to correct short reads using de Bruijn graphs, a...

0 Antoine Limasset, et al. ∙

research

∙ 02/22/2018

A new model for Cerebellar computation

The standard state space model is widely believed to account for the cer...

0 Reza Moazzezi, et al. ∙