in view of native/nonnative language teacher dichotomy, different characteristics have been assigned to these 2 groups. the dichotomy has been the source of different actions and measures to clarify the positive and negative points of being (non)native teachers. in recent years, many researchers have revisited this dichotomy. the challenge to the dichotomy can be a source of motivation to explo...

With the recent rapid progress of network technology, researchers have attempted to adopt artificial intelligence and use computer networks to develop adaptive hypermedia systems. The idea of adaptive hypermedia is to adapt the course content for a particular learner based on the profile or records of the learner. Meanwhile, researchers have also attempted to develop more effective programs to ...

Recently, e-learning has been paid much attention in the area of education. However, it is difficult for the low-achievement students to find out the key points and keywords while searching online articles. They usually cannot accurately obtain the website information even after searching for large amount of data in the Internet. Meanwhile, these low-achievement students often lack of the relat...

As an alternative to classical representations in machine learning algorithms, we explore coding strategies using events as is observed for spiking neurons in the central nervous system. Focusing on visual processing, we have previously shown that we may define a sparse spike coding scheme by implementing accordingly lateral interactions [14]. This class of algorithms is both compatible with bi...

Supervised learning of classifiers often resorts to the minimization of a quadratic error, even if this criterion is more especially matched to nonlinear regression problems. It is shown that the mapping built by a quadratic error minimization (QEM) tends to output the Bayesian discriminating rules even with nonuniform losses, provided the desired responses are chosen accordingly. This property...

Metric learning algorithms produce a linear transformation of data which is optimized for a prediction task, such as nearest-neighbor classification or ranking. However, when the input data contains a large portion of noninformative features, existing methods fail to identify the relevant features, and performance degrades accordingly. In this paper, we present an efficient and robust structura...

With the ever-increasing role of technology as an innovative force in society, we have witnessed major changes in the types of education being developed and in how learning and instruction is conceptualised. Consider, for example, the dramatic rise in the number of Internet-based courses offered in higher education as well as the evolving role of the teacher as creator of learning environments....

This paper presents a Bayesian additive “correction” to the familiar quadratic loss biasplus-variance formula. It then discusses some other loss-function-specific aspects of supervised learning. It ends by presenting a version of the bias-plus-variance formula appropriate for log loss, and then the Bayesian additive correction to that formula. Both the quadratic loss and log loss correction ter...