Abstract Machine learning models always make a prediction, even when it is likely to be
inaccurate. This behavior should be avoided in many decision support applications, where …

This paper describes an ensemble feature identification algorithm called SEQENS, and
measures its capability to identify the relevant variables in a case-control study using a …

In this work, we define cost-free learning (CFL) formally in comparison with cost-sensitive
learning (CSL). The main difference between them is that a CFL approach seeks optimal …

With the acceleration of Information and Communication Technologies and the Internet-of-
Things paradigm, smart residential environments, also known as smart homes, are …

This paper deals with the identification and processing of struck-out texts in unconstrained
offline handwritten document images. If run on the OCR engine, such texts will produce …

In this paper, a new method is presented for recognizing the handwritten Farsi/Arabic digits
by fusing the recognition results of a number of Convolutional Neural Networks with gradient …

Human behavior gained much attention as a means of identifying a subject from the
dynamics of some of its signals. This produced challenging questions, opening a broad area …

Abstract Minimal Learning Machine (MLM) is a recently proposed supervised learning
algorithm with performance comparable to most state-of-the-art machine learning methods …

The presence of struck-out text in handwritten manuscripts may affect the accuracy of
automated writer identification. This paper presents a study on such effects of struck-out text …

Shows how genetic algorithmic methods can be used to solve air traffic control (ATC)
conflicts. They authors compare these methods,(in order to validate their solutions), to more …