Kharizmi helped solidify the concept of algorithms in mathematics and popularized algebra and the use of the zero.

To address the issues of feature mismatching and map overlap drift in simultaneous localization and mapping (SLAM) within degraded environments characterized by sparse geometric features or severe ...

Abstract: In a recent paper, we developed a novel quantized kernel least mean square algorithm, in which the input space is quantized (partitioned into smaller regions) and the network size is upper ...

A total of 241 patients collected from the two centers were included in the study, of which 145 patients from the First Affiliated Hospital of Guangzhou Medical University were divided into training ...

Note: Nonnegative Matrix Factorization is an area of active research. New algorithms are proposed every year. Contributions are very welcomed. Most types and functions (except the high-level function ...

Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of ...

This paper presents a recursive feature elimination (RFE) mechanism to select the most informative genes with a least square kernel extreme learning machine (LSKELM) classifier. Describing the ...

Abstract: There are different strategies to improve the overall performance of the recursive least-squares (RLS) adaptive filter. In this letter, we focus on the data-reuse approach, aiming to improve ...

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