In this paper, we propose a physical informed neural network approach for designing the
electromagnetic metamaterial. The approach can be used to deal with various practical …

Gaussian mixture model (GMM) clustering has been extensively studied due to its
effectiveness and efficiency. Though demonstrating promising performance in various …

Clustering has been intensively studied in machine learning and data mining communities.
Although demonstrating promising performance in various applications, most of the existing …

A recommendation system is a program that utilizes techniques to suggest to a user items
that they would likely prefer. This paper focuses on an approach to improving music …

Hand gestures are the most common forms of communication and have great importance in
our world. They can help in building safe and comfortable user interfaces for a multitude of …

With the technical advances, the amount of big data is increasing day-by-day such that the
traditional software tools face a burden in handling them. Additionally, the presence of the …

Link prediction is the task of evaluating the probability that an edge exists in a network, and it
has useful applications in many domains. Traditional approaches rely on measuring the …

Paraphrase Identification or Natural Language Sentence Matching (NLSM) is one of the
important and challenging tasks in Natural Language Processing where the task is to …

Signaling pathways describe a group of molecules in a cell that collaborate to control one or
more cell functions, such as cell division or cell death. The pathways communicate by …

Ensemble methods for machine learning serve to increase the predictive power of
preexisting models by applying a meta-algorithm on top of the underlying workings of one or …