The problem of missing values has been a prominent area of research in recent years. They
may prove to be a huge obstacle during the analysis of data related to various domains …

Biological and artificial microswimmers often self-propel in external flows of vortical nature;
relevant examples include algae in small-scale ocean eddies, spermatozoa in uterine …

Abstract Human Activity Recognition (HAR) deals with the automatic recognition of physical
activities and plays a crucial role in healthcare and sports where wearable sensors and …

We propose in this paper a partial order framework for clustering incomplete data. The
paramount feature of this framework is that it spans over a partial order that can be …

Addressing missing values is a persistent challenge in the field of data mining. The
presence of incomplete data can significantly compromise the overall data quality …

Kernel functions have been used successfully in clustering algorithms to deal with the
separability of clusters efficiently. Bringing this idea to co-clustering, we propose two kernel …

In this emerging technological era, data is the new oil. For a long time, missing values in
data posed a huge challenge to machine learning, data statistics, data mining and other …

Idiomatic expressions are expressions that consist of a series of two or more words that have
a meaning that cannot be predicted from the meaning of the individual words that compose …

Data processing and optimization are two major challenges in data analysis such as
clustering. In practice, data often contains missing values that must be handled …