k-Means is a well-studied clustering problem that finds applications in many fields related to
unsupervised learning. It is known that k-means clustering is highly sensitive to the isolated …

With the knowledge of molecular biology it is highlighting that long non-coding RNAs (lncRNAs)
play a critical role in many important biological processes, such as imprinting control, …

In this paper, we study the $ k $-clustering problems with outliers in distributed setting. The
current best results for the distributed $ k $-center problem with outliers have quadratic local …

The clustering problem has been paid lots of attention in various fields of compute science.
However, in many applications, the existence of noisy data poses a big challenge for the …

In this paper, we study the following Minimum Cost Multicovering (MCMC) problem: Given a
set of \(n\) client points \(C\) and a set of \(m\) server points \(S\) in a fixed dimensional \(\…

In this paper, we present a framework for designing FPT approximation algorithms for many
k-clustering problems. Our results are based on a new technique for reducing search spaces…

The k-means problem has been paid lots of attention in many fields, and each cluster of the
k-means problem always satisfies locality property. In this paper, we study the constrained k-…

Clustering is a fundamental problem in computer science and finds applications in a wide
42 range of domains. Depending on the objective function, it has many different variants. …

The alkylation of benzene with long chain α‐olefins is a crucial process in the production of
fine chemicals, which requires the upgrading from traditional homogeneous catalysis to …

In this paper, we study the Parameterized $$P_2$$ P 2 -Packing problem and Parameterized
Co-Path Packing problem from random perspective. For the Parameterized $$P_2$$ P 2 -…