Subhabrata Majumdar

TL;DR: Experimental results show that the use of privacy budget could be reduced by 3 to 4 orders of magnitude for Influential node analysis and increase accuracy up to 12% for Decision tree induction when compared to global sensitivity based approaches.

TL;DR: In this article, the authors show that these clusters can be used as an ensemble of rulers to estimate the angular diameter distance, which comes at no extra observational cost, as these clusters form a subset of a much larger sample, assembled to build cluster number counts, and they show that using this ${d}_{\mathrm{A}}(z)$ the dark energy constraints can be improved by factors of 1.5-4, over those from just $\frac{dN}{dz}$.

TL;DR: In this article, the authors review the current understanding of active galactic nuclei (AGN) feedback, its cosmological implications and the impact that SKA can have in revolutionizing our understanding of AGN feedback in large-scale structures.

TL;DR: The amount and nature of dark energy can be tightly constrained by measuring the spatial correlation features and evolution of a sample of ~ 100,000 galaxy clusters over the redshift range 0