Related papers: Distant Cluster Search: Welcoming some Newcomers f…

We present a catalogue of 348 galaxy clusters and groups with $0.2<z<1.2$ selected in the 2.78 $deg^2$ ALHAMBRA Survey. The high precision of our photometric redshifts, close to $1\%$, and the wide spread of the seven ALHAMBRA pointings…

We present a modified version of the friends-of-friends (FOF) structure finding algorithm, designed specifically to locate groups or clusters of galaxies in photometric redshift datasets. The main objective of this paper is to show that…

We present a new (2+1)D galaxy cluster finder based on photometric redshifts called Wavelet Z Photometric (WaZP) applied to DES first year (Y1A1) data. The results are compared to clusters detected by the South Pole Telescope (SPT) survey…

The conventional clustering algorithms mine static databases and generate a set of patterns in the form of clusters. Many real life databases keep growing incrementally. For such dynamic databases, the patterns extracted from the original…

In this paper, we initiate the study of fair clustering that ensures distributional similarity among similar individuals. In response to improving fairness in machine learning, recent papers have investigated fairness in clustering…

We recently proposed a new ensemble clustering algorithm for graphs (ECG) based on the concept of consensus clustering. We validated our approach by replicating a study comparing graph clustering algorithms over benchmark graphs, showing…

We report on the progress of our search for serendipitous distant X-ray galaxy clusters in the ROSAT PSPC pointed observations archive. The initial aim of our work is to measure the X-ray luminosity function of clusters down to 4 x 10^-14…

We have created mock Sunyaev-Zel'dovich effect (SZE) surveys of galaxy clusters using high resolution N-body simulations. To the pure surveys we add `noise' contributions appropriate to instrument and primary CMB anisotropies. Applying…

We present a new algorithm to detect inter-cluster galaxy filaments based upon the assumption that the orientations of constituent galaxies along such filaments are non-isotropic. We apply the algorithm to the 2dF Galaxy Redshift Survey…

We report the first confirmation of colour-selected galaxy cluster candidates by means of weak gravitational lensing. Significant lensing signals were identified in the course of the shear-selection programme of dark matter haloes in the…

We present a catalog of galaxy clusters detected in a new ROSAT PSPC survey. The survey is optimized to sample, at high redshifts, the mass range corresponding to T> keV clusters at z=0. Technically, our survey is the extension of the 160…

We describe a new method (Poisson Probability Method, PPM) to search for high redshift galaxy clusters and groups by using photometric redshift information and galaxy number counts. The method relies on Poisson statistics and is primarily…

We discuss a method to build up and study a sample of distant galaxies, with 2<z<5, using the gravitational amplification effect in cluster-lenses for which the mass distribution is well known. The candidates are selected close to the…

The Red-Sequence Cluster Survey (RCS) is a $\sim$100 square degree, two-filter imaging survey in the $R_C$ and $z'$ filters, designed primarily to locate and characterise galaxy clusters to redshifts as high as $z=1.4$. This paper provides…

We present a new algorithm for locating a small cluster of points with differential privacy [Dwork, McSherry, Nissim, and Smith, 2006]. Our algorithm has implications to private data exploration, clustering, and removal of outliers.…

In order to enlarge publicly available optical cluster catalogs, in particular at high redshift, we have performed a systematic search for clusters of galaxies in the CFHTLS. We used the Le Phare photometric redshifts for the galaxies…

This paper introduces a novel asynchronous, event-driven algorithm for real-time detection of small event clusters in event camera data. Like other hierarchical agglomerative clustering algorithms, the algorithm detects the event clusters…

Finding a good clustering of vertices in a network, where vertices in the same cluster are more tightly connected than those in different clusters, is a useful, important, and well-studied task. Many clustering algorithms scale well,…

Context: The huge and still rapidly growing amount of galaxies in modern sky surveys raises the need of an automated and objective classification method. Unsupervised learning algorithms are of particular interest, since they discover…

The EM algorithm is one of many important tools in the field of statistics. While often used for imputing missing data, its widespread applications include other common statistical tasks, such as clustering. In clustering, the EM algorithm…