Related papers: A MST algorithm for source detection in gamma-ray …
In the manifold learning problem one seeks to discover a smooth low dimensional surface, i.e., a manifold embedded in a higher dimensional linear vector space, based on a set of measured sample points on the surface. In this paper we…
We present a new method to detect and quantify mass segregation in star clusters. It compares the minimum spanning tree (MST) of massive stars with that of random stars. If mass segregation is present, the MST length of the most massive…
We studied the problematic of uncertainties in the diffuse gamma radiation apparent in stacking analysis of EGRET data at low Galactic latitudes. Subsequently, we co-added maps of counts, exposure and diffuse background, and residuals, in…
The light we receive from distant astrophysical objects carries information about their origins and the physical mechanisms that power them. The study of these signals, however, is complicated by the fact that observations are often a…
A large fraction of the detections to be made by the Gamma-ray Large Area Space Telescope (GLAST) will initially be unidentified. We argue that traditional methodological approaches to identify individuals and/or populations of $\gamma$-ray…
We present a stacking method that makes use of co-added maps of gamma-ray counts produced from data taken with the Fermi Large Area Telescope. Sources with low integrated gamma-ray fluxes that are not detected individually may become…
Processing graphs with temporal information (the temporal graphs) has become increasingly important in the real world. In this paper, we study efficient solutions to temporal graph applications using new algorithms for Incremental Minimum…
We propose a new method for clustering based on the local minimization of the \gamma-divergence, which we call the spontaneous clustering. The greatest advantage of the proposed method is that it automatically detects the number of clusters…
Despite rapid progress in scene segmentation in recent years, 3D segmentation methods are still limited when there is severe occlusion. The key challenge is estimating the segment boundaries of (partially) occluded objects, which are…
Given a set of points in the Euclidean plane, the Euclidean \textit{$\delta$-minimum spanning tree} ($\delta$-MST) problem is the problem of finding a spanning tree with maximum degree no more than $\delta$ for the set of points such the…
We study the minimum spanning tree (MST) problem in the massively parallel computation (MPC) model. Our focus is particularly on the *strictly sublinear* regime of MPC where the space per machine is $O(n^\delta)$. Here $n$ is the number of…
This paper revisits the 2-approximation algorithm for $k$-MST presented by Garg in light of a recent paper of Paul et al.. In the $k$-MST problem, the goal is to return a tree spanning $k$ vertices of minimum total edge cost. Paul et al.…
We study the potential of weak lensing surveys to detect clusters of galaxies, using a fast Particle Mesh cosmological N-body simulation algorithm specifically tailored to investigate the statistics of these mass-selected clusters. In…
Young stellar clusters harbour complex spatial structures emerging from the star formation process. Identifying stellar over-densities is a key step to constrain better how these structures are formed. The high accuracy of distances derived…
Now a days many algorithms are invented or being inventing to find the solution for Euclidean Minimum Spanning Tree, EMST, problem, as its applicability is increasing in much wide range of fields containing spatial or spatio temporal data…
We present a multi-scale, multi-wavelength source extraction algorithm called getsources. Although it has been designed primarily for use in the far-infrared surveys of Galactic star-forming regions with Herschel, the method can be applied…
Spectral clustering is one of the most prominent clustering approaches. The distance-based similarity is the most widely used method for spectral clustering. However, people have already noticed that this is not suitable for multi-scale…
This paper introduces the use of pseudo-filters that optimize the detection/extraction of sources on a background. We assume as a first approach that such sources are described by a spherical (central) profile and that the background is…
Algorithms for dynamically maintaining minimum spanning trees (MSTs) have received much attention in both the parallel and sequential settings. While previous work has given optimal algorithms for dense graphs, all existing parallel…
In collaboration with the Observatories of Palermo and Rome and the SAX-SDC we are constructing a multi-site interactive archive system featuring specific analysis tools. In this context we developed a detection algorithm based on the…