A reversible infinite HMM using normalised random measures

We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected we define a prior over random walks on graphs that results in a reversible Markov chain. The resulting prior over infinite transition matrices is closely related to the hierarchical Dirichlet process but enforces reversibility. A reinforcement scheme has recently been proposed with similar properties, but the de Finetti measure is not well characterised. We take the alternative approach of explicitly constructing the mixing measure, which allows more straightforward and efficient inference at the cost of no longer having a closed form predictive distribution. We use our process to construct a reversible infinite HMM which we apply to two real datasets, one from epigenomics and one ion channel recording.Comment: 9 pages, 6 figure

SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases

The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the efficient alignment of large-scale knowledge bases still poses a considerable challenge. Here, we present Simple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts. SiGMa is an iterative propagation algorithm which leverages both the structural information from the relationship graph as well as flexible similarity measures between entity properties in a greedy local search, thus making it scalable. Despite its greedy nature, our experiments indicate that SiGMa can efficiently match some of the world's largest knowledge bases with high precision. We provide additional experiments on benchmark datasets which demonstrate that SiGMa can outperform state-of-the-art approaches both in accuracy and efficiency.Comment: 10 pages + 2 pages appendix; 5 figures -- initial preprin

NGC 3603 - a Local Template for Massive Young Clusters

We present a study of the star cluster associated with the massive Galactic HII region NGC3603 based on near-IR broad-- and narrowband observations taken with ISAAC/VLT under excellent seeing conditions (<0.4''). We discuss color-color diagrams and address the impact of the high UV flux on the disk evolution of the low-mass stars.Comment: 3 pages, 3 figures. To appear in the Proceedings of IAU Symposium 207 "Extragalactic Star Clusters", eds. E. Grebel, D. Geisler and D. Minitt

A Rich Population of X-ray Emitting Wolf-Rayet Stars in the Galactic Starburst Cluster Westerlund 1

Recent optical and IR studies have revealed that the heavily-reddened starburst cluster Westerlund 1 (Wd 1) contains at least 22 Wolf-Rayet (WR) stars, comprising the richest WR population of any galactic cluster. We present results of a senstive Chandra X-ray observation of Wd 1 which detected 12 of the 22 known WR stars and the mysterious emission line star W9. The fraction of detected WN stars is nearly identical to that of WC stars. The WN stars WR-A and WR-B as well as W9 are exceptionally luminous in X-rays and have similar hard heavily-absorbed spectra with strong Si XIII and S XV emission lines. The luminous high-temperature X-ray emission of these three stars is characteristic of colliding wind binary systems but their binary status remains to be determined. Spectral fits of the X-ray bright sources WR-A and W9 with isothermal plane-parallel shock models require high absorption column densities log N$_{H}$ = 22.56 (cm$^{-2}$) and yield characteristic shock temperatures kT_shock ~ 3 keV (T ~ 35 MK).Comment: ApJL, 2006, in press (3 figures, 1 table