Large Scale Visual Recommendations From Street Fashion Images

We describe a completely automated large scale visual recommendation system for fashion. Our focus is to efficiently harness the availability of large quantities of online fashion images and their rich meta-data. Specifically, we propose four data driven models in the form of Complementary Nearest Neighbor Consensus, Gaussian Mixture Models, Texture Agnostic Retrieval and Markov Chain LDA for solving this problem. We analyze relative merits and pitfalls of these algorithms through extensive experimentation on a large-scale data set and baseline them against existing ideas from color science. We also illustrate key fashion insights learned through these experiments and show how they can be employed to design better recommendation systems. Finally, we also outline a large-scale annotated data set of fashion images (Fashion-136K) that can be exploited for future vision research

MeerKLASS: MeerKAT Large Area Synoptic Survey

We discuss the ground-breaking science that will be possible with a wide area survey, using the MeerKAT telescope, known as MeerKLASS (MeerKAT Large Area Synoptic Survey). The current specifications of MeerKAT make it a great fit for science applications that require large survey speeds but not necessarily high angular resolutions. In particular, for cosmology, a large survey over $\sim 4,000 \, {\rm deg}^2$ for $\sim 4,000$ hours will potentially provide the first ever measurements of the baryon acoustic oscillations using the 21cm intensity mapping technique, with enough accuracy to impose constraints on the nature of dark energy. The combination with multi-wavelength data will give unique additional information, such as exquisite constraints on primordial non-Gaussianity using the multi-tracer technique, as well as a better handle on foregrounds and systematics. Such a wide survey with MeerKAT is also a great match for HI galaxy studies, providing unrivalled statistics in the pre-SKA era for galaxies resolved in the HI emission line beyond local structures at z > 0.01. It will also produce a large continuum galaxy sample down to a depth of about 5\,$\mu$Jy in L-band, which is quite unique over such large areas and will allow studies of the large-scale structure of the Universe out to high redshifts, complementing the galaxy HI survey to form a transformational multi-wavelength approach to study galaxy dynamics and evolution. Finally, the same survey will supply unique information for a range of other science applications, including a large statistical investigation of galaxy clusters as well as produce a rotation measure map across a huge swathe of the sky. The MeerKLASS survey will be a crucial step on the road to using SKA1-MID for cosmological applications and other commensal surveys, as described in the top priority SKA key science projects (abridged).Comment: Larger version of the paper submitted to the Proceedings of Science, "MeerKAT Science: On the Pathway to the SKA", Stellenbosch, 25-27 May 201

New science on the Open Science Grid

The Open Science Grid (OSG) includes work to enable new science, new scientists, and new modalities in support of computationally based research. There are frequently significant sociological and organizational changes required in transformation from the existing to the new. OSG leverages its deliverables to the large-scale physics experiment member communities to benefit new communities at all scales through activities in education, engagement, and the distributed facility. This paper gives both a brief general description and specific examples of new science enabled on the OSG. More information is available at the OSG web site: www.opensciencegrid.org

Science Pipelines for the Square Kilometre Array

The Square Kilometre Array (SKA) will be both the largest radio telescope ever constructed and the largest Big Data project in the known Universe. The first phase of the project will generate on the order of 5 zettabytes of data per year. A critical task for the SKA will be its ability to process data for science, which will need to be conducted by science pipelines. Together with polarization data from the LOFAR Multifrequency Snapshot Sky Survey (MSSS), we have been developing a realistic SKA-like science pipeline that can handle the large data volumes generated by LOFAR at 150 MHz. The pipeline uses task-based parallelism to image, detect sources, and perform Faraday Tomography across the entire LOFAR sky. The project thereby provides a unique opportunity to contribute to the technological development of the SKA telescope, while simultaneously enabling cutting-edge scientific results. In this paper, we provide an update on current efforts to develop a science pipeline that can enable tight constraints on the magnetised large-scale structure of the Universe.Comment: Published in Galaxies, as part of a Special Issue on The Power of Faraday Tomograph