Iterative Row Sampling

There has been significant interest and progress recently in algorithms that solve regression problems involving tall and thin matrices in input sparsity time. These algorithms find shorter equivalent of a n*d matrix where n >> d, which allows one to solve a poly(d) sized problem instead. In practice, the best performances are often obtained by invoking these routines in an iterative fashion. We show these iterative methods can be adapted to give theoretical guarantees comparable and better than the current state of the art. Our approaches are based on computing the importances of the rows, known as leverage scores, in an iterative manner. We show that alternating between computing a short matrix estimate and finding more accurate approximate leverage scores leads to a series of geometrically smaller instances. This gives an algorithm that runs in $O(nnz(A) + d^{\omega + \theta} \epsilon^{-2})$ time for any $\theta > 0$, where the $d^{\omega + \theta}$ term is comparable to the cost of solving a regression problem on the small approximation. Our results are built upon the close connection between randomized matrix algorithms, iterative methods, and graph sparsification.Comment: 26 pages, 2 figure

Decreased sensitivity to aspirin is associated with altered polyamine metabolism in human prostate cancer cells

Acknowledgments We thank NHS Grampian for financial support of this work.Peer reviewedPublisher PD

Let Google index your media fragments

Current multimedia applications in Web 2.0 have generated a massive amount of multimedia resources, but most search results for multimedia resources still focus on the whole re-source level. Media fragments expose the inside content of multimedia resources for annotations, but they are yet fully explored and indexed by major search engines. W3C has published Media Fragment 1.0 as a standard way to describe media fragments on the Web. In this proposal, we make use of Google's Ajax Application Crawler to index media fragments represented by Media Fragment URIs. Each media fragment with related annotations will have an individual snapshot page, which could be indexed by the crawler. Initial evaluation has shown that the snapshot pages are successfully fetched by Googlebot and we are expecting more media fragments to be indexed using this method, so that the search for multimedia resources would be more efficient

Creating enriched YouTube media fragments With NERD using timed-text

This demo enables the automatic creation of semantically annotated YouTube media fragments. A video is first ingested in the Synote system and a new method enables to retrieve its associated subtitles or closed captions. Next, NERD is used to extract named entities from the transcripts which are then temporally aligned with the video. The entities are disambiguated in the LOD cloud and a user interface enables to browse through the entities detected in a video or get more information. We evaluated our application with 60 videos from 3 YouTube channels

Stabilization of a Swept-Wing Boundary Layer by Discrete Roughness Elements at High Reynolds Numbers

Direct numerical simulations (DNS) are performed to study potential stabilizing ef- fect of spanwise periodic discrete roughness elements (DREs) on cross ow instabilities in a spatially developing three-dimensional boundary layer over an in nite-swept natural- laminar- ow wing at a freestream Mach number of 0:75 and a chord Reynolds number of approximately 25 million. In the DNS, both the spanwise periodic DREs and distributed roughness in the leading-edge region are implemented to simulate a typical experimen- tal scenario in which multiple steady cross ow modes including the most unstable mode (i.e., the \target" mode) emerge because of the presence of naturally distributed surface roughness in the leading edge region and spanwise periodic control cylinders of subcritical wavelength are used to force small-wavelength disturbances (i.e., the control mode) for damping the target mode. The DNS results show that the e ectiveness of DRE control is sensitive to roughness diameter, height, and chordwise placement. For the DRE parame- ters considered in this study, the stabilizing e ect on the target mode is small within the computational domain that ended at about 35% of the chord