Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing

Advancements in deep learning are often associated with increasing model sizes. The model size dramatically affects the deployment cost and latency of deep models. For instance, models like BERT cannot be deployed on edge devices and mobiles due to their sheer size. As a result, most advances in Deep Learning are yet to reach the edge. Model compression has sought much-deserved attention in literature across natural language processing, vision, and recommendation domains. This paper proposes a model-agnostic, cache-friendly model compression approach: Random Operation Access Specific Tile (ROAST) hashing. ROAST collapses the parameters by clubbing them through a lightweight mapping. Notably, while clubbing these parameters, ROAST utilizes cache hierarchies by aligning the memory access pattern with the parameter access pattern. ROAST is up to $\sim 25 \times$ faster to train and $\sim 50 \times$ faster to infer than the popular parameter sharing method HashedNet. Additionally, ROAST introduces global weight sharing, which is empirically and theoretically superior to local weight sharing in HashedNet, and can be of independent interest in itself. With ROAST, we present the first compressed BERT, which is $100\times - 1000\times$ smaller but does not result in quality degradation. These compression levels on universal architecture like transformers are promising for the future of SOTA model deployment on resource-constrained devices like mobile and edge device

Light Field Salient Object Detection: A Review and Benchmark

Salient object detection (SOD) is a long-standing research topic in computer vision and has drawn an increasing amount of research interest in the past decade. This paper provides the first comprehensive review and benchmark for light field SOD, which has long been lacking in the saliency community. Firstly, we introduce preliminary knowledge on light fields, including theory and data forms, and then review existing studies on light field SOD, covering ten traditional models, seven deep learning-based models, one comparative study, and one brief review. Existing datasets for light field SOD are also summarized with detailed information and statistical analyses. Secondly, we benchmark nine representative light field SOD models together with several cutting-edge RGB-D SOD models on four widely used light field datasets, from which insightful discussions and analyses, including a comparison between light field SOD and RGB-D SOD models, are achieved. Besides, due to the inconsistency of datasets in their current forms, we further generate complete data and supplement focal stacks, depth maps and multi-view images for the inconsistent datasets, making them consistent and unified. Our supplemental data makes a universal benchmark possible. Lastly, because light field SOD is quite a special problem attributed to its diverse data representations and high dependency on acquisition hardware, making it differ greatly from other saliency detection tasks, we provide nine hints into the challenges and future directions, and outline several open issues. We hope our review and benchmarking could help advance research in this field. All the materials including collected models, datasets, benchmarking results, and supplemented light field datasets will be publicly available on our project site https://github.com/kerenfu/LFSOD-Survey

Optimizing a Polynomial Function on a Quantum Simulator

Gradient descent method, as one of the major methods in numerical optimization, is the key ingredient in many machine learning algorithms. As one of the most fundamental way to solve the optimization problems, it promises the function value to move along the direction of steepest descent. For the vast resource consumption when dealing with high-dimensional problems, a quantum version of this iterative optimization algorithm has been proposed recently[arXiv:1612.01789]. Here, we develop this protocol and implement it on a quantum simulator with limited resource. Moreover, a prototypical experiment was shown with a 4-qubit Nuclear Magnetic Resonance quantum processor, demonstrating a optimization process of polynomial function iteratively. In each iteration, we achieved an average fidelity of 94\% compared with theoretical calculation via full-state tomography. In particular, the iterative point gradually converged to the local minimum. We apply our method to multidimensional scaling problem, further showing the potentially capability to yields an exponentially improvement compared with classical counterparts. With the onrushing tendency of quantum information, our work could provide a subroutine for the application of future practical quantum computers.Comment: 6+4 pages, 8 figure

Post-disaster assessment of 2017 catastrophic Xinmo landslide (China) by spaceborne SAR interferometry

Timely and effective post-disaster assessment is of significance for the design of rescue plan, taking disaster mitigation measures and disaster analysis. Field investigation and remote sensing methods are the common ways to perform post-disaster assessment, which are usually limited by dense cloud coverage, potential risk, and tough transportation etc. in the mountainous area. In this paper, we employ the 2017 catastrophic Xinmo landslide (Sichuan, China) to demonstrate the feasibility of using spaceborne synthetic aperture radar (SAR) data to perform timely and effective post-disaster assessment. With C-band Sentinel-1 data, we propose to combine interferometric coherence to recognize the stable area, which helps us successfully identify landslide source area and boundaries in a space-based remote sensing way. Complementarily, X-band TanDEM-X SAR data allow us to generate a precise pre-failure high-resolution digital elevation model (DEM), which provides us the ability to accurately estimate the depletion volume and accumulation volume of Xinmo landslide. The results prove that spaceborne SAR can provide a quick, valuable, and unique assistance for post-disaster assessment of landslides from a space remote sensing way. At some conditions (bad weather, clouds, etc.), it can provide reliable alternative.This work was funded by Sichuan Science and Technology Plan Key Research and Development Program (Grant No. 2018SZ0339), National Natural Science Foundation of China (Grant No. 41801391), State Key Laboratory of Geodesy and Earth’s Dynamics Open fund (Grant No. SKLGED2018-5-3-E), The Funds for Creative Research Groups of China (Grant No. 41521002) and partially supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI), and European Funds for Regional Development (FEDER), under project TIN2014-55413-C2-2-P and by the Spanish Ministry of Education, Culture and Sport, under project PRX17/00439. This work was also supported by the National Environment Research Council (NERC) through the Centre for the Observation and Modeling of Earthquakes, Volcanoes and Tectonics (COMET, ref.: come30001), the LiCS project (ref. NE/K010794/1), the ESA-MOST DRAGON-4 project (ref. 32244), and the Hunan Province Key Laboratory of Coal Resources Clean-Utilization and Mine Environment Protection, Hunan University of Science and Technology (Ref. E21608)

Synthesis and pinning properties of the infinite-layer superconductor Sr0.9La0.1CuO

We report the high-pressure synthesis of the electron-doped infinite-layer superconductor Sr0.9La0.1CuO2 and its superconducting properties. A Rietveld analysis of X-ray powder diffraction data showed that, within the resolution of the measurement, the sample had purely an infinite-layer structure without any discernible impurities. The superconducting volume fraction and the transition width were greatly improved compared to those in previous reports. The irreversibility field line and the intragranular critical current density were much higher than those of La1.85Sr0.15CuO4 and Nd1.85Ce0.15CuO4. The stronger pinning behaviors are consistent with the strong interlayer coupling due to the short distance between CuO2 planes.Comment: Physica C (in press) 5 pages, 4 figur

Email for communicating results of diagnostic medical investigations to patients

<p>Background: As medical care becomes more complex and the ability to test for conditions grows, pressure on healthcare providers to convey increasing volumes of test results to patients is driving investigation of alternative technological solutions for their delivery. This review addresses the use of email for communicating results of diagnostic medical investigations to patients.</p> <p>Objectives: To assess the effects of using email for communicating results of diagnostic medical investigations to patients, compared to SMS/ text messaging, telephone communication or usual care, on outcomes, including harms, for health professionals, patients and caregivers, and health services.</p> <p>Search methods: We searched: the Cochrane Consumers and Communication Review Group Specialised Register, Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 1 2010), MEDLINE (OvidSP) (1950 to January 2010), EMBASE (OvidSP) (1980 to January 2010), PsycINFO (OvidSP) (1967 to January 2010), CINAHL (EbscoHOST) (1982 to February 2010), and ERIC (CSA) (1965 to January 2010). We searched grey literature: theses/dissertation repositories, trials registers and Google Scholar (searched July 2010). We used additional search methods: examining reference lists and contacting authors.</p> <p>Selection criteria: Randomised controlled trials, quasi-randomised trials, controlled before and after studies and interrupted time series studies of interventions using email for communicating results of any diagnostic medical investigations to patients, and taking the form of 1) unsecured email 2) secure email or 3) web messaging. All healthcare professionals, patients and caregivers in all settings were considered.</p> <p>Data collection and analysis: Two review authors independently assessed the titles and abstracts of retrieved citations. No studies were identified for inclusion. Consequently, no data collection or analysis was possible.</p> <p>Main results: No studies met the inclusion criteria, therefore there are no results to report on the use of email for communicating results of diagnostic medical investigations to patients.</p> <p>Authors' conclusions: In the absence of included studies, we can draw no conclusions on the effects of using email for communicating results of diagnostic medical investigations to patients, and thus no recommendations for practice can be stipulated. Further well-designed research should be conducted to inform practice and policy for communicating patient results via email, as this is a developing area.</p&gt