Sub-sampled newton methods i: Globally convergent algorithms. arXiv preprint arXiv:1601.04737, 2016a.Farbod Roosta-Khorasani and Michael W Mahoney. Sub-sampled Newton methods I: globally convergent algorithms. arXiv preprint arXiv:1601.04737, 2016....
(Linear Programming), when it is considered in the sampled-mode control. In this case, if we take the sampling-interval small, then a solution, which is given by this sampled-mode system, will be available as the first approximation of a solution of the continuous system. Therefore, by ...
The details of the AIMC simulations are described in the Methods section and SI. Using the AIMC scheme, 105 geometries for each com- plex were sampled and the effects of thermal fluctuation were taken into account. In Fig. 4, it is shown that the O/OH adsorption 1.5 eV. In the ...
2(b)) to assess whether the FPM reconstruction methods could converge with under-sampling to achieve the highest SBP. Comparison of FPM reconstruction techniques for bayer images Sparsely-sampled reconstruction has been shown to be effective for aliased images with 75% sparsity23, offering an ...
Methods Research partners The study was coordinated by the Shoklo Malaria Research Unit, Faculty of Tropical Medicine, Mahidol University in Mae Sot (Thailand). Other consortium members and partners included in Cambodia, the Institut Pasteur and the National Centre for Parasitology, Entomology and Mala...
In: Field theory and non-equilibriumstatistical mechanics” lectures given by John Cardy at the LMS/EPSRC “methods of non-equilibrium statistical mechanics in turbulence” school, University of Warwick from 10-14 July (2006) Anderson, P.W.: Plasmons, Gauge Invariance, and Mass. Phys. Rev. ...
sub-sampled Newton methodvariance reductionlinear convergenceStochastic optimization on large-scale machine learning problems has been developed dramatically since stochastic gradient methods with variance reduction technique were introduced. Several stochastic second-order methods, which approximate curvature ...
sub-sampled Newton methodvariance reductionlinear convergenceStochastic optimization on large-scale machine learning problems has been developed dramatically since stochastic gradient methods with variance reduction technique were introduced. Several stochastic second-order methods, which approximate curvature ...
In the present study, methods to enhance the oxygen reduction reaction (ORR) activity of sub-nanosized Pt clusters were investigated in a theoretical manner. Using ab initio molecular dynamics and Monte Carlo simulations based on density functional theory, we have succeeded in determining the origin...
sampled in steps of 80 nm, with each field of view measuring 170 × 170 μm2. At each z-position, epi-fluorescence imaging was also performed to reveal the DAPI-stained nuclei (Fig.6a). Following the same training procedure as before, we found that PICS can infer the nuclear map ...