Learning Transferable Architectures for Scalable Image Recognition

Developing neural network image classification models often requires significant architecture engineering. In this paper, we study a method to learn the model architectures directly on the dataset of interest. As this approach is expensive when the dataset is large, we propose to search for an architectural building block on a small dataset and then transfer the block to a larger dataset. The key contribution of this work is the design of a new search space (the "NASNet search space") which enables transferability. In our experiments, we search for the best convolutional layer (or "cell") on the CIFAR-10 dataset and then apply this cell to the ImageNet dataset by stacking together more copies of this cell, each with their own parameters to design a convolutional architecture, named "NASNet architecture". We also introduce a new regularization technique called ScheduledDropPath that significantly improves generalization in the NASNet models. On CIFAR-10 itself, NASNet achieves 2.4% error rate, which is state-of-the-art. On ImageNet, NASNet achieves, among the published works, state-of-the-art accuracy of 82.7% top-1 and 96.2% top-5 on ImageNet. Our model is 1.2% better in top-1 accuracy than the best human-invented architectures while having 9 billion fewer FLOPS - a reduction of 28% in computational demand from the previous state-of-the-art model. When evaluated at different levels of computational cost, accuracies of NASNets exceed those of the state-of-the-art human-designed models. For instance, a small version of NASNet also achieves 74% top-1 accuracy, which is 3.1% better than equivalently-sized, state-of-the-art models for mobile platforms. Finally, the learned features by NASNet used with the Faster-RCNN framework surpass state-of-the-art by 4.0% achieving 43.1% mAP on the COCO dataset

Complete Integrability of Geodesic Motion in General Kerr-NUT-AdS Spacetimes

We explicitly exhibit n-1 constants of motion for geodesics in the general D-dimensional Kerr-NUT-AdS rotating black hole spacetime, arising from contractions of even powers of the 2-form obtained by contracting the geodesic velocity with the dual of the contraction of the velocity with the (D-2)-dimensional Killing-Yano tensor. These constants of motion are functionally independent of each other and of the D-n+1 constants of motion that arise from the metric and the D-n = [(D+1)/2] Killing vectors, making a total of D independent constants of motion in all dimensions D. The Poisson brackets of all pairs of these D constants are zero, so geodesic motion in these spacetimes is completely integrable.Comment: 4 pages. We have now found that the geodesic motion is not just integrable, but completely integrabl

Particle Motion and Scalar Field Propagation in Myers-Perry Black Hole Spacetimes in All Dimensions

We study separability of the Hamilton-Jacobi and massive Klein-Gordon equations in the general Myers-Perry black hole background in all dimensions. Complete separation of both equations is carried out in cases when there are two sets of equal black hole rotation parameters, which significantly enlarges the rotational symmetry group. We explicitly construct a nontrivial irreducible Killing tensor associated with the enlarged symmetry group which permits separation. We also derive first-order equations of motion for particles in these backgrounds and examine some of their properties.Comment: 16 pages, LaTeX2

Three AGN Close To The Effective Eddington Limit

The Effective Eddington Limit for dusty gas surrounding AGN is lower than the canonical Eddington limit for hydrogen gas. Previous results from the Swift/BAT 9-month catalogue suggested that in the overwhelming majority of local AGN, the dusty absorbing gas is below this Effective Eddington limit, implying that radiation pressure is insufficient to blow away the absorbing clouds. We present an analysis of three objects from that sample which were found to be close to the Effective Eddington limit (NGC454, 2MASX J03565655-4041453 and XSS J05054-2348), using newly obtained XMM-Newton data. We use the X-ray data to better constrain the absorbing column density, and supplement them with XMM optical monitor (OM) data, infrared Spitzer and Herschel data where available to construct a broad-band spectral energy distribution to estimate refined bolometric luminosities and Eddington ratios for these three objects. The new XMM-Newton observations show all three objects moving away from the region expected for short-lived absorption in the N_H-\lambda_{Edd} plane into the `long-lived absorption' region. We find our conclusions robust to different methods for estimating the bolometric luminosity and Eddington ratio. Interestingly, 2MASX J03565655-4041453 and XSS J05054-2348 now exhibit complex X-ray spectra, at variance with previous analyses of their Swift/XRT data. We find evidence for absorption variability in NGC 454 and 2MASX J03565655-4041453, perhaps implying that although the radiation pressure from the central engine is insufficient to cause clearly detectable outflows, it may cause absorption variations over longer timescales. However, more robust black hole mass estimates would improve the accuracy of the Eddington ratio estimates for these objects.Comment: 13 pages, 10 figures, 3 tables, accepted for publication in MNRA

Constants of Geodesic Motion in Higher-Dimensional Black-Hole Spacetimes

In [arXiv:hep-th/0611083] we announced the complete integrability of geodesic motion in the general higher-dimensional rotating black-hole spacetimes. In the present paper we prove all the necessary steps leading to this conclusion. In particular, we demonstrate the independence of the constants of motion and the fact that they Poisson commute. The relation to a different set of constants of motion constructed in [arXiv:hep-th/0612029] is also briefly discussed.Comment: 8 pages, no figure