Choosing the pp in LpL_p loss: rate adaptivity on the symmetric location problem

Given univariate random variables $Y_1, \ldots, Y_n$ with the $\text{Uniform}(\theta_0 - 1, \theta_0 + 1)$ distribution, the sample midrange $\frac{Y_{(n)}+Y_{(1)}}{2}$ is the MLE for $\theta_0$ and estimates $\theta_0$ with error of order $1/n$, which is much smaller compared with the $1/\sqrt{n}$ error rate of the usual sample mean estimator. However, the sample midrange performs poorly when the data has say the Gaussian $N(\theta_0, 1)$ distribution, with an error rate of $1/\sqrt{\log n}$. In this paper, we propose an estimator of the location $\theta_0$ with a rate of convergence that can, in many settings, adapt to the underlying distribution which we assume to be symmetric around $\theta_0$ but is otherwise unknown. When the underlying distribution is compactly supported, we show that our estimator attains a rate of convergence of $n^{-\frac{1}{\alpha}}$ up to polylog factors, where the rate parameter $\alpha$ can take on any value in $(0, 2]$ and depends on the moments of the underlying distribution. Our estimator is formed by the $\ell^\gamma$-center of the data, for a $\gamma\geq2$ chosen in a data-driven way -- by minimizing a criterion motivated by the asymptotic variance. Our approach can be directly applied to the regression setting where $\theta_0$ is a function of observed features and motivates the use of $\ell^\gamma$ loss function for $\gamma > 2$ in certain settings.Comment: 60 pages; 7 figure

Efficient Third-Order Distributed Feedback Laser with Enhanced Beam Pattern

A third-order distributed feedback laser has an active medium disposed on a substrate as a linear array of segments having a series of periodically spaced interstices therebetween and a first conductive layer disposed on a surface of the active medium on each of the segments and along a strip from each of the segments to a conductive electrical contact pad for application of current along a path including the active medium. Upon application of a current through the active medium, the active medium functions as an optical waveguide, and there is established an alternating electric field, at a THz frequency, both in the active medium and emerging from the interstices. Spacing of adjacent segments is approximately half of a wavelength of the THz frequency in free space or an odd integral multiple thereof, so that the linear array has a coherence length greater than the length of the linear array

Development and Evaluation of an Autonomous Sensor for the Observation of Sediment Motion

Abstract Measurements within the mobile bed layer have been limited by previous Eulerian-based technologies. A microelectromechanical system device, called a smart sediment grain (SSG), that can measure and record Lagrangian observations of coastal sediments at incipient motion has been developed. These sensors have the potential to resolve fundamental hypotheses regarding the incipient motion of coastal sediments. Angle of repose experiments verified that the sensor enclosure has mobility characteristics similar to coarse gravel. Experiments conducted in a small oscillating flow tunnel verified that the sensors detect incipient motion under various hydrodynamic conditions. Evidence suggests the influence of pressure-gradient-induced sediment motion, contrary to the more commonly assumed bed shear stress criterion. Lagrangian measurements of rotation measured with the newly developed SSG agreed to within 5% of the rotation estimates made simultaneously with high-speed video cameras

Causal Evidence for the Role of Specific GABAergic Interneuron Types in Entorhinal Recruitment of Dentate Granule Cells

The dentate gyrus (DG) is the primary gate of the hippocampus and controls information flow from the cortex to the hippocampus proper. To maintain normal function, granule cells (GCs), the principal neurons in the DG, receive fine- tuned inhibition from local-circuit GABAergic inhibitory interneurons (INs). Abnormalities of GABAergic circuits in the DG are associated with several brain disorders, including epilepsy, autism, schizophrenia, and Alzheimer disease. Therefore, understanding the network mechanisms of inhibitory control of GCs is of functional and pathophysiological importance. GABAergic inhibitory INs are heterogeneous, but it is unclear how individual subtypes contribute to GC activity. Using cell-type-specific optogenetic perturbation, we investigated whether and how two major IN populations defined by parvalbumin (PV) and somatostatin (SST) expression, regulate GC input transformations. We showed that PV-expressing (PV+) INs, and not SST- expressing (SST+) INs, primarily suppress GC responses to single cortical stimulation. In addition, these two IN classes differentially regulate GC responses to θ and γ frequency inputs from the cortex. Notably, PV+ INs specifically control the onset of the spike series, whereas SST+ INs preferentially regulate the later spikes in the series. Together, PV+ and SST+ GABAergic INs engage differentially in GC input-output transformations in response to various activity patterns

Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency

Recently, image enhancement and restoration have become important applications on mobile devices, such as super-resolution and image deblurring. However, most state-of-the-art networks present extremely high computational complexity. This makes them difficult to be deployed on mobile devices with acceptable latency. Moreover, when deploying to different mobile devices, there is a large latency variation due to the difference and limitation of deep learning accelerators on mobile devices. In this paper, we conduct a search of portable network architectures for better quality-latency trade-off across mobile devices. We further present the effectiveness of widely used network optimizations for image deblurring task. This paper provides comprehensive experiments and comparisons to uncover the in-depth analysis for both latency and image quality. Through all the above works, we demonstrate the successful deployment of image deblurring application on mobile devices with the acceleration of deep learning accelerators. To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices. This paper provides practical deployment-guidelines, and is adopted by the championship-winning team in NTIRE 2020 Image Deblurring Challenge on Smartphone Track.Comment: CVPR 2020 Workshop on New Trends in Image Restoration and Enhancement (NTIRE

The relationship of muscular endurance and coordination and dexterity with behavioral and neuroelectric indices of attention in preschool children

This study investigated the associations of non-aerobic fitness (NAF) and motor competence (MC) with attention in 4–6 year-old preschoolers. The allocation of attentional resources and speed of stimulus categorization were examined using the amplitude and latency of P3 of event-related potentials respectively, while cortical activation related to general attention and task-specific discriminative processes were examined using event-related desynchronization (ERD) at lower (8–10 Hz) and upper (10–12 Hz) alpha frequencies, respectively. Seventy-six preschoolers completed NAF (muscular power, muscular endurance, flexibility, balance) and MC (coordination and dexterity, ball skills, agility and balance) test batteries. Electroencephalogram was recorded while participants performed an auditory oddball task. After controlling for age and MC, muscular endurance was positively related to P3 amplitude. MC and its coordination and dexterity sub-component were positively related to task performance, with higher levels of coordination and dexterity showing an additional association with greater upper alpha ERD between 700 and 1000 ms following stimulus onset after controlling for age and NAF. These findings suggest relationships of NAF and MC with early childhood neurocognitive function. Specifically, muscular endurance is related to the neuroinhibition in facilitating effective allocation of attentional resources to stimulus evaluation while coordination and dexterity are related to cortical activation underlying strategic attentional preparation for subsequent stimulus evaluation

Narcissistic self-sorting of n-acene nano-ribbons yielding energy-transfer and electroluminescence at p-n junctions

The 2,3-didecyloxy derivative of an n-type anthracene (n-BG) and a p-type tetracene (p-R) have been synthesized and their self-assembly into nano-ribbons studied. Hyperspectral fluorescence imaging revealed their narcissistic self-sorting, leading to separated nanoribbons emitting with very different colors (blue or green for n-BG, depending on the growth solvent, and red for p-R). It is unique that the usual origins of self-sorting, such as specific H-bonding, different growth kinetics, or incompatible steric hindrance can be ruled out. Hence, the narcissistic behaviour is herein proposed to originate from a sofar unconsidered cause: the discrepancy between the quadrupolar character of n-BG and dipolar character of p-R. At the p-n junctions of these nanoribbons, inter-ribbon FRET and electro-luminescence switch-on were observed by fluorescence/luminescence microscopy.The authors acknowledge the financial support of the European Research Council Marie Curie Actions (FP7-PEOPLE-2012-ITN SMARTNET Grant agreement Nr 316656); the CNRS; the French Ministry of Education and Research; the Region Aquitaine; the ANR-06-JCJC-0030; the Department of Education, Science and Universities of the Basque Country Government (postdoctoral grant and project IT1639-22); the "Arina" informatic cluster of UPV/EHU; the facilities ELORGA of UB; and the ANR-17-CE24-0033-01 RESOLVE. The authors thank Dr A. Mendez-Ardoy for the CV measurements and CESAMO for structural analyses (ISM, Univ. Bordeaux)