April 2019 arXiv papers — page 50

Andrzej Dąbrowski, Tomasz Jędrzejak, Lucjan Szymaszkiewicz

Let $K=\Bbb Q(\sqrt{-q})$, where $q$ is a prime congruent to $3$ modulo $4$. Let $A=A(q)$ denote the Gross curve. Let $E=A^{(-β)}$ denote its quadratic twist, with $β=\sqrt{-q}$. The curve $E$ is defined over the Hilbert class field $H$ of $K$. We use Magma to calculate the values $L(E/H,1)$ for all such $q$'s up to some reasonable ranges (different for

D. I. Kazakov

We suggest a novel view on non-renormalizable interactions. It is based on the usual BPHZ R-operation which is equally applicable to any local QFT independently whether it is renormalizable or not. As a playground we take the phi^4_D theory in D dimensions for D=4,6,8,10 and consider the four-point scattering amplitude on shell. We derive the generalized RG

Vassili Kovalev, Siarhei Kazlouski

In this paper, we explore the possibility of generating artificial biomedical images that can be used as a substitute for real image datasets in applied machine learning tasks. We are focusing on generation of realistic chest X-ray images as well as on the lymph node histology images using the two recent GAN architectures including DCGAN and PGGAN. The possi

Jiaqi Cong, Tian Lin, Yu Zhu

This letter investigates the hybrid analog and digital beamforming (HBF) design for multiuser millimeter wave (mmWave) communication systems based on the minimum mean square error (MMSE) criterion. Using the alternating minimization method, the hybrid precoder of the base station (BS) and the hybrid combiners of the users are alternatively optimized. It is s

Dayong Tian, Dacheng Tao

Hashing methods have been widely investigated for fast approximate nearest neighbor searching in large data sets. Most existing methods use binary vectors in lower dimensional spaces to represent data points that are usually real vectors of higher dimensionality. We divide the hashing process into two steps. Data points are first embedded in a low-dimensiona

Sara Faghih-Naini, Sebastian Kuckuk, Vadym Aizinger, Daniel Zint

The shallow water equations (SWE) are a commonly used model to study tsunamis, tides, and coastal ocean circulation. However, there exist various approaches to discretize and solve them efficiently. Which of them is best for a certain scenario is often not known and, in addition, depends heavily on the used HPC platform. From a simulation software perspectiv

G. I. Syngayivska, V. V. Korotyeyev, V. A. Kochelap, L. Varani

We report the results of Monte Carlo simulation of electron dynamics in stationary and space- and time-dependent electric fields in compensated GaN samples. We have determined the frequency and wavevector dependencies of the dynamic conductivity, $σ_{ω,q}$. We have found that the spatially dependent dynamic conductivity of the drifting electrons can be negat

Mohammad Sal Moslehian, Mohsen Kian, Qingxiang Xu

We review some of the significant generalizations and applications of the celebrated Douglas theorem on the equivalence of factorization, range inclusion, and majorization of operators. We then apply it to find a characterization of the positivity of $2\times 2$ block matrices of operators in Hilbert spaces and finally describe the nature of such block matri

Daniel Richtmann, Peter A. Boyle, Tilo Wettig

With the ever-growing number of computing architectures, performance portability is an important aspect of (Lattice QCD) software. The Grid library provides a good framework for writing such code, as it thoroughly separates hardware-specific code from algorithmic functionality and already supports many modern architectures. We describe the implementation of

Jean-Paul Blaizot, Li Yan

We use a set of simple angular moments to solve the Boltzmann equation in the relaxation time approximation for a boost invariant longitudinally expanding gluonic plasma. The transition from the free streaming regime at early time to the hydrodynamic regime at late time is well captured by the first two-moments, corresponding to the monopole and quadrupole c

Claire M Postlethwaite, Alastair M Rucklidge

One of the simplest examples of a robust heteroclinic cycle involves three saddle equilibria: each one is unstable to the next in turn, and connections from one to the next occur within invariant subspaces. Such a situation can be described by a third-order ordinary differential equation (ODE), and typical trajectories approach each equilibrium point in turn

A. V. Brantov, Ph. Korneev, V. Yu. Bychenkov

A strong electron current triggered by a femtosecond relativistically intense laser pulse in a foil coil-like target is shown to be able to generate a solenoidal-type extremely strong magnetic field. The magnetic field lifetime sufficiently exceeds the laser pulse duration and is defined mainly by the target properties. The process of the magnetic field gene

Francisco J. Rubio, Bernard Rachet, Roch Giorgi, Camille Maringe

In cancer epidemiology using population-based data, regression models for the excess mortality hazard is a useful method to estimate cancer survival and to describe the association between prognosis factors and excess mortality. This method requires expected mortality rates from general population life tables: each cancer patient is assigned an expected (bac

Dayong Tian, Dacheng Tao

Blur in facial images significantly impedes the efficiency of recognition approaches. However, most existing blind deconvolution methods cannot generate satisfactory results due to their dependence on strong edges, which are sufficient in natural images but not in facial images. In this paper, we represent point spread functions (PSFs) by the linear combinat

Viktoriya Brydun, Mykhailo Zarichnyi

The notion of max-min measure is a counterpart of the notion of max-plus measure (Maslov measure or idempotent measure). In this paper we consider the spaces of max-min measures on the compact Hausdorff spaces. It is proved that the obtained functor of max-min measures is isomorphic to the functor of max-plus (idempotent) measures considered by the second-na

Federico Magliani, Kevin McGuinness, Eva Mohedano, Andrea Prati

The application of the diffusion in many computer vision and artificial intelligence projects has been shown to give excellent improvements in performance. One of the main bottlenecks of this technique is the quadratic growth of the kNN graph size due to the high-quantity of new connections between nodes in the graph, resulting in long computation times. Sev

Benjamin Jourdain, Tony Lelièvre, Pierre-André Zitt

By drawing a parallel between metadynamics and self interacting models for polymers, we study the longtime convergence of the original metadynamics algorithm in the adiabatic setting, namely when the dynamics along the collective variables decouples from the dynamics along the other degrees of freedom. We also discuss the bias which is introduced when the ad

Khaled Parvez, Robyn Worsley, Adriana Alieva, Alexandre Felten

Inkjet printable graphene inks are very attractive for applications in flexible and foldable electronics, such as wearable electronics and the Internet of Things. However, the ink preparation is still very time consuming as high concentrations can be achieved only with prolonged sonication (>24 hours) or with expensive setups. Here we demonstrate a water-bas

Valentin Lychagin, Valeriy Yumaguzhin

We study differential invariants of the third order linear differential operators and use them to find conditions for equivalence of differential operators acting in line bundles on two dimensional manifolds with respect to groups of authomorphisms.

Eduardo Ruíz Duarte, Jaap Top

We prove the Hasse-Weil inequality for genus 2 curves given by an equation of the form y^2 = f(x) with f a polynomial of degree 5, using arguments that mimic the elementary proof of the genus 1 case obtained by Yu. I. Manin in 1956.

Aku Venhola, Reynier Peletier, Eija Laurikainen, Heikki Salo

The Fornax Deep Survey Dwarf galaxy Catalog (FDSDC) includes 564 dwarf galaxies in the Fornax cluster and the in-falling Fornax A subgroup. We use the FDSDC galaxies for statistical analysis of the structural and stellar population differences in the range of galactic environments within the Fornax cluster. We present the standard scaling relations for the d

Giovanni Salmè

Solving the homogeneous Bethe-Salpeter equation directly in Minkowski space is becoming a very alive field, since, in recent years, a new approach has been introduced, and the reachable results can be potentially useful in various areas of research, as soon as the relativistic description of few-body bound systems is relevant. A brief review of the status of

Vinicius V. Melo, Danilo Vasconcellos Vargas, Wolfgang Banzhaf

Lexicase selection achieves very good solution quality by introducing ordered test cases. However, the computational complexity of lexicase selection can prohibit its use in many applications. In this paper, we introduce Batch Tournament Selection (BTS), a hybrid of tournament and lexicase selection which is approximately one order of magnitude faster than l

Alejandro B. Kolton, Pierre Le Doussal, Kay Joerg Wiese

We study several probability distributions relevant to the avalanche dynamics of elastic interfaces driven on a random substrate: The distribution of size, duration, lateral extension or area, as well as velocities. Results from the functional renormalization group and scaling relations involving two independent exponents, roughness $ζ$, and dynamics $z$, ar

Julia Rackerseder, Rüdiger Göbl, Nassir Navab, Christoph Hennersperger

Intra-operative ultrasound is an increasingly important imaging modality in neurosurgery. However, manual interaction with imaging data during the procedures, for example to select landmarks or perform segmentation, is difficult and can be time consuming. Yet, as registration to other imaging modalities is required in most cases, some annotation is necessary

Simen Thys, Wiebe Van Ranst, Toon Goedemé

Adversarial attacks on machine learning models have seen increasing interest in the past years. By making only subtle changes to the input of a convolutional neural network, the output of the network can be swayed to output a completely different result. The first attacks did this by changing pixel values of an input image slightly to fool a classifier to ou

Dinesh K. Srivastava, Rupa Chatterjee

We study the production dynamics of charm quarks in the parton cascade model for relativistic heavy ion collisions at RHIC and LHC energies. The model is eminently suited for a study of the pre-equilibrium dynamics of charm quarks at modest transverse momenta. The treatment is motivated by QCD parton picture and describes the dynamics of an ultra-relativisti

Dmitry Efimov

We present a simple and convenient analytical formula for efficient exact computation of the hafnian of Toeplitz matrices of a special type. An interpretation of the obtained results is given in the language of perfect matchings and Bessel polynomials.

Hideyuki Miyahara

Population dynamics deals with the collective phenomena of living organisms, and it has attracted much attention since it is expected to explain how not only living organisms but also human beings have been adapted to varying environments. However, it is quite difficult to insist on a general statement on living organisms since mathematical models heavily de

Dario Feliciangeli, Robert Seiringer

We consider the Pekar functional on a ball in R^3. We prove uniqueness of minimizers, and a quadratic lower bound in terms of the distance to the minimizer. The latter follows from non-degeneracy of the Hessian at the minimum.

Lukas Spiegelhofer

Cusick&#39;s conjecture on the binary sum of digits $s(n)$ of a nonnegative integer $n$ states the following: for all nonnegative integers $t$ we have \[ c_t=\lim_{N\rightarrow\infty}\frac 1N\left\lvert\{n<N:s(n+t)\geq s(n)\}\right\rvert>1/2. \] We prove that for given $\varepsilon>0$ we have \[ c_t+c_{t&#39;}>1-\varepsilon \] if the binary expansion of $t$

Victor Kitov

Style transfer is a problem of rendering a content image in the style of another style image. A natural and common practical task in applications of style transfer is to adjust the strength of stylization. Algorithm of Gatys et al. (2016) provides this ability by changing the weighting factors of content and style losses but is computationally inefficient. R

Sebastian Biewer, Pedro D&#39;Argenio, Holger Hermanns

The software running in embedded or cyber-physical systems (CPS) is typically of proprietary nature, so users do not know precisely what the systems they own are (in)capable of doing. Most malfunctionings of such systems are not intended by the manufacturer, but some are, which means these cannot be classified as bugs or security loopholes. The most prominen

Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Xiang Li

We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches, ranging from conventional pipeline systems to end-to-end neural models, in common environments. ConvLab offers a set of fully annotated datasets and

Prashantkumar Patel

In the present article, we propose the new class positive linear operators, which discrete type depending on a real parameters. These operators are similar to Jain operators but its approximation properties are different then Jain operators. Theorems of degree of approximation, direct results, Voronovskaya Asymptotic formula and statistical convergence are d

Toby Perrett, Dima Damen

Domain alignment in convolutional networks aims to learn the degree of layer-specific feature alignment beneficial to the joint learning of source and target datasets. While increasingly popular in convolutional networks, there have been no previous attempts to achieve domain alignment in recurrent networks. Similar to spatial features, both source and targe

Ke Gu, Dacheng Tao, Junfei Qiao, Weisi Lin

In this paper we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g. object detection and recognition, raw images are usually needed to be appropr

Junbao Zhuo, Shuhui Wang, Shuhao Cui, Qingming Huang

We address the unsupervised open domain recognition (UODR) problem, where categories in labeled source domain S is only a subset of those in unlabeled target domain T. The task is to correctly classify all samples in T including known and unknown categories. UODR is challenging due to the domain discrepancy, which becomes even harder to bridge when a large n

Andreas Robinson, Felix Järemo Lawin, Martin Danelljan, Fahad Shahbaz Khan

We address the highly challenging problem of video object segmentation. Given only the initial mask, the task is to segment the target in the subsequent frames. In order to effectively handle appearance changes and similar background objects, a robust representation of the target is required. Previous approaches either rely on fine-tuning a segmentation netw

Maarten Solleveld

We investigate Levi subgroups of a connected reductive algebraic group G, over a ground field K. We parametrize their conjugacy classes in terms of sets of simple roots and we prove that two Levi K-subgroups of G are rationally conjugate if and only if they are geometrically conjugate. These results are generalized to arbitrary connected linear algebraic K-g

Kübra Tanınmış, Necati Aras, İ. K. Altınel

In this paper we consider an extension of the well-known Influence Maximization Problem in a social network which deals with finding a set of k nodes to initiate a diffusion process so that the total number of influenced nodes at the end of the process is maximized. The extension focuses on a competitive variant where two decision makers are involved. The fi

Zhun Liu, Yuanhui Sun, David J. Singh, Lijun Zhang

Covalent-polar semiconductors that show intrinsic two-dimensional (2D) vertical polarization present new device opportunities. These materials differ from ordinary ferroelectrics in that they are able to maintain polarization normal to a surface even with an unscreened depolarization field. Identifying phases that exhibit intrinsic 2D vertical polarization i

Maximilian Zocholl, Elena Camossi, Anne-Laure Jousselme, Cyril Ray

Big data solutions are designed to cope with data of huge Volume and wide Variety, that need to be ingested at high Velocity and have potential Veracity issues, challenging characteristics that are usually referred to as the &#34;4Vs of Big Data&#34;. In order to evaluate possibly complex big data solutions, stress tests require to assess a large number of c

Kristi Kuljus, Bo Ranneby

In this paper, the maximum spacing method is considered for multivariate observations. Nearest neighbour balls are used as a multidimensional analogue to univariate spacings. A class of information-type measures is used to generalize the concept of maximum spacing estimators. Asymptotic normality of these generalized maximum spacing estimators is proved when

Xianglong Liu, Lei Huang, Cheng Deng, Bo Lang

Hash based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the l

Guangliang Li, Randy Gomez, Keisuke Nakamura, Jinying Lin

TAMER has proven to be a powerful interactive reinforcement learning method for allowing ordinary people to teach and personalize autonomous agents&#39; behavior by providing evaluative feedback. However, a TAMER agent planning with UCT---a Monte Carlo Tree Search strategy, can only update states along its path and might induce high learning cost especially

Vinod Kumar Dwivedi, Soumik Mukhopadhyay

We find that the long-range magnetic ordering is absent and electrical conduction suppressed in Y$_{1.7}$Bi$_{0.3}$Ir$_2$O$_7$/YSZ(100) thin film prepared by pulsed laser deposition. The sharp down-turn of inverse magnetic susceptibility X-1(T) from the conventional Curie-Weiss behaviour below T* ~ 168K suggests an inhomogeneous ferromagnetic Griffiths like

Hamed Nosrati, Elias Aboutanios, David Smith

Increasing the number of transmit and receive elements in multiple-input-multiple-output (MIMO) antenna arrays imposes a substantial increase in hardware and computational costs. We mitigate this problem by employing a reconfigurable MIMO array where large transmit and receive arrays are multiplexed in a smaller set of k baseband signals. We consider four st

Kazi Nazmul Haque, Siddique Latif, Rajib Rana

Learning disentangled representation from any unlabelled data is a non-trivial problem. In this paper we propose Information Maximising Autoencoder (InfoAE) where the encoder learns powerful disentangled representation through maximizing the mutual information between the representation and given information in an unsupervised fashion. We have evaluated our

Christian Wolf, Jacob Golding, Christopher A. Onken, Li Shao

The wish list of astronomers includes a tool that reveals quenching of star formation in galaxies directly as it proceeds. Here, we present a proof-of-concept for a new quenching-and-bursting diagnostic, a &#34;change index&#34; for star formation, that requires only photometric data, provided they include filters such as the violet $uv$ bands used by SkyMap

A. Sauer, D. A. Zocco, A. H. Said, R. Heid

Phonon measurements in the A15-type superconductors were complicated in the past because of the unavailability of large single crystals for inelastic neutron scattering, e.g., in the case of Nb$_3$Sn, or unfavorable neutron scattering properties in the case of V$_3$Si. Hence, only few studies of the lattice dynamical properties with momentum resolved methods

Daniel Wild, Maximilian Weber, Jan Egger

Segmentation is a key step in analyzing and processing medical images. Due to the low fault tolerance in medical imaging, manual segmentation remains the de facto standard in this domain. Besides, efforts to automate the segmentation process often rely on large amounts of manually labeled data. While existing software supporting manual segmentation is rich i

Xu Yang, Hanwang Zhang, Jianfei Cai

We do not speak word by word from scratch; our brain quickly structures a pattern like \textsc{sth do sth at someplace} and then fill in the detailed descriptions. To render existing encoder-decoder image captioners such human-like reasoning, we propose a novel framework: learning to Collocate Neural Modules (CNM), to generate the `inner pattern&#39; connect

Junyeong Kim, Minuk Ma, Kyungsu Kim, Sungjin Kim

This paper proposes the progressive attention memory network (PAMN) for movie story question answering (QA). Movie story QA is challenging compared to VQA in two aspects: (1) pinpointing the temporal parts relevant to answer the question is difficult as the movies are typically longer than an hour, (2) it has both video and subtitle where different questions

Duo Wang, Heng Li, Ting Yu, Bochao Cao

In-depth analyses of existing direct numerical simulations (DNS) data from various sources supported a logical and important classification of generic turbulent boundary layers (TBL), namely Type-A, -B and -C TBL, based on distribution patterns of time-averaged wall-shear stress. Among these types, Type-A TBL and its related law, as represented by the DNS da

Takaaki Matsuo, Clément Durand, Rodney Van Meter

Establishing end-to-end quantum connections requires quantified link characteristics, and operations need to coordinate decision-making between nodes across a network. We introduce the RuleSet-based communication protocol for supporting quantum operations over distant nodes to minimize classical packet transmissions for guaranteeing synchronicity. RuleSets a

Liu-Yao Zhang, Jin-Hui Chen, Zi-Wei Lin, Yu-Gang Ma

We extend our earlier study on two-particle angular correlations in $pp$ collisions at low transverse momentum ($p_T$) to $p$-Pb, Pb-Pb and Au-Au collisions at RHIC and LHC energies. We mainly use the string melting version of a multiphase transport model with improved quark coalescence for this study. We start from the analysis of $π^{\pm}$, $K^{\pm}$ and $

Yongjia Wang, Yunxiao Ye, QIngfeng Li

The cumulants of baryon multiplicity distribution in relativistic heavy-ion collisions (HICs) have attracted considerable attention recently. It has been conjectured that they may serve as a promising observable to detect the critical end point in the QCD phase diagram, while the cumulants in HICs at intermediate energies have not been widely studied to date

Julie Chang, Gordon Wetzstein

Depth estimation and 3D object detection are critical for scene understanding but remain challenging to perform with a single image due to the loss of 3D information during image capture. Recent models using deep neural networks have improved monocular depth estimation performance, but there is still difficulty in predicting absolute depth and generalizing o

Leiqiang Chu, Indra Yudhistira, Hennrik Schmidt, Tsz Chun Wu

Bilayer MoS2 is a centrosymmetric semiconductor with degenerate spin states in the six valleys at the corners of the Brillouin zone. It has been proposed that breaking of this inversion symmetry by an out-of-plane electric field breaks this degeneracy, allowing for spin and valley lifetimes to be manipulated electrically in bilayer MoS2 with an electric fiel

S. Frasca, B. Korzh, M. Colangelo, D. Zhu

We estimate the depairing current of superconducting nanowire single photon detectors (SNSPDs) by studying the dependence of the nanowires kinetic inductance on their bias current. The kinetic inductance is determined by measuring the resonance frequency of resonator style nanowire coplanar waveguides both in transmission and reflection configurations. Bias

Kwok-Kun Kwong

We obtain sharp quantitative Laplacian upper and lower estimates under no assumption on curvatures. As a result, we derive quantitative Laplacian, area and volume comparison theorems for tubes in Riemannian and Kähler manifolds under weak integral curvature assumptions. We also give some applications, such as a general Bonnet-Myers theorem and Cheng&#39;s ei

Sriram Ravula, Alexandros G. Dimakis

We extend the Deep Image Prior (DIP) framework to one-dimensional signals. DIP is using a randomly initialized convolutional neural network (CNN) to solve linear inverse problems by optimizing over weights to fit the observed measurements. Our main finding is that properly tuned one-dimensional convolutional architectures provide an excellent Deep Image Prio

Jesse Paterson, Jiwoong Han, Tom Cheng, Paxtan Laker

As the capability and complexity of UAVs continue to increase, the human-robot interface community has a responsibility to design better ways of specifying the complex 3D flight paths necessary for instructing them. Immersive interfaces, such as those afforded by virtual reality (VR), have several unique traits which may improve the user&#39;s ability to per

Won Joo Kim, Dae San Kim, Han Young Kim, Taekyun Kim

In this paper, we investigate some properties and identities for degenerate Euler polynomials in connection with degenerate Bernstein polynomials by means of fermionic p-adic integrals on Zp and generating functions. In addition, we study two variable degenerate Bernstein polynomials and the degenerate Bernstein operators.

Christophe Match, Michael Harder, Lihui Bai, Paul Hyde

The Rabi oscillations of a coupled spin-photon system are experimentally studied using time domain microwave transmission measurements. An external magnetic bias field is applied to control the amplitude and frequency of Rabi oscillations, which are a measure of the coherent spin-photon energy exchange and coupling strength respectively. The amplitude and fr

Paul Gastin, Sayan Mukherjee, B Srivathsan

A popular method for solving reachability in timed automata proceeds by enumerating reachable sets of valuations represented as zones. A naïve enumeration of zones does not terminate. Various termination mechanisms have been studied over the years. Coming up with efficient termination mechanisms has been remarkably more challenging when the automaton has dia

Longqi Yang, Chen Fang, Hailin Jin, Walter Chang

Complex design tasks often require performing diverse actions in a specific order. To (semi-)autonomously accomplish these tasks, applications need to understand and learn a wide range of design procedures, i.e., Creative Procedural-Knowledge (CPK). Prior knowledge base construction and mining have not typically addressed the creative fields, such as design

Siqi Yi, Stewart Worrall, Eduardo Nebot

Robustness and safety are crucial properties for the real-world application of autonomous vehicles. One of the most critical components of any autonomous system is localisation. During the last 20 years there has been significant progress in this area with the introduction of very efficient algorithms for mapping, localisation and SLAM. Many of these algorit

Rui Fan, Mohammud Junaid Bocus, Yilong Zhu, Jianhao Jiao

Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and labor-intensive. In this paper, we propose a novel road crack detection algorithm based on deep learning and adaptive image se

Kennichi Sugiyama

Hecke expected that an explicit set of theta series obtained from maximal orders of the definite quaternion algebra over Q which is ramified at a prime N will be a basis of the space of holomorphic modular forms of weight 2 and level N. However, later Eichler noticed that Hecke&#39;s conjecture does not hold in general. It is natural to ask for the dimension

Karthik Rajkumar

In this paper, I show that classic two-stage least squares (2SLS) estimates are highly unstable with weak instruments. I propose a ridge estimator (ridge IV) and show that it is asymptotically normal even with weak instruments, whereas 2SLS is severely distorted and un-bounded. I motivate the ridge IV estimator as a convex optimization problem with a GMM obj

William La Cava, Jason H. Moore

Multidimensional genetic programming represents candidate solutions as sets of programs, and thereby provides an interesting framework for exploiting building block identification. Towards this goal, we investigate the use of machine learning as a way to bias which components of programs are promoted, and propose two semantic operators to choose where useful

Jiaxi He, Frank Z. Xing, Ran Yang, Cishen Zhang

The quality of images captured in outdoor environments can be affected by poor weather conditions such as fog, dust, and atmospheric scattering of other particles. This problem can bring extra challenges to high-level computer vision tasks like image segmentation and object detection. However, previous studies on image dehazing suffer from a huge computation

Fabo Feng, Jeffrey D. Crane, Sharon Xuesong Wang, Johanna K. Teske

The radial velocity method plays a major role in the discovery of nearby exoplanets. To efficiently find planet candidates from the data obtained in high precision radial velocity surveys, we apply a signal diagnostic framework to detect radial velocity signals that are statistically significant, consistent in time, robust to the choice of noise models, and

Pablo R. Zangara, Jacob Henshaw, Daniela Pagliero, Ashok Ajoy

Optically-pumped color centers in semiconductor powders can potentially induce high levels of nuclear spin polarization in surrounding solids or fluids at or near ambient conditions, but complications stemming from the random orientation of the particles and the presence of unpolarized paramagnetic defects hinder the flow of polarization beyond the defect&#3

Stanley W. Smith, Yeojun Kim, Jacopo Guanetti, Alexander A. Kurzhanskiy

In this paper we propose a distributed model predictive control architecture to coordinate the longitudinal motion of a vehicle platoon at a signalized intersection. Our control approach is cooperative; we use vehicle-to-vehicle (V2V) communication in order to maintain small inter-vehicle distances and correspondingly achieve large vehicle throughput at an i

Vitalii I. Shcherbinin, Yuliya K. Moskvitina, Volodymyr I. Fesenko, Vladimir R. Tuz

Scattering from a dielectric nanowire coated by helical graphene strips (nanoribbons) is investigated for dual-polarized wave at oblique incidence. In the long-wavelength approximation, the helical strips are treated as a homogeneous layer with averaged tensor conductivity. It is shown that performance of well-known surface cloaks in the form of graphene mon

Qiaoyu Tan, Ninghao Liu, Xia Hu

Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other attribute information can be effectively preserved. Network representation leaning facilitates further appli

Xiaolong Xu, Shuai Liu, Bo Han, Yimo Han

Two-dimensional (2D) layered semiconductors, with their ultimate atomic thickness, have shown promise to scale down transistors for modern integrated circuitry. However, the electrical contacts that connect these materials with external bulky metals are usually unsatisfactory, which limits the transistor performance. Recently, contacting 2D semiconductors us

Vinay Kumar Verma, Aakansha Mishra, Ashish Mishra, Piyush Rai

We present a probabilistic model for Sketch-Based Image Retrieval (SBIR) where, at retrieval time, we are given sketches from novel classes, that were not present at training time. Existing SBIR methods, most of which rely on learning class-wise correspondences between sketches and images, typically work well only for previously seen sketch classes, and resu

Stephan Thaler, Ludger Paehler, Nikolaus A. Adams

This work presents a data-driven approach to the identification of spatial and temporal truncation errors for linear and nonlinear discretization schemes of Partial Differential Equations (PDEs). Motivated by the central role of truncation errors, for example in the creation of implicit Large Eddy schemes, we introduce the Sparse Identification of Truncation

A. Aristodemo, L. Gemignani

It is shown that the problem of balancing a nonnegative matrix by positive diagonal matrices can be recast as a constrained nonlinear multiparameter eigenvalue problem. Based on this equivalent formulation some adaptations of the power method and Arnoldi process are proposed for computing the dominant eigenvector which defines the structure of the diagonal t

Thomas Gerstner, Bastian Harrach, Daniel Roth

The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is to combine the one-step survival idea of Glasserman and Staum with the stable differentiation approach o

Stephen O&#39;Sullivan

In this paper, Runge-Kutta-Gegenbauer (RKG) stability polynomials of arbitrarily high order of accuracy are introduced in closed form. The stability domain of RKG polynomials extends in the the real direction with the square of polynomial degree, and in the imaginary direction as an increasing function of Gegenbauer parameter. Consequently, the polynomials a

Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu

Asynchronous parallel implementations of stochastic gradient (SG) have been broadly used in solving deep neural network and received many successes in practice recently. However, existing theories cannot explain their convergence and speedup properties, mainly due to the nonconvexity of most deep learning formulations and the asynchronous parallel mechanism.

Souratosh Khan, Sumit Mazumdar

Recent advances in singlet-fission research make it imperative that structure-property correlations that determine optical signatures of the triplet-triplet spin biexciton as well as its binding energy be understood precisely. We report many-body calculations of excited state absorptions from the triplet exciton and the triplet-triplet biexciton from two tra

Kyungchul Song

Diffusion over a network refers to the phenomenon of a change of state of a cross-sectional unit in one period leading to a change of state of its neighbors in the network in the next period. One may estimate or test for diffusion by estimating a cross-sectionally aggregated correlation between neighbors over time from data. However, the estimated diffusion

John Burniston, Michael Grabowecky, Carlo Maria Scandolo, Giulio Chiribella

Quantum supermaps are a higher-order generalization of quantum maps, taking quantum maps to quantum maps. It is known that any completely positive, trace non-increasing (CPTNI) map can be performed as part of a quantum measurement. By providing an explicit counterexample we show that, instead, not every quantum supermap sending a quantum channel to a CPTNI m

Edison Liang, Kevin Qinyuan Zheng, Kelly Yao, Willie Lo

A new type of compact high resolution high sensitivity gamma ray spectrometer for short pulse intense 250 keV to 50 MeV gamma rays has been developed by combining the principles of scintillators and attenuation spectrometers. The first prototype of this scintillator attenuation spectrometer or SAS was tested successfully in Trident laser experiments at LANL.

Paria Jamshid Lou, Yufei Wang, Mark Johnson

This paper studies the performance of a neural self-attentive parser on transcribed speech. Speech presents parsing challenges that do not appear in written text, such as the lack of punctuation and the presence of speech disfluencies (including filled pauses, repetitions, corrections, etc.). Disfluencies are especially problematic for conventional syntactic

Hadrien Bertrand, Mohammad Hashir, Joseph Paul Cohen

Most convolutional neural networks in chest radiology use only the frontal posteroanterior (PA) view to make a prediction. However the lateral view is known to help the diagnosis of certain diseases and conditions. The recently released PadChest dataset contains paired PA and lateral views, allowing us to study for which diseases and conditions the performan

Bradley Hauer, Grzegorz Kondrak

The study of homonymy is vital to resolving fundamental problems in lexical semantics. In this paper, we propose four hypotheses that characterize the unique behavior of homonyms in the context of translations, discourses, collocations, and sense clusters. We present a new annotated homonym resource that allows us to test our hypotheses on existing WSD resou

Yang-Hui He, Seung-Joo Lee

We use the latest techniques in machine-learning to study whether from the landscape of Calabi-Yau manifolds one can distinguish elliptically fibred ones. Using the dataset of complete intersections in products of projective spaces (CICY3 and CICY4, totalling about a million manifolds) as a concrete playground, we find that a relatively simple neural network

Ran Finkelstein, Ohr Lahad, Ohad Michel, Omri Davidson

Doppler broadening in thermal ensembles degrades the absorption cross-section and the coherence time of collective excitations. In two photon transitions, it is common to assume that this problem becomes worse with larger wavelength mismatch. Here we identify an opposite mechanism, where such wavelength mismatch leads to cancellation of Doppler broadening vi

Jeffrey Meier, Alexander Zupan

The purpose of this paper is to study geometrically simply-connected homotopy 4-spheres by analyzing $n$-component links with a Dehn surgery realizing $\#^n(S^1\times S^2)$. We call such links $n$R-links. Our main result is that a homotopy 4-sphere that can be built without 1-handles and with only two 2-handles is diffeomorphic to the standard 4-sphere in th

Yan-Zhi Meng, Liang-Duan Liu, Jun-Jie Wei, Xue-Feng Wu

The quasi-thermal components found in many Fermi gamma-ray bursts (GRBs) imply that the photosphere emission indeed contributes to the prompt emission of many GRBs. But whether the observed spectra empirically fitted by the Band function or cutoff power law, especially the spectral and peak energy ($E_{p}$) evolutions can be explained by the photosphere emis

Wolfgang Hasse, Volker Perlick

We derive and discuss a general redshift formula in Finsler spacetimes. The condition for the existence of a redshift potential is worked out. The results are illustrated with two examples, one refering to a spherically symmetric and static Finsler spacetime and the other to a cosmological Finsler spacetime.

Allan N. Kaufman, Bruce I. Cohen

These lecture notes were presented by Allan N. Kaufman in his graduate plasma theory course and a follow-on special topics course (Physics 242A, B, C and Physics 250 at the University of California Berkeley). The notes follow the order of the lectures. The equations and derivations are as Kaufman presented, but the text is a reconstruction of Kaufman&#39;s d

Trang Quynh Nguyen, Ian Schmid, Elizabeth A. Stuart

The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements -- effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array of options for effect estimation. However, the literature on these results is fast-growing and complex, whi