November 2018 arXiv papers — page 123

Issei Oikawa

In this paper, we present a flux-based formulation of the hybridizable discontinuous Galerkin (HDG) method for steady-state diffusion problems and propose a new method derived by letting a stabilization parameter tend to infinity. Assuming an inf-sup condition, we prove its well-posedness and error estimates of optimal order. We show that the inf-sup conditi

Seyed Hossein Hendi, Ali Dehghani

Considering de Rham-Gabadadze-Tolley theory of massive gravity coupled with (ghost free) higher curvature terms arisen from the Lovelock Lagrangian, we obtain charged AdS black hole solutions in diverse dimensions. We compute thermodynamic quantities in the extended phase space by considering the variations of the negative cosmological constant, Lovelock coe

Michael Usher

Following proposals of Ostrover and Polterovich, we introduce and study "coarse" and "fine" versions of a symplectic Banach-Mazur distance on certain open subsets of $\mathbb{C}^n$ and other open Liouville domains. The coarse version declares two such domains to be close to each other if each domain admits a Liouville embedding into a slight dilate of the ot

Indrajith V S, R. Muthuganesan, R. Sankaranarayanan

Correlation beyond entanglement is a subject of interest in quantum information. Here we have shown the existence of quantum correlation without entanglement in Heisenberg $XYZ$ spin model with external magnetic field, using different versions of measurement-induced nonlocality. However maximally entangled states are shown to possess maximum correlation.

Cynthia Rudin, Caroline Wang, Beau Coker

In our current society, secret algorithms make important decisions about individuals. There has been substantial discussion about whether these algorithms are unfair to groups of individuals. While noble, this pursuit is complex and ultimately stagnating because there is no clear definition of fairness and competing definitions are largely incompatible. We a

S. Kuwata, K. Kawaguchi

The product of any number of Legendre functions, under a restricted domain, can be expanded by the corresponding Legendre polynomials, with the coefficient being the sinc function. While an analogous expansion can be made for any number of Gengenbauer functions, it is not allowed for more than two Jacobi functions. To obtain such an expansion, the sampling t

Timothy C. Y. Chan, Neal Kaw

Most inverse optimization models impute unspecified parameters of an objective function to make an observed solution optimal for a given optimization problem with a fixed feasible set. We propose two approaches to impute unspecified left-hand-side constraint coefficients in addition to a cost vector for a given linear optimization problem. The first approach

Guixiang Ma, Nesreen K. Ahmed, Ted Willke, Dipanjan Sengupta

Learning a similarity metric has gained much attention recently, where the goal is to learn a function that maps input patterns to a target space while preserving the semantic distance in the input space. While most related work focused on images, we focus instead on learning a similarity metric for neuroimages, such as fMRI and DTI images. We propose an end

Satwik Acharyya, Zhengwu Zhang, Anirban Bhattacharya, Debdeep Pati

Analysis of structural and functional connectivity (FC) of human brains is of pivotal importance for diagnosis of cognitive ability. The Human Connectome Project (HCP) provides an excellent source of neural data across different regions of interest (ROIs) of the living human brain. Individual specific data were available from an existing analysis (Dai et al.

Masahiro Tanaka

A generalized method of moments (GMM) estimator is unreliable for a large number of moment conditions, that is, it is comparable, or larger than the sample size. While classical GMM literature proposes several provisions to this problem, its Bayesian counterpart (i.e., Bayesian inference using a GMM criterion as a quasi-likelihood) almost totally ignores it.

Ting-Rui Chiang, Yun-Nung Chen

Solving math word problems is a challenging task that requires accurate natural language understanding to bridge natural language texts and math expressions. Motivated by the intuition about how human generates the equations given the problem texts, this paper presents a neural approach to automatically solve math word problems by operating symbols according

Lei Lin, Weizi Li, Srinivas Peeta

Connected vehicles (CVs) can capture and transmit detailed data through vehicle-to-vehicle and vehicle-to-infrastructure communications, which bring new opportunities to improve the safety, mobility, and sustainability of transportation systems. However, the potential data explosion is likely to over-burden storage and communication systems. We design a comp

Frederick Manners

We provide a new proof of the inverse theorem for the Gowers $U^{s+1}$-norm over groups $H=\mathbb Z/N\mathbb Z$ for $N$ prime. This proof gives reasonable quantitative bounds (the worst parameters are double-exponential), and in particular does not make use of regularity or non-standard analysis, both of which are new for $s \ge 3$ in this setting.

Jan Heye Buss, He Wang, Yiming Xu, Julian Maklar

Time- and angle-resolved photoelectron spectroscopy (trARPES) is a powerful method to track the ultrafast dynamics of quasiparticles and electronic bands in energy and momentum space. We present a setup for trARPES with 22.3 eV extreme-ultraviolet (XUV) femtosecond pulses at 50-kHz repetition rate, which enables fast data acquisition and access to dynamics a

Teepanis Chachiyo, Hathaithip Chachiyo

A curious behavior of electron correlation energy is explored. Namely, the correlation energy is the energy that tends to drive the system toward that of the uniform electron gas. As such, the energy assumes its maximum value when a gradient of density is zero. As the gradient increases, the energy is diminished by a gradient suppressing factor, designed to

Thomas Oikonomou, G. Baris Bagci

We show that the Rényi entropy implies artificial biases not warranted by the data and incorrect updating information due to the finite-size of the data despite being additive. It is demonstrated that this is so because it does not conform to the system and subset independence axioms of Shore and Johnson. We finally show that the escort averaged constraints

Gaurav Gupta, Sergio Pequito, Paul Bogdan

Despite significant effort in understanding complex systems (CS), we lack a theory for modeling, inference, analysis and efficient control of time-varying complex networks (TVCNs) in uncertain environments. From brain activity dynamics to microbiome, and even chromatin interactions within the genome architecture, many such TVCNs exhibits a pronounced spatio-

Alec M. Hammond, Ryan M. Camacho

We develop and experimentally validate a novel neural network design framework for silicon photonics devices that is both practical and intuitive. The framework is applicable to nearly all known integrated photonics devices, but as case studies we consider simple waveguides and chirped Bragg Gratings. By using artificial neural networks, we decrease the comp

Jia Li, Yafei Song, Jianfeng Zhu, Lele Cheng

Many advances of deep learning techniques originate from the efforts of addressing the image classification task on large-scale datasets. However, the construction of such clean datasets is costly and time-consuming since the Internet is overwhelmed by noisy images with inadequate and inaccurate tags. In this paper, we propose a Ubiquitous Reweighting Networ

Julian A Lawn, Daniel S Kosov

Presented here is a nanowire model, consisting of coupled elastic membranes with the purpose of investigating thermal transport in quasi-one-dimensional quantum systems. The vibrations of each elastic membrane are quantized and the flow of the vibrational energy between adjacent membranes is allowed. The ends of the nanowire are attached to thermal baths hel

S. Bouhadou, Y. Ouknine

In the first part of this paper, we study RBSDEs in the case where the filtration is not quasi-left continuous and the lower obstacle is given by a predictable process. We prove the existence and uniqueness by using some results of optimal stopping theory in the predictable setting, some tools from the general theory of processes as the Merten's decompos

Ruochen Yang, Gaurav Gupta, Paul Bogdan

Identification of patterns from discrete data time-series for statistical inference, threat detection, social opinion dynamics, brain activity prediction has received recent momentum. In addition to the huge data size, the associated challenges are, for example, (i) missing data to construct a closed time-varying complex network, and (ii) contribution of unk

Martin Jankowiak

In this note we consider setups in which variational objectives for Bayesian neural networks can be computed in closed form. In particular we focus on single-layer networks in which the activation function is piecewise polynomial (e.g. ReLU). In this case we show that for a Normal likelihood and structured Normal variational distributions one can compute a v

C. R. Leedham-Green, E. A. O'Brien

For each family of finite classical groups, and their associated simple quotients, we provide an explicit presentation on a specific generating set of size at most 8. Since there exist efficient algorithms to construct this generating set in any copy of the group, our presentations can be used to verify claimed isomorphisms between representations of the cla

Fitsum A. Reda, Guilin Liu, Kevin J. Shih, Robert Kirby

We present an approach for high-resolution video frame prediction by conditioning on both past frames and past optical flows. Previous approaches rely on resampling past frames, guided by a learned future optical flow, or on direct generation of pixels. Resampling based on flow is insufficient because it cannot deal with disocclusions. Generative models curr

A. Roy, A. P. Misra, S. Banerjee

Cloud computing is recognized as one of the most promising solutions to information technology, e.g., for storing and sharing data in the web service which is sustained by a company or third party instead of storing data in a hard drive or other devices. It is essentially a physical storage system which provides large storage of data and faster computing to

Sergi Garcia, Javier Hervas, Ivana Gasulla

We report the first experimental demonstration of multi-cavity optoelectronic oscillators where the different cavities are hosted in a single multicore fiber. Different configurations are implemented on the same 20-m 7-core fiber link, exploiting both unbalanced dual-cavity operation (loop lengths are a multiple of a reference value) and multi-cavity Vernier

Alberto Marchisio, Muhammad Abdullah Hanif, Muhammad Shafique

Deep Neural Networks (DNNs) have been widely deployed for many Machine Learning applications. Recently, CapsuleNets have overtaken traditional DNNs, because of their improved generalization ability due to the multi-dimensional capsules, in contrast to the single-dimensional neurons. Consequently, CapsuleNets also require extremely intense matrix computations

Sachin Taneja, Massimo Alioto

This paper proposes an ultra-low power crypto-engine achieving sub-pJ/bit energy and sub-1K$μ$$m^2$ in 40nm CMOS, based on the Simon cryptographic algorithm. Energy and area efficiency are pursued via microarchitectural exploration, ultra-low voltage operation with high resiliency via latch-based pipelines, and power reduction techniques via multi-bit sequen

Hui Wang, Athanasios Tsiairis, Jinqiao Duan

We investigate the bifurcation phenomena for stochastic systems with multiplicative Gaussian noise, by examining qualitative changes in mean phase portraits. Starting from the Fokker-Planck equation for the probability density function of solution processes, we compute the mean orbits and mean equilibrium states. A change in the number or stability type, whe

J. E. Hirsch

When a magnetic field is applied to a ferromagnetic body it starts to spin (Einstein-de Haas effect). This demonstrates the intimate connection between the electron's magnetic moment $μ_B=e\hbar/2m_ec$, associated with its spin angular momentum $S=\hbar/2$, and ferromagnetism. When a magnetic field is applied to a superconducting body it also starts to s

Massimo Bartoletti, Tiziana Cimoli, Livio Pompianu, Sergio Serusi

The rise of blockchain technologies has given a boost to social good projects, which are trying to exploit various characteristic features of blockchains: the quick and inexpensive transfer of cryptocurrency, the transparency of transactions, the ability to tokenize any kind of assets, and the increase in trustworthiness due to decentralization. However, the

Salah E. Rihane, Bernadette Faye, Florian Luca, Alain Togbe

In this paper, we find all solutions of the exponential Diophantine equation $B_{n+1}^x-B_n^x=B_m$ in positive integer variables $(m, n, x)$, where $B_k$ is the $k$-th term of the Balancing sequence.

Michael B. Muhlestein, Benjamin M. Goldsberry, Andrew N. Norris, Michael R. Haberman

A material that exhibits Willis coupling has constitutive equations that couple the pressure-strain and momentum-velocity relationships. This coupling arises from subwavelength asymmetry and non-locality in heterogeneous media. This paper considers the problem of the scattering of a plane wave by a cylinder exhibiting Willis coupling using both analytical an

Yvain Quéau, Florian Leporcq, Ayman Alfalou

This study is concerned with the design of a Mueller imaging polarimeter for the visualization of spatially-varying Mueller matrix fields. A simplified calibration procedure is advocated, where all the optical elements are calibrated simultaneously rather than independently as in the state-of-the-art. This is shown to significantly reduce the bias inherent t

Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Paschalis C. Sofotasios, Sami Muhaidat

In the present contribution, we introduce a wireless optical communication-based system architecture which is shown to significantly improve the reliability and the spectral and power efficiency of the transcutaneous link in cochlear implants (CIs). We refer to the proposed system as optical wireless cochlear implant (OWCI).In order to provide a quantified u

Hemanshu Kaul, Jeffrey A. Mudrock

We study the list chromatic number of the Cartesian product of any graph $G$ and a complete bipartite graph with partite sets of size $a$ and $b$, denoted $χ_\ell(G \square K_{a,b})$. We have two motivations. A classic result on the gap between list chromatic number and the chromatic number tells us $χ_\ell(K_{a,b}) = 1 + a$ if and only if $b \geq a^a$. Sinc

Trek Sayed Ahmed

We study sheaves in the context of a duality theory for lattice structure endowed with extra operations, and in the context of forcing in a topos. Using Sheaf duality theory of Comer for cylindric algebras, we give a representation theorem of of distributive bounded lattices expanded by modalities (functions distributing over joins) as the continuous section

Nenad Teofanov

We define and study wave-front sets for weighted Fourier-Lebesgue spaces when the weights are moderate with respect to the associated functions for general sequences $\{ M_p\} $ which satisfy Komatsu's conditions $(M.1) - (M.3)'$. In particular, when $\{ M_p\} $ is the Gevrey sequence ($M_p = p!^s$, $s>1$) we recover some previously observed results.

S. S. Afonin, T. D. Solomko

We discuss the radial spectrum of light scalar mesons in the framework of spectral sum rules in the large-Nc (planar) limit of QCD. Two methods based on the use of linear radial Regge trajectories are presented. A special emphasis is placed on the appearance of scalar isoscalar state near 0.5 GeV. Within the considered sum rules, the existence of this meson

Yuan Hou, An Chang, Lei Zhang

In this paper, we define a homogeneous polynomial for a general hypergraph, and establish a remarkable connection between clique number and the homogeneous polynomial of a general hypergraph. For a general hypergraph, we explore some inequality relations among spectral radius, clique number and the homogeneous polynomial. We also give lower and upper bounds

Radu Tudor Ionescu, Andrei M. Butnaru

For many text classification tasks, there is a major problem posed by the lack of labeled data in a target domain. Although classifiers for a target domain can be trained on labeled text data from a related source domain, the accuracy of such classifiers is usually lower in the cross-domain setting. Recently, string kernels have obtained state-of-the-art res

Cheng Zhou, Tian Tian, Chao Gao, Wenli Gong

Ghost imaging needs massive measurements to obtain an image with good visibility and the imaging speed is usually very low. In order to realize real-time high-resolution ghost imaging of a target which is located in a scenario with a large field of view (FOV), we propose a high-speed multi-resolution progressive computational ghost imaging approach. The targ

B. Riaz, W. F. Thi, P. Caselli

We present a study of the CO isotopologues and the high-density tracers H$_{2}$CO, HCO$^{+}$, and CS in Class 0/I proto-brown dwarfs (proto-BDs). We have used the IRAM 30m telescope to observe the $^{12}$CO (2-1), $^{13}$CO (2-1), C$^{18}$O (2-1), C$^{17}$O (2-1), H$_{2}$CO (3-2), HCO$^{+}$ (3-2), and CS (5-4) lines in 7 proto-BDs. The hydrogen column densit

Salim A. Messaoudi, Michael Pokojovy, Belkacem Said-Houari

In this paper, we consider nonlinear thermoelastic systems of Timoshenko type in a one-dimensional bounded domain. The system has two dissipative mechanisms being present in the equation for transverse displacement and rotation angle - a frictional damping and a dissipation through hyperbolic heat conduction modelled by Cattaneo's law, respectively. The

Tomohiro Nakama, Yi Wang

Recently, the formation of primordial black holes (PBHs) from the collapse of primordial fluctuations has received much attention. The abundance of PBHs formed during radiation domination is sensitive to the tail of the probability distribution of primordial fluctuations. We quantify the level of fine-tuning due to this sensitivity. For example, if the main

Nima Arkani-Hamed, Paolo Benincasa

The concepts of Lorentz invariance of local (flat space) physics, and unitarity of time evolution and the S-matrix, are famously rigid and robust, admitting no obvious consistent theoretical deformations, and confirmed to incredible accuracy by experiments. But neither of these notions seem to appear directly in describing the spatial correlation functions a

Gunnar Carlsson, Rickard Brüel Gabrielsson

We perform topological data analysis on the internal states of convolutional deep neural networks to develop an understanding of the computations that they perform. We apply this understanding to modify the computations so as to (a) speed up computations and (b) improve generalization from one data set of digits to another. One byproduct of the analysis is t

Gaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov, Nilesh Chakraborty

In this paper, we conduct an empirical investigation of neural query graph ranking approaches for the task of complex question answering over knowledge graphs. We experiment with six different ranking models and propose a novel self-attention based slot matching model which exploits the inherent structure of query graphs, our logical form of choice. Our prop

Yanyuan Ma, Shaoli Wang, Lin Xu, Weixin Yao

In fitting a mixture of linear regression models, normal assumption is traditionally used to model the error and then regression parameters are estimated by the maximum likelihood estimators (MLE). This procedure is not valid if the normal assumption is violated. To relax the normal assumption on the error distribution hence reduce the modeling bias, we prop

Sujay Kumar Jauhar, Michael Gamon, Patrick Pantel

Natural language processing is heavily Anglo-centric, while the demand for models that work in languages other than English is greater than ever. Yet, the task of transferring a model from one language to another can be expensive in terms of annotation costs, engineering time and effort. In this paper, we present a general framework for easily and effectivel

Juan José Nuño Ballesteros, Rodrigo Mendes

We show that the knot type of the link of a real analytic map germ with isolated singularity $f\colon(\mathbb{R}^2,0)\to(\mathbb{R}^4,0)$ is a complete invariant for $C^0$-$\mathscr A$-equivalence. Moreover, we also prove that isolated instability implies $C^0$-finite determinacy, giving an explicit estimate for its degree. For the general case of real analy

Tommaso Morresi, Andrea Pedrielli, Silvio a Beccara, Ruggero Gabbrielli

In this work a systematic approach to the search for all-$sp^2$ bonded carbon allotropes with low density is presented. In particular, we obtain a number of novel energetically stable crystal structures, whose arrangement is closely related to the topology of graphene, by modifying the packing of congruent discs under the condition of local stability. Our pr

Peter Frankl, Andrey Kupavskii

Given a family $\mathcal F\subset 2^{[n]}$, its diversity is the number of sets not containing an element with the highest degree. The concept of diversity has proven to be very useful in the context of $k$-uniform intersecting families. In this paper, we study (different notions of) diversity in the context of other extremal set theory problems. One of the

Roohollah Etemadi, Jianguo Lu

Clustering coefficient is one of the most important metrics to understand the complex structure of networks. This paper addresses the estimation of clustering coefficient in network streams. There have been substantial work in this area, most of conducting empirical comparisons of various algorithms. The variance and the bias of the estimators have not been

Anthony Rizzi

The PBR theorem gives insight into how quantum mechanics describes a physical system. This paper explores PBRs' general result and shows that it does not disallow the ensemble interpretation of quantum mechanics and maintains, as it must, the fundamentally statistical character of quantum mechanics (QM). This is illustrated by drawing an analogy with an

Stefan Hell, Vasileios Argyriou

Virtual Reality (VR) can cause an unprecedented immersion and feeling of presence yet a lot of users experience motion sickness when moving through a virtual environment. Rollercoaster rides are popular in Virtual Reality but have to be well designed to limit the amount of nausea the user may feel. This paper describes a novel framework to get automated rati

Clément Berenfeld, Ery Arias-Castro

We propose a simple, geometrically-motivated construction of smooth random paths in the plane. The construction is such that, with probability one, the paths have finite curvature everywhere (and the realizations are visually pleasing when simulated on a computer). Our construction is Markov of order 2. We show that a simpler construction which is Markov of

Jiacheng Zhang, Yang Liu, Huanbo Luan, Jingfang Xu

Although neural machine translation has made significant progress recently, how to integrate multiple overlapping, arbitrary prior knowledge sources remains a challenge. In this work, we propose to use posterior regularization to provide a general framework for integrating prior knowledge into neural machine translation. We represent prior knowledge sources

Todd Arbogast, Zhen Tao

We develop a locally conservative, finite element method for simulation of two-phase flow on quadrilateral meshes that minimize the number of degrees of freedom (DoFs) subject to accuracy requirements and the DoF continuity constraints. We use a mixed finite element method (MFEM) for the flow problem and an enriched Galerkin method (EG) for the transport, st

Konstantinos Horaites, Stanislav Boldyrev, Mikhail V. Medvedev

We propose a kinetic model describing the formation of the strahl and halo electron populations in the solar wind. We demonstrate that the suprathermal electrons propagating from the sun along the Parker-spiral magnetic field lines are progressively focused into a narrow strahl at heliospheric distances $r\lesssim 1$ AU, while at $r\gtrsim 1$ AU the width of

G. Zasowski, M. Schultheis, S. Hasselquist, K. Cunha

We present an overview of the distributions of 11 elemental abundances in the Milky Way&#39;s inner regions, as traced by APOGEE stars released as part of SDSS Data Release 14/15 (DR14/DR15), including O, Mg, Si, Ca, Cr, Mn, Co, Ni, Na, Al, and K. This sample spans ~4000 stars with R_GC<4 kpc, enabling the most comprehensive study to date of these abundances

Tyson B. Littenberg, Nicolas Yunes

The observation of low-frequency gravitational waves with the Laser Interferometer Space Antenna will allow the study of new sources of gravitational radiation that are not accessible by ground-based instruments. Gravitational wave sources provide invaluable information both about their astrophysics, as well as the nature of the gravitational interaction in

Kirill A. Kopotun, Dany Leviatan, Igor A. Shevchuk

In this paper, among other things, we show that, given $r\in N$, there is a constant $c=c(r)$ such that if $f\in C^r[-1,1]$ is convex, then there is a number ${\mathcal N}={\mathcal N}(f,r)$, depending on $f$ and $r$, such that for $n\ge{\mathcal N}$, there are convex piecewise polynomials $S$ of order $r+2$ with knots at the Chebyshev partition, satisfying

S. Mazdak Abulnaga, Jonathan Rubin

We present a fully convolutional neural network for segmenting ischemic stroke lesions in CT perfusion images for the ISLES 2018 challenge. Treatment of stroke is time sensitive and current standards for lesion identification require manual segmentation, a time consuming and challenging process. Automatic segmentation methods present the possibility of accur

Xue Zhang, Cihan Tepedelenlioglu, Mahesh K. Banavar, Andreas Spanias

In this paper, localization using narrowband communication signals are considered in the presence of fading channels with time of arrival measurements. When narrowband signals are used for localization, due to existing hardware constraints, fading channels play a crucial role in localization accuracy. In a location estimation formulation, the Cramer-Rao lowe

Nuno Costa Dias, Cristina Jorge, Joao Nuno Prata

Given a linear ordinary differential equation (ODE) on $\RE$ and a set of interface conditions at a finite set of points $I \subset \RE$, we consider the problem of determining another differential equation whose {\it global} solutions satisfy the original ODE on $\RE \backslash I $, and the interface conditions at $I $. Using an extension of the product of

Lars Mattsson, Akshay Bhatnagar, Fred A. Gent, Beatriz Villarroel

We present high resolution ($1024^3$) simulations of super-/hyper-sonic isothermal hydrodynamic turbulence inside an interstellar molecular cloud (resolving scales of typically 20 -- 100 AU), including a multi-disperse population of dust grains, i.e., a range of grain sizes is considered. Due to inertia, large grains (typical radius $a \gtrsim 1.0\,μ$m) will

Sayantan Choudhury, Arkaprava Mukherjee

In this article, using the principles of Random Matrix Theory (RMT), we give a measure of quantum chaos by quantifying Spectral From Factor (SFF) appearing from the computation of two-point Out of Time Order Correlation function (OTOC) expressed in terms of square of the commutator bracket of quantum operators which are separated in time. We also provide a s

I. E. Assimakis, D. Bonatsos, A. Martinou, S. Sarantopoulou

The increasing deformation in atomic nuclei leads to the change of the classical magic numbers (2,8,20,28,50,82..) which dictate the arrangement of nucleons in complete shells. The magic numbers of the three-dimensional harmonic oscillator (2,8,20,40,70...) emerge at deformations around epsilon=0.6. At lower deformations the two sets of magic numbers antagon

M. Castro, A. P. Espejo, N. M. Vargas, D. Altbir

Magnetic nanorings have been widely studied due to their potential applications in spintronic and magnonic devices. In this work, by means of analytical calculations and micromagnetic simulations we have analyzed the magnetic energy of nanorings with variable anisotropy along their radius. Four magnetic states, including two new magnetic configurations, here

Adrian Penate-Sanchez, Lourdes Agapito

We present 3D Pick & Mix, a new 3D shape retrieval system that provides users with a new level of freedom to explore 3D shape and Internet image collections by introducing the ability to reason about objects at the level of their constituent parts. While classic retrieval systems can only formulate simple searches such as &#34;find the 3D model that is most

Surafel M. Lakew, Aliia Erofeeva, Marcello Federico

Both research and commercial machine translation have so far neglected the importance of properly handling the spelling, lexical and grammar divergences occurring among language varieties. Notable cases are standard national varieties such as Brazilian and European Portuguese, and Canadian and European French, which popular online machine translation service

Georgios Varnavides, Adam S. Jermyn, Polina Anikeeva, Prineha Narang

Despite the ubiquity of applications of heat transport across nanoscale interfaces, including integrated circuits, thermoelectrics, and nanotheranostics, an accurate description of phonon transport in these systems remains elusive. Here we present a theoretical and computational framework to describe phonon transport with position, momentum and scattering ev

Aditi Raghunathan, Jacob Steinhardt, Percy Liang

Despite their impressive performance on diverse tasks, neural networks fail catastrophically in the presence of adversarial inputs---imperceptibly but adversarially perturbed versions of natural inputs. We have witnessed an arms race between defenders who attempt to train robust networks and attackers who try to construct adversarial examples. One promise of

Kaiyi Ji, Yingbin Liang

An important class of distance metrics proposed for training generative adversarial networks (GANs) is the integral probability metric (IPM), in which the neural net distance captures the practical GAN training via two neural networks. This paper investigates the minimax estimation problem of the neural net distance based on samples drawn from the distributi

Tong Zhang, Pan Ji, Mehrtash Harandi, Richard Hartley

Subspace clustering algorithms are notorious for their scalability issues because building and processing large affinity matrices are demanding. In this paper, we introduce a method that simultaneously learns an embedding space along subspaces within it to minimize a notion of reconstruction error, thus addressing the problem of subspace clustering in an end

Li-Wei Hung, Davyd Betchkal, Sharolyn J. Anderson, Damon Joyce

The US National Park Service (NPS) assesses the night sky quality over parks by capturing a series of overlapping images to obtain a mosaic view of the entire night sky. The NPS Night Skies Program has integrated a sequence of scripts and software packages (a &#34;pipeline&#34;) to process and create the hemispherical mosaic images. This processing pipeline

Sean K. Sather-Wagstaff, Tony Se, Sandra Spiroff

We continue our study of ladder determinantal rings over a field $\mathsf k$ from the perspective of semidualizing modules. In particular, given a ladder of variables $Y$, we show that the associated ladder determinantal ring $\mathsf k[Y]/I_2(Y)$ admits exactly $2^n$ non-isomorphic semidualizing modules where $n$ is determined from the combinatorics of the

Nicola Arcozzi, Pavel Mozolyako, Karl-Mikael Perfekt

In this note we investigate the multi-parameter Potential Theory on the weighted $d$-tree (Cartesian product of several copies of uniform dyadic tree), which is connected to the discrete models of weighted Dirichlet spaces on the polydisc. We establish some basic properties of the respective potentials, capacities and equilibrium measures (in particular in t

Dayue Chen, Peng Chen, Nina Gantert, Dominik Schmid

We consider exclusion processes on a rooted $d$-regular tree. We start from a Bernoulli product measure conditioned on having a particle at the root, which we call the tagged particle. For $d\geq 3$, we show that the tagged particle has positive linear speed and satisfies a central limit theorem. We give an explicit formula for the speed. As a key step in th

Philipp Jordan, Paula Alexandra Silva

Science fiction literature, comics, cartoons and, in particular, audio-visual materials, such as science fiction movies and shows, can be a valuable addition in Human-computer interaction (HCI) Education. In this paper, we present an overview of research relative to future directions in HCI Education, distinct crossings of science fiction in HCI and Computer

Jeff Greensite, Evan Owen

We consider the four point connected correlator representing a static quark-antiquark pair separated by a spatial distance R, propagating for a Euclidean time T. This function is computed by lattice Monte Carlo in SU(2) pure gauge theory at lattice couplings $β=2.2$ and $β=2.5$ in both Coulomb and Landau gauges. The Coulomb gauge correlator is well behaved,

Renata Kallosh, Andrei Linde, Yusuke Yamada

We revisit phenomenological as well as string-theoretical aspects of D-brane inflation cosmological models. Phenomenologically these models stand out on par with $α$-attractors, as models with Planck-compatible values of $n_s$, moving down to the sweet spot in the data with decreasing value of $r$. On the formal side we present a new supersymmetric version o

Benjamin R. Safdi, Zhiquan Sun, Alexander Y. Chen

It has been suggested that radio telescopes may be sensitive to axion dark matter that resonantly converts to radio photons in the magnetospheres surrounding neutron stars (NSs). In this work, we closely examine this possibility by calculating the radiated power from and projected sensitivity to axion dark matter conversion in ensembles of NSs within astroph

Nouman Butt, Simon Catterall

We study a model of four reduced staggered fields transforming in the bifundamental representation of a $SU(2)\times SU(2)$ symmetry group where just one of the SU(2) factors is gauged. This field content and symmetries are similar to a Higgs-Yukawa model that has been studied recently. The key observation in the latter work is that fermions acquire masses a

Abhisekh Sankaran

This article gives a summary of the author&#39;s Ph.D. dissertation (arXiv:1609.06297). In addition to an overview of notions and results, it also provides sketches of various proofs and simplified presentations of certain abstract results of the dissertation, that concern tree representations of structures. Further, some extensions of the dissertation resul

Dhiraj Madan, Dinesh Raghu, Gaurav Pandey, Sachindra Joshi

Recently several deep learning based models have been proposed for end-to-end learning of dialogs. While these models can be trained from data without the need for any additional annotations, it is hard to interpret them. On the other hand, there exist traditional state based dialog systems, where the states of the dialog are discrete and hence easy to inter

J. Carroll, J. Coleman, G. Davies, M. Lockwood

Technology developed for the T2K electromagnetic calorimeter has been adapted to make a small footprint, reliable, segmented detector to characterise anti-neutrinos emitted by nuclear reactors. The device has been developed and demonstrated by the University of Liverpool and underwent field tests at the Wylfa Magnox Reactor on Anglesey, UK. It was situated i

Paola Marini, Ludovic Mathieu, Mourad Aïche, Serge Czajkowski

Absolute measurements of neutron fluence are an essential prerequisite of neutron-induced cross section measurements, neutron beam lines characterization and dosimetric investigations. The H(n,p) elastic scattering cross section is a very well known standard used to perform precise neutron flux measurements in high precision measurements. The use of this tec

Mario Roldán, Radu Saghin, Jiagang Yang

In this article we study the regularity of the topological and metric entropy of partially hyperbolic flows with two-dimensional center direction. We show that the topological entropy is upper semicontinuous with respect to the flow, and we give an example where the lower semicontinuity fails. We also show that if such a flow has no fixed points, then it is

Mirac Suzgun, Yonatan Belinkov, Stuart M. Shieber

Recurrent Neural Networks (RNNs) are theoretically Turing-complete and established themselves as a dominant model for language processing. Yet, there still remains an uncertainty regarding their language learning capabilities. In this paper, we empirically evaluate the inductive learning capabilities of Long Short-Term Memory networks, a popular extension of

Joseph Chuang, Radha Kessar

We show that perverse equivalences between module categories of finite-dimensional algebras preserve rationality. As an application, we give a connection between some famous conjectures from the modular representation theory of finite groups, namely Broué&#39;s Abelian Defect Group conjecture and Donovan&#39;s Finiteness conjectures.

James O&#39; Neill, Danushka Bollegala

This paper carries out an empirical analysis of various dropout techniques for language modelling, such as Bernoulli dropout, Gaussian dropout, Curriculum Dropout, Variational Dropout and Concrete Dropout. Moreover, we propose an extension of variational dropout to concrete dropout and curriculum dropout with varying schedules. We find these extensions to pe

A. Fieramosca, L. De Marco, M. Passoni, L. Polimeno

Hybrid organic-inorganic perovskites have emerged as very promising materials for photonic applications, thanks to the great synthetic versatility that allows to tune their optical properties. In the two-dimensional (2D) crystalline form, these materials behave as multiple quantum-well heterostructures with stable excitonic resonances up to room temperature.

Friedrich Götze, Anna Gusakova, Zakhar Kabluchko, Dmitry Zaporozhets

For $-π\leqβ_1<β_2\leqπ$ denote by $Φ_{β_1,β_2}(Q)$ the number of algebraic numbers on the unit circle with arguments in $[β_1,β_2]$ of degree $2m$ and with elliptic height at most $Q$. We show that \[ Φ_{β_1,β_2}(Q)=Q^{m+1}\int\limits_{β_1}^{β_2}{p(t)}\,{\rm d}t+O\left(Q^m\,\log Q\right),\quad Q\to\infty, \] where $p(t)$ coincides up to a constant factor wi

Oleg Inozemcev, Igor Volovich

Eigenstate thermalization hypothesis (ETH) is discussed. We point out that the common formulation of the ETH suffers from the mixing of random and deterministic variables. We suggest a modified formulation of the ETH which includes only deterministic variables. We also show that this formulation of the ETH implies thermalization as well.

Jerzy Matyjasek

Vacuum polarization of the quantized massive fields in Bianchi type I spacetime is investigated from the point of view of the adiabatic approximation and the Schwinger-DeWitt method. It is shown that both approaches give the same results that can be used in construction of the trace of the stress-energy tensor of the conformally coupled fields. The stress-en

David A. Monge, Elina Pacini, Cristian Mateos, Enrique Alba

Cloud Computing is becoming the leading paradigm for executing scientific and engineering workflows. The large-scale nature of the experiments they model and their variable workloads make clouds the ideal execution environment due to prompt and elastic access to huge amounts of computing resources. Autoscalers are middleware-level software components that al

Holley Friedlander

Weyl group multiple Dirichlet series are Dirichlet series in $r$ complex variables, with analytic continuation to $\mathbb{C}^r$ and a group of functional equations isomorphic to the Weyl group of a reduced root system of rank $r$. Such series may be defined for any global field $K$, but in the case when $K$ is an algebraic function field they are expected t