March 2018 arXiv papers

Taylor Dupuy, David Zureick-Brown

Faltings showed that "arithmetic Kodaira--Spencer classes" satisfying a certain compatibility axiom cannot exist. By modifying his definitions slightly, we show that the Deligne--Illusie classes satisfy what could be considered an "arithmetic Kodaira--Spencer" compatibility condition. Afterwards we discuss a "wittfinitesimal Torelli probl

Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini, Simon J. Thorpe

The primate visual system has inspired the development of deep artificial neural networks, which have revolutionized the computer vision domain. Yet these networks are much less energy-efficient than their biological counterparts, and they are typically trained with backpropagation, which is extremely data-hungry. To address these limitations, we used a deep

Runlin Zhang

Given a maximal $\mathbb{Q}$-torus in $SL(N,\mathbb{Q})$, its orbit from identity coset in $SL(N,\mathbb{R})/SL(N,\mathbb{Z})$ naturally carries a possibly infinite Haar measure. We classify all possible limit measures of it when translated by a sequence of elements from $SL(N,\mathbb{R})$. This is a natural extension of Shapira and Zheng's work where on

Jens Boos

When a positively charged impurity is placed inside a cold metal, the resulting charge density around that object exhibits characteristic ripples to negative values, known as Friedel oscillations. In this essay, we describe a somewhat analogous effect in (i) linearized higher-derivative gravity and (ii) linearized infinite-derivative "ghost-free" gra

Claudia Ceci, Katia Colaneri, Alessandra Cretarola

In this paper we investigate the pricing problem of a pure endowment contract when the insurer has a limited information on the mortality intensity of the policyholder. The payoff of this kind of policies depends on the residual life time of the insured as well as the trend of a portfolio traded in the financial market, where investments in a riskless asset,

Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein

A major goal of unsupervised learning is to discover data representations that are useful for subsequent tasks, without access to supervised labels during training. Typically, this involves minimizing a surrogate objective, such as the negative log likelihood of a generative model, with the hope that representations useful for subsequent tasks will arise as

Xinwei He, A. J. Hildebrand, Yuchen Li, Yunyi Zhang

Let $S_{a,b}$ denote the sequence of leading digits of $a^n$ in base $b$. It is well known that if $a$ is not a rational power of $b$, then the sequence $S_{a,b}$ satisfies Benford's Law; that is, digit $d$ occurs in $S_{a,b}$ with frequency $\log_{b}(1+1/d)$, for $d=1,2,\dots,b-1$. In this paper, we investigate the \emph{complexity} of such sequences. W

Alejandro Cabrera, Matias del Hoyo, Enrique Pujals

In this paper we relate the study of actions of discrete groups over connected manifolds to that of their orbit spaces seen as differentiable stacks. We show that the orbit stack of a discrete dynamical system on a simply connected manifold encodes the dynamics up to conjugation and inversion. We also prove a generalization of this result for arbitrary discr

Lazar Valkov, Dipak Chaudhari, Akash Srivastava, Charles Sutton

We present a neurosymbolic framework for the lifelong learning of algorithmic tasks that mix perception and procedural reasoning. Reusing high-level concepts across domains and learning complex procedures are key challenges in lifelong learning. We show that a program synthesis approach that combines gradient descent with combinatorial search over programs c

A. Salman Avestimehr, Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi

Dealing with the shear size and complexity of today's massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bottleneck that arises in such modern distributed computing environments is that some of the worker nodes may run slow. These nodes a.k.a.~stragglers can significantly slow down

Vitor Balestro, Horst Martini

We aim to study the classical Rosenthal-Szasz inequality for a plane whose geometry is given by a norm. This inequality states that the bodies of constant width have the largest perimeter among all planar convex bodies of given diameter. In the case where the unit circle of the norm is given by a Radon curve, we obtain an inequality which is completely analo

Wei Sun

Let $D$ be a bounded Lipschitz domain of $\mathbb{R}^d$. We consider the complement value problem $$ \left\{\begin{array}{l}(Δ+a^αΔ^{α/2}+b\cdot\nabla+c)u+f=0\ \ {\rm in}\ D,\\ u=g\ \ {\rm on}\ D^c. \end{array}\right.$$ Under mild conditions, we show that there exists a unique bounded continuous weak solution. Moreover, we give an explicit probabilistic repr

Jeferson de Oliveira, R. D. B. Fontana

We study a quintessential black hole solution in three dimensions, with mass and quintessence charge. By exploring the Carter-Penrose diagram, we show the presence of spacelike and lightlike singularities in the metric, given different values for the quintessence parameter, as well as an AdS-like spatial infinity and event horizon encapsulating the singulari

Ali Taleb Zadeh Kasgari, Walid Saad, Merouane Debbah

Human-centric applications such as virtual reality and immersive gaming will be central to the future wireless networks. Common features of such services include: a) their dependence on the human user's behavior and state, and b) their need for more network resources compared to conventional cellular applications. To successfully deploy such applications

Matthias Beck, Emerson Leon

A famous and wide-open problem, going back to at least the early 1970's, concerns the classification of chromatic polynomials of graphs. Toward this classification problem, one may ask for necessary inequalities among the coefficients of a chromatic polynomial, and we contribute such inequalities when a chromatic polynomial $χ_G(n) = χ^*_0 \binom {n+d} d

Krishnendu Chatterjee, Monika Henzinger, Veronika Loitzenbauer, Simin Oraee

Given a model and a specification, the fundamental model-checking problem asks for algorithmic verification of whether the model satisfies the specification. We consider graphs and Markov decision processes (MDPs), which are fundamental models for reactive systems. One of the very basic specifications that arise in verification of reactive systems is the str

Krzysztof Zajkowski

We discuss various forms of the Luxemburg norm in spaces of random vectors with coordinates belonging to the classical Orlicz spaces of exponential type. We prove equivalent relations between some kinds of these forms. We also show when the so-called uniform norm is majorized by norms of coordinates up to some constants. We give an application of other norm

Shmuel Friedland, Stéphane Gaubert

We extend some characterizations and inequalities for the eigenvalues of nonnegative matrices, such as Donsker-Varadhan, Friedland-Karlin, Karlin-Ost inequalities, to nonnegative tensors. Our approach involves a correspondence between nonnegative tensors, ergodic control and entropy maximization: we show in particular that the logarithm of the spectral radiu

Peter Balazs, Mitra Shamsabadi, Ali Akbar Arefijamaal, Asghar Rahimi

The Gram matrix is defined for Bessel sequences by combining synthesis with subsequent analysis operators. If different sequences are used and an operator U is inserted we reach so called U-cross Gram matrices. This can be seen as reinterpretation of the matrix representation of operators using frames. In this paper we investigate some necessary or sufficien

Nathan Glatt-Holtz, David Herzog, Scott McKinley, Hung Nguyen

The generalized Langevin equation (GLE) is a stochastic integro-differential equation that has been used to describe the velocity of microparticles in viscoelastic fluids. In this work, we consider the large-time asymptotic properties of a Markovian approximation to the GLE in the presence of a wide class of external potential wells. The qualitative behavior

Viacheslav V. Nikulin

Var3: In our papers 2013--2018 we classified degenerations and Picard lattices of Kahlerian K3 surfaces with finite symplectic automorphism groups of high order. For remaining groups of small order: $D_6$, $C_4$, $(C_2)^2$, $C_3$, $C_2$ and $C_1$ it was not completely considered. Cases of $D_6$ and $C_4$ were recently completely considered in [19] and [20].

Eleftherios N. Nikolidakis

We provide a description for the Bellman function related to the Carleson Imbedding theorem, first mentioned in [4], with the use of the Hardy operator.

David Cheng, Ashwin Ananthakrishnan, Tianxi Cai

We consider the problem of estimating the average treatment effect (ATE) in a semi-supervised learning setting, where a very small proportion of the entire set of observations are labeled with the true outcome but features predictive of the outcome are available among all observations. This problem arises, for example, when estimating treatment effects in el

Adam Czajka, Kevin W. Bowyer

Iris recognition is increasingly used in large-scale applications. As a result, presentation attack detection for iris recognition takes on fundamental importance. This survey covers the diverse research literature on this topic. Different categories of presentation attack are described and placed in an application-relevant framework, and the state of the ar

Binal P Bruno, Ahmed Raouf Fahmy, Moritz Stürmer, Ulrike Wallrabe

In this paper, we compare the performance of 8 PZT ceramics and one PMN-PT material for typical bending actuator applications. This includes the measurement of non-linear transverse charge coefficient at high electric field strength and related quantities such as the Young's modulus, relative permittivity, coercive field and their temperature dependencie

Soumyakanti Bose, M. Sanjay Kumar

Non-Gaussian entangled states of light have been found to improve the success of quantum telepor- tation. Earlier works in the literature focussed mainly on two-mode non-Gaussian states generated by de-Gaussification of two-mode squeezed vacuum states. In the current work, we study quan- tum teleportation with a class of non-Gaussian entangled resource state

Romulo Rougemont, Renato Critelli, Jorge Noronha

We compute the homogeneous limit of non-hydrodynamic quasinormal modes (QNM's) of a phenomenologically realistic Einstein-Maxwell-Dilaton (EMD) holographic model for the Quark-Gluon Plasma (QGP) that is able to: i) {\it quantitatively} describe state-of-the-art lattice results for the QCD equation of state and higher order baryon susceptibilities with $2

L. Jin, Z. Song

We propose an incident direction independent wave propagation generated by properly assembling different unidirectional destructive interferences (UDIs), which is a consequence of the appropriate match between synthetic magnetic fluxes and the incident wave vector. Single-direction lasing at spectral singularity is feasible without introducing nonlinearity.

Gabriel Cozzella, Carlo Giunti

Here we discuss the description of flavor neutrinos produced or detected in processes which involve more than one neutrino. We show that in these cases flavor neutrinos cannot be separately described by pure states, but require a density matrix description. We consider explicitly the examples of $ν_{e}$ and $\barν_μ$ production in $μ^{+}$ decay and $ν_μ$ det

Karthik Duraisamy, Gianluca Iaccarino, Heng Xiao

Data from experiments and direct simulations of turbulence have historically been used to calibrate simple engineering models such as those based on the Reynolds-averaged Navier--Stokes (RANS) equations. In the past few years, with the availability of large and diverse datasets, researchers have begun to explore methods to systematically inform turbulence mo

Olga Paris-Romaskevich, Pascal Hubert

Consider a periodic tiling of a plane by equal triangles obtained from the equilateral tiling by a linear transformation. We study a following tiling billiard: a ball follows straight segments and bounces of the boundaries of the tiles into neighbouring tiles in such a way that the coefficient of refraction is equal to -1. We show that almost all the traject

Akio Fujiwara, Koichi Yamagata

We herein develop a theory of contiguity in the quantum domain based upon a novel quantum analogue of the Lebesgue decomposition. The theory thus formulated is pertinent to the weak quantum local asymptotic normality introduced in the previous paper [Yamagata, Fujiwara, and Gill, \textit{Ann. Statist.}, \textbf{41} (2013) 2197-2217.], yielding substantial en

Melody Chan, Brian Osserman, Nathan Pflueger

We prove a smoothness result for spaces of linear series with prescribed ramification on twice-marked elliptic curves. In characteristic 0, we then apply the Eisenbud-Harris theory of limit linear series to deduce a new proof of the Gieseker-Petri theorem, along with a generalization to spaces of linear series with prescribed ramification at up to two points

Fernando Navarro, Sailesh Conjeti, Federico Tombari, Nassir Navab

Within medical imaging, manual curation of sufficient well-labeled samples is cost, time and scale-prohibitive. To improve the representativeness of the training dataset, for the first time, we present an approach to utilize large amounts of freely available web data through web-crawling. To handle noise and weak nature of web annotations, we propose a two-s

Tomoki Kawahira, Masashi Kisaka

In this paper we prove the following: Take any "small Mandelbrot set" and zoom in a neighborhood of a parabolic or Misiurewicz parameter in it, then we can see a quasiconformal image of a Cantor Julia set which is a perturbation of a parabolic or Misiurewicz Julia set. Furthermore, zoom in its middle part, then we can see a certain nested structure (

Yi Li, Gu Wang, Xiangyang Ji, Yu Xiang

Estimating the 6D pose of objects from images is an important problem in various applications such as robot manipulation and virtual reality. While direct regression of images to object poses has limited accuracy, matching rendered images of an object against the observed image can produce accurate results. In this work, we propose a novel deep neural networ

Jason Z. Kim, Zhixin Lu, Steven H. Strogatz, Danielle S. Bassett

Understanding conformational change is crucial for programming and controlling the function of many mechanical systems such as allosteric enzymes and tunable metamaterials. Of particular interest is the relationship between the network topology or geometry and the specific motions observed under controlling perturbations. We study this relationship in mechan

D. Vasylyev, W. Vogel, A. A. Semenov

The atmospheric turbulence is the main factor that influences quantum properties of propagating optical signals and may sufficiently degrade the performance of quantum communication protocols. The probability distribution of transmittance (PDT) for free-space channels is the main characteristics of the atmospheric links. Applying the law of total probability

Aya Kubota, Chris Done

We develop a new spectral model for the broadband spectral energy distribution (SED) of Active Galactic Nuclei (AGN). This includes an outer standard disc, an inner warm Comptonising region to produce the soft X-ray excess and a hot corona. We tie these together energetically by assuming Novikov-Thorne emissivity, and use this to define a size scale for the

Changpeng Shao

HHL algorithm \cite{harrow} to solve linear system is a powerful and efficient quantum technique to deal with many matrix operations (such as matrix multiplication, powers and inversion). It inspires many applications in quantum machine learning \cite{biamonte, dunjko}. However, due to the restrictions of HHL algorithm itself, many quantum machine learning a

Kyle Richardson

Recent work by (Richardson and Kuhn, 2017a,b; Richardson et al., 2018) looks at semantic parser induction and question answering in the domain of source code libraries and APIs. In this brief note, we formalize the representations being learned in these studies and introduce a simple domain specific language and a systematic translation from this language to

Piotr Mirowski, Matthew Koichi Grimes, Mateusz Malinowski, Karl Moritz Hermann

Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in the study and development of artificial intelligence. Long-range navigation is a complex cognitive task that relies on developing an internal representation of space, grounded by recognisable landmarks and robust visual processi

Ayanendranath Basu, Abhik Ghosh, Abhijit Mandal, Nirian Martin

We consider the problem of robust inference under the generalized linear model (GLM) with stochastic covariates. We derive the properties of the minimum density power divergence estimator of the parameters in GLM with random design and use this estimator to propose robust Wald-type tests for testing any general composite null hypothesis about the GLM. The as

Huaiming Guo, Xingchuan Zhu, Shiping Feng, Richard T. Scalettar

The pairing symmetry of an effective Hamiltonian for interacting fermions on a twisted bilayer graphene superlattice is studied with the determinant quantum Monte Carlo method. The model has the symmetry of a triangle lattice and a nearly-flat low energy band, features which underlie the magic-angle twisted bilayer graphene superlattice. We show that the low

J. D. Alvarado, S. Dantas, E. Mohr, D. Rautenbach

Fricke, Hedetniemi, Hedetniemi, and Hutson asked whether every tree with domination number $γ$ has at most $2^γ$ minimum dominating sets. Bien gave a counterexample, which allows to construct forests with domination number $γ$ and $2.0598^γ$ minimum dominating sets. We show that every forest with domination number $γ$ has at most $2.4606^γ$ minimum dominatin

B. X. Wang, C. Y. Zhao

We study the topological optical states in one-dimensional (1D) dimerized ultracold atomic chains, as an extension of the Su-Schrieffer-Heeger (SSH) model. By taking the fully retarded near-field and far-field dipole-dipole interactions into account, we describe the system by an effective non-Hermitian Hamiltonian, vastly different from the Hermitian Hamilto

Coralia Cartis, Jan Fiala, Benjamin Marteau, Lindon Roberts

We present DFO-LS, a software package for derivative-free optimization (DFO) for nonlinear Least-Squares (LS) problems, with optional bound constraints. Inspired by the Gauss-Newton method, DFO-LS constructs simplified linear regression models for the residuals. DFO-LS allows flexible initialization for expensive problems, whereby it can begin making progres

Cristiano Capone, Guido Gigante, Paolo Del Giudice

The combination of new recording techniques in neuroscience and powerful inference methods recently held the promise to recover useful effective models, at the single neuron or network level, directly from observed data. The value of a model of course should critically depend on its ability to reproduce the dynamical behavior of the modeled system; however,

Zhaoyu Fei, H. T. Quan, Fei Liu

We investigate quantum corrections to the classical work characteristic function (CF) as a semiclassical approximation to the full quantum work CF. In addition to explicitly establishing the quantum-classical correspondence of the Feynman-Kac formula, we find that these quantum corrections must be in even powers of $\hbar$. Exact formulas of the lowest corre

Ingrid Rotter

The aim of the paper is to study the question whether or not equilibrium states exist in open quantum systems that are embedded in at least two environments and are described by a non-Hermitian Hamilton operator $\cal H$. The eigenfunctions of $\cal H$ contain the influence of exceptional points (EPs) as well as that of external mixing (EM) of the states via

Michael Kammermeier, Paul Wenk, Florian Dirnberger, Dominique Bougeard

We theoretically investigate the D'yakonov-Perel' spin relaxation properties in diffusive wurtzite semiconductor nanowires and their impact on the quantum correction to the conductivity. Although the lifetime of the long-lived spin states is limited by the dominant $k$-linear spin-orbit contributions in the bulk, these terms show almost no effect in

Shiung Fan

The Jordan--Wigner transformation plays an important role in spin models. However, the non-locality of the transformation implies that a periodic chain of $N$ spins is not mapped to a periodic or an anti-periodic chain of lattice fermions. Since only the $N-1$ bond is different, the effect is negligible for large systems, while it is significant for small sy

Alexander Kuznetsov, Alexander Perry

We introduce the notion of a categorical join, which can be thought of as a categorification of the classical join of two projective varieties. This notion is in the spirit of homological projective duality, which categorifies classical projective duality. Our main theorem says that the homological projective dual category of the categorical join is naturall

Taku Nonomura, Hisaichi Shibata, Ryoji Takaki

A novel dynamic mode decomposition (DMD) method based on a Kalman filter is proposed. This paper explains the fast algorithm of the proposed Kalman filter DMD (KFDMD) in combination with truncated proper orthogonal decomposition for many-degree-of-freedom problems. Numerical experiments reveal that KFDMD can estimate eigenmodes more precisely compared with s

Ahmed Kenawy, Janine Splettstoesser, Maciej Misiorny

We theoretically analyze the spectrum of a magnetic molecule when its charge and spin can couple to the molecular vibrations. More specifically, we show that the interplay between charge-vibron and spin-vibron coupling leads to a renormalization of the magnetic anisotropy parameters of the molecule. This effect is discussed for a model device consisting of a

Telikepalli Kavitha

We consider the popular matching problem in a roommates instance with strict preference lists. While popular matchings always exist in a bipartite instance, they need not exist in a roommates instance. The complexity of the popular matching problem in a roommates instance has been an open problem for several years and here we show it is NP-hard. A sub-class

P Manisha, Sujit Gujar

In recent years, Generative Adversarial Networks (GANs) have received significant attention from the research community. With a straightforward implementation and outstanding results, GANs have been used for numerous applications. Despite the success, GANs lack a proper theoretical explanation. These models suffer from issues like mode collapse, non-converge

Ana Caraiani, Daniel R. Gulotta, Chi-Yun Hsu, Christian Johansson

We show that the compactly supported cohomology of certain $\mathrm{U}(n,n)$ or $\mathrm{Sp}(2n)$-Shimura varieties with $Γ_1(p^\infty)$-level vanishes above the middle degree. The only assumption is that we work over a CM field $F$ in which the prime $p$ splits completely. We also give an application to Galois representations for torsion in the cohomology o

Hugo Defienne, Matthew Reichert, Jason W. Fleischer

Light shaping facilitates the preparation and detection of optical states and underlies many applications in communications, computing, and imaging. In this Letter, we generalize light shaping to the quantum domain. We show that patterns of phase modulation for classical laser light can also shape higher orders of spatial coherence, allowing deterministic ta

Alexander Perry

We generalize Kuznetsov's theory of homological projective duality to the setting of noncommutative algebraic geometry. Simultaneously, we develop the theory over general base schemes, and remove the usual smoothness, properness, and transversality hypotheses.

Qi-Ren Zhang

A sharply peaked structure is found in the angular distribution of emitted $π^+$ mesons from the photon-proton collisions. It offers a possible way for generating a $π^+$-condensation in free space. To make the stimulated emission of $π^+$-mesons efficient, a ring resonator is designed.

Peter Stano, Chen-Hsuan Hsu, Leon Camenzind, Liuqi Yu

We theoretically investigate the orbital effects of an in-plane magnetic field on the spectrum of a quantum dot embedded in a two-dimensional electron gas (2DEG). We derive an effective two-dimensional Hamiltonian where these effects enter in proportion to the flux penetrating the 2DEG. We quantify the latter in detail for harmonic, triangular, and square po

Mei Li, Jianbo Wang, Jie Lu

We consider analytically current-driven dynamics of magnetic Néel walls in heavy metal/ferromagnetic metal/oxide trilayers where strong spin-orbit coupling and interfacial Dzyaloshinskii-Moriya interaction (i-DMI) coexist. We show that field-like spin-orbit torque (FL-SOT) with effective field along $\mathbf{n}\times\hat{\mathbf{J}}$ ($\mathbf{n}$ being the

Bo Xiong, Kristen Grauman

360$^{\circ}$ panoramas are a rich medium, yet notoriously difficult to visualize in the 2D image plane. We explore how intelligent rotations of a spherical image may enable content-aware projection with fewer perceptible distortions. Whereas existing approaches assume the viewpoint is fixed, intuitively some viewing angles within the sphere preserve high-le

Qiang Li, Qi-Shu Yan

Initial State Radiation (ISR) effect is implemented in Madgraph using photon structure functions. Detailed examinations are performed against other generators including Whizard, BabayagaNLO and KKMC, for various physics processes at linear colliders such as 240GeV CEPC and 10.58GeV Belle II. ISR effects on new physics searches are also discussed, taking anom

Ratha Pech, Dong Hao, Yan-Li Lee, Ye Yuan

Link prediction is an elemental challenge in network science, which has already found applications in guiding laboratorial experiments, digging out drug targets, recommending friends in social networks, probing mechanisms in network evolution, and so on. With a simple assumption that the likelihood of the existence of a link between two nodes can be unfolded

Yo Kobayashi, Naomi Okamura, Mariko Tsukune, Masakatsu G. Fujie

Understanding the visocoelastic properties of soft biological tissues is important for progress in the field of human healthcare. This study analyzes the viscoelastic properties of soft biological tissues using a fractional dynamics model. We conducted a dynamic viscoelastic test on several porcine samples, namely liver, breast, and skeletal muscle tissues,

Steven Chen, Kristen Grauman

Relative attribute models can compare images in terms of all detected properties or attributes, exhaustively predicting which image is fancier, more natural, and so on without any regard to ordering. However, when humans compare images, certain differences will naturally stick out and come to mind first. These most noticeable differences, or prominent differ

Yiannis Loizides, Yanli Song

We prove a Fredholm property for spin-c Dirac operators $\mathsf{D}$ on non-compact manifolds satisfying a certain condition with respect to the action of a semi-direct product group $K\ltimes Γ$, with $K$ compact and $Γ$ discrete. We apply this result to an example coming from the theory of Hamiltonian loop group spaces. In this context we prove that a cert

Jiankai Sun, Sobhan Moosavi, Rajiv Ramnath, Srinivasan Parthasarathy

In this paper, we present a framework for Question Difficulty and Expertise Estimation (QDEE) in Community Question Answering sites (CQAs) such as Yahoo! Answers and Stack Overflow, which tackles a fundamental challenge in crowdsourcing: how to appropriately route and assign questions to users with the suitable expertise. This problem domain has been the sub

Daniel W. F. Alves, Giancarlo Camilo

Using a recent proposal of circuit complexity in quantum field theories introduced by Jefferson and Myers, we compute the time evolution of the complexity following a smooth mass quench characterized by a time scale $δt$ in a free scalar field theory. We show that the dynamics has two distinct phases, namely an early regime of approximately linear evolution

Emilien Dupont

We present a framework for learning disentangled and interpretable jointly continuous and discrete representations in an unsupervised manner. By augmenting the continuous latent distribution of variational autoencoders with a relaxed discrete distribution and controlling the amount of information encoded in each latent unit, we show how continuous and catego

Cheng Ju, Antoine Chambaz, Mark J. van der Laan

We wish to infer the value of a parameter at a law from which we sample independent observations. The parameter is smooth and we can define two variation-independent features of the law, its $Q$- and $G$-components, such that estimating them consistently at a fast enough product of rates allows to build a confidence interval (CI) with a given asymptotic leve

Jingwen Wang, Wenhao Jiang, Lin Ma, Wei Liu

Dense video captioning is a newly emerging task that aims at both localizing and describing all events in a video. We identify and tackle two challenges on this task, namely, (1) how to utilize both past and future contexts for accurate event proposal predictions, and (2) how to construct informative input to the decoder for generating natural event descript

Dongmian Zou, Gilad Lerman

We generalize the scattering transform to graphs and consequently construct a convolutional neural network on graphs. We show that under certain conditions, any feature generated by such a network is approximately invariant to permutations and stable to graph manipulations. Numerical results demonstrate competitive performance on relevant datasets.

Prabhashi W. Withana Gamage, Monica Chaudari, Christopher S. McMahan, Michael R. Kosorok

The proportional hazards (PH) model is arguably one of the most popular models used to analyze time to event data arising from clinical trials and longitudinal studies, among many others. In many such studies, the event time of interest is not directly observed but is known relative to periodic examination times; i.e., practitioners observe either current st

Jason Kaufman

Radiation pressure dominated accretion discs may have turbulent velocities that exceed the electron thermal velocities. Bulk Comptonization by the turbulence may therefore dominate over thermal Comptonization in determining the emergent spectrum. We discuss how to self-consistently resolve and interpret this effect in calculations of spectra of radiation MHD

Matiur Rahman Minar, Jibon Naher

Facebook as in social network is a great innovation of modern times. Among all social networking sites, Facebook is the most popular social network all over the world. Bangladesh is no exception. People use Facebook for various reasons e.g. social networking and communication, online shopping and business, knowledge and experience sharing etc. However, some

Murphy Choy, Mark Chong

The fake news epidemic makes it imperative to develop a diagnostic framework that is both parsimonious and valid to guide present and future efforts in fake news detection. This paper represents one of the very first attempts to fill a void in the research on this topic. The LeSiE (Lexical Structure, Simplicity, Emotion) framework we created and validated al

Mahdi H. Miraz, Maaruf Ali, Peter S. Excell

This paper gives an overview of electronic learning (E-Learning) and mobile learning (M-Learning) adoption and diffusion trends, as well as their particular traits, characteristics and issues, especially in terms of cross-cultural and universal usability. E-Learning and M-Learning models using web services and cloud computing, as well as associated security

Maaneli Derakhshani

Stochastic mechanics (SM), as proposed by Edward Nelson and others in the 20th century, aims to reconstruct quantum mechanics (QM) from a more fundamental theory of classical point particles interacting with a classical-like ether, where said interaction causes the particles to undergo a diffusion process that conserves their average total energy. However, T

Romeo Meštrović

In this paper we investigate enumeration of some classes of $n$-character strings and binary necklaces. Recall that binary necklaces are necklaces in two colors with length $n$. We prove three results (Theorems 1, 1' and 2) concerning the numbers of three classes of $j$-character strings (closely related to some classes of binary necklaces or Lyndon word

Ondrej Certik, Francesca Gardini, Gianmarco Manzini, Giuseppe Vacca

We extend the conforming virtual element method to the numerical resolution of eigenvalue problems with potential terms on a polytopal mesh. An important application is that of the Schrodinger equation with a pseudopotential term. This model is a fundamental element in the numerical resolution of more complex problems from the Density Functional Theory. The

Ismail Shahin, Ali Bou Nassif, Mohammed Bahutair

This work is devoted to capturing Emirati-accented speech database (Arabic United Arab Emirates database) in each of neutral and shouted talking environments in order to study and enhance text-independent Emirati-accented speaker identification performance in shouted environment based on each of First-Order Circular Suprasegmental Hidden Markov Models (CSPHM

Neyaz A Sheikh, M Ahsan Ali

Wavelet frames have become a useful tool in time freqency analysis and image processing. Many authors worked in the field of wavelet frames and obtained various necessary and sufficient conditions. Ron and Shen [17] gave a charactarization of wavelet frames. Benedetto and Treiber [3], Ron and Shen [17] presented different presentations to the wavelet frames.

Pramod Padmanabhan, Fumihiko Sugino, Vladimir Korepin

We construct an extended quantum spin chain model by introducing new degrees of freedom to the Fredkin spin chain. The new degrees of freedom called arrow indices are partly associated to the symmetric inverse semigroup $\cS^3_1$. Ground states of the model fall into three different phases, and quantum phase transition takes place at each phase boundary. One

Leonid Bunimovich, Longmei Shu

In the recently developed theory of isospectral transformations of networks isospectral compressions are performed with respect to some chosen characteristic (attribute) of nodes (or edges) of networks. Each isospectral compression (when a certain characteristic is fixed) defines a dynamical system on the space of all networks. It is shown that any orbit of

Prudhvi Raj Dachapally, Srikanth Ramanam

Convolutional neural networks for computer vision are fairly intuitive. In a typical CNN used in image classification, the first layers learn edges, and the following layers learn some filters that can identify an object. But CNNs for Natural Language Processing are not used often and are not completely intuitive. We have a good idea about what the convoluti

F. A. Danevich, V. I. Tretyak

Low counting experiments (search for double $β$ decay and dark matter particles, measurements of neutrino fluxes from different sources, search for hypothetical nuclear and subnuclear processes, low background $α$, $β$, $γ$ spectrometry) require extremely low background of a detector. Scintillators are widely used to search for rare events both as convention

Ashish Tapdiya, Daniel Fabbri

Hadoop is emerging as the primary data hub in enterprises, and SQL represents the de facto language for data analysis. This combination has led to the development of a variety of SQL-on-Hadoop systems in use today. While the various SQL-on-Hadoop systems target the same class of analytical workloads, their different architectures, design decisions and implem

Saroj Kumar Nandi, Nir S. Gov

The dynamics within active fluids, driven by internal activity of the self-propelled particles, is a subject of intense study in non-equilibrium physics. These systems have been explored using simulations, where the motion of a passive tracer particle is followed. Similar studies have been carried out for passive granular matter that is driven by shearing it

Mahdi M. Kalayeh, Emrah Basaran, Muhittin Gokmen, Mustafa E. Kamasak

Person re-identification is a challenging task mainly due to factors such as background clutter, pose, illumination and camera point of view variations. These elements hinder the process of extracting robust and discriminative representations, hence preventing different identities from being successfully distinguished. To improve the representation learning,

David R. S. Boyd, Robert A. Koff

V909 Cas is a little-studied example of a \b{eta} Cep pulsating variable located in the OB association Cas OB8 in the Perseus spiral arm of the Milky Way. Photometric observations in 2016-7 provided 30 new times of pulsation extrema and enabled its mean pulsation period to be determined as 0.2067798(1) d. From spectroscopic observations we determined its int

Wenqi Ren, Lin Ma, Jiawei Zhang, Jinshan Pan

In this paper, we propose an efficient algorithm to directly restore a clear image from a hazy input. The proposed algorithm hinges on an end-to-end trainable neural network that consists of an encoder and a decoder. The encoder is exploited to capture the context of the derived input images, while the decoder is employed to estimate the contribution of each

Abdelhamid Boudane, Said Jabbour, Badran Raddaoui, Lakhdar Sais

In the encoding of many real-world problems to propositional satisfiability, the cardinality constraint is a recurrent constraint that needs to be managed effectively. Several efficient encodings have been proposed while missing that such a constraint can be involved in a more general propositional formulation. To avoid combinatorial explosion, Tseitin princ

Y. Wu, D. Zhai, C. Pan, B. Cheng

Confinement of electrons in graphene to make devices has proven to be a challenging task. Electrostatic methods fail because of Klein tunneling, while etching into nanoribbons requires extreme control of edge terminations, and bottom-up approaches are limited in size to a few nanometers. Fortunately, its mechanical flexibility raises the possibility of using

S. Rennie, E. Lawrence Bright, J. E. Sutcliffe, J. E. Darnbrough

Epitaxial thin films have been utilised to investigate the radiolytic dissolution of uranium dioxide interfaces. Thin films of UO$_2$ deposited on single crystal yttria stabilised zirconia substrates have been exposed to water in the presence of a high flux, monochromatic, synchrotron x-ray source. In particular, this technique was applied to induce dissolut

Vasileios Mavroeidis, Kamer Vishi, Mateusz D. Zych, Audun Jøsang

The aim of this paper is to elucidate the implications of quantum computing in present cryptography and to introduce the reader to basic post-quantum algorithms. In particular the reader can delve into the following subjects: present cryptographic schemes (symmetric and asymmetric), differences between quantum and classical computing, challenges in quantum c

Alfred Czogała, Przemysław Koprowski

We present a new proof of the celebrated quadratic reciprocity law. Our proof is based on group theory.

Łukasz Kidziński, Sharada P. Mohanty, Carmichael Ong, Jennifer L. Hicks

Synthesizing physiologically-accurate human movement in a variety of conditions can help practitioners plan surgeries, design experiments, or prototype assistive devices in simulated environments, reducing time and costs and improving treatment outcomes. Because of the large and complex solution spaces of biomechanical models, current methods are constrained