November 2018 arXiv papers — page 45

Vedran Dunjko, Erika Andersson

Most of the schemes for "noiseless" amplification of coherent states, which have recently been attracting theoretical and experimental interest, share a common trait: the amplification is not truly noiseless, or perfect, for non-zero success probability. While this must hold true for all phase-independent amplification schemes, in this work we point out that

Marco Cè, Antoine Gérardin, Konstantin Ottnad, Harvey B. Meyer

We present a preliminary study of the leading hadronic contribution to the running of the Weinberg angle $\theta_{\mathrm{W}}$. The running is extracted from the correlation function of the electromagnetic current with the vector part of the weak neutral current using both the standard time-momentum representation method and the Lorentz-covariant coordinate-

Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid, Georges Linarès

Neural network architectures are at the core of powerful automatic speech recognition systems (ASR). However, while recent researches focus on novel model architectures, the acoustic input features remain almost unchanged. Traditional ASR systems rely on multidimensional acoustic features such as the Mel filter bank energies alongside with the first, and sec

Minchao Li, Shikui Tu, Lei Xu

Neural style transfer has been demonstrated to be powerful in creating artistic image with help of Convolutional Neural Networks (CNN). However, there is still lack of computational analysis of perceptual components of the artistic style. Different from some early attempts which studied the style by some pre-processing or post-processing techniques, we inves

Xinwei Bai, Jasper Goseling

In this paper, we present a numerical framework for constructing bounds on stationary performance measures of random walks in the positive orthant using the Markov reward approach. These bounds are established in terms of stationary performance measures of a perturbed random walk whose stationary distribution is known explicitly. We consider random walks in

Ray Vandenhoeck, Andrea Lani

The present paper addresses the development and implementation of the first high-order Flux Reconstruction (FR) solver for high-speed flows within the open-source COOLFluiD (Computational Object-Oriented Libraries for Fluid Dynamics) platform. The resulting solver is fully implicit and able to simulate compressible flow problems governed by either the Euler

M. Montanari, M. Virgilio, C. L. Manganelli, P. Zaumseil

In this paper we investigate the structural and optical properties of few strain-unbalanced multiple Ge/GeSi quantum wells pseudomorphically grown on GeSi reverse-graded substrates. The obtained high epitaxial quality demonstrates that strain symmetrization is not a mandatory requirement for few quantum-well repetitions. Photoluminescence data, supported by

Petr Bouchal, Lenka Štrbková, Zbyněk Dostál, Radim Chmelík

We present geometric-phase microscopy allowing a multipurpose quantitative phase imaging in which the ground-truth phase is restored by quantifying the phase retardance. The method uses broadband spatially incoherent light that is polarization sensitively controlled through the geometric (Pancharatnam-Berry) phase. The assessed retardance possibly originates

W. F. Thi, G. Lesur, P. Woitke, I. Kamp

Context. Disks around pre-main-sequence stars evolve over time by turbulent viscous spreading. The main contender to explain the strength of the turbulence is the Magneto-Rotational-Instability (MRI) model, whose efficiency depends on the disk ionization fraction. Aims. We aim at computing self-consistently the chemistry including PAH charge chemistry, the g

Xavier L. Bacalla, Harold Linnartz, Nick L. J. Cox, Jan Cami

We report cosmic ray ionization rates towards ten reddened stars studied within the framework of the EDIBLES (ESO Diffuse Interstellar Bands Large Exploration Survey) program, using the VLT-UVES. For each sightline, between 2 and 10 individual rotational lines of OH$^+$ have been detected in its (0,0) and (1,0) $A^3\Pi-X^3\Sigma^-$ electronic band system. Th

Paul F. Jaeger, Simon A. A. Kohl, Sebastian Bickelhaupt, Fabian Isensee

The task of localizing and categorizing objects in medical images often remains formulated as a semantic segmentation problem. This approach, however, only indirectly solves the coarse localization task by predicting pixel-level scores, requiring ad-hoc heuristics when mapping back to object-level scores. State-of-the-art object detectors on the other hand,

Tobias Urban, Dennis Tatang, Martin Degeling, Thorsten Holz

The European General Data Protection Regulation (GDPR), which went into effect in May 2018, leads to important changes in this area: companies are now required to ask for users' consent before collecting and sharing personal data and by law users now have the right to gain access to the personal information collected about them. In this paper, we study and e

B. Adeva, L. Afanasyev, A. Anania, S. Aogaki

The adapted DIRAC experiment at the CERN PS accelerator observed for the first time long-lived hydrogen-like $\pi^+\pi^-$ atoms, produced by protons hitting a beryllium target. A part of these atoms crossed the gap of 96~mm and got broken up in the 2.1~\textmu{}m thick platinum foil. Analysing the observed number of atomic pairs, $n_A^L= \left.436^{+157}_{-6

Bas Lemmens, Lewis White

In recent work with Lins and Nussbaum the first author gave an algorithm that can detect the existence of a positive eigenvector for order-preserving homogeneous maps on the standard positive cone. The main goal of this paper is to determine the minimum number of iterations this algorithm requires. It is known that this number is equal to the illumination nu

Najib Alia, Volker John, Seppo Ollila

Ladle stirring is an important step of the steelmaking process to homogenize the temperature and the chemical composition of the liquid steel and to remove inclusions before casting. Gas is injected from the bottom of the bath to induce a turbulent flow of the liquid steel. Multiphase modeling of ladle stirring can become computationally expensive, especiall

Le Zhang, Songyou Peng, Stefan Winkler

Apparent personality and emotion analysis are both central to affective computing. Existing works solve them individually. In this paper we investigate if such high-level affect traits and their relationship can be jointly learned from face images in the wild. To this end, we introduce PersEmoN, an end-to-end trainable and deep Siamese-like network. It consi

Ľubomír Hambálek, Martin Vaňko, Ernst Paunzen, Barry Smalley

We present a study of the long-term optical variability of young T Tauri stars using previously unpublished data from the SuperWASP project. Other publicly available photometry from NSVS and the NASA K2 mission were used to check and supplement our results. Our sample includes twenty weak-lined T Tauri stars in the Taurus-Auriga star-forming region. We have

Haozhao Li, Bing Wang

In this paper, we show that if the mean curvature of a closed smooth embedded mean curvature flow in R^3 is of type-I, then the rescaled flow at the first finite singular time converges smoothly to a self-shrinker flow with multiplicity one. This result confirms Ilmanen's multiplicity-one conjecture under the assumption that the mean curvature is of type-I.

Mikio Morii, Shiro Ikeda, Yoshitomo Maeda

We propose an image reconstruction method for an X-ray telescope system with an angular resolution booster proposed by Maeda et al.(2018). The system consists of double multi-grid masks in front of an X-ray mirror and an off-focused two-dimensional imager. Because the obtained image is off-focused, additional image reconstruction process is assumed to be inc

Jean-Claude Saut

This survey is focused on two asymptotic models for internal waves, the Benjamin-Ono (BO) and Intermediate Long Wave (ILW) equations that are integrable by inverse scattering techniques (IST). After recalling briefly their derivations we will review old and recent results on the Cauchy problem, comparing those obtains by IST and PDE techniques and also resul

Eleonora Cinti, Carlo Sinestrari, Enrico Valdinoci

We consider the volume preserving geometric evolution of the boundary of a set under fractional mean curvature. We show that smooth convex solutions maintain their fractional curvatures bounded for all times, and the long time asymptotics approach round spheres. The proofs are based on apriori estimates on the inner and outer radii of the solutions.

Karri I. I. Koljonen, David M. Russell

The radio/X-ray correlation is one of the most important pieces of observational evidence of the disk-jet connection in accreting compact objects. However, a growing number of X-ray binaries seem to present deviations from the universal radio/X-ray correlation and the origin of these outliers are still very much debated. In previous studies, the X-ray bolome

Aurélie Astoul, Stéphane Mathis, Clément Baruteau, Florian Gallet

The energy dissipation of wave-like tidal flows in the convective envelope of low-mass stars is one of the key physical mechanisms that shape the orbital and rotational dynamics of short-period planetary systems. Tidal flows, and the excitation, propagation, and dissipation of tidally-induced inertial waves can be modified by stellar magnetic fields (e.g., W

Wei-Min Liu, Xiang-Dong Li

It has been shown that the rate of angular momentum loss (AML) in cataclysmic variables (CVs) below the period gap is about 2.47 times that caused by gravitational radiation, suggesting extra AML mechanism besides gravitational radiation. Several potential mechanisms have been proposed but none of them has been verified. In this work we examine whether AML c

Yuu Hariya

Let $B=\{ B_{t}\} _{t\ge 0}$ be a one-dimensional standard Brownian motion, to which we associate the exponential additive functional $A_{t}=\int _{0}^{t}e^{2B_{s}}ds,\,t\ge 0$. Starting from a simple observation of generalized inverse Gaussian distributions with particular sets of parameters, we show, with the help of a result by Matsumoto--Yor (2000), that

Sunjin Choi, Joonho Kim, Seok Kim, June Nahmgoong

We study the index of $\mathcal{N}=4$ Yang-Mills theory on $S^3\times\mathbb{R}$. We argue that the index should undergo a large $N$ deconfinement phase transition, by computing an upper bound of its `temperature.' We compute this bound by optimizing the phases of fugacities. The bound we find has some features analogous to the Hagedorn temperature. We brief

Gwang-Il Ri, Chol-Gyun Ri, Su-Rim Ji

In this paper we propose a novel fingerprint indexing approach for speeding up in the fingerprint recognition system. What kind of features are used for indexing and how to employ the extracted features for searching are crucial for the fingerprint indexing. In this paper, we select a minutia descriptor, which has been used to improve the accuracy of the fin

Andrea Tassi, Robert J. Piechocki, Andrew Nix

This paper considers a network where a node wishes to transmit a source message to a legitimate receiver in the presence of an eavesdropper. The transmitter secures its transmissions employing a sparse implementation of Random Linear Network Coding (RLNC). A tight approximation to the probability of the eavesdropper recovering the source message is provided.

Jie Zhu, Meng-Jun Hu, Shuming Cheng, Michael J. W. Hall

We experimentally test the recently predicted anisotropic invariance properties of pure three-qubit states, via generation and measurement of polarisation-path entangled three-qubit states. These properties do not require aligned reference frames and can be determined from measurements on any two of the qubits. They have several applications, such as a unive

David Chataur, Joana Cirici

We describe the E-infinity algebra structure on the complex of singular cochains of a topological space, in the context of sheaf theory. As a first application, for any algebraic variety we define a weight filtration compatible with its E-infinity structure. This naturally extends the theory of mixed Hodge structures in rational homotopy to p-adic homotopy t

Wei Rong, Bowen Zhang, Xixiang Lv

Web parameter injection attacks are common and powerful. In this kind of attacks, malicious attackers can employ HTTP requests to implement attacks against servers by injecting some malicious codes into the parameters of the HTTP requests. Against the web parameter injection attacks, most of the existing Web Intrusion Detection Systems (WIDS) cannot find unk

Yaohua Xie, Danli Wang, Fang Sun

When viewing stereoscopic displays, people may not always be able to stay exactly in front of the display. It is known that viewing stereoscopic display from different vertical angles lead to different visual discomfort. However, the effects of horizontal viewing angle on stereoscopic visual discomfort have been rarely investigated, especially for household

Chengyuan Wu, Bo Wang, Dongdong Liu

The double-degenerate model, involving the merger of double carbon-oxygen white dwarfs (CO WDs), is one of the two classic models for the progenitors of type Ia supernovae (SNe Ia). Previous studies suggested that off-centre carbon burning would occur if the mass-accretion rate (Macc) is relatively high during the merging process, leading to the formation of

N. A. Kuzmin, E. A. Ladygin, V. P. Ladygin, Yu. P. Petukhov

A Multi-gap Resistive Plate Chamber (MRPC) equipped with heaters to improve the counting rate capability was designed for the BM@N experiment in Dubna. The measurements were performed using a muon beam at IHEP U-70 accelerator in Protvino. The MRPC at 40$^0$C tolerates counting rate up to 6 kHz/cm$^2$ with time resolution ~65 ps and efficiency ~95\% which co

Li Haoyu

Based on the theory of invariant sets of descending flow, we give a new proof of the existence of three nontrivial solutions and some remarks on it.

Nina Shevchenko

The paper is devoted to the $\bar{K}NNN$ system, which is an exotic system consisting of an antikaon and three nucleons. Four-body Faddeev-type AGS equations, which are being used for evaluation of the possible quasi-bound state in the system are described.

P. P. Petrov, K. N. Grankin, J. F. Gameiro, S. A. Artemenko

Classical T Tauri stars with ages of less than 10 Myr possess accretion discs. Magnetohydrodynamic processes at the boundary between the disc and the stellar magnetosphere control the accretion and ejections gas flows. We carried out a long series of simultaneous spectroscopic and photometric observations of the classical T Tauri stars RY Tau and SU Aur with

Yifan Yang, Qijing Huang, Bichen Wu, Tianjun Zhang

Using FPGAs to accelerate ConvNets has attracted significant attention in recent years. However, FPGA accelerator design has not leveraged the latest progress of ConvNets. As a result, the key application characteristics such as frames-per-second (FPS) are ignored in favor of simply counting GOPs, and results on accuracy, which is critical to application suc

Kazuki Tachikawa, Yuji Kawai, Jihoon Park, Minoru Asada

Integrated gradients are widely employed to evaluate the contribution of input features in classification models because it satisfies the axioms for attribution of prediction. This method, however, requires an appropriate baseline for reliable determination of the contributions. We propose a compensated integrated gradients method that does not require a bas

Xueyang Fu, Qi Qi, Yue Huang, Xinghao Ding

We propose a simple yet effective deep tree-structured fusion model based on feature aggregation for the deraining problem. We argue that by effectively aggregating features, a relatively simple network can still handle tough image deraining problems well. First, to capture the spatial structure of rain we use dilated convolutions as our basic network block.

Fabrizio Garotta, Nicola Demo, Marco Tezzele, Massimo Carraturo

In this contribution, we coupled the isogeometric analysis to a reduced order modelling technique in order to provide a computationally efficient solution in parametric domains. In details, we adopt the free-form deformation method to obtain the parametric formulation of the domain and proper orthogonal decomposition with interpolation for the computational

Bingqing Cheng, Edgar A. Engel, Jörg Behler, Christoph Dellago

Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations and proton disorder. This is made possible by combining advanced free energy methods and state-of-the-art machine

A. Turan Gurkanli

In this article, notations are included in Section 1. In Section 2, we define the grand Wiener amalgam space by using the classical Wiener amalgam space [9, 15, 16, 17] and the generalized grand Lebesgue space [18, 13] . Section 3, concerns the inclusions between these spaces and some applications. In last section Section 4, we prove the Holders inequality f

Donghao Wu, Dongdong Liu, Bo Wang

It has been suggested that SNe Ia could be produced in the condition of the violent merger scenario of the double-degenerate model, in which a thermonuclear explosion could be produced when the merging of double carbon-oxygen white dwarfs (CO WDs) is still ongoing. It has been recently found that the nucleus of the bipolar planetary nebula Henize 2-428 consi

Shuntaro Sumita, Takuya Nomoto, Ken Shiozaki, Youichi Yanase

Recent development in exact classification of a superconducting gap has elucidated various unconventional gap structures, which have not been predicted by the classification of order parameter based on the point group. One of the important previous results is that all symmetry-protected line nodes are characterized by nontrivial topological numbers. Another

Yuri N. Obukhov, Dirk Puetzfeld

How does one measure the gravitational field? We give explicit answers to this fundamental question and show how all components of the curvature tensor, which represents the gravitational field in Einstein's theory of General Relativity, can be obtained by means of two different methods. The first method relies on the measuring the accelerations of a suitabl

Andrea Signori

In this work, we investigate a distributed optimal control problem for an extended phase field system of Cahn--Hilliard type which physical context is that of tumor growth dynamics. In a previous contribution, the author has already studied the corresponding problem for the logarithmic potential. Here, we try to extend the analysis by taking into account a n

Helle Bakke, Lars Frogner, Boris Vilhelm Gudiksen

Context. We introduce a model for including accelerated particles in pure magnetohydrodynamics (MHD) simulations of the solar atmosphere. Aims. We show that the method is viable and produces results that enhance the realism of MHD simulations of the solar atmosphere. Methods. The acceleration of high-energy electrons in solar flares is an accepted fact, but

Z. T Han, S. B. Qian, L. Y. Zhu, Q. J. Zhi

We present a timing analysis of the eclipsing post-common envelope binary (PCEB) DE CVn. Based on new CCD photometric observations and the published data, we found that the orbital period in DE CVn has a cyclic period oscillation with an amplitude of $28.08$ s and a period of $11.22$ years plus a rapid period decrease at a rate of $\dot{P}=-3.35\times10^{-11

Andrew W. Stephan, Jiaxi Hu, Steven J. Koester

We propose a new design for a cellular neural network with spintronic neurons and CMOS-based synapses. Harnessing the magnetoelectric and inverse Rashba-Edelstein effects allows natural emulation of the behavior of an ideal cellular network. This combination of effects offers an increase in speed and efficiency over other spintronic neural networks. A rigoro

Martino Fassina, Yifei Pan

Let $\Omega\subset\mathbb{R}^n, n\geq 2$, be an open set. For an elliptic differential operator $L$ on $\Omega$ with real analytic coefficients and a point $p\in\Omega$, we construct a smooth function $g$ with the following properties: $g$ is flat at $p$ and the equation $Lu=g$ has no smooth local solution $u$ that is flat at $p$.

Zhaoqun Li, Cheng Xu, Biao Leng

How to obtain the desirable representation of a 3D shape, which is discriminative across categories and polymerized within classes, is a significant challenge in 3D shape retrieval. Most existing 3D shape retrieval methods focus on capturing strong discriminative shape representation with softmax loss for the classification task, while the shape feature lear

Ka Yan Au Yeung, Brian Yang, Liang Sun, Kehang Bai

We report the phenomenon of coherent super decay, where a linear sum of several damped oscillators can collectively decay much faster than the individual ones in the first stage, followed by stagnating ones after more than 90 percent of the energy has already been dissipated. The parameters of the damped oscillators for CSD are determined by the process of r

Saurav Jha, Akhilesh Sudhakar, Anil Kumar Singh

The ambiguities introduced by the recombination of morphemes constructing several possible inflections for a word makes the prediction of syntactic traits in Morphologically Rich Languages (MRLs) a notoriously complicated task. We propose the Multi Task Deep Morphological analyzer (MT-DMA), a character-level neural morphological analyzer based on multitask l

Jinhyeok Jang, Jaehong Kim, Jaeyeon Lee, Seungjoon Yang

This work presents an adaptive activation method for neural networks that exploits the interdependency of features. Each pixel, node, and layer is assigned with a polynomial activation function, whose coefficients are provided by an auxiliary activation network. The activation of a feature depends on the features of neighboring pixels in a convolutional laye

Huitao Feng, Kefeng Liu, Xueyuan Wan

In this short note, we prove that a complex Finsler vector bundle with positive Kobayashi curvature must be ample, which partially solves a problem of S. Kobayashi posed in 1975. As applications, a strongly pseudoconvex complex Finsler manifold with positive Kobayashi curvature must be biholomorphic to the complex projective space; we also show that all Schu

Bruno Salvy

A lot of information concerning solutions of linear differential equations can be computed directly from the equation. It is therefore natural to consider these equations as a data-structure, from which mathematical properties can be computed. A variety of algorithms has thus been designed in recent years that do not aim at "solving", but at computing with t

Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag, Matthew McDermott

Joint embeddings between medical imaging modalities and associated radiology reports have the potential to offer significant benefits to the clinical community, ranging from cross-domain retrieval to conditional generation of reports to the broader goals of multimodal representation learning. In this work, we establish baseline joint embedding results measur

Jiajun Xu, Sam Huang

Tetris is an Asynchronous Byzantine Fault Tolerance consensus algorithm designed for next generation high-throughput permission and permissionless blockchain. The core concept of Tetris is derived from Reasoning About Knowledge, which we believe to be the most appropriate tools for revealing and analyzing the fundamental complexity of distributed systems. By

Arkadii Slinko

This is a survey article outlining what is known about absolute primes.

Dmitriy Rumynin

We investigate geometry of D-affine varieties. Our main result is that a D-affine rational projective surface over an algebraically closed field is a generalised flag variety of a reductive group.

Wanchen Sui, Qing Zhang, Jun Yang, Wei Chu

In this paper, we propose a novel integrated framework for learning both text detection and recognition. For most of the existing methods, detection and recognition are treated as two isolated tasks and trained separately, since parameters of detection and recognition models are different and two models target to optimize their own loss functions during indi

Rahul Singh, Viraj Shah, Balaji Pokuri, Soumik Sarkar

A key problem in computational material science deals with understanding the effect of material distribution (i.e., microstructure) on material performance. The challenge is to synthesize microstructures, given a finite number of microstructure images, and/or some physical invariances that the microstructure exhibits. Conventional approaches are based on sto

Zhipeng Chen, Yiming Cui, Wentao Ma, Shijin Wang

Machine Reading Comprehension (MRC) with multiple-choice questions requires the machine to read given passage and select the correct answer among several candidates. In this paper, we propose a novel approach called Convolutional Spatial Attention (CSA) model which can better handle the MRC with multiple-choice questions. The proposed model could fully extra

Seyed Hamid Safavi, Manas Khatua, Ngai-Man Cheung, Farah Torkamani-Azar

In this paper, we propose a new regression-based algorithm to compute Graph Fourier Transform (GFT). Our algorithm allows different regularizations to be included when computing the GFT analysis components, so that the resulting components can be tuned for a specific task. We propose using the lasso penalty in our proposed framework to obtain analysis compon

Jatin N. Kumar, Qianxiao Li, Karen Y. T. Tang, Tonio Buonassisi

Inverse design is an outstanding challenge in disordered systems with multiple length scales such as polymers, particularly when designing polymers with desired phase behavior. We demonstrate high-accuracy tuning of poly(2-oxazoline) cloud point via machine learning. With a design space of four repeating units and a range of molecular masses, we achieve an a

Tomohiro Tamaya, Takeo Kato, Satoru Konabe, Shiro Kawabata

We theoretically investigate surface plasmon polaritons propagating in the thin-film Weyl semimetals. We show how the properties of surface plasmon polaritons are affected by hybridization between plasmons localized at the two metal-dielectric interfaces. Generally, this hybridization results in new mixed plasmon modes, which are called short-range surface p

Jonathan P. Chen, Fritz Obermeyer, Vladimir Lyapunov, Lionel Gueguen

We leverage automatic differentiation (AD) and probabilistic programming to develop an end-to-end optimization algorithm for batch triangulation of a large number of unknown objects. Given noisy detections extracted from noisily geo-located street level imagery without depth information, we jointly estimate the number and location of objects of different typ

Wolfram Weise

Global symmetries and symmetry breaking patterns of QCD with light quarks, in particular chiral symmetry, provide basic guidance not only for low-energy hadron physics but also for nuclear forces and the nuclear many-body problem. Recent developments of Chiral Effective Field Theory applications to nuclear and neutron matter are summarized, with special emph

Uday Bhaskar Sharma, Anupam Singh

This paper concerns the enumeration of simultaneous conjugacy classes of tuples of commuting unitary matrices and of commuting symplectic matrices over a finite field $\mathbf{F}_q$ of odd size. For any given conjugacy class, the orbits for the action of its centralizer group on itself by conjugation are called branches. We determine the branching rules for

Yongjung Kim, Myungshin Im, Yiseul Jeon, Minjin Kim

The faint quasars with $M_{1450}>-24$ mag are known to hold the key to the determination of the ultraviolet emissivity for the cosmic re-ionization. But only a few have been identified so far because of the limitations on the survey data. Here, we present the first results of the $z\sim5$ faint quasar survey with the Infrared Medium-deep Survey (IMS), which

Enze Xie, Yuhang Zang, Shuai Shao, Gang Yu

Scene text detection methods based on deep learning have achieved remarkable results over the past years. However, due to the high diversity and complexity of natural scenes, previous state-of-the-art text detection methods may still produce a considerable amount of false positives, when applied to images captured in real-world environments. To tackle this i

Christopher Kath, Florian Ziel

We propose a multivariate elastic net regression forecast model for German quarter-hourly electricity spot markets. While the literature is diverse on day-ahead prediction approaches, both the intraday continuous and intraday call-auction prices have not been studied intensively with a clear focus on predictive power. Besides electricity price forecasting, w

Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu

Entity Linking aims to link entity mentions in texts to knowledge bases, and neural models have achieved recent success in this task. However, most existing methods rely on local contexts to resolve entities independently, which may usually fail due to the data sparsity of local information. To address this issue, we propose a novel neural model for collecti

Young-bin Kim, Myung Gil Kang, Wan Choi

To improve diversity gain in an interference channel and hence to maximize diversity multiplexing tradeoff (DMT), we propose on-off switched interference alignment (IA) where IA is intermittently utilized by switching IA on/off. For on-off switching, either IA with symbol extension or IA with Alamouti coding is adopted in this paper. Deriving and analyzing D

Trevor Hyde

We observe that the necklace polynomials $M_d(x) = \frac{1}{d}\sum_{e\mid d}\mu(e)x^{d/e}$ are highly reducible over $\mathbb{Q}$ with many cyclotomic factors. Furthermore, the sequence $\Phi_d(x) - 1$ of shifted cyclotomic polynomials exhibits a qualitatively similar phenomenon, and it is often the case that $M_d(x)$ and $\Phi_d(x) - 1$ have many common cyc

Pengfei Liu, Shuaichen Chang, Xuanjing Huang, Jian Tang

Recently, a large number of neural mechanisms and models have been proposed for sequence learning, of which self-attention, as exemplified by the Transformer model, and graph neural networks (GNNs) have attracted much attention. In this paper, we propose an approach that combines and draws on the complementary strengths of these two methods. Specifically, we

Zhonghua Wu, Guosheng Lin, Qingyi Tao, Jianfei Cai

Most existing virtual try-on applications require clean clothes images. Instead, we present a novel virtual Try-On network, M2E-Try On Net, which transfers the clothes from a model image to a person image without the need of any clean product images. To obtain a realistic image of person wearing the desired model clothes, we aim to solve the following challe

M. S. Fujii, Y. Hori

In clustered environments, stellar encounters can liberate planets from their host stars via close encounters. Although the detection probability of planets suggests that the planet population in open clusters resembles that in the field, only a few dozen planet-hosting stars have been discovered in open clusters. We explore the survival rates of planets aga

S. Davood Sadatian, S. M. Hosseini

In this letter, we explore a generalized model based on two scenarios including the Randall-Sundrum model and Gravity model $F(T,\Theta)$. We first study the standard Randall-Sundrum Gravitational model and then add a function containing two parameters as torsion and trace energy-momentum tensor to the main action of the model. Next, we derive the equations

Linnan Wang, Wei Wu, Junyu Zhang, Hang Liu

The performance and efficiency of distributed training of Deep Neural Networks highly depend on the performance of gradient averaging among all participating nodes, which is bounded by the communication between nodes. There are two major strategies to reduce communication overhead: one is to hide communication by overlapping it with computation, and the othe

Vahid Tadayon

The Stochastic Approximation EM (SAEM) algorithm, a variant stochastic approximation of EM, is a versatile tool for inference in incomplete data models. In this paper, we review the fundamental EM algorithm and then focus especially on the stochastic version of EM. In order to construct the SAEM, the algorithm combines EM with a variant of stochastic approxi

Thanh T. Nguyen, Dung Nguyen

Attentively important regions in video frames account for a majority part of the semantics in each frame. This information is helpful in many applications not only for entertainment (such as auto generating commentary and tourist guide) but also for robotic control which holds a larascope supported for laparoscopic surgery. However, it is not always straight

Ali Rouhani, Mahdi Bashiri, Rashed Sahraeian

In this paper, a green transportation location problem is considered with uncertain demand parameter. Increasing robustness influences the number of trucks for sending goods and products, and consequently, makes the air pollution enhance. In this paper, two green approaches are introduced which demand is the main uncertain parameter in both. These approaches

Albert Haque, Michelle Guo, Adam S Miner, Li Fei-Fei

With more than 300 million people depressed worldwide, depression is a global problem. Due to access barriers such as social stigma, cost, and treatment availability, 60% of mentally-ill adults do not receive any mental health services. Effective and efficient diagnosis relies on detecting clinical symptoms of depression. Automatic detection of depressive sy

Mauricio Ayllon Unzueta, Will Mixter, Zachary Croft, John Joseph

Associated Particle Imaging (API) is a nuclear technique that allows for the nondestructive determination of 3D isotopic distributions. The technique is based on the detection of the alpha particles associated with the neutron emitted in the deuterium-tritium (DT) fusion reaction, which provides information regarding the direction and time of the emitted 14

Yue Zhang, Mao-Kang Shen, Zai-Dong Li, Xiao-Fei Yang

Domain walls (DWs) in perpendicularly magnetized nanotracks (PMNTs) with interfacial Dzyaloshinskii-Moriya interaction (DMI) have become the primary objects of theoretical and experimental interest due to their technological suitability in spintronic nanodevices. Chiral DWs in PMNTs can be driven efficiently by the spin-orbit torque. However, the high-freque

Mengdi Wang, Qing Zhang, Jun Yang, Xiaoyuan Cui

In this work, we propose a graph-adaptive pruning (GAP) method for efficient inference of convolutional neural networks (CNNs). In this method, the network is viewed as a computational graph, in which the vertices denote the computation nodes and edges represent the information flow. Through topology analysis, GAP is capable of adapting to different network

Yoshinori Konishi, Kosuke Hattori, Manabu Hashimoto

We propose a fast and accurate 6D object pose estimation from a RGB-D image. Our proposed method is template matching based and consists of three main technical components, PCOF-MOD (multimodal PCOF), balanced pose tree (BPT) and optimum memory rearrangement for a coarse-to-fine search. Our model templates on densely sampled viewpoints and PCOF-MOD which exp

Xuding Zhu

Assume $k$ is a positive integer, $\lambda=\{k_1, k_2, \ldots, k_q\}$ is a partition of $k$ and $G$ is a graph. A $\lambda$-list assignment of $G$ is a $k$-list assignment $L$ of $G$ such that the colour set $\cup_{v\in V(G)}L(v)$ can be partitioned into $q$ subsets $C_1 \cup C_2 \ldots \cup C_q$ and for each vertex $v$ of $G$, $|L(v) \cap C_i| \ge k_i$. We

Changjian Li, Krzysztof Czarnecki

Autonomous driving is a challenging domain that entails multiple aspects: a vehicle should be able to drive to its destination as fast as possible while avoiding collision, obeying traffic rules and ensuring the comfort of passengers. In this paper, we present a deep learning variant of thresholded lexicographic Q-learning for the task of urban driving. Our

Zhong Huang, Xueliang Li

Let $G$ be a nontrivial connected, edge-colored graph. An edge-cut $S$ of $G$ is called a rainbow cut if no two edges in $S$ are colored with a same color. An edge-coloring of $G$ is a rainbow disconnection coloring if for every two distinct vertices $s$ and $t$ of $G$, there exists a rainbow cut $S$ in $G$ such that $s$ and $t$ belong to different component

Chaoqi Chen, Weiping Xie, Wenbing Huang, Yu Rong

Unsupervised domain adaptation (UDA) transfers knowledge from a label-rich source domain to a fully-unlabeled target domain. To tackle this task, recent approaches resort to discriminative domain transfer in virtue of pseudo-labels to enforce the class-level distribution alignment across the source and target domains. These methods, however, are vulnerable t

Ligang Jin, Tsai-Lien Wong, Xuding Zhu

Assume $G$ is a graph. We view $G$ as a symmetric digraph, in which each edge $uv$ of $G$ is replaced by a pair of opposite arcs $e=(u,v)$ and $e^{-1}=(v,u)$. Assume $S$ is an inverse closed subset of permutations of positive integers. We say $G$ is $S$-$k$-colourable if for any mapping $\sigma: E(G) \to S$ with $\sigma (x,y) = (\sigma (y,x))^{-1}$, there is

Qiming Shao, Guoqiang Yu, Yann-Wen Lan, Yumeng Shi

The electronic and optoelectronic properties of two dimensional materials have been extensively explored in graphene and layered transition metal dichalcogenides (TMDs). Spintronics in these two-dimensional materials could provide novel opportunities for future electronics, for example, efficient generation of spin current, which should enable the efficient

Zhenyu Tang, Hui-Ling Zhen

Higher-order nonlinear Schr\"odinger(HNLS) equation which can be used to describe the propagation of short light pulses in the optical fibers, is studied in this paper. Using the phase plane analysis, HNLS equation is reduced into the equivalent dynamical system, the periodicity of such system is obtained with the phase projections and power spectra given. B

Chuanxing Geng, Sheng-jun Huang, Songcan Chen

In real-world recognition/classification tasks, limited by various objective factors, it is usually difficult to collect training samples to exhaust all classes when training a recognizer or classifier. A more realistic scenario is open set recognition (OSR), where incomplete knowledge of the world exists at training time, and unknown classes can be submitte

Michael Freedman, Modjtaba Shokrian-Zini, Zhenghan Wang

There are two schools of "measurement-only quantum computation". The first ([11]) using prepared entanglement (cluster states) and the second ([4]) using collections of anyons, which according to how they were produced, also have an entanglement pattern. We abstract the common principle behind both approaches and find the notion of a graph or even continuous

Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara

Population attributes are essential in health for understanding who the data represents and precision medicine efforts. Even within disease infection labels, patients can exhibit significant variability; "fever" may mean something different when reported in a doctor's office versus from an online app, precluding directly learning across different datasets fo

Ahmed A. Mostafa, Bernard Marius 't Hart, Denise Y. P. Henriques

An accurate estimate of limb position is necessary for movement. Where we localize our unseen hand after a reach depends on felt hand position, or proprioception, but often only predicted sensory consequences based on efference copies of motor commands are considered. Both signals should contribute, so here we use passive training with rotated visual feedbac