April 2020 arXiv papers — page 6

Alexandru Topirceanu

Electoral forecasting is an ongoing scientific challenge with high social impact, as current data-driven methods try to efficiently combine statistics with economic indices and machine learning. However, recent studies in network science pinpoint towards the importance of temporal characteristics in the diffusion of opinion. As such, we combine concepts of m

Alexandros-Apostolos A. Boulogeorgos, Stylianos E. Trevlakis, Nestor D. Chatzidiamantis

This article discusses the fundamental architectures for optical wireless systems for biomedical applications. After summarizing the main applications and reporting their requirements, {we describe the characteristics of the transdermal and in-body optical channels as well as the challenges that they impose in the design of communication systems.} In more de

Richard Santiago, Yuichi Yoshida

Weak submodularity is a natural relaxation of the diminishing return property, which is equivalent to submodularity. Weak submodularity has been used to show that many (monotone) functions that arise in practice can be efficiently maximized with provable guarantees. In this work we introduce two natural generalizations of weak submodularity for non-monotone

Sufeng Duan, Juncheng Cao, Hai Zhao

Transformer hugely benefits from its key design of the multi-head self-attention network (SAN), which extracts information from various perspectives through transforming the given input into different subspaces. However, its simple linear transformation aggregation strategy may still potentially fail to fully capture deeper contextualized information. In thi

Jifan Chen, Greg Durrett

Current textual question answering models achieve strong performance on in-domain test sets, but often do so by fitting surface-level patterns in the data, so they fail to generalize to out-of-distribution settings. To make a more robust and understandable QA system, we model question answering as an alignment problem. We decompose both the question and cont

Naoyuki Itagaki, Tokuro Fukui, Junki Tanaka, Yuma Kikuchi

The possibility of the $^8$He and $^{9}$Li clusters in atomic nuclei is discussed. Until now most of the clusters in the conventional models have been limited to the closures of the three-dimensional harmonic oscillators, such as $^4$He, $^{16}$O, and $^{40}$Ca. In the neutron-rich nuclei, however, the neutron to proton ratio is not unity, and it is worthwhi

Daniel Guo, Bernardo Avila Pires, Bilal Piot, Jean-bastien Grill

Learning a good representation is an essential component for deep reinforcement learning (RL). Representation learning is especially important in multitask and partially observable settings where building a representation of the unknown environment is crucial to solve the tasks. Here we introduce Prediction of Bootstrap Latents (PBL), a simple and flexible s

G. Hebrard, R. F. Diaz, A. C. M. Correia, A. Collier Cameron

We present the discovery and characterization of WASP-148, a new extrasolar system that includes at least two giant planets. The host star is a slowly rotating inactive late-G dwarf with a V=12 magnitude. The planet WASP-148b is a hot Jupiter of 0.72 R_Jup and 0.29 M_Jup that transits its host with an orbital period of 8.80 days. We found the planetary candi

Pierre Jacob, David Picard, Aymeric Histace, Edouard Klein

Recent breakthroughs in representation learning of unseen classes and examples have been made in deep metric learning by training at the same time the image representations and a corresponding metric with deep networks. Recent contributions mostly address the training part (loss functions, sampling strategies, etc.), while a few works focus on improving the

Xuefang Xu, Di Li, Y. Sophia Dai, Gary A. Fuller

We present high-angular-resolution ALMA (Atacama Large Millimeter Array) images of N$_{2}$H$^{+}$ (1--0) that has been combined with those from the Nobeyama telescope toward OMC-2 and OMC-3 filamentary regions. The filaments (with typical widths of $\sim$ 0.1 pc) and dense cores are resolved. The measured 2D velocity gradients of cores are between 1.3 and 16

Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim

We introduce Jukebox, a model that generates music with singing in the raw audio domain. We tackle the long context of raw audio using a multi-scale VQ-VAE to compress it to discrete codes, and modeling those using autoregressive Transformers. We show that the combined model at scale can generate high-fidelity and diverse songs with coherence up to multiple

Jan Rataj

The translative intersection formula of integral geometry yields an expression for the mean Euler characteristic of a stationary random closed set intersected with a fixed observation window. We formulate this result in the setting of sets with positive reach and using flag measures which yield curvature measures as marginals. As an application, we consider

Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego

Search engine ranking pipelines are commonly based on large ensembles of machine-learned decision trees. The tight constraints on query response time recently motivated researchers to investigate algorithms to make faster the traversal of the additive ensemble or to early terminate the evaluation of documents that are unlikely to be ranked among the top-k. I

Niclas Boehmer, Edith Elkind

In the multidimensional stable roommate problem, agents have to be allocated to rooms and have preferences over sets of potential roommates. We study the complexity of finding good allocations of agents to rooms under the assumption that agents have diversity preferences [Bredereck et al., 2019]: each agent belongs to one of the two types (e.g., juniors and

Yu Su, Xiaoqi Ren, Shai Vardi, Adam Wierman

Scheduling precedence-constrained tasks is a classical problem that has been studied for more than fifty years. However, little progress has been made in the setting where there are communication delays between tasks. Results for the case of identical machines were derived nearly thirty years ago, and yet no results for related machines have followed. In thi

Sinan Tan, Huaping Liu, Di Guo, Xinyu Zhang

Embodiment is an important characteristic for all intelligent agents (creatures and robots), while existing scene description tasks mainly focus on analyzing images passively and the semantic understanding of the scenario is separated from the interaction between the agent and the environment. In this work, we propose the Embodied Scene Description, which ex

Martin Hellkvist, Ayça Özçelikkale, Anders Ahlén

Distributed learning facilitates the scaling-up of data processing by distributing the computational burden over several nodes. Despite the vast interest in distributed learning, generalization performance of such approaches is not well understood. We address this gap by focusing on a linear regression setting. We consider the setting where the unknowns are

Jianlong Lu

A scheme of neutrino mass generation is proposed by [arXiv:2003.12069], in which the small nonzero neutrino masses come from nonzero vacuum expectation value (VEV) of the charged Higgs field in the Higgs doublet in the Standard Model of particle physics (SM). However, the introduction of nonzero VEV for the charged Higgs field implies broken ${\rm U}(1)$ sym

ATLAS Collaboration

This paper reports on a search for heavy resonances decaying into $WW$, $ZZ$ or $WZ$ using proton-proton collision data at a centre-of-mass energy of $\sqrt{s}=13$ TeV. The data, corresponding to an integrated luminosity of 139 $\mathrm{fb^{-1}}$, were recorded with the ATLAS detector from 2015 to 2018 at the Large Hadron Collider. The search is performed fo

Seppo Yrjola, Petri Ahokangas, Marja Matinmikko-Blue, Risto Jurva

Developing products, services and vertical applications for the future digitized society in the 6G era requires a multidisciplinary approach and a re-definition of how we create, deliver and consume network resources, data and services for both communications and sensing purposes. This development will change and disrupt the traditional business models and e

Alberto Cappellaro, Luca Salasnich

We investigate the low-temperature properties of a ultracold gas made of bosonic alkali-metal atoms with finite-range interaction under the effect of a disordered environment. The statistical characterization of the disorder is investigated within an effective-field-theory formalism for a generic spatial dimension $d$. Moving to $d=3$, where all the arising

Alexey Bobtsov, Romeo Ortega, Nikolay Nikolaev, Wei He

In this paper we propose a PI passivity-based controller, applicable to a large class of switched power converters, that ensures global state regulation to a desired equilibrium point. A solution to this problem was reported in \cite{HERetal} but it requires full state-feedback, which makes it practically unfeasible. To overcome this limitation we construct

Andrei Novitskii, Gabin Guélou, Andrei Voronin, Takao Mori

Herein, we demonstrate that BiCuSeO compound can be formed in bulk directly from the raw materials through reactive spark plasma sintering (RSPS) followed by ball milling and a second short spark plasma sintering step. Compared to BiCuSeO samples obtained by a conventional solid-state reaction, the electrical transport properties of the RSPS bulk were modera

Hans Keßler, Jayson G. Cosme, Christoph Georges, Ludwig Mathey

We propose the dynamical stabilization of a nonequilibrium order in a driven dissipative system comprised an atomic Bose-Einstein condensate inside a high finesse optical cavity, pumped with an optical standing wave operating in the regime of anomalous dispersion. When the amplitude of the pump field is modulated close to twice the characteristic limit-cycle

Benjamin Aram Berendsohn, László Kozma

Group testing is concerned with identifying $t$ defective items in a set of $m$ items, where each test reports whether a specific subset of items contains at least one defective. In non-adaptive group testing, the subsets to be tested are fixed in advance. By testing multiple items at once, the required number of tests can be made much smaller than $m$. In f

D. J. Prabhakaran, K. Ranjith kumar

On pages 338 and 339 in his first notebook, Ramanujan defined the remarkable product of theta-functions $a_{m, n}$. Also he recorded eighteen explicit values depending on two parameters, namely, $m$, and $n$, where these are odd integers. All these values were established by Berndt et al. In this paper, we initiate to study explicit evaluations of $a_{m, n}$

Yaroslav Grosu, Yanqi Zhao, Alberto Giacomello, Simone Meloni

Impregnation of Phase Change Materials (PCMs) into a porous medium is a promising way to stabilize their shape and improve thermal conductivity which are essential for thermal energy storage and thermal management of small-size applications, such as electronic devices or batteries. However, in these composites a general understanding of how leakage is relate

P. M. W. Kalberla, J. Kerp, U. Haud

Context. There are significant amounts of H2 in the Milky Way. Due to its symmetry H2 does not radiate at radio frequencies. CO is thought to be a tracer for H2, however CO is formed at significantly higher opacities than H2. Thus, toward high Galactic latitudes significant amounts of H2 are hidden and called CO-dark. Aims. We demonstrate that the dust-to-ga

Jianhai Bao, Panpan Ren, Feng-Yu Wang

To characterize the regularity of distribution-path dependent SDEs in the initial distribution which varies in the class of probability measures on the path space, we introduce the intrinsic and Lions derivatives for probability measures on Banach spaces, and prove the chain rule of the Lions derivative for the distribution of Banach-valued random variables.

Aleksander Filip Zarnecki

The International Linear Collider (ILC) and the Compact Linear Collider (CLIC) are the two options for a future high-energy, high-luminosity linear electron-positron collider. Both are expected to be built in stages, optimised for their physics potential. The main goals are the precision measurements of Higgs-boson and top-quark properties as well as direct

Dingqian Sun

We study the optimal investment stopping problem in both continuous and discrete case, where the investor needs to choose the optimal trading strategy and optimal stopping time concurrently to maximize the expected utility of terminal wealth. Based on the work [9] with an additional stochastic payoff function, we characterize the value function for the conti

Tasnim Mohiuddin, Prathyusha Jwalapuram, Xiang Lin, Shafiq Joty

Although coherence modeling has come a long way in developing novel models, their evaluation on downstream applications for which they are purportedly developed has largely been neglected. With the advancements made by neural approaches in applications such as machine translation (MT), summarization and dialog systems, the need for coherence evaluation of th

Tim Jahn, Bangti Jin

Stochastic gradient descent (SGD) is a promising numerical method for solving large-scale inverse problems. However, its theoretical properties remain largely underexplored in the lens of classical regularization theory. In this note, we study the classical discrepancy principle, one of the most popular \textit{a posteriori} choice rules, as the stopping cri

Matthew Cordes, Matthieu Dussaule, Ilya Gekhtman

We construct a one-to-one continuous map from the Morse boundary of a hierarchically hyperbolic group to its Martin boundary. This construction is based on deviation inequalities generalizing Ancona's work on hyperbolic groups. This provides a possibly new metrizable topology on the Morse boundary of such groups. We also prove that the Morse boundary has mea

Atticus Geiger, Kyle Richardson, Christopher Potts

We address whether neural models for Natural Language Inference (NLI) can learn the compositional interactions between lexical entailment and negation, using four methods: the behavioral evaluation methods of (1) challenge test sets and (2) systematic generalization tasks, and the structural evaluation methods of (3) probes and (4) interventions. To facilita

Carlos D'Andrea, Gabriela Jeronimo, Martin Sombra

We present a product formula for the initial parts of the sparse resultant associated to an arbitrary family of supports, generalising a previous result by Sturmfels. This allows to compute the homogeneities and degrees of the sparse resultant, and its evaluation at systems of Laurent polynomials with smaller supports. We obtain a similar product formula for

Ka-Ming Tam, Nicholas Walker, Juana Moreno

State government-mandated social distancing measures have helped to slow down the growth of the COVID-19 pandemic in the United States. Current predictive models of the development of COVID-19, especially after mitigation efforts, are largely based on extrapolating the data from other countries. Since most states enforced stay-at-home orders towards the end

Wei Ping Cheng, Zhi Hong Zhang, Pu Wang

The normal distribution is used as a unified probability distribution, however, our researcher found that it is not good agreed with the real-life dynamical system's data. We collected and analyzed representative naturally occurring data series (e.g., the earth environment, sunspots, brain waves, electrocardiograms, some cases are classic chaos systems and s

Tomasz Limisiewicz, Rudolf Rosa, David Mareček

This work focuses on analyzing the form and extent of syntactic abstraction captured by BERT by extracting labeled dependency trees from self-attentions. Previous work showed that individual BERT heads tend to encode particular dependency relation types. We extend these findings by explicitly comparing BERT relations to Universal Dependencies (UD) annotation

Milind Naphade, Shuo Wang, David Anastasiu, Zheng Tang

The AI City Challenge was created to accelerate intelligent video analysis that helps make cities smarter and safer. Transportation is one of the largest segments that can benefit from actionable insights derived from data captured by sensors, where computer vision and deep learning have shown promise in achieving large-scale practical deployment. The 4th an

Sudip Mandal, Natalie A. Krivova, Sami K. Solanki, Nimesh Sinha

Long and consistent sunspot area records are important for understanding the long-term solar activity and variability. Multiple observatories around the globe have regularly recorded sunspot areas, but such individual records only cover restricted periods of time. Furthermore, there are also systematic differences between them, so that these records need to

Sri Karlapati, Alexis Moinet, Arnaud Joly, Viacheslav Klimkov

Prosody Transfer (PT) is a technique that aims to use the prosody from a source audio as a reference while synthesising speech. Fine-grained PT aims at capturing prosodic aspects like rhythm, emphasis, melody, duration, and loudness, from a source audio at a very granular level and transferring them when synthesising speech in a different target speaker's vo

Sosuke Inui, Makoto Tsubota

We study the dynamical process of the vortex tangle development under a spherically symmetric thermal counterflow around a heat source submerged into a bulk superfluid 4He. We reveal a peculiar vortex dynamics that is unique to this geometry, which is greatly diverse from the vortex dynamics in a homogeneous counterflow. Two types of heater are considered he

Luc Le Magoarou, Stéphane Paquelet

Channel estimation is a difficult problem in MIMO systems. Using a physical model allows to ease the problem, injecting a priori information based on the physics of propagation. However, such models rest on simplifying assumptions and require to know precisely the system configuration, which is unrealistic.In this paper, we propose to perform online learning

Yi-Lin Tuan, Wei Wei, William Yang Wang

Dialogue generation has been successfully learned from scratch by neural networks, but tends to produce the same general response, e.g., "what are you talking about?", in many conversations. To reduce this homogeneity, external knowledge such as the speaker's profile and domain knowledge is applied as an additional condition to diversify a model's output. Th

Hoang Dung Trinh, Khanh Duy Trinh

Beta Laguerre processes which are generalizations of the eigenvalue process of Wishart/Laguerre processes can be defined as the square of radial Dunkl processes of type B. In this paper, we study the limiting behavior of their empirical measure processes. By the moment method, we show the convergence to a limit in a high temperature regime, a regime where $\

A. M. Moro, J. A. Lay, J. Gómez-Camacho

A novel method to extract the $B(E1)$ strength of a weakly bound nucleus from experimental Coulomb dissociation data is proposed. The method makes use of continuum discretized coupled channels (CDCC) calculations, in which both nuclear and Coulomb forces are taken into account to all orders. This is a crucial advantage with respect to the standard procedure

Alfred Q. R. Baron, Masanori Inui, Daisuke Ishikawa, Kazuhiro Matsuda

The design and implementation of a furnace for inelastic x-ray scattering from liquids with sample temperatures up to ~1600C is described. Carbon composite heaters operating in vacuum provide robust heating elements: one pair of heaters has been used for >18 days of operational time above 1500C, including 8 cycles to room temperature. High quality data has b

An-Qi Wang, Xing-Guo Ye, Da-Peng Yu, Zhi-Min Liao

Characterized by bulk Dirac or Weyl cones and surface Fermi-arc states, topological semimetals have sparked enormous research interest in recent years. The nanostructures, with large surface-to-volume ratio and easy field-effect gating, provide ideal platforms to detect and manipulate the topological quantum states. Exotic physical properties originating fro

S. Jaiswal, Ed Thomas

The formation of self-consistent dust crystal and its melting is a well known phenomenon in rf generated plasma but remains challenging in DC glow discharge plasma. Here, we report the melting of a two dimensional dusty plasma crystal, suspended in the cathode sheath of a DC glow discharge plasma. The experiments are carried out in a $\Pi-$shaped Dusty Plasm

Serge Troubetzkoy, Paulo Varandas

In this short note we prove that a continuous map which is locally eventually onto and is expansive satisfies the periodic specification property. We also discuss the role of continuity as a key condition in the previous characterization. We include several examples to illustrate the relation between these concepts.

Prathyusha Jwalapuram, Barbara Rychalska, Shafiq Joty, Dominika Basaj

Despite increasing instances of machine translation (MT) systems including contextual information, the evidence for translation quality improvement is sparse, especially for discourse phenomena. Popular metrics like BLEU are not expressive or sensitive enough to capture quality improvements or drops that are minor in size but significant in perception. We in

Ehsanur Rahman, Alireza Nojeh

We investigate the performance of a micro gap vacuum thermionic energy converter considering the loss mechanisms due to the space charge effect and interelectrode radiative heat transfer. The dependencies of the space charge effect and near-field radiative heat exchange on the interelectrode distance are derived based on established theories. The electrode t

Alix Deleporte, Michael Hitrik, Johannes Sjoestrand

We develop a direct approach to the semiclassical asymptotics for Bergman projections in exponentially weighted spaces of holomorphic functions, with real analytic strictly plurisubharmonic weights. In particular, the approach does not rely upon the Kuranishi trick and it allows us to shorten and simplify proofs of a result due to Rouby-Sj\"ostrand-V\~u Ngoc

Arghya Pal, Vineeth N Balasubramanian

The paucity of large curated hand-labeled training data forms a major bottleneck in the deployment of machine learning models in computer vision and other fields. Recent work (Data Programming) has shown how distant supervision signals in the form of labeling functions can be used to obtain labels for given data in near-constant time. In this work, we presen

E. Sánchez, A. Mishchenko, J. M. García-Regaña, R. Kleiber

In this work, the first nonlinear particle-in-cell simulations carried out in a stellarator with the global gyrokinetic code EUTERPE using realistic plasma parameters are reported. Several studies are conducted with the aim of enabling reliable nonlinear simulations in stellarators with this code. First, EUTERPE is benchmarked against ORB5 in both linear and

Tracey K. M. Lee, Mohammed Belkhatir, Saeid Sanei

Global security concerns have raised a proliferation of video surveillance devices. Intelligent surveillance systems seek to discover possible threats automatically and raise alerts. Being able to identify the surveyed object can help determine its threat level. The current generation of devices provide digital video data to be analysed for time varying feat

Maike Gruchot, Alastair Litterick, Gerhard Roehrle

In this note, we unify and extend various concepts in the area of $G$-complete reducibility, where $G$ is a reductive algebraic group. By results of Serre and Bate--Martin--R\"{o}hrle, the usual notion of $G$-complete reducibility can be re-framed as a property of an action of a group on the spherical building of the identity component of $G$. We show that o

Thao Minh Le, Vuong Le, Svetha Venkatesh, Truyen Tran

We present Language-binding Object Graph Network, the first neural reasoning method with dynamic relational structures across both visual and textual domains with applications in visual question answering. Relaxing the common assumption made by current models that the object predicates pre-exist and stay static, passive to the reasoning process, we propose t

Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, Gangwoo Kim

Many extractive question answering models are trained to predict start and end positions of answers. The choice of predicting answers as positions is mainly due to its simplicity and effectiveness. In this study, we hypothesize that when the distribution of the answer positions is highly skewed in the training set (e.g., answers lie only in the k-th sentence

Isabel Papadimitriou, Dan Jurafsky

We propose transfer learning as a method for analyzing the encoding of grammatical structure in neural language models. We train LSTMs on non-linguistic data and evaluate their performance on natural language to assess which kinds of data induce generalizable structural features that LSTMs can use for natural language. We find that training on non-linguistic

Dhanush Anil Hangal

Jet charge, defined as the momentum-weighted sum of the electric charges of particles inside a jet is sensitive to the electric charge of the initiating parton and can be used to study the color charge dependence of the parton energy loss in the QGP. In this paper, the first measurements of jet charge in heavy-ion collisions are presented using lead-lead (Pb

Jiahua Duan, Nathaniel Capote-Robayna, Javier Taboada-Gutierrez, Gonzalo Alvarez-Perez

Recent discoveries have shown that when two layers of van der Waals (vdW) materials are superimposed with a relative twist angle between their respective in-plane principal axes, the electronic properties of the coupled system can be dramatically altered. Here, we demonstrate that a similar concept can be extended to the optics realm, particularly to propaga

Yue Zhao, Lin Liang, Yanrong Li, Khuat Thi Thu Hien

The pyriform silk of the attachment disc of a spider was studied using infrared-visible vibrational sum frequency generation (SFG) spectroscopy. The spider can attach dragline and radial lines to many kinds of substrates in nature (concrete, alloy, metal, glass, plant branches, leaves, etc.) with the attachment disc. The adhesion can bear the spider's own we

Yoshiko Kanada-En'yo, Kazuyuki Ogata

Elastic and inelastic cross sections of the $p+{}^6\textrm{He}$, $p+{}^8\textrm{He}$, and $\alpha+{}^8\textrm{He}$ reactions were investigated using the Melbourne $g$-matrix folding approach with the theoretical densities of ${}^6\textrm{He}$ and ${}^8\textrm{He}$ obtained by a microscopic structure model of antisymmetrized molecular dynamics (AMD). Microsco

I. S. Burmistrov

We report a complete analytical expression for the one-loop correction to the ac conductivity $\sigma(\omega)$ of a disordered two-dimensional electron system in the diffusive regime. The obtained expression includes the weak localization and Altshuler-Aronov corrections as well as the corrections due to superconducting fluctuations above superconducting tra

Christian Marzahl, Marc Aubreville, Christof A. Bertram, Jennifer Maier

In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation. However, keeping track of these annotations to ensure a high-quality multi-purpose data set is a challenging and labour intensive task. We developed the open-source online platform EXACT (EXpert Algorithm Collaboration

Aditya Gahlawat, Pan Zhao, Andrew Patterson, Naira Hovakimyan

We present $\mathcal{L}_1$-$\mathcal{GP}$, an architecture based on $\mathcal{L}_1$ adaptive control and Gaussian Process Regression (GPR) for safe simultaneous control and learning. On one hand, the $\mathcal{L}_1$ adaptive control provides stability and transient performance guarantees, which allows for GPR to efficiently and safely learn the uncertain dyn

Adrian Iftene

The habilitation thesis presents two main directions: 1. Exploiting data from social networks (Twitter, Facebook, Flickr, etc.) - creating resources for text and image processing (classification, retrieval, credibility, diversification, etc.); 2. Creating applications with new technologies : augmented reality (eLearning, games, smart museums, gastronomy, etc

Xi-Lin Li

We report a triangular neural network implementation of neural autoregressive flow (NAF). Unlike many universal autoregressive density models, our design is highly modular, parameter economy, computationally efficient, and applicable to density estimation of data with high dimensions. It achieves state-of-the-art bits-per-dimension indices on MNIST and CIFAR

Jiayi Zhang, Chongyang Tao, Zhenjing Xu, Qiaojing Xie

Generating qualitative responses has always been a challenge for human-computer dialogue systems. Existing dialogue systems generally derive from either retrieval-based or generative-based approaches, both of which have their own pros and cons. Despite the natural idea of an ensemble model of the two, existing ensemble methods only focused on leveraging one

Ying-Hao Zhang, Xiao Fan Liu

Low throughput has been the biggest obstacle of large-scale blockchain applications. During the past few years, researchers have proposed various schemes to improve the systems' throughput. However, due to the inherent inefficiency and defects of the Internet, especially in data broadcasting tasks, these efforts all rendered unsatisfactory. In this paper, we

Sudip Bera, Sajal Kumar Mukherjee

In this article we prove an algebraic identity which significantly generalizes the formula for sum of powers of consecutive integers involving Stirling numbers of the second kind. Also we have obtained a generalization of Newton-Girard power sum identity.

Daniel Kang, Tatsunori Hashimoto

Neural language models are usually trained to match the distributional properties of a large-scale corpus by minimizing the log loss. While straightforward to optimize, this approach forces the model to reproduce all variations in the dataset, including noisy and invalid references (e.g., misannotation and hallucinated facts). Worse, the commonly used log lo

M. Chen, X. Lin, T. Dinh, Z. Zheng

Moire engineering as a configuration method to twist van der Waals materials has delivered a series of advances in electronics, magnetics and optics. Yet these advances stem from peculiar moire superlattices which form at small specific twisting angles. Here we report the configuration of nanoscale light-matter waves-the polaritons-by twisting stacked $\alph

Jiao Li, Shi Jia, Yan Gao, Deng-Kai Jiang

Several dozen hypervelocity star (HVS) candidates have been reported based on the second data release of Gaia (Gaia DR2). However, it has been proven that the radial velocities of some Gaia HVS candidates are not reliable. In this paper, we employ refined astrometric criteria to re-examine Gaia DR2, arriving at a more reliable sample of HVS and high velocity

Qiang Fan, Jianan Bai, Hongxia Zhang, Yang Yi

Fog nodes in the vicinity of IoT devices are promising to provision low latency services by offloading tasks from IoT devices to them. Mobile IoT is composed by mobile IoT devices such as vehicles, wearable devices and smartphones. Owing to the time-varying channel conditions, traffic loads and computing loads, it is challenging to improve the quality of ser

M. Maree, M. Belkhatir

Ontologies form the basic interest in various computer science disciplines such as semantic web, information retrieval, database design, etc. They aim at providing a formal, explicit and shared conceptualization and understanding of common domains between different communities. In addition, they allow for concepts and their constraints of a specific domain t

Mohammad Alidoust

We theoretically study the profile of a supercurrent in two-dimensional Josephson junctions with Rashba-Dresselhaus spin-orbit interaction (RDSOI) in the presence of a Zeeman field. Through investigating self-biased supercurrent (so called $\varphi_0$-Josephson state), we obtain explicit expressions for the functionality of the $\varphi_0$ state with respect

J. D. Whalen, S. K. Kanungo, Y. Lu, S. Yoshida

We report the creation of heteronuclear ultralong-range Rydberg-molecule dimers by excitation of minority $^{88}\text{Sr}$ atoms to $5sns\,^3S_1$ Rydberg states ($n=31-39$) in a dense background of $^{84}\text{Sr}$. We observe an isotope shift of the $\nu=0$ vibrational state over this range of $n$ and compare our measurements with a theoretical prediction a

Ragav Venkatesan, Gurumurthy Swaminathan, Xiong Zhou, Anna Luo

In the last decade convolutional neural networks have become gargantuan. Pre-trained models, when used as initializers are able to fine-tune ever larger networks on small datasets. Consequently, not all the convolutional features that these fine-tuned models detect are requisite for the end-task. Several works of channel pruning have been proposed to prune a

Ting-Jung Kuo, Youngae Lee, Chang-Shou Lin

We consider non-topological solutions of a nonlinear elliptic system problem derived from the $SU(3)$ Chern-Simons models in $\mathbb{R}^2$. The existence of non-topological solutions even for radial symmetric case has been a long standing open problem. Recently, [Choe, Kim, Lin (2015, 2016)] showed the existence of radial symmetric non-topological solution

Zhao Zhang, Zheng Lin, Jun Xu, Wenda Jin

Most existing RGB-D salient object detection (SOD) methods focus on the foreground region when utilizing the depth images. However, the background also provides important information in traditional SOD methods for promising performance. To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention

Eisuke Shibuya, Kazuhiro Hotta

Human brain is a layered structure, and performs not only a feedforward process from a lower layer to an upper layer but also a feedback process from an upper layer to a lower layer. The layer is a collection of neurons, and neural network is a mathematical model of the function of neurons. Although neural network imitates the human brain, everyone uses only

Md Navid Akbar, Marianna La Rocca, Rachael Garner, Dominique Duncan

Post-traumatic epilepsy (PTE) is a life-long complication of traumatic brain injury (TBI) and is a major public health problem that has an estimated incidence that ranges from 2%-50%, depending on the severity of the TBI. Currently, the pathomechanism that in-duces epileptogenesis in TBI patients is unclear, and one of the most challenging goals in the epile

Zhiyu Chen, Wenhu Chen, Hanwen Zha, Xiyou Zhou

Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured data, e.g., multi-row tables, it is often desirable for an NLG system to describe interesting facts from logical inferences across records. If only provided with the table, it is ha

Hao Fang, Biao Ma, Wei Wei

We prove some extensions of Andrews inequality.

Hayley Ross, Jonathon Cai, Bonan Min

Extracting temporal relations between events and time expressions has many applications such as constructing event timelines and time-related question answering. It is a challenging problem which requires syntactic and semantic information at sentence or discourse levels, which may be captured by deep contextualized language models (LMs) such as BERT (Devlin

Noboru Sakamoto, Masaaki Nagahara

This paper presents analyses for the maximum hands-off control using the geometric methods developed for the theory of turnpike in optimal control. First, a sufficient condition is proved for the existence of the maximum hands-off control for linear time-invariant systems with arbitrarily fixed initial and terminal points using the relation with $L^1$ optima

Gorka Kobeaga, María Merino, Jose A. Lozano

In this paper, we extend techniques developed in the context of the Travelling Salesperson Problem for cycle problems. Particularly, we study the shrinking of support graphs and the exact algorithms for subcycle elimination separation problems. The efficient application of the considered techniques has proved to be essential in the Travelling Salesperson Pro

Kwan-Lok Li, Jay Strader, James C. A. Miller-Jones, Craig O. Heinke

We report new simultaneous X-ray and radio continuum observations of 3FGL J0427.9-6704, a candidate member of the enigmatic class of transitional millisecond pulsars. These XMM-Newton and Australia Telescope Compact Array observations of this nearly edge-on, eclipsing low-mass X-ray binary were taken in the sub-luminous disk state at an X-ray luminosity of ~

Huaixin Cao, Yuxing Du, Zhihua Guo, Kanyuan Han

Masking of quantum information means that information is hidden from a subsystem and spread over a composite system. Modi et al. proved in [Phys. Rev. Lett. 120, 230501 (2018)] that this is true for some restricted sets of nonorthogonal quantum states and it is not possible for arbitrary quantum states. In this paper, we discuss the problem of masking quantu

Aadhavan Sadasivam, Kausic Gunasekar, Hasan Davulcu, Yezhou Yang

Image memes have become a widespread tool used by people for interacting and exchanging ideas over social media, blogs, and open messengers. This work proposes to treat automatic image meme generation as a translation process, and further present an end to end neural and probabilistic approach to generate an image-based meme for any given sentence using an e

Jiangning Zhang, Liang Liu, Zhucun Xue, Yong Liu

Audio-guided face reenactment aims at generating photorealistic faces using audio information while maintaining the same facial movement as when speaking to a real person. However, existing methods can not generate vivid face images or only reenact low-resolution faces, which limits the application value. To solve those problems, we propose a novel deep neur

Shu Gu, Jinping Zhuge

In this paper, we systematically study the regularity theory of the linear system of nearly incompressible elasticity. In the setting of stochastic homogenization, we develop new techniques to establish the large-scale estimates of displacement and pressure, which are uniform in both the scale parameter and the incompressibility parameter. In particular, we

Max Pflueger, Gaurav S. Sukhatme

Robot control problems are often structured with a policy function that maps state values into control values, but in many dynamic problems the observed state can have a difficult to characterize relationship with useful policy actions. In this paper we present a new method for learning state embeddings from plans or other forms of demonstrations such that t

Yuhui Xu, Yuxi Li, Shuai Zhang, Wei Wen

To enable DNNs on edge devices like mobile phones, low-rank approximation has been widely adopted because of its solid theoretical rationale and efficient implementations. Several previous works attempted to directly approximate a pretrained model by low-rank decomposition; however, small approximation errors in parameters can ripple over a large prediction

Chenguang Zhu

The natural language generation (NLG) module in a task-oriented dialogue system produces user-facing utterances conveying required information. Thus, it is critical for the generated response to be natural and fluent. We propose to integrate adversarial training to produce more human-like responses. The model uses Straight-Through Gumbel-Softmax estimator fo

Brian Thompson, Matt Post

We frame the task of machine translation evaluation as one of scoring machine translation output with a sequence-to-sequence paraphraser, conditioned on a human reference. We propose training the paraphraser as a multilingual NMT system, treating paraphrasing as a zero-shot translation task (e.g., Czech to Czech). This results in the paraphraser's output mod

Xingwang Li, Mengle Zhao, Yuanwei Liu, Lihua Li

We investigate the reliability and security of the ambient backscatter (AmBC) non-orthogonal multiple access (NOMA) systems, where the source aims to communication with two NOMA users in the presence of an eavesdropper. We consider a more practical case that nodes and backscatter device (BD) suffer from in-phase and quadrature-phase imbalance (IQI). More spe