June 2019 arXiv papers — page 20

Phanideep Gampa, Sairam Satwik Kondamudi, Lakshmanan Kailasam

We consider the finite horizon continuous reinforcement learning problem. Our contribution is three-fold. First,we give a tractable algorithm based on optimistic value iteration for the problem. Next,we give a lower bound on regret of order $\Omega(T^{2/3})$ for any algorithm discretizes the state space, improving the previous regret bound of $\Omega(T^{1/2}

Alona Sydorova, Nina Poerner, Benjamin Roth

Interpretability of machine learning (ML) models becomes more relevant with their increasing adoption. In this work, we address the interpretability of ML based question answering (QA) models on a combination of knowledge bases (KB) and text documents. We adapt post hoc explanation methods such as LIME and input perturbation (IP) and compare them with the se

Helena Ferreira, Marta Ferreira, Luís A. Alexandre

The modeling of risk situations that occur in a space-time framework can be done using max-stable random fields on lattices. Although the summary coefficients for the spatial and temporal behaviour do not characterize the finite-dimensional distributions of the random field, they have the advantage of being immediate to interpret and easier to estimate. The

Yael Mathov, Noga Agmon, Asaf Shabtai, Rami Puzis

For years, attack graphs have been an important tool for security assessment of enterprise networks, but IoT devices, a new player in the IT world, might threat the reliability of this tool. In this paper, we review the challenges that must be addressed when using attack graphs to model and analyze enterprise networks that include IoT devices. In addition, w

Gunter Hermann, Vincent Pohl, Gopal Dixit, Jean Christophe Tremblay

The current flux density is a vector field that can be used to describe theoretically how electrons flow in a system out-of-equilibrium. In this work, we unequivocally demonstrate that the signal obtained from time-resolved X-ray scattering does not only map the time-evolution of the electronic charge distribution, but also encodes information about the asso

Azadeh Khaleghi, Daniil Ryabko

The problem of time-series clustering is considered in the case where each data-point is a sample generated by a piecewise stationary ergodic process. Stationary processes are perhaps the most general class of processes considered in non-parametric statistics and allow for arbitrary long-range dependence between variables. Piecewise stationary processes stud

Rémi Leluc, François Portier, Johan Segers

Monte Carlo integration with variance reduction by means of control variates can be implemented by the ordinary least squares estimator for the intercept in a multiple linear regression model with the integrand as response and the control variates as covariates. Even without special knowledge on the integrand, significant efficiency gains can be obtained if

M. A. J. van Limbeek, S. Vanapalli

Interleaving fins can significantly increase the heat transfer by increasing the effective area per unit base area. The fins are separated uniformly by a gap, which is filled with a flow medium to control the heat flux. The heat flux between the plates depends strongly on the thermal conductivity of the fin material and the medium between them as well as the

Bart Bussmann, Jacqueline Heinerman, Joel Lehman

As reinforcement learning (RL) scales to solve increasingly complex tasks, interest continues to grow in the fields of AI safety and machine ethics. As a contribution to these fields, this paper introduces an extension to Deep Q-Networks (DQNs), called Empathic DQN, that is loosely inspired both by empathy and the golden rule ("Do unto others as you would ha

Pierre Sutra

This paper identifies a problem in both the TLA+ specification and the implementation of the Egalitarian Paxos protocol. It is related to how replicas switch from one ballot to another when computing the dependencies of a command. The problem may lead replicas to diverge and break the linearizability of the replicated service.

Honggang Chen, Yongbo Li, Mingzhong Wang, Guangyu Han

Improving the critical transition temperature (TC) of Bi(Pb)SrCaCuO (B(P)SCCO) high-temperature superconductors is important, however, considerable challenges exist. In this study, on the basis of the metamaterial structure and the idea that the injecting energy will promote the formation of Cooper pairs, a smart meta-superconductor B(P)SCCO consisting of B(

P. Belli, R. Bernabei, R. S. Boiko, F. Cappella

The double-electron capture and the electron capture with positron emission in $^{168}$Yb have been investigated for the first time at the STELLA facility of the Gran Sasso underground laboratory (Italy) measuring 371 g of highly purified ytterbium oxide placed on the end-cap of a 465 cm$^3$ ultra-low-background high purity Germanium detector (HPGe). No gamm

Sudip Pal, Kranti Kumar, Rohit Sharma, A Banerjee

Two-dimensional layered transition-metal-dichalcogenide compound 1T-TaS2 shows the rare coexistence of charge density wave (CDW) and electron correlation driven Mott transition. In addition, atomic-cluster spins on the triangular lattice of the CDW state of 1T-TaS2 give rise to the possibility of the exotic spin-singlet state in which quantum fluctuations of

Kelly Bickel, James Eldred Pascoe, Alan Sola

We study the boundary behavior of rational inner functions (RIFs) in dimensions three and higher from both analytic and geometric viewpoints. On the analytic side, we use the critical integrability of the derivative of a rational inner function of several variables to quantify the behavior of a RIF near its singularities, and on the geometric side we show th

Enrique Ruiz Arriola, Jacobo Ruiz de Elvira

We show that it makes sense to coarse grain hadronic interactions such as $\pi\pi$ and $\pi N$ reactions following previous work on NN scattering. Moreover, if the interaction is taken to be given by chiral dynamics at long distances above a given value $r > r_c$ larger than the elementary radii of the interaction hadrons the unknown short distance region $r

Eleonora Anna Romano

We discuss the flatness property of some fiber type contractions of complex smooth projective varieties of arbitrary dimensions. We relate the flatness of some morphisms having one-dimensional fibers with their conic bundles structures, also in the general case in which some mild singularities of the varieties are admitted.

Youngnam Lee, Youngduck Choi, Junghyun Cho, Alexander R. Fabbri

Machine learning plays an increasing role in intelligent tutoring systems as both the amount of data available and specialization among students grow. Nowadays, these systems are frequently deployed on mobile applications. Users on such mobile education platforms are dynamic, frequently being added, accessing the application with varying levels of focus, and

Zhuangzhuang Cui, Ke Guan, César Briso, Danping He

In this paper, we present a probabilistic two-ray (PTR) path loss model for air-to-air (AA) propagation channel in built-up areas. Based on the statistical model of city deployment, the PTR path loss model can be applied to suburban, urban, dense urban, and high-rise urban. The path loss is optimally fitted as the Weibull distribution and its fluctuation is

Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz

High-performance Deep Neural Networks (DNNs) are increasingly deployed in many real-world applications e.g., cloud prediction APIs. Recent advances in model functionality stealing attacks via black-box access (i.e., inputs in, predictions out) threaten the business model of such applications, which require a lot of time, money, and effort to develop. Existin

Kai Hakala, Aleksi Vesanto, Niko Miekka, Tapio Salakoski

A common approach for improving OCR quality is a post-processing step based on models correcting misdetected characters and tokens. These models are typically trained on aligned pairs of OCR read text and their manually corrected counterparts. In this paper we show that the requirement of manually corrected training data can be alleviated by estimating the O

Kari Astala, Albert Clop, Daniel Faraco, Jarmo Jääskeläinen

We establish surprising improved Schauder regularity properties for solutions to the Leray-Lions divergence type equation in the plane. The results are achieved by studying the nonlinear Beltrami equation and making use of special new relations between these two equations. In particular, we show that solutions to an autonomous Beltrami equation enjoy a quant

D. B. But, M. Mittendorff, C. Consejo, F. Teppe

The Landau level laser has been proposed a long time ago as a unique source of monochromatic radiation, widely tunable in the THz and infrared spectral ranges using an externally applied magnetic field. In spite of decades of efforts, this appealing concept never resulted in the design of a reliable device. This is due to efficient Auger scattering of Landau

Claudio Carmeli, Teiko Heinosaari, Takayuki Miyadera, Alessandro Toigo

We introduce the notion of incompatibility witness for quantum channels, defined as an affine functional that is non-negative on all pairs of compatible channels and strictly negative on some incompatible pair. This notion extends the recent definition of incompatibility witnesses for quantum measurements. We utilize the general framework of channels acting

Christian Altenhofen, Marco Attene, Oliver Barrowclough, Michele Chiumenti

In the industrial practice, additive manufacturing processes are often followed by post-processing operations such as subtractive machining, milling, etc. to achieve the desired surface quality and dimensional accuracy. Hence, a given part must be 3D printed with extra material to enable such finishing phase. This combined additive/subtractive technique can

Chandan Mondal, Asmita Mukherjee, Sreeraj Nair

We investigate the double parton distributions (DPDs) for a positronium-like bound state using light-front QED. We incorporate the higher Fock three particle component of the state, that includes a photon. We obtain the overlap representation of the DPDs in terms of the three-particle light-front wave functions (LFWFs). Our calculation explores the correlati

Edvin G. Idrisov, Ivan P. Levkivskyi, Eugene V. Sukhorukov

We present the theoretical model of the "quantum ammeter", a device that is able to measure the full counting statistics of an electron current at quantum time scales. It consists of an Ohmic contact, perfectly coupled to chiral quantum Hall channels, and of a quantum dot attached to one of the outgoing channels. At energies small compared to its charging en

Chunyu Zhang, Qing Gao, Yungui Gong, Dicong Liang

Space-based gravitational wave detectors cannot keep rigid structures and precise arm length equality, so the precise equality of detector arms which is required in a ground-based interferometer to cancel the overwhelming laser noise is impossible. The time-delay interferometry method is applied to unequal arm lengths to cancel the laser frequency noise. We

Shilong Sun, Bert Jan Kooij, Alexander G. Yarovoy

In this paper, a linear model based on multiple measurement vectors model is proposed to formulate the inverse scattering problem of highly conductive objects at one single frequency. Considering the induced currents which are mostly distributed on the boundaries of the scatterers, joint sparse structure is enforced by a sum-of-norm regularization. Since no

Tao Liu, Kirill Melnikov, Alexander A. Penin

We discuss nonfactorizable QCD corrections to Higgs boson production in vector boson fusion at the Large Hadron Collider. We point out that these corrections can be computed in the eikonal approximation retaining all the terms that are not suppressed by the ratio of the transverse momenta of the tagging jets to the total center-of-mass energy. Our analysis s

Daniela Kartoon, Guy Makov

At high pressure, bismuth acquires a complex incommensurate host-guest structure, only recently discovered. Characterizing the structure and properties of this incommensurate phase from first principles is challenging owing to its non-periodic nature. In this study we use large scale DFT calculations to model commensurate approximants to the Bi-III phase, an

Yao Xu, Xueshuang Xiang, Meiyu Huang

This paper introduces a novel deep learning based method, named bridge neural network (BNN) to dig the potential relationship between two given data sources task by task. The proposed approach employs two convolutional neural networks that project the two data sources into a feature space to learn the desired common representation required by the specific ta

Shunan Guo, Zhuochen Jin, Qing Chen, David Gotz

Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When applied to the analysis of event sequence data, the task of anomaly detection can be complex because the sequential and temporal nature of such data results in diverse definitions and flexible forms of

Christoffer Karoff, Carsten Sønderskov Jørgensen, V. Senthamizh Pavai, Rainer Arlt

The number of spots on the surface of the Sun is one of the best tracers of solar variability we have. The sunspot number is not only known to change in phase with the 11-year solar cycles, but also to show variability on longer time scales. It is, however, not only the sunspot number that changes in connection with solar variability. The location of the spo

Yusef Maleki, Alireza Maleki

Quantum mechanics imposes a fundamental bound on the minimum time required for the quantum systems to evolve between two states of interest. This bound introduces a limit on the speed of the dynamical evolution of the systems, known as the quantum speed limit. We show that black holes can drastically affect the speed limit of a two-level fermionic quantum sy

Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan

Home appliance manufacturers strive to obtain feedback from users to improve their products and services to build a smart home system. To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' da

Li Chen, Laurent Desvillettes, Evangelos Latos

In this paper, global-in-time existence and blow up results are shown for a reaction-diffusion equation appearing in the theory of aggregation phenomena (including chemotaxis). Properties of the corresponding steady-state problem are also presented. Moreover, the stability around constant equilibria and the non-existence of non-constant solutions are studied

Javier Naranjo-Alcazar, Sergi Perez-Castanos, Irene Martin-Morato, Pedro Zuccarello

Residual learning is a recently proposed learning framework to facilitate the training of very deep neural networks. Residual blocks or units are made of a set of stacked layers, where the inputs are added back to their outputs with the aim of creating identity mappings. In practice, such identity mappings are accomplished by means of the so-called skip or r

Ben G. Lillard, Tilman Plehn, Alexis Romero, Tim M. P. Tait

Typical LHC analyses search for local features in kinematic distributions. Assumptions about anomalous patterns limit them to a relatively narrow subset of possible signals. Wavelets extract information from an entire distribution and decompose it at all scales, simultaneously searching for features over a wide range of scales. We propose a systematic wavele

Yu Yamashiro, Masaki Ohkuwa, Hidetoshi Nishimori, Daniel A. Lidar

Reverse annealing is a relatively new variant of quantum annealing, in which one starts from a classical state and increases and then decreases the amplitude of the transverse field, in the hope of finding a better classical state than the initial state for a given optimization problem. We numerically study the unitary quantum dynamics of reverse annealing f

Martin Kegnenlezom, Patrice Takam Soh, Antoine-Marie Bogso, Yves Emvudu Wono

We propose a new model for electricity pricing based on the price cap principle. The particularity of the model is that the asset price is an exponential functional of a jump L\'evy process. This model can capture both mean reversion and jumps which are observed in electricity market. It is shown that the value of an European option of this asset is the uniq

Jiayun Wang, Rudrasis Chakraborty, Stella X. Yu

Deep neural networks are widely used for understanding 3D point clouds. At each point convolution layer, features are computed from local neighborhoods of 3D points and combined for subsequent processing in order to extract semantic information. Existing methods adopt the same individual point neighborhoods throughout the network layers, defined by the same

Zibin Zhou, Fei Wang, Wenjuan Xi, Huaying Chen

Tracking living cells in video sequence is difficult, because of cell morphology and high similarities between cells. Tracking-by-detection methods are widely used in multi-cell tracking. We perform multi-cell tracking based on the cell centroid detection, and the performance of the detector has high impact on tracking performance. In this paper, UNet is uti

Maciej Besta, Marcel Schneider, Karolina Cynk, Marek Konieczny

We introduce FatPaths: a simple, generic, and robust routing architecture that enables state-of-the-art low-diameter topologies such as Slim Fly to achieve unprecedented performance. FatPaths targets Ethernet stacks in both HPC supercomputers as well as cloud data centers and clusters. FatPaths exposes and exploits the rich ("fat") diversity of both minimal

Carsten Sønderskov Jørgensen, Christoffer Karoff, V. Senthamizh Pavai, Rainer Arlt

Between 1761 and 1776, Christian Horrebow made regular observations of sunspots from Rundetaarn in Copenhagen. Based on these observations he writes in 1775 that "it appears that after the course of a certain number of years, the appearance of the Sun repeats itself with respect to the number and size of the spots". Thus, Horrebow hypothesized the idea of a

Guohui Zhao

Spline functions have long been used in numerical solution of differential equations. Recently it revives as isogeometric analysis, which offers integration of finite element analysis and NURBS based CAD into a single unified process. Usually many NURBS pieces are needed to build geometrically continuous CAD models. In this paper, we introduce some splines d

Sylvia Schmitz, Martin Weinmann, Boitumelo Ruf

The comparison of current image data with existing 3D model data of a scene provides an efficient method to keep models up to date. In order to transfer information between 2D and 3D data, a preliminary co-registration is necessary. In this paper, we present a concept to automatically co-register aerial imagery and untextured 3D model data. To refine a given

Ammar Mahmood, Ana Giraldo Ospina, Mohammed Bennamoun, Senjian An

Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes for experts to identify organisms found in these images. With this limitation in mind, a large effort has been

Joël Merker, Paweł Nurowski

On a $3$D manifold, a Weyl geometry consists of pairs $(g, A) =$ (metric, $1$-form) modulo gauge $\widehat{g} = {\rm e}^{2\varphi} g$, $\widehat{A} = A + {\rm d}\varphi$. In 1943, Cartan showed that every solution to the Einstein-Weyl equations $R_{(\mu\nu)} - \frac{1}{3} R g_{\mu\nu} = 0$ comes from an appropriate $3$D leaf space quotient of a $7$D connecti

R. Chan

We have shown the outcome of N-body simulations of the interactions of two disc galaxies without gas with the same mass. Both disc galaxies have halos of dark matter, central bulges and initial supermassive black hole (SMBH) seeds at their centers. The purpose of this work is to study the mass and dynamical evolution of the initial SMBH seed during a Hubble

Mahyar TajDini, Volodymyr Sokolov, Volodymyr Buriachok

The article presents a method of organizing men-in-the-middle attack and penetration test on Bluetooth Low Energy devices and ZigBee packets using software define radio with sniffing and spoofing packets, capture and analysis techniques on wireless waves with the focus on Bluetooth. The paper contains the analysis of the latest scientific work in this area,

Volodymyr Buriachok, Volodymyr Sokolov, Pavlo Skladannyi

The paper examines quantitative assessment of wireless distribution system security, as well as an assessment of risks from attacks and security violations. Furthermore, it describes typical security breach and formal attack models and five methods for assessing security. The proposed normalized method for assessing the degree of security assurance operates

Naoyuki Kanda, Shota Horiguchi, Ryoichi Takashima, Yusuke Fujita

In this paper, we propose a novel auxiliary loss function for target-speaker automatic speech recognition (ASR). Our method automatically extracts and transcribes target speaker's utterances from a monaural mixture of multiple speakers speech given a short sample of the target speaker. The proposed auxiliary loss function attempts to additionally maximize in

Shilong Sun, Bert Jan Kooij, Alexander G. Yarovoy, Tian Jin

In this paper, a novel linear method for shape reconstruction is proposed based on the generalized multiple measurement vectors (GMMV) model. Finite difference frequency domain (FDFD) is applied to discretized Maxwell's equations, and the contrast sources are solved iteratively by exploiting the joint sparsity as a regularized constraint. Cross validation (C

Pierluigi Colli, Gianni Gilardi, Jürgen Sprekels

In this paper, we study a system of three evolutionary operator equations involving fractional powers of selfadjoint, monotone, unbounded, linear operators having compact resolvents. This system constitutes a generalization of a phase field system of Cahn-Hilliard type modelling tumor growth that has been proposed in Hawkins-Daarud et al. (Int. J. Numer. Mat

Amer Chamseddine, George Candea

Smartphones hold important private information, yet users routinely expose this information to questionable applications written by developers they know nothing about. Users may be tempted to think of smartphones as old-style dumb phones, not as powerful network-connected computers, and this opens a gap between the permissions-based security paradigm (offere

Tomotaka Kuwahara, Keiji Saito

This work explores fundamental statistical and thermodynamic properties of short-and long-range-interacting systems. The purpose of this study is twofold. Firstly, we rigorously prove that the probability distribution of arbitrary few-body observables is restricted by a Gaussian concentration bound (or Chernoff--Hoeffding inequality) above some threshold tem

Metin Gürses, Aslı Pekcan, Konstyantyn Zheltukhin

We show that nonlocal reductions of systems of integrable nonlinear partial differential equations are the special discrete symmetry transformations.

Daniel Erman, Steven V Sam, Andrew Snowden

We prove an analogue of Ananyan--Hochster's small subalgebra theorem in the context of sheaves on projective space, and deduce from this a version of Stillman's Conjecture for cohomology tables of sheaves. The main tools in the proof are Draisma's GL-noetherianity theorem and the BGG correspondence.

Giacomo Capodaglio, Max Gunzburger

The probability density function (PDF) associated with a given set of samples is approximated by a piecewise-linear polynomial constructed with respect to a binning of the sample space. The kernel functions are a compactly supported basis for the space of such polynomials, i.e. finite element hat functions, that are centered at the bin nodes rather than at t

Rong-Yao Yang, Wei-Zhou Jiang, Si-Na Wei

It is very difficult for any nuclear model to pin down the saturation property and high-density equation of state (EOS) simultaneously because of high nonlinearity of the nuclear many-body problem. In this work, we propose, for the first time, to use the special property of light kaonic nuclei to characterize the relation between saturation property and high

Jian-Dong Zhang, Zi-Jing Zhang, Jun-Yan Hu, Long-Zhu Cen

Many works have stated that nonlinear interactions can improve phase sensitivity beyond the Heisenberg limit scaling of $1/N$ with $N$ being the mean photon number. This raises some open questions---among them the conclusive sensitivity limits with respect to single-mode inputs. Namely, when one of two inputs is vacuum, is there a shot-noise-style sensitivit

Michele Villa

Let $\mathbb{S} \subset \mathbb{C}$ be the circle in the plane, and let $\Omega: \mathbb{S} \to \mathbb{S}$ be an odd bi-Lipschitz map with constant $1+\delta_\Omega$, where $\delta_\Omega>0$ is small. Assume also that $\Omega$ is twice continuously differentiable. Motivated by a question raised by Mattila and Preiss in [MP95], we prove the following: if a R

Frederico Botafogo

We review and interpret two basic propositions published by Ellerman (2014). The propositions address the algebraic structure of T accounts and double entry bookkeeping (DEB). The paper builds on this previous contribution with the view of reconciling the two, apparently dichotomous, perspectives of accounting measurement: the one that focuses preferably on

Shilong Sun, Bert Jan Kooij, Tian Jin, Alexander G. Yarovoy

In this paper, we improved the performance of the contrast source inversion (CSI) method by incorporating a so-called cross-correlated cost functional, which interrelates the state error and the data error in the measurement domain. The proposed method is referred to as the cross-correlated CSI. It enables better robustness and higher inversion accuracy than

K. Moriwaki, N. Yoshida, M. B. Eide, B. Ciardi

We study statistics of the 21-cm signal from the epoch of reionization. We propose to use [OIII] line emitting galaxies to cross-correlate with the 21-cm signal from $z = 7 - 10$. To this aim, we employ simulations of reionization obtained post-processing the high-resolution cosmological hydrodynamic simulation Massive Black-II with the three-dimensional (3D

Zhilin Hou, Xinsheng Fang, Yong Li, Badreddine Assouar

Typical acoustic refractive metasurfaces governed by generalized Snell law require several types of subwavelength subunits to provide an extra phase gradient along the surface. This design strategy, however, has several kinds of drawback. For instance, the inevitable viscous loss brought out by the complex subwavelength subunits, and the negligence of the co

V. A. Roman'kov, E. I. Timoshenko

We study verbally closed subgroups of free solvable groups. A number of results is proved that give sufficient conditions under whose a verbally closed subgroup is turned to be a retract and so algebraically closed of the full group.

Meisam Navaki Arefi, Rajkumar Pandi, Michael Carl Tschantz, Jedidiah R. Crandall

Widespread Chinese social media applications such as Weibo are widely known for monitoring and deleting posts to conform to Chinese government requirements. In this paper, we focus on analyzing a dataset of censored and uncensored posts in Weibo. Despite previous work that only considers text content of posts, we take a multi-modal approach that takes into a

Adam Lev-Libfeld

As demand for Real-Time applications rises among the general public, the importance of enabling large-scale, unbound algorithms to solve conventional problems with low to no latency is critical for product viability. Timer algorithms are prevalent in the core mechanisms behind operating systems, network protocol implementation, stream processing, and several

Peng-fei Wu, Zhen-hua Ling, Li-juan Liu, Yuan Jiang

This paper proposes an end-to-end emotional speech synthesis (ESS) method which adopts global style tokens (GSTs) for semi-supervised training. This model is built based on the GST-Tacotron framework. The style tokens are defined to present emotion categories. A cross entropy loss function between token weights and emotion labels is designed to obtain the in

Huiqin Ni, Xinsheng Fang, Zhilin Hou, Yong Li

As an inversely designed artificial device, metasurface usually means densely arranged meta-atoms with complex substructures. In acoustics, those meta-atoms are usually constructed by multi-folded channels or multi-connected cavities of deep sub-wavelength feature, which limits their implementation in pragmatic applications. We propose here a comprehensive c

Neri Merhav

Motivated by earlier results on universal randomized guessing, we consider an individual-sequence approach to the guessing problem: in this setting, the goal is to guess a secret, individual (deterministic) vector $x^n=(x_1,\ldots,x_n)$, by using a finite-state machine that sequentially generates randomized guesses from a stream of purely random bits. We def

Fabrice Baudoin, Nizar Demni, Jing Wang

We define and study the 3-dimensional windings along Brownian paths in the quaternionic Euclidean, projective and hyperbolic spaces. In particular, the asymptotic laws of these windings are shown to be Gaussian for the flat and spherical geometries while the hyperbolic winding exhibits a different long time-behavior. The corresponding asymptotic law seems to

Moti Kadosh, Yael Moses, Ariel Shamir

Humans can build a mental map of a geographical area to find their way and recognize places. The basic task we consider is geo-localization - finding the pose (position & orientation) of a camera in a large 3D scene from a single image. We aim to experimentally explore the role of geometry in geo-localization in a convolutional neural network (CNN) solution.

Sam Azadi, T. D. Kuehne

We reassess the phase diagram of high-pressure solid hydrogen using mean-field and many-body wave function based approaches to determine the nature of phase III of solid hydrogen. To discover the best candidates for phase III, density functional theory calculations within the meta-generalized gradient approximation by means of the strongly constrained and ap

Emil Björnson, Luca Sanguinetti

This paper takes a new look at Cell-free Massive MIMO (multiple-input multiple-output) through the lens of the dynamic cooperation cluster framework from the Network MIMO literature. The purpose is to identify and address scalability issues that appear in prior work. We provide distributed algorithms for initial access, pilot assignment, cluster formation, p

Vasile Patrascu

This article presents a new method of segmenting grayscale images by minimizing Shannon's neutrosophic entropy. For the proposed segmentation method, the neutrosophic information components, i.e., the degree of truth, the degree of neutrality and the degree of falsity are defined taking into account the belonging to the segmented regions and at the same time

Sadaqat ur Rehman, Zhongliang Yang, Muhammad Shahid, Nan Wei

Water supplies are crucial for the development of living beings. However, change in the hydrological process i.e. climate and land usage are the key issues. Sustaining water level and accurate estimating for dynamic conditions is a critical job for hydrologists, but predicting hydrological extremes is an open issue. In this paper, we proposed two deep learni

Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Zhi-Hua Zhou

To deal with changing environments, a new performance measure -- adaptive regret, defined as the maximum static regret over any interval, was proposed in online learning. Under the setting of online convex optimization, several algorithms have been successfully developed to minimize the adaptive regret. However, existing algorithms lack universality in the s

Shuhong Yang, Jun Zhang, Xiaohong Li, Zhong Liu

In the highly dynamic chromosphere, there exist many kinds of small-scale activities, such as spicules, surges, and Ellerman bombs. Here, we report the discovery of a new phenomenon in the chromosphere observed with the New Vacuum Solar Telescope at the Fuxian Solar Observatory. In the high tempo-spatial resolution H$\alpha$ images, some dark or bright struc

Daijiro Suematsu

Recent neutrino oscillation experiments suggest that the PMNS matrix in the lepton sector has a $CP$ violating phase as the CKM matrix in the quark sector. However, origin of these phases in both matrices are not clarified by now. Although complex Yukawa couplings could induce these phases, they remain as free parameters of the model even in that case. If th

Jing Han, Shengqian Ma, Yujie Wang, Geert Leus

Orthogonal signal-division multiplexing (OSDM) is an attractive alternative to conventional orthogonal frequency-division multiplexing (OFDM) due to its enhanced ability in peak-to-average power ratio (PAPR) reduction. Combining OSDM with multiple-input multiple-output (MIMO) signaling has the potential to achieve high spectral and power efficiency. However,

Vivek Sadhu

In this article, we construct a natural group homomorphism $$ \psi: \text{Br}(f)\to H^{1}_{et}(S, f_{*}\mathcal{O}_{X}^{\times}/\mathcal{O}_{S}^{\times})$$ for a faithful affine map $f: X \to S$ of noetherian schemes. Here $\text{Br}(f)$ denotes the relative Brauer group of $f.$ We also discuss the behavior of Brauer groups for a subintegral map. Furthermore

Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier

Tree ensembles such as Random Forests have achieved impressive empirical success across a wide variety of applications. To understand how these models make predictions, people routinely turn to feature importance measures calculated from tree ensembles. It has long been known that Mean Decrease Impurity (MDI), one of the most widely used measures of feature

Yuguang Yang, Michael A. Bevan, Bo Li

Equipping active colloidal robots with intelligence such that they can efficiently navigate in unknown complex environments could dramatically impact their use in emerging applications like precision surgery and targeted drug delivery. Here we develop a model-free deep reinforcement learning that can train colloidal robots to learn effective navigation strat

Ercan Yildiz, Joshua Safyan, Marc Harper

We study user sentiment (reported via optional surveys) as a metric for fully randomized A/B tests. Both user-level covariates and treatment assignment can impact response propensity. We propose a set of consistent estimators for the average and local treatment effects on treated and respondent users. We show that our problem can be mapped onto the intersect

Devashish Khulbe, Manu Pathak

The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines

Soheil Kolouri, Aniruddha Saha, Hamed Pirsiavash, Heiko Hoffmann

The unprecedented success of deep neural networks in many applications has made these networks a prime target for adversarial exploitation. In this paper, we introduce a benchmark technique for detecting backdoor attacks (aka Trojan attacks) on deep convolutional neural networks (CNNs). We introduce the concept of Universal Litmus Patterns (ULPs), which enab

Kenji Bekki

The observed discrete multiple stellar populations and internal abundance spreads in r- and s-process elements within globular clusters (GCs) have been suggested to be explained self-consistently by discrete star formation events over a longer timescale (10^8 yr). We here investigate whether such star formation is really possible within GCs using numerical s

Shao-Wen Wei, Yu-Xiao Liu, Robert B. Mann

The Ruppeiner geometry of thermodynamic fluctuations provides a powerful diagnostic of black hole microstructures. We investigate this for charged AdS black holes and find that while an attractive microstructure interaction dominates for most parameter ranges, a weak repulsive interaction dominates for small black holes of high temperature. This unique prope

Shimei Pan, Tao Ding

Automated representation learning is behind many recent success stories in machine learning. It is often used to transfer knowledge learned from a large dataset (e.g., raw text) to tasks for which only a small number of training examples are available. In this paper, we review recent advance in learning to represent social media users in low-dimensional embe

Alberto Alberello, Luke Bennetts, Petra Heil, Clare Eayrs

High temporal resolution in--situ measurements of pancake ice drift are presented, from a pair of buoys deployed on floes in the Antarctic marginal ice zone during the winter sea ice expansion, over nine days in which the region was impacted by four polar cyclones. Concomitant measurements of wave-in-ice activity from the buoys is used to infer that pancake

David Gunawan, Guy E. Hawkins, Robert Kohn, Minh-Ngoc Tran

Many psychological experiments have subjects repeat a task to gain the statistical precision required to test quantitative theories of psychological performance. In such experiments, time-on-task can have sizable effects on performance, changing the psychological processes under investigation. Most research has either ignored these changes, treating the unde

Rafael Pass, Muthuramakrishnan Venkitasubramaniam

Consider the following two fundamental open problems in complexity theory: (a) Does a hard-on-average language in NP imply the existence of one-way functions?, or (b) Does a hard-on-average language in NP imply a hard-on-average problem in TFNP (i.e., the class of total NP search problem)? Our main result is that the answer to (at least) one of these questio

Jiaren Yuan, Yumeng Yang, yongqing Cai, Yihong Wu

Skyrmions are localized solitonic spin textures with protected topology, which are promising as information carriers in ultra-dense and energy-efficient logic and memory devices. Recently, magnetic skyrmions have been observed in magnetic thin films, and are stabilized by the extrinsic interfacial Dzyaloshinskii-Moriya interaction (DMI) and/or external magne

Tomoki Nishi, Satoshi Koide, Keisuke Otaki, Ayano Okoso

Mobility-on-Demand (MoD) services, such as taxi-like services, are promising applications. Rebalancing the vehicle locations against customer requests is a key challenge in the services because imbalance between the two worsens service quality (e.g., longer waiting times). Previous work would be hard to apply to large-scale MoD services because of the comput

Zhenchuan Yang, Chun Zhang, Weibin Zhang, Jianxiu Jin

It is well known that a speech recognition system that combines multiple acoustic models trained on the same data significantly outperforms a single-model system. Unfortunately, real time speech recognition using a whole ensemble of models is too computationally expensive. In this paper, we propose to distill the knowledge of essence in an ensemble of models

Sota Arakawa, Ryuki Hyodo, Hidenori Genda

Recent studies have revealed that all large (over 1000 km in diameter) trans-Neptunian objects (TNOs) form satellite systems. Although the largest Plutonian satellite, Charon, is thought to be an intact fragment of an impactor directly formed via a giant impact, whether giant impacts can explain the variations in secondary-to-primary mass ratios and spin/orb

Guohua Wu, Xiaoyong Xi, Xiaoquan Xu, Dongsheng Zhao

We prove that for every $T_0$ space $X$, there is a well-filtered space $W(X)$ and a continuous mapping $\eta_X: X\lra W(X)$ such that for any well-filtered space $Y$ and any continuous mapping $f: X\lra Y$ there is a unique continuous mapping $\hat{f}: W(X)\lra Y$ such that $f=\hat{f}\circ \eta_X$. Such a space $W(X)$ will be called the well-filterification

Suyong Choi, Hayoung Oh

Data-driven methods of background estimations are often used to obtain more reliable descriptions of backgrounds. In hadron collider experiments, data-driven techniques are used to estimate backgrounds due to multi-jet events, which are difficult to model accurately. In this article, we propose an improvement on one of the most widely used data-driven method