March 2020 arXiv papers — page 55

Andreas A. Aigner, Walter Schrabmair

Benjamin Graham introduced a very simple formula for valuing a growth stock in 1962. How does it work and why? What is a sensible way to calculate this across many stocks and provide a scoring system to compare stocks amongst each other? We are presenting a methodology here which is put into practice.

A. M. Howard, S. J. Freeman, D. K. Sharp, T. Bloxham

A systematic study of neutron-hole strength in the N = 81 nuclei 137Ba, 139Ce, 141Nd and 143Sm is reported. The single-neutron removal reactions (p,d) and (3He,4He) were measured at energies of 23 and 34 MeV, respectively. Spectroscopic factors were extracted from measured cross sections through a distorted-wave Born approximation analysis and centroids of s

Andreas A. Aigner, Walter Schrabmair

'The trend is your friend' is a common saying, the difficulty lies in determining if and when you are in a trend. Is the trend strong enough to trade? When does the trend reverse and how are you going to determine this? We will try and answer at least some of these questions here. We are deriving a novel indicator to measure the power of a trend usin

Dan Alistarh, Giorgi Nadiradze, Amirmojtaba Sabour

We consider the following dynamic load-balancing process: given an underlying graph $G$ with $n$ nodes, in each step $t\geq 0$, one unit of load is created, and placed at a randomly chosen graph node. In the same step, the chosen node picks a random neighbor, and the two nodes balance their loads by averaging them. We are interested in the expected gap betwe

Nikhil Varma Keetha, Samson Anosh Babu P, Chandra Sekhara Rao Annavarapu

Early diagnosis and analysis of lung cancer involve a precise and efficient lung nodule segmentation in computed tomography (CT) images. However, the anonymous shapes, visual features, and surroundings of the nodule in the CT image pose a challenging problem to the robust segmentation of the lung nodules. This article proposes U-Det, a resource-efficient mod

Rafael T. Sousa, Lucas A. Pereira, Anderson S. Soares

Supervised learning with irregularly sampled time series have been a challenge to Machine Learning methods due to the obstacle of dealing with irregular time intervals. Some papers introduced recently recurrent neural network models that deals with irregularity, but most of them rely on complex mechanisms to achieve a better performance. This work propose a

Salvador Villegas

Consider the equation div$(φ^2 \nabla σ)=0$ in $\mathbb{R}^N,$ where $φ>0$. Berestycki, Caffarelli and Nirenberg proved that if there exists $C>0$ such that $\int_{B_R}(φσ)^2 \leq CR^2$ for every $R\geq 1$ then $σ$ is necessarily constant. In this paper we provide necessary and sufficient conditions on $0<Ψ\in C([1,\infty))$ for which this result remains tru

Zehao Wang, Shicheng Zhang, Xiaoou Chen

Melody is one of the most important components in music. Unlike other components in music theory, such as harmony and counterpoint, computable features for melody is urgently in need. These features are highly demanded as data-driven methods dominating the fields such as musical information retrieval and automatic music composition. To boost the performance

F. Marin, C. Beluffi

The architecture of a large interstellar spaceship, which is capable of serving as a living environment for a population over many generations, is mainly dictated by the needs of said population in terms of food, water and breathable gases. These resources cannot be stored for the entire duration of a journey that goes on for several centuries, so they must

Ilias I. Giannakopoulos, José E. C. Serrallés, Luca Daniel, Daniel K. Sodickson

Objective: Global Maxwell Tomography (GMT) is a recently introduced volumetric technique for noninvasive estimation of electrical properties (EP) from magnetic resonance measurements. Previous work evaluated GMT using ideal radiofrequency (RF) excitations. The aim of this simulation study was to assess GMT performance with a realistic RF coil. Methods: We de

Céline Duval, Ester Mariucci

We propose non-asymptotic controls of the cumulative distribution function $P(|X_{t}|\ge \varepsilon)$, for any $t>0$, $\varepsilon>0$ and any Lévy process $X$ such that its Lévy density is bounded from above by the density of an $α$-stable type Lévy process in a neighborhood of the origin. The results presented are non-asymptotic and optimal, they apply to

Richard S. J. Tol

A kernel density is an aggregate of kernel functions, which are itself densities and could be kernel densities. This is used to decompose a kernel into its constituent parts. Pearson&#39;s test for equality of proportions is applied to quantiles to test whether the component distributions differ from one another. The proposed methods are illustrated with a m

Leonardo Tinti

Second-order relativistic hydrodynamics is surprisingly predictive, even in the presence of large gradients. The hydrodynamic expansion from the method of moments does not require a gradient expansion, but it is intrinsically bound to the classic nature of relativistic kinetic theory. In this work a modified version of the method of moments is applied the Wi

Man-Kwun Chiu, Aruni Choudhary, Wolfgang Mulzer

The classic Ham-Sandwich theorem states that for any $d$ measurable sets in $\mathbb{R}^d$, there is a hyperplane that bisects them simultaneously. An extension by Bárány, Hubard, and Jerónimo [DCG 2008] states that if the sets are convex and \emph{well-separated}, then for any given $α_1, \dots, α_d \in [0, 1]$, there is a unique oriented hyperplane that cu

Yuya Yonezu, Rai Kou, Hidetaka Nishi, Koji Yamada

We evaluate the nonlinear coefficient of graphene-on-silicon waveguides through the coincidence measurement of photon-pairs generated via spontaneous four-wave mixing. We observed the temporal correlation of the photon-pairs from the waveguides over various transfer layouts of graphene sheets. A simple analysis of the experimental results using coupled-wave

Phan Xuan Tan, Tho Nguyen Duc, Chanh Minh Tran, Eiji Kamioka

Continuous QoE prediction is crucial in the purpose of maximizing viewer satisfaction, by which video service providers could improve the revenue. Continuously predicting QoE is challenging since it requires QoE models that are capable of capturing the complex dependencies among QoE influence factors. The existing approaches that utilize Long-Short-Term-Memo

Ulrich Langer, Andreas Schafelner

We consider locally stabilized, conforming finite element schemes on completely unstructured simplicial space-time meshes for the numerical solution of parabolic initial-boundary value problems with variable, possibly discontinuous in space and time, coefficients. Distributional sources are also admitted. Discontinuous coefficients, non-smooth boundaries, ch

Anna Björk Nikulásdóttir, Jón Guðnason, Anton Karl Ingason, Hrafn Loftsson

In this paper, we describe a new national language technology programme for Icelandic. The programme, which spans a period of five years, aims at making Icelandic usable in communication and interactions in the digital world, by developing accessible, open-source language resources and software. The research and development work within the programme is carri

Youming Qin, Yihang Li, Xu Wei, Fu Zhang

Exploiting contacts with environment structures provides extra force support to a UAV, often reducing the power consumption and hence extending the mission time. This paper investigates one such way to exploit flat surfaces in the environment by a novel aerial-ground hybrid locomotion. Our design is a single passive wheel integrated at the UAV bottom, servin

Nida Khan, Tabrez Ahmad, Anass Patel, Radu State

Blockchain governance is a subject of ongoing research and an interdisciplinary view of blockchain governance is vital to aid in further research for establishing a formal governance framework for this nascent technology. In this paper, the position of blockchain governance within the hierarchy of Institutional governance is discussed. Blockchain governance

Kazumasa Fujiwara, Masahiro Ikeda, Yuta Wakasugi

In the present paper, we prove time decay estimates of solutions in weighted Sobolev spaces to the second order evolution equation with fractional Laplacian and damping for data in Besov spaces. Our estimates generalize the estimates obtained in the previous studies. The second aim of this article is to apply these estimates to prove small data global well-p

Tunahan Demirci, Niclas Schneider, Tobias Steinpilz, Tabea Bogdan

A planetesimal moves through the gas of its protoplanetary disc where it experiences a head wind. Though the ambient pressure is low, this wind can erode and ultimately destroy the planetesimal if the flow is strong enough. For the first time, we observe wind erosion in ground based and microgravity experiments at pressures relevant in protoplanetary discs,

Abhishek Balakrishna, Justin T. Webster

The large deflections of panels in subsonic flow are considered. Specifically, a fully clamped von Karman plate accounting for both rotational inertia in plate filaments and structural damping of square root type is considered. The panel is taken to be embedded in the boundary of a linear, subsonic potential flow on the positive halfspace in $\mathbb R^3$. S

A. B. Leoneti, G. A. Prataviera

Motivated by empirical evidence that individuals within group decision making simultaneously aspire to maximize utility and avoid inequality we propose a criterion based on the entropy-norm pair for geometric selection of strict Nash equilibria in n-person games. For this, we introduce a mapping of an n-person set of Nash equilibrium utilities in an Entropy-

Lidong Cheng, Xi Deng, Bin Xie, Yi Jiang

Solving compressible flows containing discontinuities remains a major challenge for numerical methods especially on unstructured grids. Thus in this work, we make contributions to shock capturing schemes on unstructured grids with aim of resolving discontinuities with low numerical dissipation. Different from conventional shock capturing schemes which only u

Anmol Bhasin, Bharatram Natarajan, Gaurav Mathur, Himanshu Mangla

Intent and Slot Identification are two important tasks in Spoken Language Understanding (SLU). For a natural language utterance, there is a high correlation between these two tasks. A lot of work has been done on each of these using Recurrent-Neural-Networks (RNN), Convolution Neural Networks (CNN) and Attention based models. Most of the past work used two s

Hannah Markwig

This is a survey article written for the Jahresberichte der DMV. Tropical geometry can be viewed as an efficient combinatorial tool to study degenerations in algebraic geometry. Abstract tropical curves are essentially metric graphs, and covers of tropical curves maps between metric graphs satisfying certain conditions. In this short survey, we offer an intr

Jianglong Wu, Pu Zhang

In this paper, the main aim is to consider the boundedness of commutators of multilinear Calderón-Zygmund operators with Lipschitz functions in the context of the variable exponent Lebesgue spaces. Furthermore, the variable versions of the Lipschitz spaces are also discussed, and with the help of a key tool of a pointwise estimate involving the sharp maximal

Antoine Julia, Sebastiano Nicolussi Golo

We give a geometric criterion for a topological surface in the first Heisenberg group to be an intrinsic Lipschitz graph, using planar cones instead of the usual open cones.

Kangkang Deng, Zheng Peng

Canonical correlation analysis (CCA for short) describes the relationship between two sets of variables by finding some linear combinations of these variables that maximizing the correlation coefficient. However, in high-dimensional settings where the number of variables exceeds sample size, or in the case of that the variables are highly correlated, the tra

Thomas Kappeler, Yannick Widmer

The spectral curve associated with the sinh-Gordon equation on the torus is defined interms of the spectrum of the Lax operator appearing in the Lax pair formulation of the equation. If thespectrum is simple, it is an open Riemann surface of infinite genus. In this paper we construct normalizeddifferentials and derive estimates for the location of their zero

K. Y. Chew, Nurisya M. Shah, K. T. Chan

Quantum computation started to become significant field of studies as it hold great promising towards the upgrade of our current computational power. Studying the evolution of quantum states serves as a good fundamental in understanding quantum information which lead to quantum computation. This was assisted with the respective mathematical tools such as Lie

Sobhan Kanti Dhara, Debashis Sen

A pivotal step in image super-resolution techniques is interpolation, which aims at generating high resolution images without introducing artifacts such as blurring and ringing. In this paper, we propose a technique that performs interpolation through an infusion of high frequency signal components computed by exploiting `process similarity&#39;. By `process

Yoonjae Jeong, Hoon-Young Cho

The purpose of this study is to detect the mismatch between text script and voice-over. For this, we present a novel utterance verification (UV) method, which calculates the degree of correspondence between a voice-over and the phoneme sequence of a script. We found that the phoneme recognition probabilities of exaggerated voice-overs decrease compared to or

Ioanna Mitsioni, Yiannis Karayiannidis, Danica Kragic

Data-driven approaches for modelling contact-rich tasks address many of the difficulties that analytical models bear. For real-world scenarios, the hardware capabilities constrain the available measurements and consequently, every step of the problem&#39;s formulation. In this work, we propose a formulation that encapsulates knowledge from a baseline control

Morten Hannemose, Jakob Wilm, Jeppe Revall Frisvad

The most prevalent routine for camera calibration is based on the detection of well-defined feature points on a purpose-made calibration artifact. These could be checkerboard saddle points, circles, rings or triangles, often printed on a planar structure. The feature points are first detected and then used in a nonlinear optimization to estimate the internal

Rui Xiang, Feng Zheng, Huapeng Su, Zhe Zhang

In this paper, we propose an end-to-end deep learning network named 3dDepthNet, which produces an accurate dense depth image from a single pair of sparse LiDAR depth and color image for robotics and autonomous driving tasks. Based on the dimensional nature of depth images, our network offers a novel 3D-to-2D coarse-to-fine dual densification design that is b

Gunhee Nam, Seoung Wug Oh, Joon-Young Lee, Seon Joo Kim

We propose a novel memory-based tracker via part-level dense memory and voting-based retrieval, called DMV. Since deep learning techniques have been introduced to the tracking field, Siamese trackers have attracted many researchers due to the balance between speed and accuracy. However, most of them are based on a single template matching, which limits the p

Jiaao Li, Yulai Ma, Yongtang Shi, Weifan Wang

A bridgeless graph $G$ is called $3$-flow-critical if it does not admit a nowhere-zero $3$-flow, but $G/e$ has for any $e\in E(G)$. Tutte&#39;s $3$-flow conjecture can be equivalently stated as that every $3$-flow-critical graph contains a vertex of degree three. In this paper, we study the structure and extreme edge density of $3$-flow-critical graphs. We a

Danijel Grahovac

We investigate stochastic processes possessing scale invariance properties which we refer to as multifractal processes. The examples of such processes known so far do not go much beyond the original cascade construction of Mandelbrot. We provide a new definition of the multifractal process by generalizing the definition of the self-similar process. We establ

Shaik Tanveer Ul Huq, Vadlamani Ravi

In this paper, two multi-objective optimization frameworks in two variants (i.e., NSGA-III-ARM-V1, NSGA-III-ARM-V2; and MOEAD-ARM-V1, MOEAD-ARM-V2) are proposed to find association rules from transactional datasets. The first framework uses Non-dominated sorting genetic algorithm III (NSGA-III) and the second uses Decomposition based multi-objective evolutio

Ferdinand Verhulst

We will present a survey of low energy periodic Fermi-Pasta-Ulam chains with leading idea the &#34;breaking of symmetry&#34;. The classical periodic FPU-chain (equal masses for all particles) was analysed by Rink in 2001 with main conclusions that the normal form of the beta-chain is always integrable and that in many cases this also holds for the alfa-chain

Chang-Dong Xu, Xing-Ran Zhao, Xin Jin, Xiu-Shen Wei

In this paper, we tackle the domain adaptive object detection problem, where the main challenge lies in significant domain gaps between source and target domains. Previous work seeks to plainly align image-level and instance-level shifts to eventually minimize the domain discrepancy. However, they still overlook to match crucial image regions and important i

Hong-Gyu Jung, Seong-Whan Lee

In this article, we consider the problem of few-shot learning for classification. We assume a network trained for base categories with a large number of training examples, and we aim to add novel categories to it that have only a few, e.g., one or five, training examples. This is a challenging scenario because: 1) high performance is required in both the bas

Magda Friedjungová, Daniel Vašata, Tomáš Chobola, Marcel Jiřina

One task that is often discussed in a computer vision is the mapping of an image from one domain to a corresponding image in another domain known as image-to-image translation. Currently there are several approaches solving this task. In this paper, we present an enhancement of the UNIT framework that aids in removing its main drawbacks. More specifically, w

Kazumasa Iida, Jens Hänisch, Akiyasu Yamamoto

Understanding the nature of grain boundary (GB) characteristics in combination with creating low-energy GBs by modifying the processing conditions, so-called GB engineering, is of great importance for controlling and reducing the defect density, leading to improved functionalities of polycrystalline metals and ceramics. For superconductors particularly, incl

Bin Chen, Jie Wu, Yichao Zhang

In this paper, we consider the first negative eigenvalue of eigenforms of half-integral weight k + 1/2 and obtain an almost type bound.

Simon Kitson

A generalisation of the equivariant Dixmier-Douady invariant is constructed as a second-degree cohomology class within a new semi-equivariant Čech cohomology theory. This invariant obstructs liftings of semi-equivariant principal bundles that are associated to central exact sequences of structure groups in which each structure group is acted on by the equiva

Pierre-Henri Cocquet, Sebastián Riffo, Julien Salomon

This paper deals with bathymetry-oriented optimization in the case of long waves with small amplitude. Under these two assumptions, the free-surface incompressible Navier-Stokes system can be written as a wave equation where the bathymetry appears as a parameter in the spatial operator. Looking then for time-harmonic fields and writing the bottom topography

Silvano Dal Zilio

MCC is a tool designed for a very specific task: to transform the models of High-Level Petri nets, given in the PNML syntax, into equivalent Place/Transition nets. The name of the tool derives from the annual Model-Checking Contest, a competition of model-checking tools that provides a large and diverse collection of PNML models. This choice in naming serves

Will Johnson

We investigate fields of characteristic 0 and dp-rank 2. While we do not obtain a classification, we prove that any unstable field of characteristic 0 and dp-rank 2 admits a unique definable V-topology. If this statement could be generalized to higher ranks, we would obtain the expected classification of fields of finite dp-rank. We obtain the unique definab

Yu. Sokolovskaya, O. Miroshkina, V. Sokolovskiy, M. Zagrebin

In the present work, the aspects of magnetic and structural properties of Ni-Mn-Ga alloys are described in the framework of fist-principles approach and mapped into ternary composition diagrams. The stable atomic arrangement and magnetic alignment for compositions with cubic austenite and tetragonal martensite structures across phase diagrams are predicted.

Manuela Weigold, Johanna Barzen, Uwe Breitenbücher, Michael Falkenthal

Patterns describe proven solutions for recurring problems. Typically, patterns in a particular domain are interrelated and organized in pattern languages. As real-world problems often require patterns of multiple domains, different pattern languages have to be considered to address these problems. However, cross-domain knowledge about how patterns of differe

Helena Ferreira, Marta Ferreira

The extreme values theory presents specific tools for modeling and predicting extreme phenomena. In particular, risk assessment is often analyzed through measures for tail dependence and high values clustering. Despite technological advances allowing an increasingly larger and more efficient data collection, there are sometimes failures in the records, which

Fei Tao, Gokhan Tur

Speaker verification is an established yet challenging task in speech processing and a very vibrant research area. Recent speaker verification (SV) systems rely on deep neural networks to extract high-level embeddings which are able to characterize the users&#39; voices. Most of the studies have investigated on improving the discriminability of the networks

Younghyun Jo, Jaeyeon Kang, Seoung Wug Oh, Seonghyeon Nam

With more advanced deep network architectures and learning schemes such as GANs, the performance of video restoration algorithms has greatly improved recently. Meanwhile, the loss functions for optimizing deep neural networks remain relatively unchanged. To this end, we propose a new framework for building effective loss functions by learning a discriminativ

Hongbo Zhao

In this paper we use Lie conformal algebras to realize some moonshine type VOAs, whose Greiss algebras are Jordan algebras. On the other hand, we consider some free fields which realizes the corresponding simple VOAs. As an application, we can calculate the correlation functions of these VOAs in a relatively easy way.

Zhiwei Dong, Guoxuan Li, Yue Liao, Fei Wang

Keypoint-based detectors have achieved pretty-well performance. However, incorrect keypoint matching is still widespread and greatly affects the performance of the detector. In this paper, we propose CentripetalNet which uses centripetal shift to pair corner keypoints from the same instance. CentripetalNet predicts the position and the centripetal shift of t

Eugene N. Ivanov, Michael E. Tobar

Based on the principles of microwave circuit interferometry we have constructed a Reduced Noise Amplifier (RNA) with power spectral density of phase, as well as amplitude, fluctuations close to -170 dBc/Hz at 1 kHz offset. The RNA has been incorporated with a cryogenic sapphire resonator as a loop oscillator whose noise performance is governed by the Leeson&

Xinyu Zhang, Yang Zhao, Hao Zhang

A wealth of angle problems occur when facial recognition is performed: At present, the feature extraction network presents eigenvectors with large differences between the frontal face and profile face recognition of the same person in many cases. For this reason, the state-of-the-art facial recognition network will use multiple samples for the same target to

Victor Didenko, Bernd Silbermann

The paper describes various approaches to the invertibility of Toeplitz plus Hankel operators in Hardy and $l^p$-spaces, integral and difference Wiener-Hopf plus Hankel operators and generalized Toeplitz plus Hankel operators. Special attention is paid to a newly developed method, which allows to establish necessary, sufficient and also necessary and suffici

German I. Parisi, Vincenzo Lomonaco

Online continual learning (OCL) refers to the ability of a system to learn over time from a continuous stream of data without having to revisit previously encountered training samples. Learning continually in a single data pass is crucial for agents and robots operating in changing environments and required to acquire, fine-tune, and transfer increasingly co

Arthur Baragar

We call a packing of hyperspheres in $n$ dimensions an Apollonian sphere packing if the spheres intersect tangentially or not at all; they fill the $n$-dimensional space; and every sphere in the packing is a member of a cluster of $n+2$ mutually tangent spheres (and a few more properties described herein). In this paper, we describe an Apollonian packing in

Lei Zhang, Zhijun Qiao

In this paper, we prove the global Hadamard well-posedness of strong solutions to a non-isospectral two-component cubic Camassa-Holm system in the critical Besov space $B_{2,1}^{\frac{1}{2}}(\mathbb{T})$. Our results shows that in comparison with the well-known work for classic Camassa-Holm-type equations, the existence of global solution only relies on the

Stephan Tornier

This article concerns Burger--Mozes universal groups acting on regular trees locally like a given permutation group of finite degree. We also consider locally isomorphic generalizations of the former due to Le Boudec and Lederle. For a large class of such permutation groups and primes $p$ we determine their local $p$-Sylow subgroups as well as subgroups of t

Dong Wang, Yuan Zhang, Kexin Zhang, Liwei Wang

Applying artificial intelligence techniques in medical imaging is one of the most promising areas in medicine. However, most of the recent success in this area highly relies on large amounts of carefully annotated data, whereas annotating medical images is a costly process. In this paper, we propose a novel method, called FocalMix, which, to the best of our

Kazumasa Iida, Takuya Matsumoto, Keisuke Kondo, Takafumi Hatano

NdFeAs(O,F) thin films having different fluorine contents were grown on 5 deg. or 10 deg. vicinal cut MgO and CaF2 single crystalline substrates by molecular beam epitaxy. Structural characterisations by reflection high-energy electron diffraction and x-ray diffraction confirmed the epitaxial growth of NdFeAs(O,F). The resistivities of the ab-plane and along

Clare D&#39;Cruz

In this survey article we give a brief history of symbolic powers and its connection with the interesting problem of set-theoretic complete intersection. We also state a few problems and conjectures. Recently, in connection to symbolic powers is the containment problem. We list a few interesting results and related problems on the resurgence, Waldschmidt con

Christopher L. Asplund, Takashi Obana, Parag Bhatnagar, Xun Quan Koh

Vibration is an efficient way of conveying information from a device to its user, and it is increasingly used for wrist or finger-worn devices such as smart rings. Unexpected vibrations or sounds from the environment may disrupt the perception of such information. Although disruptive effects have been systematically explored in vision and audition, they have

Rakshith S Srinivasa, Mark A Davenport, Justin Romberg

We consider sketched approximate matrix multiplication and ridge regression in the novel setting of localized sketching, where at any given point, only part of the data matrix is available. This corresponds to a block diagonal structure on the sketching matrix. We show that, under mild conditions, block diagonal sketching matrices require only O(stable rank

Takehiro Yonehara, Takahito Nakajima, Hikaru Kobayashi, King-Chuen Lin

A new type of, called stereo-specific entangled, roaming mechanism is presented in the reaction of structurally unstable B5 cluster with the hydrogen atom, by using the direct ab initio trajectory calculation with a practical level of DFT method using the rang-separated functional. In this mechanism, the light moiety, i.e. H roams around far from the B5 clus

Jingwen Ye, Yixin Ji, Xinchao Wang, Xin Gao

Recent advances in deep learning have provided procedures for learning one network to amalgamate multiple streams of knowledge from the pre-trained Convolutional Neural Network (CNN) models, thus reduce the annotation cost. However, almost all existing methods demand massive training data, which may be unavailable due to privacy or transmission issues. In th

Minjee Kim, Joonmyeong Choi, Namkug Kim

Hand hygiene is one of the most significant factors in preventing hospital acquired infections (HAI) which often be transmitted by medical staffs in contact with patients in the operating room (OR). Hand hygiene monitoring could be important to investigate and reduce the outbreak of infections within the OR. However, an effective monitoring tool for hand hyg

Fan Liu, Zhiyong Cheng, Lei Zhu, Chenghao Liu

As important side information, attributes have been widely exploited in the existing recommender system for better performance. In the real-world scenarios, it is common that some attributes of items/users are missing (e.g., some movies miss the genre data). Prior studies usually use a default value (i.e., &#34;other&#34;) to represent the missing attribute,

Huu Le, Christopher Zach

Due to the highly non-convex nature of large-scale robust parameter estimation, avoiding poor local minima is challenging in real-world applications where input data is contaminated by a large or unknown fraction of outliers. In this paper, we introduce a novel solver for robust estimation that possesses a strong ability to escape poor local minima. Our algo

Kshitij Tayal, Chieh-Hsin Lai, Vipin Kumar, Ju Sun

In many physical systems, inputs related by intrinsic system symmetries are mapped to the same output. When inverting such systems, i.e., solving the associated inverse problems, there is no unique solution. This causes fundamental difficulties for deploying the emerging end-to-end deep learning approach. Using the generalized phase retrieval problem as an i

Ed T. Upchurch

Servers produced by mainstream vendors are inefficient in processing Big Data queries due to bottlenecks inherent in the fundamental architecture of these systems. Current server blades contain multicore processors connected to DRAM memory and disks by an interconnection chipset. The multicore processor chips perform all the computations while the DRAM and d

Richard S. Laugesen

The center of mass of a finite measure with respect to a radially increasing weight is shown to exist, be unique, and depend continuously on the measure.

Szu-Yeu Hu, Shuhang Wang, Wei-Hung Weng, JingChao Wang

Modern deep learning algorithms geared towards clinical adaption rely on a significant amount of high fidelity labeled data. Low-resource settings pose challenges like acquiring high fidelity data and becomes the bottleneck for developing artificial intelligence applications. Ultrasound images, stored in Digital Imaging and Communication in Medicine (DICOM)

Jerome Droniou, Robert Eymard

Gradient schemes is a framework that enables the unified convergence analysis of many numerical methods for elliptic and parabolic partial differential equations: conforming and non-conforming Finite Element, Mixed Finite Element and Finite Volume methods. We show here that this framework can be applied to a family of degenerate non-linear parabolic equation

Dongyue Li, R. D. Saxton, Weimin Yuan, Luming Sun

We present multiwavelength studies of a transient X-ray source, XMMSL1 J131952.3+225958, associated with the galaxy NGC 5092 at $z=0.023$ detected in the XMM-Newton SLew survey (XMMSL). The source brightened in the 0.2--2 keV band by a factor of $>20$ in 2005 as compared with previous flux limits and then faded by a factor of $>200$ as observed with it XMM-N

Jonathan Wylie, Tom Chou

We derive and asymptotically analyze mass-action models for disease spread that include transient pair formation and dissociation. Populations of unpaired susceptibles and infecteds are distinguished from the population of three types of pairs of individuals; both susceptible, one susceptible and one infected, and both infected. Disease transmission can occu

Zehan Chao, Longxiu Huang, Deanna Needell

In our paper, we have studied the tensor completion problem when the sampling pattern is deterministic. We first propose a simple but efficient weighted HOSVD algorithm for recovery from noisy observations. Then we use the weighted HOSVD result as an initialization for the total variation. We have proved the accuracy of the weighted HOSVD algorithm from theo

Ai Du, Yuhan Xie, Yan Li, Yongdong Pan

The manipulation of sound with acoustic metamaterials is a field of intense research, where interaction via resonance is a common application despite the significant disadvantages. We propose a novel procedure for introducing well-designed coupling interfaces with a cell size of less than 10 nm into an ultra-soft porous medium, to prepare a meta-aerogel, whe

Tonghe Wang, Yang Lei, Joseph Harms, Beth Ghavidel

Purpose: Dual-energy CT (DECT) has been used to derive relative stopping power (RSP) map by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques, which would affect subsequent clinical applications. Thi

Jakub Nikonowicz, Aamir Mahmood, Mikael Gidlund

Energy detection process for enabling opportunistic spectrum access in dynamic primary user (PU) scenarios, where PU changes state from active to inactive at random time instances, requires estimation of several parameters ranging from noise variance and signal-to-noise ratio (SNR) to instantaneous and average PU activity. A prerequisite to parameter estimat

Anders M. N. Niklasson

Extended Lagrangian Born-Oppenheimer molecular dynamics [{\em Phys.\ Rev.\ Lett.\ } {\bf 2008}, {\em 100}, 123004] is presented for Hartree-Fock theory, where the extended electronic degrees of freedom are represented by a density matrix, including fractional occupation numbers at elevated electronic temperatures. In contrast to regular direct Born-Oppenheim

Chen Bar-Haim, Haim Diamant

We study theoretically the surface response of a semi-infinite viscoelastic polymer network using the two-fluid model. We focus on the overdamped limit and on the effect of the network's intrinsic length scales. We calculate the decay rate of slow surface fluctuations, and the surface displacement in response to a localized force. Deviations from the large-s

John F. Donoghue, Gabriel Menezes

In the understanding of the fundamental interactions, the origin of an arrow of time is viewed as problematic. However, quantum field theory has an arrow of causality, which tells us which time direction is the past lightcone and which is the future. This direction is tied to the conventions used in the quantization procedures. The different possible causal

Elizabeth H. Krath, Forrest L. Carpenter, Paul G. A. Cizmas, David A. Johnston

This paper presents a novel, more efficient proper orthogonal decomposition (POD) based reduced-order model (ROM) for compressible flows. In this POD model the governing equations, i.e., the conservation of mass, momentum, and energy equations were written using specific volume instead of density. This substitution allowed for the pre-computation of the coef

Constanza Fierro, Jorge Pérez, Javier Mora

Deep learning techniques have been successfully applied to predict unplanned readmissions of patients in medical centers. The training data for these models is usually based on historical medical records that contain a significant amount of free-text from admission reports, referrals, exam notes, etc. Most of the models proposed so far are tailored to Englis

Robert T. Zellem, Kyle A. Pearson, Ethan Blaser, Martin Fowler

Due to the efforts by numerous ground-based surveys and NASA's Kepler and TESS, there will be hundreds, if not thousands, of transiting exoplanets ideal for atmospheric characterization via spectroscopy with large platforms such as JWST and ARIEL. However their next predicted mid-transit time could become so increasingly uncertain over time that significant

Victor Venturi, Holden Parks, Zeeshan Ahmad, Venkatasubramanian Viswanathan

The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending and generalizing crystal graph convolutional neural networks to systems with planar periodicity, and train an ensemble of

R. Avella, J. J. Mendoza-Arenas, R. Franco, J. Silva-Valencia

Superfluid-insulator transitions in a one-dimensional mixture of two-color fermions and scalar bosons are studied within the framework of the Bose-Fermi-Hubbard model. Zero-temperature phase diagrams are constructed for repulsive intraspecies interactions and attractive or repulsive interspecies couplings. In addition to the trivial Mott insulator phases, we

Ryan Hoque, Daniel Seita, Ashwin Balakrishna, Aditya Ganapathi

Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks, making it difficult to generalize across different but related tasks. We extend the Visual Foresight framework to learn fabric dynamics that can be efficiently reused to accomplis

Duarte Azevedo, Rodrigo Capucha, António Onofre, Rui Santos

In this paper we explore CP discrimination in the associated production of top-quark pairs ($t\bar{t}$) with a generic scalar boson ($\phi$) at the LHC. We probe the CP-sensitivity of several observables for a varying scalar boson mass and CP-number, either CP-even ($\phi=H$) or CP-odd ($\phi=A$), using dileptonic final states of the $t\bar{t}\phi$ system, w

Tommaso Favalli, Augusto Smerzi

Time in quantum mechanics is peculiar: it is an observable that cannot be associated to an Hermitian operator. As a consequence it is impossible to explain dynamics in an isolated system without invoking an external classical clock, a fact that becomes particularly problematic in the context of quantum gravity. An unconventional solution was pioneered by Pag

Kensen Shi, David Bieber, Rishabh Singh

The success and popularity of deep learning is on the rise, partially due to powerful deep learning frameworks such as TensorFlow and PyTorch that make it easier to develop deep learning models. However, these libraries also come with steep learning curves, since programming in these frameworks is quite different from traditional imperative programming with

Kananart Kuwaranancharoen, Lei Xin, Shreyas Sundaram

The problem of distributed optimization requires a group of agents to reach agreement on a parameter that minimizes the average of their local cost functions using information received from their neighbors. While there are a variety of distributed optimization algorithms that can solve this problem, they are typically vulnerable to malicious (or ``Byzantine'

Guy David, Joseph Feneuil, Svitlana Mayboroda

Take an open domain $\Omega \subset \mathbb R^n$ whose boundary may be composed of pieces of different dimensions. For instance, $\Omega$ can be a ball on $\mathbb R^3$, minus one of its diameters $D$, or $\Omega \subset \mathbb R^3$ could be a so-called saw-tooth domain, with a boundary consisting of pieces of 1-dimensional curves intercepted by 2-dimension