November 2019 arXiv papers — page 43

Johannes Zabl, Nicolas F. Bouché, Ilane Schroetter, Martin Wendt

Galactic outflows are thought to eject baryons back out to the circum-galactic medium (CGM). Studies based on metal absorption lines (MgII in particular) in the spectra of background quasars indicate that the gas is ejected anisotropically, with galactic winds likely leaving the host in a bi-conical flow perpendicular to the galaxy disk. In this paper, we pr

Tomohiro Okuma

This article consists of two parts. The first part is a survey on the normal reduction numbers of normal surface singularities. It includes results on elliptic singularities, cone-like singularities and homogeneous hypersurface singularities. In the second part, we prove a new results on the normal reduction numbers and related invariants of Brieskorn comple

Beomki Yeo, MyeongJae Lee, Yoshitaka Kuno

This paper discusses a parallelized event reconstruction of the COMET Phase-I experiment. The experiment aims to discover charged lepton flavor violation by observing 104.97 MeV electrons from neutrinoless muon-to-electron conversion in muonic atoms. The event reconstruction of electrons with multiple helix turns is a challenging problem because hit-to-turn

Vong Anh Ho, Duong Huynh-Cong Nguyen, Danh Hoang Nguyen, Linh Thi-Van Pham

Emotion recognition or emotion prediction is a higher approach or a special case of sentiment analysis. In this task, the result is not produced in terms of either polarity: positive or negative or in the form of rating (from 1 to 5) but of a more detailed level of analysis in which the results are depicted in more expressions like sadness, enjoyment, anger,

Chuyuan Xiong, Deyuan Zhang, Tao Liu, Xiaoyong Du

Cross-modal associations between voice and face from a person can be learnt algorithmically, which can benefit a lot of applications. The problem can be defined as voice-face matching and retrieval tasks. Much research attention has been paid on these tasks recently. However, this research is still in the early stage. Test schemes based on random tuple minin

P. Warzanowski, N. Borgwardt, K. Hopfer, T. C. Koethe

The honeycomb compound $\alpha$-RuCl$_3$ is widely discussed as a proximate Kitaev spin-liquid material. This scenario builds on spin-orbit entangled $j = 1/2$ moments arising for a $t_{2g}^5$ electron configuration with strong spin-orbit coupling $\lambda$ and a large cubic crystal field. The low-energy electronic structure of $\alpha$-RuCl$_3$, however, is

Han Shi, Renjie Pi, Hang Xu, Zhenguo Li

Neural Architecture Search (NAS) has shown great potentials in finding better neural network designs. Sample-based NAS is the most reliable approach which aims at exploring the search space and evaluating the most promising architectures. However, it is computationally very costly. As a remedy, the one-shot approach has emerged as a popular technique for acc

Aanjaneya Kumar, Suman Kulkarni, M. S. Santhanam

Extreme events are emergent phenomena in multi-particle transport processes on complex networks. In practice, such events could range from power blackouts to call drops in cellular networks to traffic congestion on roads. All the earlier studies of extreme events on complex networks have focused only on the nodal events. If random walks are used to model tra

V. I. Yavrukova, G. M. Radulova, K. D. Danov, P. A. Kralchevsky

This is a review article on the rheological properties of mixed solutions of sulfonated methyl esters (SME) and cocamidopropyl betaine (CAPB), which are related to the synergistic growth of giant micelles. Effects of additives, such as fatty alcohols, cocamide monoethanolamine (CMEA) and salt, which are expected to boost the growth of wormlike micelles, are

Nejib Ghanmi

For a positive integer $N$ and $\mathbb{A}$ a subset of $\mathbb{Q}$, let $\mathbb{A}$-$\mathcal{KS}(N)$ denote the set of $α=\dfrac{α_{1}}{α_{2}}\in \mathbb{A}\setminus \{0,N\}$ verifying $α_{2}r-α_{1}$ divides $α_{2}N-α_{1}$ for every prime divisor $r$ of $N$. The set $\mathbb{A}$-$\mathcal{KS}(N)$ is called the set of $N$-Korselt bases in $\mathbb{A}$. Le

Hyunjong Park, Bumsub Ham

Person re-identification (reID) aims at retrieving an image of the person of interest from a set of images typically captured by multiple cameras. Recent reID methods have shown that exploiting local features describing body parts, together with a global feature of a person image itself, gives robust feature representations, even in the case of missing body

Alberto Barbado, Óscar Corcho, Richard Benjamins

OneClass SVM is a popular method for unsupervised anomaly detection. As many other methods, it suffers from the black box problem: it is difficult to justify, in an intuitive and simple manner, why the decision frontier is identifying data points as anomalous or non anomalous. Such type of problem is being widely addressed for supervised models. However, it

Long Chen, Gudrun Heinrich, Stephan Jahn, Stephen P. Jones

We present a calculation of the NLO QCD corrections to the loop-induced production of a photon pair through gluon fusion, including massive top quarks at two loops, where the two-loop integrals are calculated numerically. Matching the fixed-order NLO results to a threshold expansion, we obtain accurate results around the top quark pair production threshold.

Tianwei Zhang, Jun Jiang, Yinqian Zhang

We systematize software side-channel attacks with a focus on vulnerabilities and countermeasures in the cryptographic implementations. Particularly, we survey past research literature to categorize vulnerable implementations, and identify common strategies to eliminate them. We then evaluate popular libraries and applications, quantitatively measuring and co

Alireza Abdoli, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh

Poultry farms are a major contributor to the human food chain. However, around the world, there have been growing concerns about the quality of life for the livestock in poultry farms; and increasingly vocal demands for improved standards of animal welfare. Recent advances in sensing technologies and machine learning allow the possibility of monitoring birds

Zhenyu Weng, Yuesheng Zhu

Binary codes are widely used to represent the data due to their small storage and efficient computation. However, there exists an ambiguity problem that lots of binary codes share the same Hamming distance to a query. To alleviate the ambiguity problem, weighted binary codes assign different weights to each bit of binary codes and compare the binary codes by

Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu

Regularization plays a crucial role in machine learning models, especially for deep neural networks. The existing regularization techniques mainly rely on the i.i.d. assumption and only consider the knowledge from the current sample, without the leverage of the neighboring relationship between samples. In this work, we propose a general regularizer called \t

Sorna Prava Barik, Rashmi R. Nayak, Kamal L. Panigrahi

We discuss finite-size corrections to the spiky strings in $AdS$ space which is dual to the long $\mathcal{N}=4$ SYM operators of the form Tr($\Delta_+ ^{J_1}\phi_1\Delta_+ ^{J_2}\phi_2...\Delta_+ ^{J_n}\phi_n$). We express the finite-size dispersion relation in terms of Lambert $\mathbf{W}$-function. We further establish the finite-size scaling relation bet

Aaron Chan, William Wong

In the 40s, Mayer introduced a construction of (simplicial) $p$-complex by using the unsigned boundary map and taking coefficients of chains modulo $p$. We look at such a $p$-complex associated to an $(n-1)$-simplex; in which case, this is also a $p$-complex of representations of the symmetric group of rank $n$ - specifically, of permutation modules associat

William Donnelly, Sydney Timmerman, Nicolás Valdés-Meller

Two-dimensional Yang-Mills theory is a useful model of an exactly solvable gauge theory with a string theory dual at large $N$. We calculate entanglement entropy in the $1/N$ expansion by mapping the theory to a system of $N$ fermions interacting via a repulsive entropic force. The entropy is a sum of two terms: the "Boltzmann entropy", $\log \dim (R)$ per p

N. S. Pavlov, T. K. Kim, A. Yaresko, Ki-Young Choi

The electronic spectral function of BaNi$_2$As$_2$ is investigated using both the angle-resolved photoemission spectroscopy (ARPES) and a combined computational scheme of local density approximation together with dynamical mean-field theory (LDA+DMFT). In contrast to well studied isostructural iron arsenide high temperature superconductors, the BaNi$_2$As$_2

Bingyuan Liu, Jiantao Zhang, Xiaoting Zhang, Wei Zhang

Understanding interior scenes has attracted enormous interest in computer vision community. However, few works focus on the understanding of furniture within the scenes and a large-scale dataset is also lacked to advance the field. In this paper, we first fill the gap by presenting DeepFurniture, a richly annotated large indoor scene dataset, including 24k i

Ligong Han, Ruijiang Gao, Mun Kim, Xin Tao

Conditional generative adversarial networks have shown exceptional generation performance over the past few years. However, they require large numbers of annotations. To address this problem, we propose a novel generative adversarial network utilizing weak supervision in the form of pairwise comparisons (PC-GAN) for image attribute editing. In the light of B

J. F. Tao, J. Cai, Q. Z. Xia, J. Liu

In this paper, we propose a new method to characterize the temporal structure of arbitrary optical laser pulses with low pulse energies. This approach is based on strong field photoelectron holography with the glory rescattering effect as the underlying mechanism in the near-forward direction. Utilizing the subfemtosecond glory rescattering process as a fast

Enia Xhakaj, Benedikt Diemer, Alexie Leauthaud, Asher Wasserman

The splashback radius ($R_{\rm sp}$) of dark matter halos has recently been detected using weak gravitational lensing and cross-correlations with galaxies. However, different methods have been used to measure $R_{\rm sp}$ and to assess the significance of its detection. In this paper, we use simulations to study the precision and accuracy to which we can det

Lipo Wang, Guiwen Tan, Hui Cao

The geometrical structure is among the most fundamental ingredients in understanding complex systems. Is there any systematic approach in defining structures quantitatively, rather than illustratively? If yes, what are the basic principles to follow? By introducing the concept of extremal points at different scale levels, a multi-level dissipation element ap

Jin Zhang, Jeffrey M. McMahon, Artem R. Oganov, Xinfeng Li

Search for stable high-pressure compounds in the Ti--H system reveals the existence of titanium hydrides with new stoichiometries, including Ibam-Ti$_2$H$_5$, I4/m-Ti$_5$H$_{13}$, I$\bar{4}$-Ti$_5$H$_{14}$, Fddd-TiH$_4$, Immm-Ti$_2$H$_{13}$, P$\bar{1}$-TiH$_{12}$, and C2/m-TiH$_{22}$. Our calculations predict I4/mmm $\rightarrow$ R$\bar{3}$m and I4/mmm $\rig

E. Nakhmedov, B. D. Suleymanli, O. Z. Alekperov, F. Tatardar

Josephson current between two one-dimensional nanowires with proximity induced $p$-wave superconducting pairing is calculated in the presence of Rashba spin-orbit interaction, in-plane and normal magnetic fields. We show that Andreev retro-tunneling is realized by means of three channels. The main contribution to the Josephson current gives a scattering in a

Tal Golan, Prashant C. Raju, Nikolaus Kriegeskorte

Distinct scientific theories can make similar predictions. To adjudicate between theories, we must design experiments for which the theories make distinct predictions. Here we consider the problem of comparing deep neural networks as models of human visual recognition. To efficiently compare models' ability to predict human responses, we synthesize controver

Shashank Acharya, Wenjun Kou, Sourav Halder, Dustin A. Carlson

Balloon dilation catheters are often used to quantify the physiological state of peristaltic activity in tubular organs and comment on their ability to propel fluid which is important for healthy human function. To fully understand this system's behavior, we analyzed the effect of a solitary peristaltic wave on a fluid-filled elastic tube with closed ends. A

Asaf Karagila

We combine several folklore observations to provide a working framework for iterating constructions which contradict the axiom of choice. We use this to define a model in which any kind of structural failure must fail with a proper class of counterexamples. For example, the rational numbers have a proper class of non-isomorphic algebraic closures, every part

C. Ishizuka, X. Zhang, M. D. Usang, F. A. Ivanyuk

In this work we try to settle down the controversial predictions on the effect of doubly magic nuclei $^{132}$Sn and $^{208}$Pb on the mass distributions of fission fragments of super-heavy nuclei. For this we have calculated the mass distribution of super-heavy nuclei from $^{286}$Cn to $^{306}$122 within the dynamical 4-dimensional Langevin approach. We ha

Guang Jiang, Mengzhen Shi, Ying Su, Pengcheng An

Addressing students by their names helps a teacher to start building rapport with students and thus facilitates their classroom participation. However, this basic yet effective skill has become rather challenging for university lecturers, who have to handle large-sized (sometimes exceeding 100) groups in their daily teaching. To enhance lecturers' competence

Alexander Kurganov, Yongle Liu, Vladimir Zeitlin

We develop a well-balanced central-upwind scheme for rotating shallow water model with horizontal temperature and/or density gradients---the thermal rotating shallow water (TRSW). The scheme is designed using the flux globalization approach: first, the source terms are incorporated into the fluxes, which results in a hyperbolic system with global fluxes; sec

Massimo L. Villinger, Abbas Shiri, Soroush Shabahang, Ali K. Jahromi

Minimizing the material usage in thin-film solar cells can reduce manufacturing costs and enable mechanically flexible implementations, but concomitantly diminishes optical absorption. Coherent optical effects can help alleviate this inevitable drawback at discrete frequencies. For example, coherent perfect absorption guarantees that light is fully absorbed

Dazhong Shen, Qi Zhang, Tong Xu, Hengshu Zhu

Identifying the arrival times of seismic P-phases plays a significant role in real-time seismic monitoring, which provides critical guidance for emergency response activities. While considerable research has been conducted on this topic, efficiently capturing the arrival times of seismic P-phases hidden within intensively distributed and noisy seismic waves,

Pulong Ma, Anirban Mondal, Bledar Konomi, Jonathan Hobbs

Observing system uncertainty experiments (OSUEs) have been recently proposed as a cost-effective way to perform probabilistic assessment of retrievals for NASA's Orbiting Carbon Observatory-2 (OCO-2) mission. One important component in the OCO-2 retrieval algorithm is a full-physics forward model that describes the mathematical relationship between atmospher

Ryan Baker, Michel Pleimling

Cyclic dominance between species may yield spiral waves that are known to provide a mechanism enabling persistent species coexistence. This observation holds true even in presence of spatial heterogeneity in the form of quenched disorder. In this work we study the effects on spatio-temporal patterns and species coexistence of structured spatial heterogeneity

Ceyuan Yang, Yujun Shen, Bolei Zhou

Despite the success of Generative Adversarial Networks (GANs) in image synthesis, there lacks enough understanding on what generative models have learned inside the deep generative representations and how photo-realistic images are able to be composed of the layer-wise stochasticity introduced in recent GANs. In this work, we show that highly-structured sema

Katsuhiro Morita, Takami Tohyama

Frustrated quantum spin systems such as the Heisenberg and Kitaev models on various lattices, have been known to exhibit various exotic properties not only at zero temperature but also for finite temperatures. Inspired by the remarkable development of the quantum frustrated spin systems in recent years, we investigate the finite-temperature properties of the

Xiao Wang, Daisuke Kihara, Jiebo Luo, Guo-Jun Qi

Deep neural networks have been successfully applied to many real-world applications. However, such successes rely heavily on large amounts of labeled data that is expensive to obtain. Recently, many methods for semi-supervised learning have been proposed and achieved excellent performance. In this study, we propose a new EnAET framework to further improve ex

Xue Dong, Yang Lei, Sibo Tian, Yingzi Liu

As bone and air produce weak signals with conventional MR sequences, segmentation of these tissues particularly difficult in MRI. We propose to integrate patch-based anatomical signatures and an auto-context model into a machine learning framework to iteratively segment MRI into air, bone and soft tissue. The proposed semantic classification random forest (S

Ziqi Liu

In Baker and Lorscheid's paper, they introduce a new hyperstructure: the polynomial hyperstructure Poly$(\mathbb{F})$ over a hyperfield $\mathbb{F}$. In this work, the author focuses on associativity of hypermultiplications in those hyperstructures and gives elementary propositions. The author also shows examples of polynomial hyperstructures over hyperfield

Yifan Cui, Eric Tchetgen Tchetgen

There is a fast-growing literature on estimating optimal treatment regimes based on randomized trials or observational studies under a key identifying condition of no unmeasured confounding. Because confounding by unmeasured factors cannot generally be ruled out with certainty in observational studies or randomized trials subject to noncompliance, we propose

Jiajing Wu, Qi Yuan, Dan Lin, Wei You

Recently, blockchain technology has become a topic in the spotlight but also a hotbed of various cybercrimes. Among them, phishing scams on blockchain have been found making a notable amount of money, thus emerging as a serious threat to the trading security of the blockchain ecosystem. In order to create a favorable environment for investment, an effective

Yonatan Gur, Gregory Macnamara, Ilan Morgenstern, Daniela Saban

We consider a platform facilitating trade between sellers and buyers with the objective of maximizing consumer surplus. Even though in many such marketplaces prices are set by revenue-maximizing sellers, platforms can influence prices through (i) price-dependent promotion policies that can increase demand for a product by featuring it in a prominent position

H. N. S. Krishnamoorthy, G. Adamo, J. Yin, V. Savinov

High-index dielectric materials are in great demand for nanophotonic devices and applications, from ultrathin optical elements to metal-free sub-diffraction light confinement and waveguiding. Here we show that chalcogenide topological insulators are particularly apt candidates for dielectric nanophotonic architectures in the infrared spectral range by report

Tunhou Zhang, Hsin-Pai Cheng, Zhenwen Li, Feng Yan

Resource is an important constraint when deploying Deep Neural Networks (DNNs) on mobile and edge devices. Existing works commonly adopt the cell-based search approach, which limits the flexibility of network patterns in learned cell structures. Moreover, due to the topology-agnostic nature of existing works, including both cell-based and node-based approach

Diogo C Luvizon, Hedi Tabia, David Picard

3D human pose estimation is frequently seen as the task of estimating 3D poses relative to the root body joint. Alternatively, we propose a 3D human pose estimation method in camera coordinates, which allows effective combination of 2D annotated data and 3D poses and a straightforward multi-view generalization. To that end, we cast the problem as a view frus

Son Doan, Amanda Ritchart, Nicholas Perry, Juan D Chaparro

Background: Stress is a contributing factor to many major health problems in the United States, such as heart disease, depression, and autoimmune diseases. Relaxation is often recommended in mental health treatment as a frontline strategy to reduce stress, thereby improving health conditions. Objective: The objective of our study was to understand how people

Bohdan Bulanyi, Antoine Lemenant

In this paper we prove a partial $C^{1,\alpha}$ regularity result in dimension $N=2$ for the optimal $p$-compliance problem, extending for $p\not = 2$ some of the results obtained by A. Chambolle, J. Lamboley, A. Lemenant, E. Stepanov (2017). Because of the lack of good monotonicity estimates for the $p$-energy when $p\not = 2$, we employ an alternative tech

Ugo Rosolia, Francesco Borrelli

In this paper we present a Learning Model Predictive Control (LMPC) strategy for linear and nonlinear time optimal control problems. Our work builds on existing LMPC methodologies and it guarantees finite time convergence properties for the closed-loop system. We show how to construct a time varying safe set and terminal cost function using closed-loop data.

Chen Zhou

For a holomorphic one-form $\mathbf{\xi}$ on a weakly 1-complete manifold $X$ with certain properties, we discussed the connectivity of the pair $(\hat{X}, F^{-1}(z))$, where $\pi : \hat{X} \to X$ is a covering map and $dF=\pi^*\mathbf{\xi}$. We also discussed the criteria about when such a manifold $X$ admits a proper holomorphic mapping onto a Riemann surf

Nobuhiro Okabe, Simon Dicker, Dominique Eckert, Tony Mroczkowski

We present results from simultaneous modeling of high angular resolution GBT/MUSTANG-2 90 GHz Sunyaev-Zel'dovich effect (SZE) measurements and XMM-XXL X-ray images of three rich galaxy clusters selected from the HSC-SSP Survey. The combination of high angular resolution SZE and X-ray imaging enables a spatially resolved multi-component analysis, which is cru

Ugo Rosolia, Xiaojing Zhang, Francesco Borrelli

A robust Learning Model Predictive Controller (LMPC) for uncertain systems performing iterative tasks is presented. At each iteration of the control task the closed-loop state, input and cost are stored and used in the controller design. This paper first illustrates how to construct robust invariant sets and safe control policies exploiting historical data.

Visak Kumar, Tucker Hermans, Dieter Fox, Stan Birchfield

Using simulation to train robot manipulation policies holds the promise of an almost unlimited amount of training data, generated safely out of harm's way. One of the key challenges of using simulation, to date, has been to bridge the reality gap, so that policies trained in simulation can be deployed in the real world. We explore the reality gap in the

Timothy E. Lee, Jonathan Tremblay, Thang To, Jia Cheng

We present an approach for estimating the pose of an external camera with respect to a robot using a single RGB image of the robot. The image is processed by a deep neural network to detect 2D projections of keypoints (such as joints) associated with the robot. The network is trained entirely on simulated data using domain randomization to bridge the reality

Behrooz Semnani, Jeremy Flannery, Rubayet Al Maruf, Michal Bajcsy

Chirality refers to a geometric phenomenon in which objects are not superimposable on their mirror image. Structures made of nano-scale chiral elements can display chiroptical effects, such as dichroism for left- and right- handed circularly polarized light, which makes them of high interest for applications ranging from quantum information processing and qu

Anna Karlsson

In density matrix theory, entanglement is monogamous. However, we show that qubits can be arbitrarily entangled in a different, recently constructed model of qubit entanglement [arXiv:1907.11805]. We illustrate the differences between these two models, analyse how the density matrix property of monogamy of entanglement originates in assumptions of classical

Jorge Fandinno, Johannes Fichte

This is the Proceedings of the twelfth Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP) 2019, which was held in Philadelphia, USA, June 3rd , 2019.

Amin Bemani, Alireza Baghban, Shahaboddin Shamshirband, Amir Mosavi

In the present work, a novel and the robust computational investigation is carried out to estimate solubility of different acids in supercritical carbon dioxide. Four different algorithms such as radial basis function artificial neural network, Multi-layer Perceptron (MLP) artificial neural network (ANN), Least squares support vector machine (LSSVM) and adap

Priyank Pathak, Amir Erfan Eshratifar, Michael Gormish

The ability to identify the same person from multiple camera views without the explicit use of facial recognition is receiving commercial and academic interest. The current status-quo solutions are based on attention neural models. In this paper, we propose Attention and CL loss, which is a hybrid of center and Online Soft Mining (OSM) loss added to the atte

Ipek Ustun, Ege Ozer, Erim Habib, Burcin Tatliesme

This paper studied the change of vigilance based on stimulus coming consecutively using the computerized version of the Mackworth Clock Test run from PsyToolkit website. 7 participants (16.57 +/-1 years old, 2 males), performed 10 consecutive trials in order to measure whether or not it is a realistic goal for high school students to display the level of vig

Abhishek Kesarwani, Pabitra Mohan Khilar

Cloud computing is the technology that provides different types of services as a useful resource on the Internet. Resource trust value will help the cloud users to select the services of a cloud provider for processing and storing their essential information. Also, service providers can give access to users based on trust value to secure cloud resources from

Mohammad W. Alomari

In this work, we improve and refine some numerical radius inequalities. In particular, for all Hilbert space operators $T$, the celebrated Kittaneh inequality reads: \begin{align*} \frac{1}{4}\left\| T^*T + TT^*\right\|\le w^{2 }\left(T \right) \le \frac{1}{2}\left\| T^*T + TT^*\right\|. \end{align*} In this work we provide some important refinements for the

Ziming Liu, Xiaobo Liu

The traditional PCA fault detection methods completely depend on the training data. The prior knowledge such as the physical principle of the system has not been taken into account. In this paper, we propose a new multi-PCA fault detection model combined with prior knowledge. This new model can adapt to the variable operating conditions of the central air co

Chi Zhang, Massoud Rezavand, Xiangyu Hu

In this paper, we present a multi-resolution smoothed particle hydrodynamics (SPH) method for modeling fluid-structure interaction (FSI) problems. By introducing different smoothing lengths and time steps, the spatio-temporal discretization is applied with different resolutions for fluid and structure. To ensure momentum conservation at the fluid-structure c

Jonathan Connell

The visual world is very rich and generally too complex to perceive in its entirety. Yet only certain features are typically required to adequately perform some task in a given situation. Rather than hardwire-in decisions about when and what to sense, this paper describes a robotic system whose behavioral policy can be set by verbal instructions it receives.

R. A. S. Paiva, R. G. G. Amorim, S. C. Ulhoa, A. E. Santana

The two-dimensional hydrogen atom in an external magnetic field is considered in the context of phase space. Using solution of the Schrödinger equation in phase space the Wigner function related to the Zeeman effect is calculated. For this purpose, the Bohlin mapping is used to transform the Coulomb potential into a harmonic oscillator problem. Then it is po

Kooktae Lee

This paper proposes a control algorithm for stable implementation of asynchronous parallel quadratic programming (PQP) through dual decomposition technique. In general, distributed and parallel optimization requires synchronization of data at each iteration step due to the interdependency of data. The synchronization latency may incur a large amount of waiti

Christian de Ronde, César Massri

In this paper we argue against the orthodox definition of quantum entanglement which has been explicitly grounded on several "common sense" (metaphysical) presuppositions and presents today serious formal and conceptual drawbacks. This interpretation which some researchers in the field call "minimal", has ended up creating a narrative accordi

Jie Han

Keevash and Mycroft [\emph{Mem.~Amer.~Math.~Soc., 2015}] developed a geometric theory for hypergraph matchings and characterized the dense simplicial complexes that contain a perfect matching. Their proof uses the hypergraph regularity method and the hypergraph blow-up lemma recently developed by Keevash. In this note we give a new proof of their results, wh

K. D. Elworthy, Xue-Mei Li

There are two open problem on the analysis of continuous paths on a Riemannian manifold, the Markov uniqueness and the independence of the closure of the differential operator $d$ on its initial domain. The operator $d$ acts naturally on $BC^1$ functions, one is concerned with its extensions to the $L^2$ spaces. With a suitable choice of an initial domain we

Fangchen Liu, Zhan Ling, Tongzhou Mu, Hao Su

Consider an imitation learning problem that the imitator and the expert have different dynamics models. Most of the current imitation learning methods fail because they focus on imitating actions. We propose a novel state alignment-based imitation learning method to train the imitator to follow the state sequences in expert demonstrations as much as possible

Ramy Tanios, Samah El Mohtar, Omar Knio, Issam Lakkis

In geophysical fluid dynamics, the screened Poisson equation appears in the shallow-water, quasi geostrophic equations. Recently, many attempts have been made to solve those equations on the sphere using different numerical methods. These include vortex methods, which solve a Poisson equation to compute the stream-function from the (relative) vorticity. Alte

Dragan Hajdukovic

The aim of this brief review is twofold. First, we give an overview of the unprecedented experimental efforts to measure the gravitational acceleration of antimatter; with antihydrogen in three competing experiments at CERN (AEGIS, ALPHA and GBAR, and with muonium and positronium in other laboratories in the world. Second, we present the 21st Century's a

K. D. Elworthy, Xue-Mei Li

Formulae are given for $dP_t ϕ$, $d^*P_tϕ$ and $ΔP_tϕ$ for $P_t$ the heat semigroup acting on a q-form $ϕ$. The formulae are Brownian motion expectations of $ϕ$ composed with random translations determined by Weitzenbock curvarure terms. Derivatives of the curvature are not involved.

Chaitra, Sara Bertocco, Marco Molinaro, Sergio Molinari

The Virtual Observatory (VO) simulation standards, Simulation Data Model (SimDM) and Simulation Data Access Layer (SimDAL), establish a framework for the discoverability and dissemination of data created in simulation projects. These standards address the complexity of having a standard access and facade for data which is expected to be multifaceted and, of

Sofiat Olaosebikan, David Manlove

We study a variant of the Student-Project Allocation problem with lecturer preferences over Students where ties are allowed in the preference lists of students and lecturers (SPA-ST). We investigate the concept of strong stability in this context. Informally, a matching is strongly stable if there is no student and lecturer $l$ such that if they decide to fo

Tian-You Fan, Zhi-Yi Tang

Based on extended free energy of soft-matter quasicrystals and the variation principle on thermodynamic stability, this study reports the results on stability of the first kind of soft-matter quasicrystals. They are dependent only upon the material constants, and quite simple and intuitive, the material constants can be measured by experiments. The results a

Didan Deng, Zhaokang Chen, Yuqian Zhou, Bertram Shi

Spatial-temporal feature learning is of vital importance for video emotion recognition. Previous deep network structures often focused on macro-motion which extends over long time scales, e.g., on the order of seconds. We believe integrating structures capturing information about both micro- and macro-motion will benefit emotion prediction, because human per

Amir Zadeh, Tianjun Ma, Soujanya Poria, Louis-Philippe Morency

Monoaural audio source separation is a challenging research area in machine learning. In this area, a mixture containing multiple audio sources is given, and a model is expected to disentangle the mixture into isolated atomic sources. In this paper, we first introduce a challenging new dataset for monoaural source separation called WildMix. WildMix is design

Jonathan Connell

Home robots may come with many sophisticated built-in abilities, however there will always be a degree of customization needed for each user and environment. Ideally this should be accomplished through one-shot learning, as collecting the large number of examples needed for statistical inference is tedious. A particularly appealing approach is to simply expl

Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Wenqi Wei

Membership inference attacks seek to infer the membership of individual training instances of a privately trained model. This paper presents a membership privacy analysis and evaluation system, called MPLens, with three unique contributions. First, through MPLens, we demonstrate how membership inference attack methods can be leveraged in adversarial machine

Ruqi Zhang, Christopher De Sa

Gibbs sampling is a Markov chain Monte Carlo method that is often used for learning and inference on graphical models. Minibatching, in which a small random subset of the graph is used at each iteration, can help make Gibbs sampling scale to large graphical models by reducing its computational cost. In this paper, we propose a new auxiliary-variable minibatc

Eun Kyong Shin, Youngsang Kwon, Arash Shaban-Nejad

Our objective was to develop and test a new concept (affinity) analogous to multimorbidity of chronic conditions for individuals at census tract level in Memphis, TN. The use of affinity will improve the surveillance of multiple chronic conditions and facilitate the design of effective interventions. We used publicly available chronic condition data (Center

Konstantin Wernli

We review the Atiyah-Singer Index theorem and some applications. Only basic knowledge of differential geometry and Lie groups is required.

Lizet Sanchez, Patricia Lorenzo-Luaces, Claudia Fonte, Agustin Lage

Progress in immunotherapy revolutionized the treatment landscape for advanced lung cancer, raising survival expectations beyond those that were historically anticipated with this disease. In the present study, we describe the methods for the adjustment of mixture parametric models of two populations for survival analysis in the presence of long survivors. A

Nii Antiaye Addy, Arash Shaban-Nejad, David L. Buckeridge, Laurette Dubé

The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process

P. Chris Fragile

Across black hole (BH) and neutron star (NS) low-mass X-ray binaries (LMXBs), there appears to be some correlation between certain high- and low-frequency quasi-periodic oscillations (QPOs). In a previous paper, we showed that for BH LMXBs, this could be explained by the simultaneous oscillation and precession of a hot, thick, torus-like corona. In the curre

V. I. Abrosimov, O. I. Davydovska

The low-energy isoscalar dipole response of heavy spherical nuclei is studied by using a semiclassical model, based on the solution of the linearized Vlasov kinetic equation for finite Fermi systems. In this translation-invariant model the excitations of the center of mass motion are exactly separated from the internal ones. The low-energy dipole strength fu

David Oscari

We prove that every cubic surface in $\mathbb{C}[x,y,z,t]$ is Pfaffian. A constructive proof is given.

Paul Hongsuck Seo, Piyush Sharma, Tomer Levinboim, Bohyung Han

Human ratings are currently the most accurate way to assess the quality of an image captioning model, yet most often the only used outcome of an expensive human rating evaluation is a few overall statistics over the evaluation dataset. In this paper, we show that the signal from instance-level human caption ratings can be leveraged to improve captioning mode

Nahuel Andrés, Fouad Sahraoui, Sebastien Galtier, Lina Z. Hadid

The first complete estimation of the compressible energy cascade rate $|\varepsilon_\text{C}|$ at magnetohydrodynamic (MHD) and sub-ion scales is obtained in the Earth's magnetosheath using Magnetospheric MultiScale (MMS) spacecraft data and an exact law derived recently for {\it compressible} Hall MHD turbulence. A multi-spacecraft technique is used to

Yu Ye, Hao Chen, Zheng Ma, Ming Xiao

The alternating direction method of multipliers (ADMM) has recently been recognized as a promising approach for large-scale machine learning models. However, very few results study ADMM from the aspect of communication costs, especially jointly with running time. In this letter, we investigate the communication efficiency and running time of ADMM in solving

Konstantin Wernli

The goal of these lectures is to exhibit the framing anomaly in the Batalin-Vilkovisky formulation of perturbative Chern-Simons theory. Concretely, we show that the partition function fails to satisfy the Quantum Master Equation, and show that this can be remedied at the cost of introducing a framing. Along the way, we discuss principal bundles and connectio

K. D. Elworthy, Yves Le Jan, Xue-Mei Li

Integration by parts formulae are given for a class of measures on the space of paths of a smooth manifold $M$ determined by the laws of degenerate diffusions. The mother of such formulae, on the path space of diffeomorphism group of $M$ is shown to arise from a quasi-invariance property of measures determined by stochastic flows. From this the other formula

Son Doan, Quoc-Hung Ngo, Ai Kawazoe, Nigel Collier

We present the Global Health Monitor, an online Web-based system for detecting and mapping infectious disease outbreaks that appear in news stories. The system analyzes English news stories from news feed providers, classifies them for topical relevance and plots them onto a Google map using geo-coding information, helping public health workers to monitor th

K. D. Elworthy, Xue-Mei Li

An integration by parts formula is the foundation for stochastic analysis on path spaces over a (finite dimensional) Riemannian manifold or over $R^n$, from which we may deduce the operator $d$ is closable and define the Laplacian operator on path spaces. A useful formula on the Riemannian manifold is $$dP_tf(v)=(1/t)E f(x_t) \int_0^t \langle d\{x_s\}, v_s\r

Yu Meng, Maryam Karimzadehgan, Honglei Zhuang, Donald Metzler

In personal email search, user queries often impose different requirements on different aspects of the retrieved emails. For example, the query "my recent flight to the US" requires emails to be ranked based on both textual contents and recency of the email documents, while other queries such as "medical history" do not impose any constraints