April 2020 arXiv papers — page 20

Fred Diamond, Payman L Kassaei

We prove that all mod $p$ Hilbert modular forms arise via multiplication by generalized partial Hasse invariants from forms whose weight falls within a certain minimal cone. This answers a question posed by Andreatta and Goren, and generalizes our previous results which treated the case where $p$ is unramified in the totally real field. Whereas our previous

Zonghe Chua, Anthony M. Jarc, Sherry Wren, Ilana Nisky

The lack of haptic feedback in Robot-assisted Minimally Invasive Surgery (RMIS) is a potential barrier to safe tissue handling during surgery. Bayesian modeling theory suggests that surgeons with experience in open or laparoscopic surgery can develop priors of tissue stiffness that translate to better force estimation abilities during RMIS compared to surgeo

David Lee

Upwinded mass fluxes are described and analysed for advection operators discretised using mixed mimetic spectral elements. This involves a Petrov-Galerkin formulation by which the mass flux test functions are evaluated at downstream locations along velocity characteristics. As for the original mixed mimetic spectral element advection operator, the upwinded m

Shousuke Ohmori, Yoshihiro Yamazaki

Bifurcations of one dimensional dynamical systems are discussed based on some ultradiscrete equations. The ultradiscrete equations are derived from normal forms of one-dimensional nonlinear differential equations, each of which has saddle-node, transcritical, or supercritical pitchfork bifurcations. An additional bifurcation, which is similar to flip bifurca

M. B. Andorf, V. A. Lebedev, P. Piot

An amplifier based on a highly-doped Chromium Zinc-Selenide (Cr:ZnSe) crystal is proposed to increase the pulse energy emitted by an electron bunch after it passes through an undulator magnet. The primary motivation is a possible use of the amplified undulator radiation emitted by a beam circulating in a particle accelerator storage ring to increase the part

Kazuki Yamaga

In this paper, Non-Equilibrium Steady State induced by electric field and the conductivity of non-interacting fermion systems under the dissipative dynamics is discussed. The dissipation is taken into account within a framework of the quantum dynamical semigroup introduced by Davies (1977). We obtain a formula of the conductivity for the stationary state, wh

Kyubyong Park

Korean is a morphologically rich language. Korean verbs change their forms in a fickle manner depending on tense, mood, speech level, meaning, etc. Therefore, it is challenging to construct comprehensive conjugation paradigms of Korean verbs. In this paper we introduce a Korean (verb) conjugation paradigm generator, dubbed KoParadigm. To the best of our know

Artem Abanov, Andrey V. Chubukov

We analyze a class of quantum-critical models, in which momentum integration and the selection of a particular pairing symmetry can be done explicitly, and the competition between non-Fermi liquid and pairing can be analyzed within an effective model with dynamical electron-electron interaction $V(\Omega_m)\sim 1/|\Omega_m|^\gamma$ (the $\gamma$-model). In t

Elissa M. Redmiles

The COVID19 pandemic spread across the world in late 2019 and early 2020. As the pandemic spread, technologists joined forces with public health officials to develop apps to support COVID19 response. Yet, for these technological solutions to benefit public health, users must be willing to adopt these apps.This paper details the potential inputs to a user's d

Duong Tung Nguyen, Hieu Trung Nguyen, Ni Trieu, Vijay K. Bhargava

Edge computing has emerged as a key technology to reduce network traffic, improve user experience, and enable various Internet of Things applications. From the perspective of a service provider (SP), how to jointly optimize the service placement, sizing, and workload allocation decisions is an important and challenging problem, which becomes even more compli

Rodrigo Santa Cruz, Anoop Cherian, Basura Fernando, Dylan Campbell

This paper presents a framework to recognize temporal compositions of atomic actions in videos. Specifically, we propose to express temporal compositions of actions as semantic regular expressions and derive an inference framework using probabilistic automata to recognize complex actions as satisfying these expressions on the input video features. Our approa

Elisa Franco

Transmission rates in epidemic outbreaks may vary over time depending on the societal response. Non-pharmacological mitigation strategies such as social distancing and the adoption of protective equipment aim precisely at reducing transmission rates by reducing infectious contacts. To investigate the effects of mitigation strategies on the evolution of epide

Siva Kumar Sastry Hari, Paolo Rech, Timothy Tsai, Mark Stephenson

High-performance and safety-critical system architects must accurately evaluate the application-level silent data corruption (SDC) rates of processors to soft errors. Such an evaluation requires error propagation all the way from particle strikes on low-level state up to the program output. Existing approaches that rely on low-level simulations with fault in

Daniel Leykam, Daria A. Smirnova

Topological invariants characterising filled Bloch bands attract enormous interest, underpinning electronic topological insulators and analogous artificial lattices for Bose-Einstein condensates, photons, and acoustic waves. In the latter bosonic systems there is no Fermi exclusion principle to enforce uniform band filling, which makes measurement of their b

Rafael - Michael Karampatsis, Charles Sutton

Continuous embeddings of tokens in computer programs have been used to support a variety of software development tools, including readability, code search, and program repair. Contextual embeddings are common in natural language processing but have not been previously applied in software engineering. We introduce a new set of deep contextualized word represe

Wenjuan Hou, Tao Fang, Zhi Pei, Qiao-Chu He

The real challenge in drone-logistics is to develop an economically-feasible Unmanned Aerial Mobility Network (UAMN). In this paper, we propose an integrated airport location (strategic decision) and routes planning (operational decision) optimization framework to minimize the total cost of the network, while guaranteeing flow constraints, capacity constrain

Elzbieta Polak, Dustin Ross

We study the number of ways of factoring elements in the complex reflection groups G(r,s,n) as products of reflections. We prove a result that compares factorization numbers in G(r,s,n) to those in the symmetric group on n letters, and we use this comparison, along with the ELSV formula, to deduce a polynomial structure for factorizations in G(r,s,n).

Vladimir V. Tchernyi, Sergey V. Kapranov, Andrey Yu. Pospelov

It is demonstrated how Saturn rings may be originated due to interaction of iced particles (with II kind superconductivity) moving by chaotic orbits within protoplanetary cloud with magnetic field of Saturn after it appearance. Eventually all orbits of particles coming to the magnetic equator plane of Saturn where they locked within three-dimensional magneti

Waleed Abdallah, Sandhya Choubey, Sarif Khan

In this work, we discuss two component fermionic FIMP dark matter (DM) in a popular $B-L$ extension of the standard model (SM) with inverse seesaw mechanism. Due to the introduced $\mathbb{Z}_{2}$ discrete symmetry, a keV SM gauge singlet fermion is stable and can be a warm DM candidate. Also, this $\mathbb{Z}_{2}$ symmetry helps the lightest right-handed ne

Jules Lamers, Vincent Pasquier, Didina Serban

We study the $q$-analogue of the Haldane-Shastry model, a partially isotropic (XXZ-like) long-range spin chain that enjoys quantum-affine (really: quantum-loop) symmetries at finite size. We derive the pairwise form of the Hamiltonian, found by one of us building on work of Uglov, via 'freezing' from the affine Hecke algebra. We obtain explicit expressions f

Hans Havlicek

Our main aim is to analyse three articles of Germán Ancochea (published 1941, 1942 and 1947) and to describe their impact in algebra and geometry.

J. Horner, S. R. Kane, J. P. Marshall, P. A. Dalba

Over the past three decades, we have witnessed one of the great revolutions in our understanding of the cosmos - the dawn of the Exoplanet Era. Where once we knew of just one planetary system (the Solar system), we now know of thousands, with new systems being announced on a weekly basis. Of the thousands of planetary systems we have found to date, however,

Stephan Ramon Garcia, Gabe Udell, Jiahui Yu

Assuming Dickson's conjecture, we obtain multidimensional analogues of recent results on the behavior of certain multiplicative arithmetic functions near twin-prime arguments. This is inspired by analogous unconditional theorems of Schinzel undertaken without primality assumptions.

Raheam A. Al-Saphory, Zinah A. Khalid

The purpose of this paper is to deals with the problem of regional boundary asymptotic gradient full order observer (regional boundary asymptotic gradient full order observer) concept by using internal regional case. Thus, we study the relation between this notion and the corresponding asymptotic detectability and sensors. More precisely, various important r

J. M. Ortega, O. J. Santos, S. Mondié

In this note, we present some complementary results on the infinite horizon optimal control for linear time-delay systems. We formally establish some properties of the matrices arising in the Bellman functional, and we prove that no concentrated delay term is present in the optimal control law.

Danielle Barquinero, Lorenzo Ruffoni, Kaidi Ye

We study Artin kernels, i.e. kernels of discrete characters of right-angled Artin groups, and we show that they decompose as graphs of groups in a way that can be explicitly computed from the underlying graph. When the underlying graph is chordal we show that every such subgroup either surjects to an infinitely generated free group or is a generalized Baumsl

Ignacio Tamarit, María Pereda, José A. Cuesta

When some 'entities' are related by the 'features' they share they are amenable to a bipartite network representation. Plant-pollinator ecological communities, co-authorship of scientific papers, customers and purchases, or answers in a poll, are but a few examples. Analyzing clustering of such entities in the network is a useful tool with applications in ma

Francisco J. Peña, Oscar Negrete, Natalia Cortés, Patricio Vargas

In this paper, we analyze the total work extracted and the efficiency of the magnetic Otto cycle in its classic and quantum versions. As a general result, we found that the work and efficiency of the classical engine is always greater than or equal to that of its quantum counterpart independent of the working substance. In the classical case, this is due to

Ruizhen Hu, Zeyu Huang, Yuhan Tang, Oliver van Kaick

We introduce a learning framework for automated floorplan generation which combines generative modeling using deep neural networks and user-in-the-loop designs to enable human users to provide sparse design constraints. Such constraints are represented by a layout graph. The core component of our learning framework is a deep neural network, Graph2Plan, which

Graham Neubig, Shruti Rijhwani, Alexis Palmer, Jordan MacKenzie

Despite recent advances in natural language processing and other language technology, the application of such technology to language documentation and conservation has been limited. In August 2019, a workshop was held at Carnegie Mellon University in Pittsburgh to attempt to bring together language community members, documentary linguists, and technologists

Bohan Fan, Diego Ihara Centurion, Neshat Mohammadi, Francesco Sgherzi

We study the problem of finding a mapping $f$ from a set of points into the real line, under ordinal triple constraints. An ordinal constraint for a triple of points $(u,v,w)$ asserts that $|f(u)-f(v)|<|f(u)-f(w)|$. We present an approximation algorithm for the dense case of this problem. Given an instance that admits a solution that satisfies $(1-\varepsilo

Chennakesava Kadapa, Mokarram Hossain

We propose a novel mixed displacement-pressure formulation based on an energy functional that takes into account the relation between the pressure and the volumetric energy function. We demonstrate that the proposed two-field mixed displacement-pressure formulation is not only applicable for nearly and truly incompressible cases but also is consistent in the

Thomas D. Russell, Richard L. White, Knox S. Long, William P. Blair

We present a new catalogue of radio sources in the face-on spiral galaxy M83. Radio observations taken in 2011, 2015, and 2017 with the Australia Telescope Compact Array (ATCA) at 5.5 and 9 GHz have detected 270 radio sources. Although a small number of these sources are background extragalactic sources, most are either H II regions or supernova remnants (SN

Raphael Marschall, Ying Liao, Nicolas Thomas, Jong-Shinn Wu

The European Space Agency's (ESA) Rosetta mission has returned a vast data set of measurements of the inner gas coma of comet 67P/Churyumov-Gerasimenko. These measurements have been used by different groups to determine the distribution of the gas sources at the nucleus surface. The solutions that have been found differ from each other substantially and illu

Giannis Moutsinas, Mengbang Zou, Weisi Guo

Resilience is a system's ability to maintain its function when perturbations and errors occur. Whilst we understand low-dimensional networked systems' behavior well, our understanding of systems consisting of a large number of components is limited. Recent research in predicting the network level resilience pattern has advanced our understanding of the coupl

Michael A. Bender, Mayank Goswami, Dzejla Mededovic, Pablo Montes

In the unit-cost comparison model, a black box takes an input two items and outputs the result of the comparison. Problems like sorting and searching have been studied in this model, and it has been generalized to include the concept of priced information, where different pairs of items (say database records) have different comparison costs. These comparison

Jayaraman J. Thiagarajan, Prasanna Sattigeri, Deepta Rajan, Bindya Venkatesh

The wide-spread adoption of representation learning technologies in clinical decision making strongly emphasizes the need for characterizing model reliability and enabling rigorous introspection of model behavior. While the former need is often addressed by incorporating uncertainty quantification strategies, the latter challenge is addressed using a broad c

Brenden Balch, Chris Peterson, Clayton Shonkwiler

Lens spaces are a family of manifolds that have been a source of many interesting phenomena in topology and differential geometry. Their concrete construction, as quotients of odd-dimensional spheres by a free linear action of a finite cyclic group, allows a deeper analysis of their structure. In this paper, we consider the problem of moments for the distanc

Naomi Saphra, Adam Lopez

Recent work in NLP shows that LSTM language models capture compositional structure in language data. For a closer look at how these representations are composed hierarchically, we present a novel measure of interdependence between word meanings in an LSTM, based on their interactions at the internal gates. To explore how compositional representations arise o

Nathan O. Lambert, Farhan Toddywala, Brian Liao, Eric Zhu

Building intelligent autonomous systems at any scale is challenging. The sensing and computation constraints of a microrobot platform make the problems harder. We present improvements to learning-based methods for on-board learning of locomotion, classification, and navigation of microrobots. We show how simulated locomotion can be achieved with model-based

Jian-Wei Qiu, Ted C. Rogers, Bowen Wang

The transverse momentum dependent (TMD) and collinear higher twist theoretical factorization frameworks are the most frequently used approaches to describing spin dependent hard cross sections weighted by and integrated over transverse momentum. Of particular interest is the contribution from small transverse momentum associated with the target bound state.

Andrea M Armani, Darrell E Hurt, Darryl Hwang, Meghan C McCarthy

A global effort is ongoing in the scientific community and in the Maker Movement, which focuses on creating devices and tinkering with them, to reverse engineer commercial medical equipment and get it to healthcare workers. For these low-tech solutions to have a real impact, it is important for them to coalesce around approved designs.

Luc Vinet

This text offers reminiscences of my personal interactions with Roman Jackiw as a way of looking back at the very fertile period in theoretical physics in the last quarter of the 20th century.

William D. Taylor

This paper establishes the fundamental properties of the $s$-closures, a recently introduced family of closure operations on ideals of rings of positive characteristic. The behavior of the $s$-closure of homogeneous ideals in graded rings is studied, and criteria are given for when the $s$-closure of an ideal can be described exactly in terms of its tight cl

Favio Neira, Timo Anguita, Georgios Vernardos

We present a tool to generate mock quasar microlensing light curves and sample them according to any observing strategy. An updated treatment of the fixed and random velocity components of observer, lens, and source is used, together with a proper alignment with the external shear defining the magnification map caustic orientation. Our tool produces quantita

Jiangpeng He, Zeman Shao, Janine Wright, Deborah Kerr

Deep learning based methods have achieved impressive results in many applications for image-based diet assessment such as food classification and food portion size estimation. However, existing methods only focus on one task at a time, making it difficult to apply in real life when multiple tasks need to be processed together. In this work, we propose an end

Mark Risser

Heat waves resulting from prolonged extreme temperatures pose a significant risk to human health globally. Given the limitations of observations of extreme temperature, climate models are often used to characterize extreme temperature globally, from which one can derive quantities like return values to summarize the magnitude of a low probability event for a

Christian M. Pluchar, Aman Agrawal, Edward Schenk, Dalziel J. Wilson

We demonstrate feedback cooling of a millimeter-scale, 40 kHz SiN membrane from room temperature to 5 mK (3000 phonons) using a Michelson interferometer, and discuss the challenges to ground state cooling without an optical cavity. This advance appears within reach of current membrane technology, positioning it as a compelling alternative to levitated system

Atul Kedia, Nishanth Sasankan, Grant J. Mathews, Motohiko Kusakabe

Multicomponent relativistic fluids have been studied for decades. However, simulating the dynamics of the particles and fluids in such a mixture has been a challenge due to the fact that such simulations are computationally expensive in three spatial dimensions. Here, we report on the development and application of a multi dimensional relativistic Monte Carl

Erin Gauger

In this manuscript, various beauty production measurements using the ALICE detector will be presented. We will show new measurements of non-prompt D$^0$ mesons in pp collisions at $\sqrt{s} = 5.02$ TeV and beauty-tagged jet production in p--Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV. The $R_{\mathrm{AA}}$ of beauty-hadron decay electrons in central

Daniel Collins, Rachid Guerraoui, Jovan Komatovic, Matteo Monti

We address the problem of online payments, where users can transfer funds among themselves. We introduce Astro, a system solving this problem efficiently in a decentralized, deterministic, and completely asynchronous manner. Astro builds on the insight that consensus is unnecessary to prevent double-spending. Instead of consensus, Astro relies on a weaker pr

Philip H. Handle

Aqueous solutions of LiCl are probably the most studied electrolyte solutions related to the complexity of liquid water at low temperatures. Despite the large amount of available experimental data hardly any computational studies were performed on LiCl solutions in this context. In this study, we present molecular dynamics simulations of LiCl-water at ambien

Wentian Jin, Sheriff Sadiqbatcha, Jinwei Zhang, Sheldon X. -D. Tan

In this paper, we propose a fast transient hydrostatic stress analysis for electromigration (EM) failure assessment for multi-segment interconnects using generative adversarial networks (GANs). Our work leverages the image synthesis feature of GAN-based generative deep neural networks. The stress evaluation of multi-segment interconnects, modeled by partial

Emmanuel Briand

We give three proofs of the following result conjectured by Carriegos, De Castro-Garc\'{\i}a and Mu\~noz Casta\~neda in their work on enumeration of control systems: when $\binom{k+1}{2} \le n < \binom{k+2}{2}$, there are as many partitions of $n$ with $k$ corners as pairs of partitions $(\alpha, \beta)$ such that $\binom{k+1}{2} + |\alpha| + |\beta| = n$.

M. V. Falessi, N. Carlevaro, V. Fusco, E. Giovannozzi

In this work, the FALCON code is adopted for illustrating the features of shear Alfv\'en and continuous spectra in toroidal fusion plasmas. The FALCON codes employs the local Floquet analysis discussed in [Phys. of Plasmas \textbf{26} (8), 082502 (2019)] for computing global structures of continuous spectra in general toroidal geometry. As particular applica

Semra Ahmetolan, Ayse Humeyra Bilge, Ali Demirci, Ayse Peker-Dobie

The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its spread. Since the earliest stages of this major pandemic, academics have done a huge amount of research in order to under

Noah Rhodes, David Fobes, Carleton Coffrin, Line Roald

With the escalating frequency of extreme grid disturbances, such as natural disasters, comes an increasing need for efficient recovery plans. Algorithms for optimal power restoration play an important role in developing such plans, but also give rise to challenging mixed-integer nonlinear optimization problems, where tractable solution methods are not yet av

Chitra Shukla, Priya Malpani, Kishore Thapliyal

The advent of a new kind of entangled state known as hybrid entangled state, i.e., entanglement between different degrees of freedom, makes it possible to perform various quantum computational and communication tasks with lesser amount of resources. Here, we aim to exploit the advantage of these entangled states in communication over quantum networks. Unfort

Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol

Objective: Employing transfer learning (TL) with convolutional neural networks (CNNs), well-trained on non-medical ImageNet dataset, has shown promising results for medical image analysis in recent years. We aimed to conduct a scoping review to identify these studies and summarize their characteristics in terms of the problem description, input, methodology,

Aleksandr K. Tusnin, Alexey M. Tikan, Tobias J. Kippenberg

Recent advances in the study of synthetic dimensions revealed a possibility to employ the frequency space as an additional degree of freedom which allows for investigating and exploiting higher-dimensional phenomena in a priori low-dimensional systems. However, the influence of nonlinear effects on the synthetic frequency dimensions was studied only under si

Fangliang Bai, Jinchao Liu, Xiaojuan Liu, Margarita Osadchy

Recent work showed neural-network-based approaches to reconstructing images from compressively sensed measurements offer significant improvements in accuracy and signal compression. Such methods can dramatically boost the capability of computational imaging hardware. However, to date, there have been two major drawbacks: (1) the high-precision real-valued se

Joseph Colonel, Christopher Curro, Sam Keene

A method for musical audio synthesis using autoencoding neural networks is proposed. The autoencoder is trained to compress and reconstruct magnitude short-time Fourier transform frames. The autoencoder produces a spectrogram by activating its smallest hidden layer, and a phase response is calculated using real-time phase gradient heap integration. Taking an

Martin Speight, Thomas Winyard

The standard Ginzburg-Landau model of competing-order superconductors is studied. It is observed that this model possesses two distinct species of vortex, and consequently has two distinct integer valued topological charges. A simple point particle model of long range forces between (anti)vortices of any species is developed and compared with numerical simul

Amir Shakouri, Seid H. Pourtakdoust, Mohammad Sayanjali

This paper proposes a solution for multiple-impulse orbital maneuvers near circular orbits for special cases where orbital observations are not globally available and the spacecraft is being observed through a limited window from a ground or a space-based station. The current study is particularly useful for small private launching companies with limited acc

Baigong Zheng, Kaibo Liu, Renjie Zheng, Mingbo Ma

Adaptive policies are better than fixed policies for simultaneous translation, since they can flexibly balance the tradeoff between translation quality and latency based on the current context information. But previous methods on obtaining adaptive policies either rely on complicated training process, or underperform simple fixed policies. We design an algor

Marco H A Inácio

Performance assessment is a key issue in the process of proposing new machine learning/statistical estimators. A possible method to complete such task is by using simulation studies, which can be defined as the procedure of estimating and comparing properties (such as predictive power) of estimators (and other statistics) by averaging over many replications

Ben Burridge, Imad I. Faruque, John Rarity, Jorge Barreto

Single-photons with high spectro-temporal purity are an essential resource for quantum photonic technologies. The highest reported purity up until now from a conventional silicon photonic device is 92% without any spectral filtering. We have experimentally generated and observed single-photons with 98.0+-0.3 % spectro-temporal purity using a conventional mic

Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus

We propose an energy-based model (EBM) of protein conformations that operates at atomic scale. The model is trained solely on crystallized protein data. By contrast, existing approaches for scoring conformations use energy functions that incorporate knowledge of physical principles and features that are the complex product of several decades of research and

Patrick Esser, Robin Rombach, Björn Ommer

Neural networks have greatly boosted performance in computer vision by learning powerful representations of input data. The drawback of end-to-end training for maximal overall performance are black-box models whose hidden representations are lacking interpretability: Since distributed coding is optimal for latent layers to improve their robustness, attributi

Calvin Alexandre Fracassi Farias, Renato Pakter, Yan Levin

The evolution of a self-gravitating system to a non-equilibrium steady state occurs through a process of violent relaxation. In the thermodynamic limit the dynamics of a many body system should be governed by the Vlasov equation. Recently, however, a question was raised regarding the validity of Vlasov equation during the process of violent relaxation. In th

Sudan Han, Luca Pallotta, Xiaotao Huang, Gaetano Giunta

This paper considers the design of tunable decision schemes capable of rejecting with high probability mismatched signals embedded in Gaussian interference with unknown covariance matrix. To this end, a sparse recovery technique is exploited to enhance the resolution at which the target angle of arrival is estimated with the objective to obtain high-selectiv

Fernando Izaurieta, Samuel Lepe, Omar Valdivia

Allowing for a nonvanishing spin tensor for cold dark matter ($\omega_{\mathrm{DM}}=0$) has the consequence of giving rise to an effective $\mathrm{FLRW}$ dynamics with a small negative barotropic constant for an effective dark matter density ($-1/3<\omega_{\mathrm{eff}}\leq0$). This turns out to solve the Hubble parameter tension in a straightforward way.

Andy Zucker

Generalizing and simplifying recent work of Dobrinen, we show that if $\mathcal{L}$ is a finite binary relational language and $\mathcal{F}$ is a finite set of finite irreducible $\mathcal{L}$-structures, then the class $\mathcal{K} = \mathrm{Forb}(\mathcal{F})$ has finite big Ramsey degrees.

Gözde Gül Şahin, Yova Kementchedjhieva, Phillip Rust, Iryna Gurevych

Deep neural models have repeatedly proved excellent at memorizing surface patterns from large datasets for various ML and NLP benchmarks. They struggle to achieve human-like thinking, however, because they lack the skill of iterative reasoning upon knowledge. To expose this problem in a new light, we introduce a challenge on learning from small data, PuzzLin

Jie Yang, Chin-Teng Lin

Grouping similar objects is a fundamental tool of scientific analysis, ubiquitous in disciplines from biology and chemistry to astronomy and pattern recognition. Inspired by the torque balance that exists in gravitational interactions when galaxies merge, we propose a novel clustering method based on two natural properties of the universe: mass and distance.

Richard Klavans, Kevin W. Boyack, Dewey A. Murdick

The prediction of exceptional or surprising growth in research is an issue with deep roots and few practical solutions. In this study we develop and validate a novel approach to forecasting growth in highly specific research communities. Each research community is represented by a cluster of papers. Multiple indicators were tested, and a composite indicator

Max Hodapp, Alexander Shapeev

A well-known drawback of state-of-the-art machine-learning interatomic potentials is their poor ability to extrapolate beyond the training domain. For small-scale problems with tens to hundreds of atoms this can be solved by using active learning which is able to select atomic configurations on which a potential attempts extrapolation and add them to the ab

Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega

We introduce the concept of \emph{expected exposure} as the average attention ranked items receive from users over repeated samples of the same query. Furthermore, we advocate for the adoption of the principle of equal expected exposure: given a fixed information need, no item should receive more or less expected exposure than any other item of the same rele

Anastasios Zachos

We determine a positive real number (weight) which corresponds to the intersection point (vertex) of two non-overlapping geodesic arcs, which depends on the two weights which correspond to two points of these geodesicarcs, respectively, and an infinitesimal number \epsilon. As a limiting case, for \epsilon \to 0,the triad of the corresponding weights yields

Antonio Paris, Evan Davies, Laurence Tognetti, Carly Zahniser

After surveying 1,500 images from MRO, this investigation has identified three candidate lava tubes in the vicinity of Hadriacus Mons as prospective sites for manned exploration. This investigation, therefore, concluded that terrestrial lava tubes can be leveraged for radiation shielding and, accordingly, that the candidate lava tubes on Mars (as well as kno

Natsuha Kuroda, Gregory D. Fleishman, Dale E. Gary, Gelu M. Nita

Nonthermal electrons accelerated in solar flares produce electromagnetic emission in two distinct, highly complementary domains - hard X-rays (HXRs) and microwaves (MWs). This paper reports MW imaging spectroscopy observations from the Expanded Owens Valley Solar Array of an M1.2 flare that occurred on 2017 September 9, from which we deduce evolving coronal

Victor Reijgwart, Alexander Millane, Helen Oleynikova, Roland Siegwart

Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps

Seungmin Park, Hyunju Lee, Kiwoon Kwon

Automatic diagnosis of malignant melanoma highly depends on the segmentation methods used for the suspicious lesion. We suggest the parameter selection method (PSM) and maximum area method (MAM) for the segmentation of the lesion to be diagnosed. Herein, these segmentation methods are compared to a skin cancer expert's segmentation and three other convention

Brandon Fain, William Fan, Kamesh Munagala

We study higher statistical moments of Distortion for randomized social choice in a metric implicit utilitarian model. The Distortion of a social choice mechanism is the expected approximation factor with respect to the optimal utilitarian social cost (OPT). The $k^{th}$ moment of Distortion is the expected approximation factor with respect to the $k^{th}$ p

Joshua Lockhart, Samuel Assefa, Tucker Balch, Manuela Veloso

Document classification is ubiquitous in a business setting, but often the end users of a classifier are engaged in an ongoing feedback-retrain loop with the team that maintain it. We consider this feedback-retrain loop from a multi-agent point of view, considering the end users as autonomous agents that provide feedback on the labelled data provided by the

Isaia Albisetti, Fadoua Balabdaoui, Hajo Holzmann

We construct new testing procedures for spherical and elliptical symmetry based on the characterization that a random vector $X$ with finite mean has a spherical distribution if and only if $\Ex[u^\top X | v^\top X] = 0$ holds for any two perpendicular vectors $u$ and $v$. Our test is based on the Kolmogorov-Smirnov statistic, and its rejection region is fou

Zhe Zhang, Chung-Wei Hang, Munindar P. Singh

Sentiments in opinionated text are often determined by both aspects and target words (or targets). We observe that targets and aspects interrelate in subtle ways, often yielding conflicting sentiments. Thus, a naive aggregation of sentiments from aspects and targets treated separately, as in existing sentiment analysis models, impairs performance. We propose

Azza Gaysin

The $\mathcal{H}$-coloring problem for undirected simple graphs is a computational problem from a huge class of the constraint satisfaction problems (CSP): an $\mathcal{H}$-coloring of a graph $\mathcal{G}$ is just a homomorphism from $\mathcal{G}$ to $\mathcal{H}$ and the problem is to decide for fixed $\mathcal{H}$, given $\mathcal{G}$, if a homomorphism e

Lauri Alho, Adrian Burian, Janne Helenius, Joni Pajarinen

Identifying mobile network problems in 4G cells is more challenging when the complexity of the network increases, and privacy concerns limit the information content of the data. This paper proposes a data driven model for identifying 4G cells that have fundamental network throughput problems. The proposed model takes advantage of clustering and Deep Neural N

Carsten Habenicht, Axel Lubk, Roman Schuster, Martin Knupfer

We have investigated the effect of potassium (K) intercalation on $2H$-MoS$_2$ using transmission electron energy-loss spectroscopy. For K concentrations up to approximately 0.4, the crystals appear to be inhomogeneous with a mix of structural phases and irregular potassium distribution. Above this intercalation level, MoS$_2$ exhibits a $2a \times 2a$ super

Xin Qian, Diego Klabjan

The mini-batch stochastic gradient descent (SGD) algorithm is widely used in training machine learning models, in particular deep learning models. We study SGD dynamics under linear regression and two-layer linear networks, with an easy extension to deeper linear networks, by focusing on the variance of the gradients, which is the first study of this nature.

Ece Çiğdem Mutlu, Toktam Oghaz, Ege Tütüncüler, Jasser Jasser

For years, many studies employed sentiment analysis to understand the reasoning behind people's choices and feelings, their communication styles, and the communities which they belong to. We argue that gaining more in-depth insight into moral dimensions coupled with sentiment analysis can potentially provide superior results. Understanding moral foundations

Mikhail Anikushin

We study the well-posedness of nonautonomous nonlinear delay equations in $\mathbb{R}^{n}$ as evolutionary equations in a proper Hilbert space. We present a construction of solving operators (nonautonomous case) or nonlinear semigroups (autonomous case) for a large class of such equations. The main idea can be easily extended for certain PDEs with delay. Our

Camille Eloy, Olaf Hohm, Henning Samtleben

We dimensionally reduce the spacetime action of bosonic string theory, and that of the bosonic sector of heterotic string theory after truncating the Yang-Mills gauge fields, on a $d$-dimensional torus including all higher-derivative corrections to first order in $\alpha'$. A systematic procedure is developed that brings this action into a minimal form in wh

Alexander Haberl, Dirk Praetorius, Stefan Schimanko, Martin Vohralik

We consider a second-order elliptic boundary value problem with strongly monotone and Lipschitz-continuous nonlinearity. We design and study its adaptive numerical approximation interconnecting a finite element discretization, the Banach-Picard linearization, and a contractive linear algebraic solver. We in particular identify stopping criteria for the algeb

Calypso Herrera, Florian Krach, Josef Teichmann

The Lipschitz constant is an important quantity that arises in analysing the convergence of gradient-based optimization methods. It is generally unclear how to estimate the Lipschitz constant of a complex model. Thus, this paper studies an important problem that may be useful to the broader area of non-convex optimization. The main result provides a local up

Xiao Chen, S. Maiti, R. M. Fernandes, P. J. Hirschfeld

Electronic nematic behavior has been identified and studied in iron-based superconductors for some time, particularly in the well-known BaFe$_2$As$_2$ system, where it is well-known to compete with superconductivity. On the other hand, it has been shown recently that FeSe displays a negligible effect of nematicity on superconductivity near the superconductin

Wanlu Lei, Yu Ye, Ming Xiao

We develop a framework based on deep reinforce-ment learning (DRL) to solve the spectrum allocation problem inthe emerging integrated access and backhaul (IAB) architecturewith large scale deployment and dynamic environment. The avail-able spectrum is divided into several orthogonal sub-channels,and the donor base station (DBS) and all IAB nodes have thesame

Hyungki Shim, Zeyu Kuang, Owen D. Miller

This article reviews the material properties that enable maximum optical response. We highlight theoretical results that enable shape-independent quantification of material "figures of merit," ranging from classical sum rules to more recent single-frequency scattering bounds. A key delineation at optical frequencies is between polaritonic materials that supp

Ece Çiğdem Mutlu, Ivan Garibay

Despite the widespread use of Barabasi's scale-free networks and Erdos-Renyi networks of which degree correlation (assortativity) is neutral, numerous studies demonstrated that online social networks tend to show assortative mixing (positive degree correlation), while non-social networks show a disassortative mixing (negative degree correlation). First, we a