October 2020 arXiv papers — page 60

Christophe Yèche, Nathalie Palanque-Delabrouille, Charles-Antoine Claveau, David D. Brooks

The DESI survey will measure large-scale structure using quasars as direct tracers of dark matter in the redshift range $0.9<z<2.1$ and using quasar Ly-$α$ forests at $z>2.1$. We present two methods to select candidate quasars for DESI based on imaging in three optical ($g, r, z$) and two infrared ($W1, W2$) bands. The first method uses traditional color cut

Mohammadreza Armandpour, Mingyuan Zhou

A decision tree is commonly restricted to use a single hyperplane to split the covariate space at each of its internal nodes. It often requires a large number of nodes to achieve high accuracy, hurting its interpretability. In this paper, we propose convex polytope trees (CPT) to expand the family of decision trees by an interpretable generalization of their

Wojciech Kozlowski, Fernando Kuipers, Stephanie Wehner

The quantum technology revolution brings with it the promise of a quantum internet. A new -- quantum -- network stack will be needed to account for the fundamentally new properties of quantum entanglement. The first realisations of quantum networks are imminent and research interest in quantum network protocols has started growing. In the non-quantum world,

Marta Boczon

I measure the uncertainty affecting estimates of economic inequality in the US and investigate how accounting for properly estimated standard errors can affect the results of empirical and structural macroeconomic studies. In my analysis, I rely upon two data sets: the Survey of Consumer Finances (SCF), which is a triennial survey of household financial cond

Jan Barton, Michal Gulka, Jan Tarabek, Yuliya Mindarava

Biocompatible nanoscale probes for sensitive detection of paramagnetic species and molecules associated with their (bio)chemical transformations would provide a desirable tool for a better understanding of cellular redox processes. Here, we describe an analytical tool based on quantum sensing techniques. We magnetically coupled negatively charged nitrogen-va

Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, Vladlen Koltun

Some of the most challenging environments on our planet are accessible to quadrupedal animals but remain out of reach for autonomous machines. Legged locomotion can dramatically expand the operational domains of robotics. However, conventional controllers for legged locomotion are based on elaborate state machines that explicitly trigger the execution of mot

A. W. Nelsen, E. G. Ballantyne, R. E. Calvert, C. B. Crawford

The recent measurement of the lifetime of the free neutron using the beam method has an 8.7 s (4$σ$) discrepancy with UCN measurements. The goal of the BL3 experiment is to improve the statistical error of this measurement and help rule out systematic uncertainties as an explanation for the discrepancy. A well-characterized neutron flux detector with flat re

Tianze Shi, Chen Zhao, Jordan Boyd-Graber, Hal Daumé

Large-scale semantic parsing datasets annotated with logical forms have enabled major advances in supervised approaches. But can richer supervision help even more? To explore the utility of fine-grained, lexical-level supervision, we introduce Squall, a dataset that enriches 11,276 WikiTableQuestions English-language questions with manually created SQL equiv

Karel Horák, Branislav Bošanský, Vojtěch Kovařík, Christopher Kiekintveld

Many security and other real-world situations are dynamic in nature and can be modelled as strictly competitive (or zero-sum) dynamic games. In these domains, agents perform actions to affect the environment and receive observations -- possibly imperfect -- about the situation and the effects of the opponent&#39;s actions. Moreover, there is no limitation on

Johannes Lauinger, Lars Baumgärtner, Anna-Katharina Wickert, Mira Mezini

The Go programming language aims to provide memory and thread safety through measures such as automated memory management with garbage collection and a strict type system. However, it also offers a way of circumventing this safety net through the use of the unsafe package. While there are legitimate use cases for unsafe, developers must exercise caution to a

Sirigireddy Dhanalaxmi, Rohit Agarwal, Aman Sinha

Social media such as Twitter is a hotspot of user-generated information. In this ongoing Covid-19 pandemic, there has been an abundance of data on social media which can be classified as informative and uninformative content. In this paper, we present our work to detect informative Covid-19 English tweets using RoBERTa model as a part of the W-NUT workshop 2

Shannon M. Danforth, Patrick D. Holmes, Ram Vasudevan

People with lower-limb loss, the majority of which use passive prostheses, exhibit a high incidence of falls each year. Powered lower-limb prostheses have the potential to reduce fall rates by actively helping the user recover from a stumble, but the unpredictability of the human response makes it difficult to design controllers that ensure a successful reco

Alex Wilf, Emily Mower Provost

Robustness to environmental noise is important to creating automatic speech emotion recognition systems that are deployable in the real world. Prior work on noise robustness has assumed that systems would not make use of sample-by-sample training noise conditions, or that they would have access to unlabelled testing data to generalize across noise conditions

Matteo Lucca, Laura Sagunski, Federico Guercilena, Christian M. Fromm

The main features of the gravitational dynamics of binary neutron star systems are now well established. While the inspiral can be precisely described in the post-Newtonian approximation, fully relativistic magneto-hydrodynamical simulations are required to model the evolution of the merger and post-merger phase. However, the interpretation of the numerical

Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein

Memory-based meta-learning is a powerful technique to build agents that adapt fast to any task within a target distribution. A previous theoretical study has argued that this remarkable performance is because the meta-training protocol incentivises agents to behave Bayes-optimally. We empirically investigate this claim on a number of prediction and bandit ta

Jaejin Cho, Piotr Zelasko, Jesus Villalba, Shinji Watanabe

Zero-shot multi-speaker Text-to-Speech (TTS) generates target speaker voices given an input text and the corresponding speaker embedding. In this work, we investigate the effectiveness of the TTS reconstruction objective to improve representation learning for speaker verification. We jointly trained end-to-end Tacotron 2 TTS and speaker embedding networks in

Courtney B. Watson, Sarbani Basu

Helioseismic data for solar cycles 23 and 24 have shown unequivocally that solar dynamics changes with solar activity. Changes in solar structure have been more difficult to detect. Basu & Mandel (2004) had claimed that the then available data revealed changes in the HeII ionization zone of the Sun. The amount of change, however, indicated the need for large

Giorgio Fagiolo

In this paper, I study epidemic diffusion in a generalized spatial SEIRD model, where individuals are initially connected in a social or geographical network. As the virus spreads in the network, the structure of interactions between people may endogenously change over time, due to quarantining measures and/or spatial-distancing policies. I explore via simul

Daniel J. Prole, Remco F. J. van der Burg, Michael Hilker, Lee R. Spitler

Understanding the formation and evolution of low surface brightness galaxies (LSBGs) is critical for explaining their wide-ranging properties. However, studies of LSBGs in deep photometric surveys are often hindered by a lack of distance estimates. In this work, we present a new catalogue of 479 LSBGs, identified in deep optical imaging data from the Hyper S

Maksym Lisogorskyi, Hugh R. A. Jones, Fabo Feng, R. Paul Butler

We examine the influence of activity- and telluric-induced radial velocity signals on high resolution spectra taken with an iodine absorption cell. We exclude 2 Angstrom spectral chunks containing active and telluric lines based on the well characterised K1V star Alpha Centauri B and illustrate the method on Epsilon Eridani - an active K2V star with a long p

Dirk van Dam, Matthew Kenworthy, Trevor David, Eric Mamajek

K2 observations of the weak-lined T Tauri binary V928 Tau A+B show the detection of a single, asymmetric eclipse which may be due to a previously unknown substellar companion eclipsing one component of the binary with an orbital period $>$ 66 days. Over an interval of about 9 hours, one component of the binary dims by around 60%, returning to its normal brig

V. Ashley Villar, Miles Cranmer, Gabriella Contardo, Shirley Ho

Supernovae mark the explosive deaths of stars and enrich the cosmos with heavy elements. Future telescopes will discover thousands of new supernovae nightly, creating a need to flag astrophysically interesting events rapidly for followup study. Ideally, such an anomaly detection pipeline would be independent of our current knowledge and be sensitive to unexp

C. Spingola, D. Dallacasa, S. Belladitta, A. Caccianiga

We present Director&#39;s Discretionary Time multi-frequency observations obtained with the Jansky Very Large Array (VLA) and the Very Long Baseline Array (VLBA) of the blazar PSO J030947.49+271757.31 (hereafter PSO J0309+27) at $z = 6.10\pm0.03$. The milliarcsecond angular resolution of our VLBA observations at 1.5, 5 and 8.4 GHz unveils a bright one-sided

Valerio Faraoni

A simplified climate model based on maximum entropy production, described by a variational principle, is revisited and an analytical solution to its Euler-Lagrange equation is found. Mindful of controversy about maximum or minimum entropy production in open thermodynamical systems, we show that the solution extremizing the action integral corresponds to a ma

M. Erkintalo, S. G. Murdoch, S. Coen

Dissipative Kerr cavity solitons are pulses of light that can persist in coherently driven nonlinear optical resonators. They have attracted significant attention over the past decade due to their rich nonlinear dynamics and key role in the generation of coherent microresonator optical frequency combs. Whilst the vast majority of implementations have relied

Tianze Shi, Igor Malioutov, Ozan İrsoy

We reduce the task of (span-based) PropBank-style semantic role labeling (SRL) to syntactic dependency parsing. Our approach is motivated by our empirical analysis that shows three common syntactic patterns account for over 98% of the SRL annotations for both English and Chinese data. Based on this observation, we present a conversion scheme that packs SRL a

Eszter Fehér, Gábor Domokos, Bernd Krasukopf

We present a numerical method for computing the evolution of a planar, star-shaped curve under a broad class of curvature-driven geometric flows, which we refer to as the Andrews-Bloore flows. This family of flows has two parameters that control one constant and one curvature-dependent component for the velocity in the direction of the normal to the curve. T

E. Nissen, A. Källberg, A. Simonsson

In this work we perform the first ever demonstration of gear-changing in a real world collider. Gear-changing refers to a collision scheme where each ring of a collider stores a different harmonic number of bunches. These bunches are kept synchronized using different velocities. Such a system has been theorized, but has now been demonstrated using the Double

Paul Callens, Milos Cernak

Acoustic environment characterization opens doors for sound reproduction innovations, smart EQing, speech enhancement, hearing aids, and forensics. Reverberation time, clarity, and direct-to-reverberant ratio are acoustic parameters that have been defined to describe reverberant environments. They are closely related to speech intelligibility and sound quali

Guy Meyer, Alan Wassyng, Mark Lawford, Kourosh Sabri

A sudden reliance on the internet has resulted in the global standardization of specific software and interfaces tailored for the average user. Whether it be web apps or dedicated software, the methods of interaction are seemingly similar. But when the computer tool is presented with unique users, specifically with a disability, the quality of interaction de

Ajjen Joshi, Survi Kyal, Sandipan Banerjee, Taniya Mishra

Driving in a state of drowsiness is a major cause of road accidents, resulting in tremendous damage to life and property. Developing robust, automatic, real-time systems that can infer drowsiness states of drivers has the potential of making life-saving impact. However, developing drowsiness detection systems that work well in real-world scenarios is challen

Maxime Vaidis, Johann Laconte, Vladimír Kubelka, François Pomerleau

Mapping algorithms that rely on registering point clouds inevitably suffer from local drift, both in localization and in the built map. Applications that require accurate maps, such as environmental monitoring, benefit from additional sensor modalities that reduce such drift. In our work, we target the family of mappers based on the Iterative Closest Point (

Hao Huang, Lingjing Wang, Xiang Li, Yi Fang

Point signature, a representation describing the structural neighborhood of a point in 3D shapes, can be applied to establish correspondences between points in 3D shapes. Conventional methods apply a weight-sharing network, e.g., any kind of graph neural networks, across all neighborhoods to directly generate point signatures and gain the generalization abil

Antonio Barbalau, Adrian Cosma, Radu Tudor Ionescu, Marius Popescu

We study the task of replicating the functionality of black-box neural models, for which we only know the output class probabilities provided for a set of input images. We assume back-propagation through the black-box model is not possible and its training images are not available, e.g. the model could be exposed only through an API. In this context, we pres

Edward M. Molter, Imke de Pater, Statia Luszcz-Cook, Joshua Tollefson

We present ALMA and VLA spatial maps of the Uranian atmosphere taken between 2015 and 2018 at wavelengths from 1.3 mm to 10 cm, probing pressures from $\sim$1 to $\sim$50 bar at spatial resolutions from 0.1&#39;&#39; to 0.8&#39;&#39;. Radiative transfer modeling was performed to determine the physical origin of the brightness variations across Uranus&#39;s d

A. Egorov, A. Vesnin

By Andreev theorem acute-angled polyhedra of finite volume in a hyperbolic space $\mathbb H^{3}$ are uniquely determined by combinatorics of their 1-skeletons and dihedral angles. For a class of compact right-angled polyhedra and a class of ideal right-angled polyhedra estimates of volumes in terms of the number of vertices were obtained by Atkinson in 2009.

Arles Rodríguez, Jonatan Gómez, Ada Diaconescu

In many distributed systems, from cloud to sensor networks, different configurations impact system performance, while strongly depending on the network topology. Hence, topological changes may entail costly reconfiguration and optimisation processes. This paper proposes a multi-agent solution for recovering networks from node failures. To preserve the networ

Toshio Nagano

In this paper, by using asymptotic expansions of oscillatory integrals with positive real power phase functions in one variable, we obtain asymptotic expansions of oscillatory integrals with phase functions expressed by a product of positive real power function and real analytic function in one variable. Moreover we show an example which we can compute all c

Yan Zeng, Jian-Yun Nie

We investigate the problem of multi-domain Dialogue State Tracking (DST) with open vocabulary, which aims to extract the state from the dialogue. Existing approaches usually concatenate previous dialogue state with dialogue history as the input to a bi-directional Transformer encoder. They rely on the self-attention mechanism of Transformer to connect tokens

Thomas G. J. Chandler, Dominic Vella

Winkler&#39;s mattress model is often used as a simplified model to understand how a thin elastic layer, such as a coating, deforms when subject to a distributed normal load: the deformation of the layer is assumed proportional to the applied normal load. This simplicity means that the Winkler model has found a wide range of applications from soft matter to

Daniel Li, Te I, Naveen Arivazhagan, Colin Cherry

Neural Machine Translation (NMT) models have demonstrated strong state of the art performance on translation tasks where well-formed training and evaluation data are provided, but they remain sensitive to inputs that include errors of various types. Specifically, in the context of long-form speech translation systems, where the input transcripts come from Au

J. Bialopetravičius, D. Narbutis

We present a study of evolutionary and structural parameters of star cluster candidates in the spiral galaxy M83. For this we use a convolutional neural network trained on mock clusters and capable of fast identification and localization of star clusters, as well as inference of their parameters from multi-band images. We use this pipeline to detect 3,380 cl

Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma

Existing work in translation demonstrated the potential of massively multilingual machine translation by training a single model able to translate between any pair of languages. However, much of this work is English-Centric by training only on data which was translated from or to English. While this is supported by large sources of training data, it does not

Paul Smolen, Douglas A Baxter, John H Byrne

Genetic disorders such as Rubinstein-Taybi syndrome (RTS) and Coffin-Lowry syndrome (CLS) cause lifelong cognitive disability, including deficits in learning and memory. Can pharmacological therapies be suggested to improve learning and memory in these disorders? To address this question, we simulated drug effects within a computational model describing indu

Javier Segura

Parabolic Cylinder functions (PCFs) are classical special functions with applications in many different fields. However, there is little information available regarding simple uniform approximations and bounds for these functions. We obtain very sharp bounds for the ratio $Φ_n(x)=U(n-1,x)/U(n,x)$ and the double ratio $Φ_n(x)/Φ_{n+1}(x)$ in terms of elementar

Ryan Gabrys, Srilakshmi Pattabiraman, Olgica Milenkovic

The problem of string reconstruction from substring information has found many applications due to its relevance in DNA- and polymer-based data storage. One practically important and challenging paradigm requires reconstructing mixtures of strings based on the union of compositions of their prefixes and suffixes, generated by mass spectrometry readouts. We d

Joachim Deutscher

This paper is concerned with the cooperative output regulation problem for a network of agents with different dynamics described by parabolic PDEs subject to spatially- and time-varying parameters. Firstly, a networked controller is designed achieving output synchronization for identical finite-dimensional reference models, which deliver the state of the glo

Christian Bartz, Joseph Bethge, Haojin Yang, Christoph Meinel

Generative Adversarial Networks (GANs) have achieved state-of-the-art performance for several image generation and manipulation tasks. Different works have improved the limited understanding of the latent space of GANs by embedding images into specific GAN architectures to reconstruct the original images. We present a novel StyleGAN-based autoencoder archite

Tania Biswas, Elisabetta Rocca

We consider a phase-field model of prostate cancer growth with chemotherapy and antiangiogenic therapy effects which is introduced in [2]. It is comprised of phase-field equation to describe tumor growth, which is coupled to a reaction-diffusion type equation for generic nutrient for the tumor. An additional equation couples the concentration of prostate-spe

H. A. S. Costa, P. R. S. Carvalho

In this Letter we compute analytically the effect of conformal symmetry on the radiative corrections to the amplitude ratios for O($N$) $λϕ^{4}$ massless scalar field theories in curved spacetime for probing the two-scale-factor universality hypothesis. For that we employ three distinct and independent field-theoretic renormalization group methods. The ampli

Joachim Deutscher

This paper considers the robust cooperative output regulation for a network of parabolic PDE systems. The solution of this problem is obtained by extending the cooperative internal model principle from finite to infinite dimensions. For a time-invariant digraph describing the communication topology, a two-step backstepping approach is presented to systematic

Kai Li

Research instruments play significant roles in the construction of scientific knowledge, even though we have only acquired very limited knowledge about their lifecycles from quantitative studies. This paper aims to address this gap by quantitatively examining the citation contexts of an exemplary research instrument, the Diagnostic and Statistical Manual of

Attia Batool, Gergő Pál, Ferenc Kun

We investigate the impact induced damage and fracture of a bar shaped specimen of heterogeneous materials focusing on how the system approaches perforation as the impact energy is gradually increased. A simple model is constructed which represents the bar as two rigid blocks coupled by a breakable interface with disordered local strength. The bar is clamped

An Tran, Konstantinos Drossos, Tuomas Virtanen

Automated audio captioning (AAC) is a novel task, where a method takes as an input an audio sample and outputs a textual description (i.e. a caption) of its contents. Most AAC methods are adapted from from image captioning of machine translation fields. In this work we present a novel AAC novel method, explicitly focused on the exploitation of the temporal a

Sai Muralidhar Jayanthi, Danish Pruthi, Graham Neubig

We introduce NeuSpell, an open-source toolkit for spelling correction in English. Our toolkit comprises ten different models, and benchmarks them on naturally occurring misspellings from multiple sources. We find that many systems do not adequately leverage the context around the misspelt token. To remedy this, (i) we train neural models using spelling error

Di Wang, Hanshen Xiao, Srini Devadas, Jinhui Xu

In this paper, we consider the problem of designing Differentially Private (DP) algorithms for Stochastic Convex Optimization (SCO) on heavy-tailed data. The irregularity of such data violates some key assumptions used in almost all existing DP-SCO and DP-ERM methods, resulting in failure to provide the DP guarantees. To better understand this type of challe

Tao Yu, Shafiq Joty

Huge amounts of textual conversations occur online every day, where multiple conversations take place concurrently. Interleaved conversations lead to difficulties in not only following the ongoing discussions but also extracting relevant information from simultaneous messages. Conversation disentanglement aims to separate intermingled messages into detached

Dalton A. Hahn, Drew Davidson, Alexandru G. Bardas

Service meshes have emerged as an attractive DevOps solution for collecting, managing, and coordinating microservice deployments. However, current service meshes leave fundamental security mechanisms missing or incomplete. The security burden means service meshes may actually cause additional workload and overhead for administrators over traditional monolith

Hong Shen, Wei Xu, Shulei Gong, Chunming Zhao

In this paper, we focus on intelligent reflecting surface (IRS) assisted multi-antenna communications with transceiver hardware impairments encountered in practice. In particular, we aim to maximize the received signal-to-noise ratio (SNR) taking into account the impact of hardware impairments, where the source transmit beamforming and the IRS reflect beamfo

Dimitris G. Chachlakis, Tongdi Zhou, Fauzia Ahmad, Panos P. Markopoulos

Coprime arrays enable Direction-of-Arrival (DoA) estimation of an increased number of sources. To that end, the receiver estimates the autocorrelation matrix of a larger virtual uniform linear array (coarray), by applying selection or averaging to the physical array&#39;s autocorrelation estimates, followed by spatial-smoothing. Both selection and averaging

Tie-Jun Huang, Li-Zheng Yin, Jin Zhao, Chao-Hai Du

Gradient metasurfaces have been extensively applied in recent years for enabling an unprecedented control of light beam over thin optical components. However, these metasurfaces suffer from low efficiency when it comes to bending light with large angle and high fabrication demand when it requires fine discretion. In this work, we investigate the all-dielectr

Thomas J. Sturges, Taavi Repän, Charles A. Downing, Carsten Rockstuhl

We explore by theoretical means an extreme renormalisation of the eigenmodes of a dimer of dipolar meta-atoms due to strong light-matter interactions. Firstly, by tuning the height of an enclosing photonic cavity, we can lower the energy level of the symmetric `bright&#39; mode underneath that of the anti-symmetric `dark&#39; mode. This is possible due to th

Avik Ranjan Adhikary, Yanghe Feng, Zhengchun Zhou, Pingzhi Fan

Quasi-complementary sequence sets (QCSSs) can be seen as a generalized version of complete complementary codes (CCCs), which enables multicarrier communication systems to support more users. The contribution of this work is two-fold. First, we propose a systematic construction of Florentine rectangles. Secondly, we propose several sets of CCCs and QCSS, usin

Heiko Röglin

In a multiobjective optimization problem a solution is called Pareto-optimal if no criterion can be improved without deteriorating at least one of the other criteria. Computing the set of all Pareto-optimal solutions is a common task in multiobjective optimization to filter out unreasonable trade-offs. For most problems the number of Pareto-optimal solutions

Shivesh Khaitan, Qin Lin, John M. Dolan

Motion Planning under uncertainty is critical for safe self-driving. In this paper, we propose a unified obstacle avoidance framework that deals with 1) uncertainty in ego-vehicle motion; and 2) prediction uncertainty of dynamic obstacles from environment. A two-stage traffic participant trajectory predictor comprising short-term and long-term prediction is

Hongda Shen, Eren Kurshan

Machine learning models have widely been used in fraud detection systems. Most of the research and development efforts have been concentrated on improving the performance of the fraud scoring models. Yet, the downstream fraud alert systems still have limited to no model adoption and rely on manual steps. Alert systems are pervasively used across all payment

L. Chen, T. T. Han, C. Cai, Z. G. Wang

Excitonic insulator (EI) is an intriguing insulating phase of matter, where electrons and holes are bonded into pairs, so called excitons, and form a phase-coherent state via Bose-Einstein Condensation (BEC). Its theoretical concept has been proposed several decades ago, but the followed research is very limited, due to the rare occurrence of EI in natural m

Jannik Hüls, Carina Pilch, Patricia Schinke, Henner Niehaus

Hybrid Petri nets have been extended to include general transitions that fire after a randomly distributed amount of time. With a single general one-shot transition the state space and evolution over time can be represented either as a Parametric Location Tree or as a Stochastic Time Diagram. Recent work has shown that both representations can be combined an

Jiaming Luo, Frederik Hartmann, Enrico Santus, Yuan Cao

Most undeciphered lost languages exhibit two characteristics that pose significant decipherment challenges: (1) the scripts are not fully segmented into words; (2) the closest known language is not determined. We propose a decipherment model that handles both of these challenges by building on rich linguistic constraints reflecting consistent patterns in his

Leandro Farina, Guillaume Lang, P. A. Martin

This paper is concerned mainly with the deceptively simple integral equation \[ u(x) - \frac{1}π\int_{-1}^{1} \frac{α\, u(y)}{α^2+(x-y)^2} \, \rd y = 1, \quad -1 \leq x \leq 1, \] where $α$ is a real non-zero parameter and $u$ is the unknown function. This equation is classified as a Fredholm integral equation of the second kind with a continuous kernel. As

Sparsh Sharma, Marten Klein, Heiko Schmidt, Ennes Sarradj

Noise prediction requires the resolution of relevant acoustic sources on all scales of a turbulent flow. High-resolution direct numerical and large-eddy simulation would be ideal but both are usually too costly despite developments in high performance computing. Lower-order modeling approaches are therefore of general interest. A crucial but standing problem

Yang Liu, Dewei Wang, Xiaodong Sun, Yang Liu

In this paper, we develop a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of the two-fluid model-based multiphase computational fluid dynamics (MCFD) for bubbly flow simulations. The proposed approach is supported by high-resolution two-phase flow measurement techniques, including double-sensor conductivity probe

Chenjie Fan, Zehua Zhao

In this article, we study Stochastic mass critical nonlinear Schrödinger equations with a multiplicative noise in 3D with a slight time decay ($\langle t \rangle^{-ε}$), and prove associated space-time bound and scattering behavior.

Alan E. Robinson

Recent results from the SENSEI experiment show that a cut on event clustering can reduce low-energy excesses in their eV-sensitive calorimeter. This hints at the role of surrounding uninstrumented surfaces in producing backgrounds. Charged particles crossing dielectric boundaries are well known to produce low-energy radiation. In particular, transition radia

Jie Liu, Chen Lin, Chuming Li, Lu Sheng

Several variants of stochastic gradient descent (SGD) have been proposed to improve the learning effectiveness and efficiency when training deep neural networks, among which some recent influential attempts would like to adaptively control the parameter-wise learning rate (e.g., Adam and RMSProp). Although they show a large improvement in convergence speed,

Miloš Simić

The traditional binary classification framework constructs classifiers which may have good accuracy, but whose false positive and false negative error rates are not under users&#39; control. In many cases, one of the errors is more severe and only the classifiers with the corresponding rate lower than the predefined threshold are acceptable. In this study, w

Sai Li, T. Tony Cai, Hongzhe Li

Transfer learning for high-dimensional Gaussian graphical models (GGMs) is studied with the goal of estimating the target GGM by utilizing the data from similar and related auxiliary studies. The similarity between the target graph and each auxiliary graph is characterized by the sparsity of a divergence matrix. An estimation algorithm, Trans-CLIME, is propo

Yacine Izza, Alexey Ignatiev, Joao Marques-Silva

Decision trees (DTs) epitomize what have become to be known as interpretable machine learning (ML) models. This is informally motivated by paths in DTs being often much smaller than the total number of features. This paper shows that in some settings DTs can hardly be deemed interpretable, with paths in a DT being arbitrarily larger than a PI-explanation, i.

Philip W. Livermore, Christopher C. Finlay, Matthew Bayliff

The wandering of Earth&#39;s north magnetic pole, the location where the magnetic field points vertically downwards, has long been a topic of scientific fascination. Since the first in-situ measurements in 1831 of its location in the Canadian arctic, the pole has drifted inexorably towards Siberia, accelerating between 1990 and 2005 from its historic speed o

Ulrich Bindseil, Edoardo Lanari

Bank&#39;s asset fire sales and recourse to central bank credit are modelled with continuous asset liquidity, allowing to derive the liability structure of a bank. Both asset sales liquidity and the central bank collateral framework are modeled as power functions within the unit interval. Funding stability is captured as a strategic bank run game in pure str

Frank Ebbers

This paper examines the up-to-dateness of installed firmware versions of IoT devices accessible via public internet. It analyzes datasets of 1.06m devices collected from the IoT search engine Censys and maps the results against the latest firmware version each manufacturer offers. By applying the SEMMA data mining process, a fully scalable and adaptive appro

Ammar Malik, Hugo Lhachemi, Robert Shorten

I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging on mixed reality technologies. This paper presents novel advances in the development of the interaction platform I-nteract to generate 3D models using both constructive solid geometry and ar

Nina Vesseron, Ievgen Redko, Charlotte Laclau

The theoretical analysis of deep neural networks (DNN) is arguably among the most challenging research directions in machine learning (ML) right now, as it requires from scientists to lay novel statistical learning foundations to explain their behaviour in practice. While some success has been achieved recently in this endeavour, the question on whether DNNs

Pranaydeep Singh, Els Lefever

This paper describes our contribution to the SemEval-2020 Task 9 on Sentiment Analysis for Code-mixed Social Media Text. We investigated two approaches to solve the task of Hinglish sentiment analysis. The first approach uses cross-lingual embeddings resulting from projecting Hinglish and pre-trained English FastText word embeddings in the same space. The se

Huaao Zhang, Shigui Qiu, Xiangyu Duan, Min Zhang

Neural machine translation with millions of parameters is vulnerable to unfamiliar inputs. We propose Token Drop to improve generalization and avoid overfitting for the NMT model. Similar to word dropout, whereas we replace dropped token with a special token instead of setting zero to words. We further introduce two self-supervised objectives: Replaced Token

Xiangyu Ni, Bill Goodwine

This paper focuses on computing the frequency response and transfer functions for large self-similar networks under different circumstances. Modeling large scale systems is difficult due, typically, to the dimension of the problem, and self-similarity is the characteristic we exploit to make the problem more tractable. For each circumstance, we propose algor

Salem Al-Yakoob, Dragan Stevanovic

Transmission of a vertex v of a connected graph G is the sum of distances from v to all other vertices in G. Graph G is transmission irregular (TI) if no two of its vertices have the same transmission, and G is interval transmission irregular (ITI) if it is TI and the vertex transmissions of G form a sequence of consecutive integers. Here we give a positive

Charles Brazier, Gerhard Widmer

Robust real-time opera tracking (score following) would be extremely useful for many processes surrounding live opera staging and streaming, including automatic lyrics displays, camera control, or live video cutting. Recent work has shown that, with some appropriate measures to account for common problems such as breaks and interruptions, spontaneous applaus

J. M. A. Sarr, T. Brochier, P. Brehmer, Y. Perrot

Quantitative and qualitative analysis of acoustic backscattered signals from the seabed bottom to the sea surface is used worldwide for fish stocks assessment and marine ecosystem monitoring. Huge amounts of raw data are collected yet require tedious expert labeling. This paper focuses on a case study where the ground truth labels are non-obvious: echograms

Elena Kulinskaya, David C. Hoaglin, Joseph Newman, Ilyas Bakbergenuly

A variety of problems in random-effects meta-analysis arise from the conventional $Q$ statistic, which uses estimated inverse-variance (IV) weights. In previous work on standardized mean difference and log-odds-ratio, we found superior performance with an estimator of the overall effect whose weights use only group-level sample sizes. The $Q$ statistic with

Jun Jiang, Xian-Jun Li, Xia Wang, Chen-Zhong Dong

The static and dynamic electric-dipole polarizabilities and tune-out wavelengths for the ground state of Cs atoms are calculated by using a semiempirical relativistic configuration interaction plus core polarization approach. By considering the hyperfine splittings, the static and dynamic polarizabilities, hyperfine Stark shifts, and tune-out wavelengths of

Nathan Kallus, Yuta Saito, Masatoshi Uehara

We study off-policy evaluation (OPE) from multiple logging policies, each generating a dataset of fixed size, i.e., stratified sampling. Previous work noted that in this setting the ordering of the variances of different importance sampling estimators is instance-dependent, which brings up a dilemma as to which importance sampling weights to use. In this pap

Fabian Hofmann, Alexander Zerrahn, Carlos Gaete-Morales

We develop novel quantitative techno-economic evaluation criteria for power flow allocation schemes. Such schemes assign which nodes are responsible for which proportion of power flows on a line in a meshed electricity transmission network. As this allocation is, as such, indeterminate, the literature has proposed a number of dedicated schemes. To better und

Sohee Yang, Minjoon Seo

The state of the art in open-domain question answering (QA) relies on an efficient retriever that drastically reduces the search space for the expensive reader. A rather overlooked question in the community is the relationship between the retriever and the reader, and in particular, if the whole purpose of the retriever is just a fast approximation for the r

L. Elisa Celis, Chris Hays, Anay Mehrotra, Nisheeth K. Vishnoi

A robust body of evidence demonstrates the adverse effects of implicit bias in various contexts--from hiring to health care. The Rooney Rule is an intervention developed to counter implicit bias and has been implemented in the private and public sectors. The Rooney Rule requires that a selection panel include at least one candidate from an underrepresented g

Kartik Sharma, Iqra Altaf Gillani, Sourav Medya, Sayan Ranu

In signed networks, each edge is labeled as either positive or negative. The edge sign captures the polarity of a relationship. Balance of signed networks is a well-studied property in graph theory. In a balanced (sub)graph, the vertices can be partitioned into two subsets with negative edges present only across the partitions. Balanced portions of a graph h

Marcus Michelen

Let $f_n(z) = \sum_{k = 0}^n \varepsilon_k z^k$ be a random polynomial where $\varepsilon_0,\ldots,\varepsilon_n$ are i.i.d. random variables with $\mathbb{E} \varepsilon_1 = 0$ and $\mathbb{E} \varepsilon_1^2 = 1$. Letting $r_1, r_2,\ldots, r_k$ denote the real roots of $f_n$, we show that the point process defined by $\{|r_1| - 1,\ldots, |r_k| - 1 \}$ conv

Jiayu Sun, Shaoyun Zhou, Kenta Yamanakab, Yuji Ichikawa

Metalization of carbon fiber reinforced polymers (CFRPs) composites by the surface modification method to enhance their electrical conductivity, thermal conductivity, electromagnetic shielding, erosion, and radiation protection, has a significant meaning in the aerospace field. In this study, Sn coating was successfully fabricated on the CFRP composite subst

Seong-il Im, Hyejin Lee, Jaesang Lee, Jae-Seung Jeong

Interest in Restricted Boltzmann Machine (RBM) is growing as a generative stochastic artificial neural network to implement a novel energy-efficient machine-learning (ML) technique. For a hardware implementation of the RBM, an essential building block is a reliable stochastic binary neuron device that generates random spikes following the Boltzmann distribut

Basile Gallet, Raffaele Ferrari

The mean state of the atmosphere and ocean is set through a balance between external forcing (winds, radiation, heat and freshwater fluxes) and the emergent turbulence, which transfers energy to dissipative structures. The forcing gives rise to jets in the atmosphere and currents in the ocean, which spontaneously develop turbulent eddies through the baroclin