November 2019 arXiv papers — page 44

J. Keski-Rahkonen, A. Ruhanen, E. J. Heller, E. Räsänen

A quantum scar - an enhancement of a quantum probability density in the vicinity of a classical periodic orbit - is a fundamental phenomenon connecting quantum and classical mechanics. Here we demonstrate that some of the eigenstates of the perturbed two-dimensional anisotropic (elliptic) harmonic oscillator are strongly scarred by the Lissajous orbits of th

Xinyi Wang, Jason Weston, Michael Auli, Yacine Jernite

Neural sequence to sequence models are well established for applications which can be cast as mapping a single input sequence into a single output sequence. In this work, we focus on cases where generation is conditioned on both a short query and a long context, such as abstractive question answering or document-level translation. We modify the standard sequ

Wenyuan Fan, Henryk Anglart

The volume of fluid (VOF) method is increasingly used in computational fluid dynamics (CFD) simulations of turbulent two-phase flows. The Reynolds-Averaged Navier-Stokes (RANS) approach is an economic and practical way for turbulent VOF simulations. Even though RANS-VOF simulations are widely conducted, the underlying physics is barely discussed. This study

Bertram Bitsch, Chiara Battistini

The composition of the protoplanetary disc is linked to the composition of the host star, where a higher overall metallicity of the host star provides more building blocks for planets. However, most planet formation simulations only link the stellar iron abundance [Fe/H] to planet formation and [Fe/H] in itself is used as a proxy to scale all elements. But l

Xiuyuan Lu, Benjamin Van Roy

We integrate information-theoretic concepts into the design and analysis of optimistic algorithms and Thompson sampling. By making a connection between information-theoretic quantities and confidence bounds, we obtain results that relate the per-period performance of the agent with its information gain about the environment, thus explicitly characterizing th

Erich Elsen, Marat Dukhan, Trevor Gale, Karen Simonyan

Historically, the pursuit of efficient inference has been one of the driving forces behind research into new deep learning architectures and building blocks. Some recent examples include: the squeeze-and-excitation module, depthwise separable convolutions in Xception, and the inverted bottleneck in MobileNet v2. Notably, in all of these cases, the resulting

Yun Chen, Xingqin Lin, Talha Khan, Mohammad Mozaffari

Flying drones can be used in a wide range of applications and services from surveillance to package delivery. To ensure robust control and safety of drone operations, cellular networks need to provide reliable wireless connectivity to drone user equipments (UEs). To date, existing mobile networks have been primarily designed and optimized for serving ground

Jean Marie Uwabeza Vianney, Shubhra Aich, Bingbing Liu

In this paper, we strive for solving the ambiguities arisen by the astoundingly high density of raw PseudoLiDAR for monocular 3D object detection for autonomous driving. Without much computational overhead, we propose a supervised and an unsupervised sparsification scheme of PseudoLiDAR prior to 3D detection. Both the strategies assist the standard 3D detect

C. Froment, P. Antolin, V. M. J. Henriques, P. Kohutova

Thermal non-equilibrium (TNE) is a phenomenon that can occur in solar coronal loops when the heating is quasi-constant and highly-stratified. Under such heating conditions, coronal loops undergo cycles of evaporation and condensation. The recent observations of ubiquitous long-period intensity pulsations in coronal loops and their relationship with coronal r

Edward Gillen, Joshua T. Briegal, Simon T. Hodgkin, Daniel Foreman-Mackey

We determine rotation periods for 127 stars in the ~115 Myr old Blanco 1 open cluster using ~200 days of photometric monitoring with the Next Generation Transit Survey (NGTS). These stars span F5-M3 spectral types (1.2 $\gtrsim M \gtrsim$ 0.3 M$_{\odot}$) and increase the number of known rotation periods in Blanco 1 by a factor of four. We determine rotation

Wu Changye, Christian P. Robert

For Bayesian computation in big data contexts, the divide-and-conquer MCMC concept splits the whole data set into batches, runs MCMC algorithms separately over each batch to produce samples of parameters, and combines them to produce an approximation of the target distribution. In this article, we embed random forests into this framework and use each subpost

Y. Gong, X. D. Tang, C. Henkel, K. M. Menten

In order to search for further observational evidence of cloud-cloud collisions in one of the promising candidates, L1188, we carried out observations of multiple molecular lines toward the intersection region of the two nearly orthogonal filamentary molecular clouds in L1188. Based on these observations, we find two parallel filamentary structures, both of

E. Sanchez-Diaz, A. Rouillard, B. Lavraud, E. Kilpua

The release of density structures at the tip of the coronal helmet streamers, likely as a consequence of magnetic reconnection, contributes to the mass flux of the slow solar wind. In situ measurements in the vicinity of the heliospheric plasma sheet of the magnetic field, protons and suprathermal electrons reveal details of the processes at play during the

Artur Garcia-Saez, Jordi Riu

We present a classical control mechanism for Quantum devices using Reinforcement Learning. Our strategy is applied to the Quantum Approximate Optimization Algorithm (QAOA) in order to optimize an objective function that encodes a solution to a hard combinatorial problem. This method provides optimal control of the Quantum device following a reformulation of

Matata Ponyo Mapon, Jean-Paul K. Tsasa

This paper reexamines the validity of the natural resource curse hypothesis, using the database of mineral exporting countries. Our findings are as follows: (i) Resource-rich countries (RRCs) do not necessarily exhibit poor political, economic and social performance; (ii) RRCs that perform poorly have a low diversified exports portfolio; (iii) In contrast, R

Richard A. Lockhart, Chandanie W. Navaratna

In this paper, we compare maximum likelihood (ML), quasi likelihood (QL) and weighted least squares (WLS) estimators for proportional error nonlinear regression models. Literature on thermoluminescence sedimentary dating revealed another estimator similar to weighted least squares but observed responses used as weights. This estimator that we refer to as dat

Jorge K. Barrera-Ballesteros, Dyas Utomo, Alberto D. Bolatto, Sebastián F. Sánchez

We present an empirical relation between the cold gas surface density ($Σ_{\rm gas}$) and the optical extinction (${\rm A_V}$) in a sample of 103 galaxies from the Extragalactic Database for Galaxy Evolution (EDGE) survey. This survey provides CARMA interferometric CO observations for 126 galaxies included in the Calar Alto Legacy Integral Field Area (CALIFA

Pratyusha Sharma, Deepak Pathak, Abhinav Gupta

We study a generalized setup for learning from demonstration to build an agent that can manipulate novel objects in unseen scenarios by looking at only a single video of human demonstration from a third-person perspective. To accomplish this goal, our agent should not only learn to understand the intent of the demonstrated third-person video in its context b

G. Vasilopoulos, S. K. Lander, F. Koliopanos, C. D. Bailyn

In the current work we explore the applicability of standard theoretical models of accretion to the observed properties of M51 ULX-7. The spin-up rate and observed X-ray luminosity are evidence of a neutron star with a surface magnetic field of $2-7\times10^{13}$ G, rotating near equilibrium. Analysis of the X-ray light-curve of the system (Swift/XRT data) r

Alex Labach, Shahrokh Valaee

Dropout and similar stochastic neural network regularization methods are often interpreted as implicitly averaging over a large ensemble of models. We propose STE (stochastically trained ensemble) layers, which enhance the averaging properties of such methods by training an ensemble of weight matrices with stochastic regularization while explicitly averaging

Chenglong Wang, Yu Feng, Rastislav Bodik, Alvin Cheung

While visualizations play a crucial role in gaining insights from data, generating useful visualizations from a complex dataset is far from an easy task. Besides understanding the functionality provided by existing visualization libraries, generating the desired visualization also requires reshaping and aggregating the underlying data as well as composing di

Tom Markvart

In a recent paper, Guillemoles et al [J.F. Guillemoles, T. Kirchartz, D. Cahen and U Rau, Guide for the perplexed to the Shockley-Queisser model for solar cells, Nat. Photonics, 13, 501 (2019)] attempt to clarify and explain the often cited paper by Shockley and Queisser (SQ) which defines the limits to photovoltaic conversion by a single-junction solar cell

Sam Witteveen, Martin Andrews

Recently, large language models such as GPT-2 have shown themselves to be extremely adept at text generation and have also been able to achieve high-quality results in many downstream NLP tasks such as text classification, sentiment analysis and question answering with the aid of fine-tuning. We present a useful technique for using a large language model to

Haytham M. Fayek, Justin Johnson

Multimodal question answering tasks can be used as proxy tasks to study systems that can perceive and reason about the world. Answering questions about different types of input modalities stresses different aspects of reasoning such as visual reasoning, reading comprehension, story understanding, or navigation. In this paper, we use the task of Audio Questio

Zheng-Yang Li, Tian-Xue Ma, A-Li Chen, Yue-Sheng Wang

Thermal wave crystals based on the dual-phase-lag model are investigated in this paper by both theoretical analysis and numerical simulation to control the non-Fourier heat conduction process. The transfer matrix method is used to calculate the complex dispersion curves. The temperature field is calculated by the finite difference time domain method. The res

Hooman Mohajeri Moghaddam, Arsalan Mosenia

In an era of pervasive online surveillance, Internet users are in need of better anonymity solutions for online communications without sacrificing performance. Existing overlay anonymity tools, such as the Tor network, suffer from performance limitations and recent proposals to embed anonymity into Internet protocols face fundamental deployment challenges. I

Brennan Bean, Yan Sun, Marc Maguire

Many geosciences data are imprecise due to various limitations and uncertainties in the measuring process. One way to preserve this imprecision in a geostatistical mapping framework is to characterize the measurements as intervals rather than single values. To effectively analyze the interval-valued data, this paper proposes and develops interval-valued krig

Ruilin Li, Robert Tibshirani

We develop a baseline-adjusted C-index to evaluate fitted Cox proportional hazard models. This metric is particularly useful in evaluating stratified Cox models, as well as model selection using cross validation. Our metric is able to compare all pairs of comparable individuals in strata or cross validation folds, as opposed to only pairs within the same str

Paola Pozzi, Björn Stinner

A new semi-discrete finite element scheme for the evolution of three parametrized curves by curvature flow that are connected by a triple junction is presented and analyzed. In this triple junction, conditions are imposed on the angles at which the curves meet. One of the key problems in analyzing motion of networks by curvature law is the choice of a tangen

Stefan Adams, Chiranjib Mukherjee

It is well-known that the {\it Gross-Pitaevskii} variational formula describes the the ground state energy of of $N$-indistinguishable trapped particles (bosons) in a dilute state in the large system size $N\to\infty$. The goal of the present article is to prove that the Gross-Pitaevskii formula also appears in the {\it iterative limit} of zero temperature a

Fabien Defrance, Cecile Jung-Kubiak, Sofia Rahiminejad, Theodore Macioce

We present the design, simulation, and planned fabrication process of a flat high resistivity silicon gradient index (GRIN) lens for millimeter and submillimeter wavelengths with very low absorption losses. The gradient index is created by subwavelength holes whose size increases with the radius of the lens. The effective refractive index created by the subw

Edi Halyo

We claim that there is a one to one correspondence between $NAdS_2$ spacetimes and dilatonic $AdS_2$ black holes. We show that these have the same thermodynamics and can be described by the same states of 1D CFTs with the same central charge. In addition, we show that these are actually the same set of solutions since a field redefinition in the Schwarzian t

Alejandro Allendes, Francisco Fuica, Enrique Otarola, Daniel Quero

We devise and analyze a reliable and efficient a posteriori error estimator for a semilinear control-constrained optimal control problem in two and three dimensional Lipschitz, but not necessarily convex, polytopal domains. We consider a fully discrete scheme that discretizes the state and adjoint equations with piecewise linear functions and the control var

P. G. Grinevich, R. G. Novikov

We continue to develop the method for creation and annihilation of contour singularities in the $\bar\partial$--spectral data for the two-dimensional Schrödinger equation at fixed energy. Our method is based on the Moutard-type transforms for generalized analytic functions. In this note we show that this approach successfully works for point potentials.

Matt Booth

A version of the Bondal-Orlov conjecture, proved by Bridgeland, states that if $X$ and $Y$ are smooth complex projective threefolds linked by a flop, then they are derived equivalent. Van den Bergh gave a new proof of Bridgeland's theorem using the notion of a NCCR, which is in particular a ring $A$ together with a derived equivalence between $X$ and $A$

Minah Oh

In this paper, we will construct and analyze a multigrid algorithm that can be applied to weighted H(div)-problems on a two-dimensional domain. These problems arise after performing a dimension reduction to a three-dimensional axisymmetric H(div)-problem. We will use recently developed Fourier finite element spaces that can be applied to axisymmetric H(div)-

K. D. Elworthy, Xue-Mei Li

We prove a Kodaira-Hodge decomposition on differential 1-forms on the space of non-smooth paths over a Riemannian manifold, allowing us to define the corresponding first cohomology group. This uses the Itô map of a Brownian system and damped stochastic parallel translation.

Marta Sarrico, Kai Arulkumaran, Andrea Agostinelli, Pierre Richemond

Deep networks have enabled reinforcement learning to scale to more complex and challenging domains, but these methods typically require large quantities of training data. An alternative is to use sample-efficient episodic control methods: neuro-inspired algorithms which use non-/semi-parametric models that predict values based on storing and retrieving previ

Robert Runkel, Zoltán Szőr, Juan Pablo Vesga, Stefan Weinzierl

We present a new formulation of the loop-tree duality theorem for higher loop diagrams valid both for massless and massive cases. $l$-loop integrals are expressed as weighted sum of trees obtained from cutting $l$ internal propagators of the loop graph. In addition, the uncut propagators gain a modified $i δ$-prescription, named dual-propagators. In this new

Abdulhameed Qahtan Abbood Altai

In this paper, we introduce formulations of the Trotter Kato theorem for approximation of bi continuous semigroups that provide a useful framework whenever convergence of numerical approximations to solutions of PDEs are studied with respect to an additional locally convex topology coarser than the norm topology to treat the lack of the strong continuity. Ap

William Graham

The Springer resolution of the nilpotent cone of a semisimple Lie algebra has played an important role in representation theory. The nilpotent cone is equal to Spec R, where R is the ring of regular functions on the nilpotent cone. This paper constructs and studies an analogue of the Springer resolution for the variety Spec S, where S is the ring of regular

Alexander Gomez-Villa, Adrian Martín, Javier Vazquez-Corral, Jesús Malo

Visual illusions are a very useful tool for vision scientists, because they allow them to better probe the limits, thresholds and errors of the visual system. In this work we introduce the first ever framework to generate novel visual illusions with an artificial neural network (ANN). It takes the form of a generative adversarial network, with a generator of

Feibo Jiang, Kezhi Wang, Li Dong, Cunhua Pan

In this paper, we consider a hybrid mobile edge computing (H-MEC) platform, which includes ground stations (GSs), ground vehicles (GVs) and unmanned aerial vehicle (UAVs), all with mobile edge cloud installed to enable user equipments (UEs) or Internet of thing (IoT) devices with intensive computing tasks to offload. Our objective is to obtain an online offl

Justin P. Haldar

The optimization of MRI data sampling and image reconstruction methods has been a priority for the MRI community since the very early days of the field. Designing an "optimal" method requires the definition of an optimality metric (i.e., a quantitative evaluation of the "goodness" of different competing approaches that allows an objective com

Yingkun Li, Tonghai Yang

In this paper, we prove the conjecture of Yui and Zagier concerning the factorization of the resultants of minimal polynomials of Weber class invariants. The novelty of our approach is to systematically express differences of certain Weber functions as products of Borcherds products.

Faranak Abri, Sima Siami-Namini, Mahdi Adl Khanghah, Fahimeh Mirza Soltani

The detection of zero-day attacks and vulnerabilities is a challenging problem. It is of utmost importance for network administrators to identify them with high accuracy. The higher the accuracy is, the more robust the defense mechanism will be. In an ideal scenario (i.e., 100% accuracy) the system can detect zero-day malware without being concerned about mi

E. Kara, C. Pinto, D. J. Walton, W. N. Alston

Ultraluminous X-ray Sources (ULXs) provide a unique opportunities to probe the geometry and energetics of super-Eddington accretion. The radiative processes involved in super-Eddington accretion are not well understood, and so studying correlated variability between different energy bands can provide insights into the causal connection between different emit

Opeyemi S. Orioke, Tauhidul Alam, Joseph Quinn, Ramneek Kaur

Ocean ecosystems have spatiotemporal variability and dynamic complexity that require a long-term deployment of an autonomous underwater vehicle for data collection. A new long-range autonomous underwater vehicle called Tethys is adapted to study different oceanic phenomena. Additionally, an ocean environment has external forces and moments along with changin

Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet

Rare events, and more general risk-sensitive quantities-of-interest (QoIs), are significantly impacted by uncertainty in the tail behavior of a distribution. Uncertainty in the tail can take many different forms, each of which leads to a particular ambiguity set of alternative models. Distributional robustness bounds over such an ambiguity set constitute a s

Craig Lage

Removing systematic effects from astronomical images taken with CCDs requires a detailed understanding of the physics of the imaging process. To aid in this understanding, we have built detailed electrostatic simulations of the LSST CCDs. In order to build an electrostatic model of the LSST CCDs, physical information about the CCDs is required. These details

Guerrino Mazzarolo, Anca Delia Jurcut

Insider threats have become reality for civilian firms such as Tesla, which experienced sabotage and intellectual property theft, and Capital One, which suffered from fraud. Even greater social impact was caused by the data breach at the US Department of Defense, perpetrated by well-known attackers Chelsea Manning and Edward Snowden, whose espionage and hack

L. Löbling, M. A. Maney, T. Rauch, P. Quinet

We have identified 484 lines of the trans-iron elements (TIEs) Zn, Ga, Ge, Se, Br, Kr, Sr, Zr, Mo, In, Te, I, Xe, and Ba, for the first time in the ultraviolet spectrum of a DAO-type WD, namely BD$-22{^\circ}3467$, surrounded by the ionized nebula Abell 35. Our TIE abundance determination shows extremely high overabundances of up to five dex -- a similar eff

Wenxin Hu, Xiaofeng Zhang, Gang Yang

Automatically generating macro research reports from economic news is an important yet challenging task. As we all know, it requires the macro analysts to write such reports within a short period of time after the important economic news are released. This motivates our work, i.e., using AI techniques to save manual cost. The goal of the proposed system is t

Craig Lage

The Brighter-Fatter (hereafter BF) effect in CCD sensors causes increases in the image size of bright objects due to electrostatic repulsion of collected charges. Correcting this effect in the LSST camera is required in order to meet the science goals of the project, especially galaxy shape measurements for weak lensing. The current plan for BF image correct

Kwang-Sung Jun, Francesco Orabona

We consider the problem of minimizing a convex risk with stochastic subgradients guaranteeing $ε$-locally differentially private ($ε$-LDP). While it has been shown that stochastic optimization is possible with $ε$-LDP via the standard SGD (Song et al., 2013), its convergence rate largely depends on the learning rate, which must be tuned via repeated runs. Fu

Leonardo Mariani, Mauro Pezzè, Oliviero Riganelli, Rui Xin

Many applications are implemented as multi-tier software systems, and are executed on distributed infrastructures, like cloud infrastructures, to benefit from the cost reduction that derives from dynamically allocating resources on-demand. In these systems, failures are becoming the norm rather than the exception, and predicting their occurrence, as well as

Andrea Agostinelli, Kai Arulkumaran, Marta Sarrico, Pierre Richemond

Recently, neuro-inspired episodic control (EC) methods have been developed to overcome the data-inefficiency of standard deep reinforcement learning approaches. Using non-/semi-parametric models to estimate the value function, they learn rapidly, retrieving cached values from similar past states. In realistic scenarios, with limited resources and noisy data,

Mohammad Masiur Rahaman, Wenqiang Fang, Alice Lux Fawzi, Yang Wan

We present an algorithm for determining the acceleration field of a rigid body using measurements from four tri-axial accelerometers. The acceleration field is an important quantity in bio-mechanics problems, especially in the study of mild Traumatic Brain Injury (mTBI). The in vivo strains in the brain, which are hypothesized to closely correlate with brain

Dávid Visontai, József Stéger, János Márk Szalai-Gindl, László Dobos

Research collaborations are continuously emerging catalyzed by online platforms, where people can share their codes, calculations, data and results. These virtual research platforms are innovative, community oriented, flexible and secure as required by modern scientific approaches. A wide range of open source and commercial solutions are available in this fi

Hao Wang, Pu Lu, Hui Zhang, Mingkun Yang

Recently, end-to-end text spotting that aims to detect and recognize text from cluttered images simultaneously has received particularly growing interest in computer vision. Different from the existing approaches that formulate text detection as bounding box extraction or instance segmentation, we localize a set of points on the boundary of each text instanc

Christopher Zerafa, Pauline Galea, Cristiana Sebu

Full-waveform inversion (FWI) is a widely used technique in seismic processing to produce high resolution Earth models that fully explain the recorded seismic data. FWI is a local optimisation problem which aims to minimise in a least-squares sense the misfit between recorded and modelled data. The inversion process begins with a best-guess initial model whi

Martin Neumüller, Martin Schwalsberger

We expand the applicabilities and capabilities of an already existing space-time parallel method based on a block Jacobi smoother. First we formulate a more detailed criterion for spatial coarsening, which enables the method to deal with unstructured meshes and varying material parameters. Further we investigate the application to the eddy-current equation,

Calum Milloy, Giulio Falcioni, Einan Gardi

We discuss the relation between the infrared singularities of on-shell partonic form factors and parton distribution functions (PDFs) near the elastic limit, through their factorisation in terms of Wilson-line correlators. Ultimately we identify the difference between the anomalous dimensions controlling single poles of these two quantities to all loops in t

Jindong Gu, Volker Tresp

Deep neural networks (DNNs) can easily fit a random labeling of the training data with zero training error. What is the difference between DNNs trained with random labels and the ones trained with true labels? Our paper answers this question with two contributions. First, we study the memorization properties of DNNs. Our empirical experiments shed light on h

Benny Sudakov, Istvan Tomon, Adam Zsolt Wagner

The Boolean lattice $2^{[n]}$ is the family of all subsets of $[n]=\{1,\dots,n\}$ ordered by inclusion, and a chain is a family of pairwise comparable elements of $2^{[n]}$. Let $s=2^{n}/\binom{n}{\lfloor n/2\rfloor}$, which is the average size of a chain in a minimal chain decomposition of $2^{[n]}$. We prove that $2^{[n]}$ can be partitioned into $\binom{n

I. Brevik, A. V. Timoshkin

We investigate bounce cosmological models in the presence of a viscous fluid, making use of generalized holographic cutoffs introduced by Nojiri and Odintsov (2017). We consider both an exponential, a power-law, and a double exponential form for the scale factor. By use of these models we calculate expressions for infrared cutoffs analytically, such that the

Janne Heittokangas, Hui Yu, M. Amine Zemirni

Assuming that $A_0,\ldots,A_{n-1}$ are entire functions and that $p\in \{0,\ldots,n-1\}$ is the smallest index such that $A_p$ is transcendental, then, by a classical theorem of Frei, each solution base of the differential equation $f^{(n)}+A_{n-1}f^{(n-1)}+\cdots +A_{1}f'+A_{0}f=0$ contains at least $n-p$ entire functions of infinite order. Here, the tr

Sima Siami-Namini, Neda Tavakoli, Akbar Siami Namin

Machine and deep learning-based algorithms are the emerging approaches in addressing prediction problems in time series. These techniques have been shown to produce more accurate results than conventional regression-based modeling. It has been reported that artificial Recurrent Neural Networks (RNN) with memory, such as Long Short-Term Memory (LSTM), are sup

Matias D. Cattaneo, Nicolas Idrobo, Rocio Titiunik

In this Element and its accompanying Element, Matias D. Cattaneo, Nicolas Idrobo, and Rocio Titiunik provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. In this Element, the a

Nicolas Chevalier

Peristalsis enables transport of the food bolus in the gut. Here, I show by dynamic ex-vivo intra-cellular calcium imaging on living embryonic gut transverse sections that the most primitive form of peristalsis that occurs in the embryo is the result of inter-cellular, gap-junction dependent calcium waves that propagate in the circular smooth muscle layer. I

Luiz A. Zanlorensi, Diego R. Lucio, Alceu S. Britto, Hugo Proença

One of the major challenges in ocular biometrics is the cross-spectral scenario, i.e., how to match images acquired in different wavelengths (typically visible (VIS) against near-infrared (NIR)). This article designs and extensively evaluates cross-spectral ocular verification methods, for both the closed and open-world settings, using well known deep learni

Kia Khezeli, Eilyan Bitar

We introduce the safe linear stochastic bandit framework---a generalization of linear stochastic bandits---where, in each stage, the learner is required to select an arm with an expected reward that is no less than a predetermined (safe) threshold with high probability. We assume that the learner initially has knowledge of an arm that is known to be safe, bu

Tobias Gabler, Karsten Backhaus, Steffen Großmann, Ronny Fritsche

It is state-of-the-art to describe the dielectric behavior of an insulation material by its permittivity and its specific electric conductivity in order to estimate the dielectric stress of an insulation system. Thus, the electric field at DC voltage stress is determined according to the stationary electrical conduction field with the electric conductivity o

Michiya Mori, Peter Šemrl

Let $H$ be a finite-dimensional Hilbert space, $\dim H \ge 2$. We prove that every continuous coexistency preserving map on the effect algebra $E(H)$ is either a standard automorphism of $E(H)$, or a standard automorphism of $E(H)$ composed with the orthocomplementation. We present examples showing the optimality of the result.

Martin Aleksandrov, Toby Walsh

We survey a burgeoning and promising new research area that considers the online nature of many practical fair division problems. We identify wide variety of such online fair division problems, as well as discuss new mechanisms and normative properties that apply to this online setting. The online nature of such fair division problems provides both opportuni

Christoph Gote, Ingo Scholtes, Frank Schweitzer

Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Most of the studied networks are based on

Valentin Zagrebnov

We revise the strong convergent Chernoff product formula and extend it, in a Hilbert space, to convergence in the operator-norm topology. Main results deal with the self-adjoint Chernoff product formula. The nonself-adjoint case concerns the quasi-sectorial contractions.

Victor Petrén Bach Hansen, Anders Søgaard

In conversation, we often ask one-word questions such as `Why?' or `Who?'. Such questions are typically easy for humans to answer, but can be hard for computers, because their resolution requires retrieving both the right semantic frames and the right arguments from context. This paper introduces the novel ellipsis resolution task of resolving such o

Wim Veldman

We show that the intuitionistic first-order theory of equality has continuum many complete extensions. We also study the Vitali equivalence relation and show there are many intuitionistically precise versions of it.

Golnaz Habibi, Nikita Japuria, Jonathan P. How

This paper presents a novel incremental learning algorithm for pedestrian motion prediction, with the ability to improve the learned model over time when data is incrementally available. In this setup, trajectories are modeled as simple segments called motion primitives. Transitions between motion primitives are modeled as Gaussian Processes. When new data i

Sahan Bulathwela, Maria Perez-Ortiz, Emine Yilmaz, John Shawe-Taylor

The recent advances in computer-assisted learning systems and the availability of open educational resources today promise a pathway to providing cost-efficient, high-quality education to large masses of learners. One of the most ambitious use cases of computer-assisted learning is to build a lifelong learning recommendation system. Unlike short-term courses

Mohammad H. Mamduhi, Ehsan Hashemi, John S. Baras, Karl H. Johansson

This paper proposes an event-triggered add-on safety mechanism to adjust the control parameters for timely braking in a networked vehicular system while maintaining maneuverability. Passenger vehicle maneuverability is significantly affected by the combined-slip friction effect, in which larger longitudinal tire slips result in considerable drop in lateral t

Hongbo Zhao

In this paper we study certain analogues of the map defined by Alain Connes, which follows an idea of Atiyah in trying to simplify the proof of Feit-Thompson theorem. It turns out that the the non-zero fixed points of the map can be characterized explicitly as an abelian group, and we can calculate some examples. It turns out that most fixed points are not o

Geoffrey Hibert, Etienne Grau, Didier Pintori, Sébastien Lecommandoux

Trehalose diesters exhibiting $α$,$ω$-unsaturation are glycolipids which can be easily polymerized by ADMET (acyclic diene metathesis) polymerization. In this paper, enzymatic esterification was performed to selectively esterify primary hydroxyl groups of trehalose (6 and 6'-positions) with vinyl undecenoate. The vinyl ester was beforehand obtained by pa

David Bergman, Teng Huang, Philip Brooks, Andrea Lodi

Business research practice is witnessing a surge in the integration of predictive modeling and prescriptive analysis. We describe a modeling framework JANOS that seamlessly integrates the two streams of analytics, for the first time allowing researchers and practitioners to embed machine learning models in an optimization framework. JANOS allows for specifyi

Frédéric Voisin

Sound environment is a prime source of conscious and unconscious information which allows listeners to place themselves, to communicate, to feel, to remember. The author describes the process of designing a new audio interactive apparatus for Alzheimer's care, in the context of an active multidisciplinary research project led by the author in collaborati

Jinhang Zuo, Xiaoxi Zhang, Carlee Joe-Wong

We consider the stochastic multi-armed bandit (MAB) problem in a setting where a player can pay to pre-observe arm rewards before playing an arm in each round. Apart from the usual trade-off between exploring new arms to find the best one and exploiting the arm believed to offer the highest reward, we encounter an additional dilemma: pre-observing more arms

B. Etmański, M. R. Schmidt, R. Szczerba

The HIFI instrument on board of the Herschel Space Observatory (HSO) has been very successful in detecting molecular lines from circumstellar envelopes around evolved stars, like massive red supergiants, Asymptotic Giant Branch (AGB) and post-AGB stars, as well as planetary nebulae. Among others, ammonia has been found in circumstellar envelopes of C-rich AG

Shamit Shrivastava, Robin O. Cleveland

This study investigates the emission of light and sound from cavitation caused by intense pressure pulses in water. Based on time-resolved measurements of (a) pressure waveform at the focus, (b) light scattering upon cavitation, (c) acoustic emission, and (d) photoemission (sonoluminescence) it is shown that emissions occur upon the creation or expansion as

Josh Merel, Diego Aldarondo, Jesse Marshall, Yuval Tassa

Parallel developments in neuroscience and deep learning have led to mutually productive exchanges, pushing our understanding of real and artificial neural networks in sensory and cognitive systems. However, this interaction between fields is less developed in the study of motor control. In this work, we develop a virtual rodent as a platform for the grounded

Zhipeng Wei, Jingjing Chen, Xingxing Wei, Linxi Jiang

We study the problem of attacking video recognition models in the black-box setting, where the model information is unknown and the adversary can only make queries to detect the predicted top-1 class and its probability. Compared with the black-box attack on images, attacking videos is more challenging as the computation cost for searching the adversarial pe

Kishor Bharti, Maharshi Ray, Antonios Varvitsiotis, Adán Cabello

The onset of the era of fully-programmable error-corrected quantum computers will be marked by major breakthroughs in all areas of science and engineering. These devices promise to have significant technological and societal impact, notable examples being the analysis of big data through better machine learning algorithms and the design of new materials. Nev

Pablo Spiga

In this paper we show that two distinct conjectures, the first proposed by Babai and Godsil in $1982$ and the second proposed by Xu in $1998$, concerning the asymptotic enumeration of Cayley graphs are in fact equivalent. This result follows from a more general theorem concerning the asymptotic enumeration of a certain family of Cayley graphs.

Roy Karasik, Osvaldo Simeone, Marco Di Renzo, Shlomo Shamai

A communication link aided by a Reconfigurable Intelligent Surface (RIS) is studied, in which the transmitter can control the state of the RIS via a finite-rate control link. Prior work mostly assumed a fixed RIS configuration irrespective of the transmitted information. In contrast, this work derives information-theoretic limits, and demonstrates that the c

Sergey I. Nikulin, Olga S. Rozanova

We study the mean field games equations, consisting of the coupled Kolmogorov-Fokker-Planck and Hamilton-Jacobi-Bellman equations. The equations are complemented by initial and terminal conditions. It is shown that with some specific choice of data, this problem can be reduced to solving a quadratically nonlinear system of ODEs. This situation occurs natural

Xue Zhang, Qing-Guo Huang

Adopting the low-redshift observational datasets, including the Pantheon sample of Type Ia supernovae, baryon acoustic oscillation measurements, and the tomographic Alcock-Paczynski method, we determine the Hubble constant to be $67.95^{+0.78}_{-1.03}$ , $69.81^{+2.22}_{-2.70}$ and $66.75^{+3.42}_{-4.23}$ km s$^{-1}$ Mpc$^{-1}$ at 68\% confidence level in th

Xin-Zhen Weng, Li-Ye Xiao, Wei-Zhen Deng, Xiao-Lin Chen

With an extended quark pair creation model we systematically study the OZI-allowed three body open flavor decays of higher vector charmonium and bottomonium states. We obtain that the $BB^*π$ and $B^*B^*π$ partial decay widths of $Υ(10860)$ are consistent with experiment, and the corresponding partial decay widths of $Υ(11020)$ can reach up to 2$\sim$3 MeV.

Andrea Castro

The ATLAS and CMS Collaborations have performed a variety of measurements of the top quark mass, taking advantage of the abundant production of top quarks at the LHC. The most recent measurements are reported here, based on data collected at 8 and 13 TeV, with particular emphasis on the distinction between the so-called "direct" measurements and the

Zhaoyang Liu, Donghao Luo, Yabiao Wang, Limin Wang

Efficiency is an important issue in designing video architectures for action recognition. 3D CNNs have witnessed remarkable progress in action recognition from videos. However, compared with their 2D counterparts, 3D convolutions often introduce a large amount of parameters and cause high computational cost. To relieve this problem, we propose an efficient t

Jianwei Zhao, Qi Dong, Yanjie Zhao, Bolei Wang

Unmanned aerial vehicle (UAV) has become an appealing solution for a wide range of commercial and civilian applications because of its high mobility and flexible deployment. Due to the continuous UAV navigation, the channel between UAV and base station (BS) is subject to the Doppler effect. Meanwhile, when the BS is equipped with massive number of antennas,