November 2018 arXiv papers — page 18

Shaddin Dughmi, David Kempe, Ruixin Qiang

To select a subset of samples or "winners" from a population of candidates, order sampling [Rosen 1997] and the k-unit Myerson auction [Myerson 1981] share a common scheme: assign a (random) score to each candidate, then select the k candidates with the highest scores. We study a generalization of both order sampling and Myerson's allocation rule

Qiang Sun

In this study, molecular dynamic simulations are employed to investigate the nucleation of NaCl crystal in solutions. According to the simulations, the dissolved behaviors of NaCl in water are dependent on ion concentrations. With increasing NaCl concentrations, the dissolved Na$^+$ and Cl$^-$ ions tend to be aggregated in solutions. In combination with our

Mohd Suhail Rizvi

The transportation of the cargoes in biological cells is primarily driven by the motor proteins on filamentous protein tracks. The stochastic nature of the motion of motor protein often leads to its spontaneous detachment from the track. Using the available experimental data, we demonstrate a tradeoff between the speed of the motor and its rate of spontaneou

Shijin Ding, Quanrong Li

This paper is concerned with the validity of the Prandtl boundary layer theory in the inviscid limit of the steady incompressible Navier-Stokes equations, which is an extension of the pioneer paper (Y. Guo et al., 2017, Ann. PDE) from a domain of $[0,L]\times\mathbb{R}_+$ to $[0,L]\times[0,2]$. Under the symmetry assumption, we establish the validity of the

Sharareh Sayyad, Naoto Tsuji, Abolhassan Vaezi, Massimo Capone

We study the dynamical behavior of doped electronic systems subject to a global ramp of the repulsive Hubbard interaction. We start with formulating a real-time generalization of the fluctuation-exchange approximation. Implementing this numerically, we investigate the weak-coupling regime of the Hubbard model both in the electron-doped and hole-doped regimes

Chuanchen Luo, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang

With the surge of deep learning techniques, the field of person re-identification has witnessed rapid progress in recent years. Deep learning based methods focus on learning a feature space where samples are clustered compactly according to their corresponding identities. Most existing methods rely on powerful CNNs to transform the samples individually. In c

Daqiang Bao, Chengjie Zhu, Yaping Yang, G. S. Agarwal

We investigate the cavity excitation spectrum and the photon number distribution in a cavity QED system driven by a broadband squeezed vacuum. In an empty cavity, we show that only states with even number of photons can be measured under resonant condition since the squeezed vacuum consists of states with even number of photons only. When a single atom is tr

Jie Liu, Zhen Yan, Jian-Ping Yuan, Ru-Shuang Zhao

One large glitch was detected in PSR B1737$-$30 using data spanning from MJD 57999 to 58406 obtained with the newly built Shanghai Tian Ma Radio Telescope (TMRT). The glitch took place at the time around MJD 58232.4 when the pulsar underwent an increase in the rotation frequency of $Δν$ about 1.38$\times 10^{-6}$ Hz, corresponding to a fractional step change

Grigory Vekstein

The present paper provides comprehensive description of various regimes involved in the two-fluid model of the resistive tearing instability. These include two novel regimes of this instability, which correspond to the long-wave modes that can develop in a highly-elongated current sheet. This issue is relevant to the study of fast magnetic reconnection and m

Toshihiro Noda, Yasuhiro Hieida, Shin-ichi Tadaki

On highways with two lanes, cars are requested to run on the slow lane and are allowed to run on the fast lane for overtaking. However, on real two-lane highways, we daily observe a phenomenon called "reverse lane usage", in which the flow on the fast lane exceeds that on the slow lane. The origins of the phenomenon have not been discussed clearly. I

Andrey Sayanskiy, Anton S. Kupriianov, Su Xu, Polina Kapitanova

We reveal peculiarities of the trapped (dark) mode excitation in a polarization-insensitive all-dielectric metasurface, whose unit super-cell is constructed by particularly arranging four cylindrical dielectric particles. Involving group-theoretical description we discuss in detail the effect of different orientations of particles within the super-cell on ch

Shao-Meng Qin

C-dismantling (CD) problem aims at finding the minimum vertex set D of a graph G(V,E) after removing which the remaining graph will break into connected components with the size not larger than C. In this paper, we introduce a spin-glass model with C+1 integer-value states into the CD problem and then study the properties of this spin-glass model by the beli

Ziran Zhang, Zixuan Yao, Qinbo Sun, Huihuan Qian

Autonomous Surface Vehicles (ASVs) provide an effective way to actualize applications such as environment monitoring, search and rescue, and scientific researches. However, the conventional ASVs depends overly on the stored energy. Hybrid Sailboat, mainly powered by the wind, can solve this problem by using an auxiliary propulsion system. The electric energy

Ramtin Zand, Kerem Y. Camsari, Supriyo Datta, Ronald F. DeMara

Magnetoresistive random access memory (MRAM) technologies with thermally unstable nanomagnets are leveraged to develop an intrinsic stochastic neuron as a building block for restricted Boltzmann machines (RBMs) to form deep belief networks (DBNs). The embedded MRAM-based neuron is modeled using precise physics equations. The simulation results exhibit the de

Pavel Tolmachev, Rishi R. Dhingra, Michael Pauley, Mathias Dutschmann

Computational models of the respiratory central pattern generator (rCPG) are usually based on biologically-plausible Hodgkin Huxley neuron models. Such models require numerous parameters and thus are prone to overfitting. The HH approach is motivated by the assumption that the biophysical properties of neurons determine the network dynamics. Here, we impleme

Chandrashekar Murugeshan, Virginia Kilborn, Danail Obreschkow, Karl Glazebrook

The neutral atomic hydrogen (HI) content of spiral galaxies has been observed to vary with environment, with more HI-deficient spirals residing in high density environments. This can be attributed to environmental effects such as ram pressure stripping and tidal interactions, which remove HI from the discs of galaxies. However, some spirals in low-density en

Ian Miller, Jon Wallace

A key limitation of current multi-robot systems is a lack of relative localization, particularly in environments without GPS or motion capture systems. This article presents a centralized method for relatively localizing a 2D swarm using sensors and beacons on the robots themselves. The UKF-based algorithm as well as the requisite novel and cost-effective se

Tatsuo Kobayashi, Shio Tamba

We study modular transformation of holomorphic Yukawa couplings in magnetized D-brane models. It is found that their products are modular forms, which are non-trivial representations of finite modular subgroups, e.g. $S_3$, $S_4$, $Δ(96)$ and $Δ(384)$.

Xueying Li, Yanqi Luo, Martin Holt, Zhonghou Cai

Using nanoprobe X-ray diffraction microscopy, we investigate the relationship between residual strains from crystal growth in CsPbBr$_3$ thin film crystals, their stability, and local bandgap. We find that out-of-plane compressive strain that arises from cooldown from crystallization is detrimental to material stability under X-ray irradiation. We also find

C. H. Jeffrey Pang

This work builds on our recent work on a distributed optimization algorithm for graphs with directed unreliable communications. We show its linear convergence when we take either the proximal of each function or an affine minorant for when the function is smooth.

Wei Wei, Megan Barry, Thomas Klähn, Prashanth Jaikumar

Compact stars containing quark matter may masquerade as neutron stars in the range of measured mass and radius, making it difficult to draw firm conclusions on the phase of matter inside the star. The sensitivity of core $g$-mode oscillations to the presence of a mixed phase may alleviate this difficulty. In hybrid stars that admit quark matter in a mixed ph

Ming Yan, Jiangnan Xia, Chen Wu, Bin Bi

A fundamental trade-off between effectiveness and efficiency needs to be balanced when designing an online question answering system. Effectiveness comes from sophisticated functions such as extractive machine reading comprehension (MRC), while efficiency is obtained from improvements in preliminary retrieval components such as candidate document selection a

Panagiotis Kouvaros, Alessio Lomuscio

We address the problem of verifying neural-based perception systems implemented by convolutional neural networks. We define a notion of local robustness based on affine and photometric transformations. We show the notion cannot be captured by previously employed notions of robustness. The method proposed is based on reachability analysis for feed-forward neu

Suvendu Rakshit, Ansu Johnson, C. S. Stalin, Poshak Gandhi

We present the color and flux variability analysis at 3.4 μm (W1-band) and 4.6 μm (W 2-band) of 492 narrow-line Seyfert 1 (NLSy1) galaxies using archival data from the Wide-field Infrared Survey Explorer (WISE). In the WISE color-color, (W1 - W2) versus (W2 - W3) diagram, ~58% of the NLSy1 galaxies of our sample lie in the region occupied by the blazar categ

Majid Hashemi, Gholamhossein Haghighat

In this study, we investigate observability of the neutral scalar ($H$) and pseudoscalar ($A$) Higgs bosons in the framework of the Type-I 2HDM at SM-like scenario at a linear collider operating at $\sqrt s=$ 500 and 1000 GeV. The signal process chain $e^- e^+ \rightarrow A H \rightarrow ZHH\rightarrow jj b\bar{b}b\bar{b}$ where $jj$ is a di-jet resulting fr

Stephen Deterding

Let $U$ be a bounded open subset of the complex plane. Let $0<α<1$ and let $A_α(U)$ denote the space of functions that satisfy a Lipschitz condition with exponent $α$ on the complex plane, are analytic on $U$ and are such that for each $ε>0$, there exists $δ>0$ such that for all $z$, $w \in U$, $|f(z)-f(w)| \leq ε|z-w|^α$ whenever $|z-w| < δ$. We show that i

K. Vasudevan, K. Madhu, Shivani Singh

Single user massive multiple input multiple output (MIMO) can be used to increase the spectral efficiency, since the data is transmitted simultaneously from a large number of antennas located at both the base station and mobile. It is feasible to have a large number of antennas in the mobile, in the millimeter wave frequencies. However, the major drawback of

Q. M. Zhang, D. Li, Y. Huang

In this paper, we report our multiwavelength imaging observations of chromospheric evaporation in a C5.5 circular-ribbon flare (CRF) on 2014 August 24. The flare was observed by the Atmospheric Imaging Assembly (AIA) on board the \textit{Solar Dynamics Observatory} (\textit{SDO}), X-ray Telescope (XRT) on board the \textit{Hinode} spacecraft, and ground-base

Hidetomo Nagai, Yasuhiro Ohta, Ryogo Hirota

We propose new type of discrete and ultradiscrete soliton equations, which admit extended soliton solution called periodic phase soliton solution. The discrete equation is derived from the discrete DKP equation and the ultradiscrete one is obtained by applying the ultradiscrete limit. The soliton solutions have internal freedom and change their shape periodi

Ying Zhang

Convolutions of independent random variables often arise in a natural way in many applied problems. In this article, we compare convolutions of two sets of gamma (negative binomial) random variables in the convolution order and the usual stochastic order in a unified set-up, when the shape and scale parameters satisfy a partial order called reverse-coupled m

David Warde-Farley, Tom Van de Wiele, Tejas Kulkarni, Catalin Ionescu

Learning to control an environment without hand-crafted rewards or expert data remains challenging and is at the frontier of reinforcement learning research. We present an unsupervised learning algorithm to train agents to achieve perceptually-specified goals using only a stream of observations and actions. Our agent simultaneously learns a goal-conditioned

Suhani Vora, Reza Mahjourian, Soeren Pirk, Anelia Angelova

Predicting the future to anticipate the outcome of events and actions is a critical attribute of autonomous agents; particularly for agents which must rely heavily on real time visual data for decision making. Working towards this capability, we address the task of predicting future frame segmentation from a stream of monocular video by leveraging the 3D str

Zhong-Xiao Man, Yun-Jie Xia, Rosario Lo Franco

We study the validity of Landauer principle in the non-Markovian regime by means of collision models where the intracollisions inside the reservoir cause memory effects generating system-environment correlations. We adopt the system-environment correlations created during the dynamical process to assess the effect of non-Markovianity on the Landauer principl

Samuel Bladwell

In this paper, I present a simple method of obtaining spin-polarised current from a QPC with a large Rashba interaction. The origin of this spin polarisation is the adiabatic evolution of spin &#34;up&#34; of the first QPC sub-band, into spin &#34;down&#34; of the second QPC sub-band. Unique experimental signatures of this effect can be obtained using a magn

Xiangcun Meng, Jiao Li

Although type Ia supernovae (SNe Ia) are so important in many astrophysical fields, a debate on their progenitor model is still endless. Searching the surviving companion in a supernova remnant (SNR) may distinguish different progenitor models, since a companion still exists in the remnant for the single-degenerate (SD) model, but does not for the double deg

Yuan Li, Dun Zhao, Qingxuan Wang

We study the following nonlinear Hartree-type equation \begin{equation*} -Δu+V(x)u-a(\frac{1}{|x|^γ}\ast |u|^2)u=λu,~\text{in}~\mathbb{R}^N, \end{equation*} where $a>0$, $N\geq3$, $γ\in(0,2)$ and $V(x)$ is an external potential. We first study the asymptotic behavior of the ground state of equation for $V(x)\equiv1$, $a=1$ and $λ=0$ as $γ\nearrow2$. Then we

Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner

An accurate model of a patient&#39;s individual survival distribution can help determine the appropriate treatment for terminal patients. Unfortunately, risk scores (e.g., from Cox Proportional Hazard models) do not provide survival probabilities, single-time probability models (e.g., the Gail model, predicting 5 year probability) only provide for a single t

Sean Gomes, Andrew Hassell

We show that for almost all perturbations in a one-parameter family of KAM Hamiltonians on a smooth compact surface, for almost all KAM Lagrangian tori $Λ_ω$, we can find a semiclassical measure with positive mass on $Λ_ω$.

Faizal Hafiz, Akshya Swain, Eduardo MAM Mendes

The present study proposes a new structure selection approach for non-linear system identification based on Two-Dimensional particle swarms (2D-UPSO). The 2D learning framework essentially extends the learning dimension of the conventional particle swarms and explicitly incorporates the information about the cardinality, i.e., number of terms, into the searc

Dabin Zheng, Mu Yuan, Nian Li, Lei Hu

An involution over finite fields is a permutation polynomial whose inverse is itself. Owing to this property, involutions over finite fields have been widely used in applications such as cryptography and coding theory. As far as we know, there are not many involutions, and there isn&#39;t a general way to construct involutions over finite fields. This paper

Liang Jin, Lu Peng, Xiaojun Cui

We show that if $(\mathbb{T}^{2},g)$ is a class A Lorentzian 2-torus with timelike poles, then there exists a Lipschitz foliation by complete future-directed timelike geodesics with any pre-assigned asymptotic direction in the interior of the stable time cone. This is done by constructing certain $C^{1,1}$ solutions to the equation $g(\nabla u,\nabla u)=-1$

Nan Du, Zhikang Wang, Hanshen Xiao

Generalized Chinese Remainder Theorem (CRT) has been shown to be a powerful approach to solve the ambiguity resolution problem. However, with its close relationship to number theory, study in this area is mainly from a coding theory perspective under deterministic conditions. Nevertheless, it can be proved that even with the best deterministic condition know

Brittany Terese Fasy, Samuel Micka, David L. Millman, Anna Schenfisch

Shape recognition and classification is a problem with a wide variety of applications. Several recent works have demonstrated that topological descriptors can be used as summaries of shapes and utilized to compute distances. In this abstract, we explore the use of a finite number of Euler Characteristic Curves (ECC) to reconstruct plane graphs. We highlight

Satoru Hayami, Yukitoshi Motome

We report our numerical results for the effect of magnetic anisotropy on a Skyrmion crystal with a high topological number of two, which was recently discovered in an itinerant electron model [R. Ozawa, S. Hayami, and Y. Motome, Phys. Rev. Lett. 118, 147205 (2017)]. By performing numerical simulations based on the kernel polynomial method and the Langevin dy

Erdem Koyuncu, Hamid Jafarkhani

We consider ad-hoc networks consisting of $n$ wireless nodes that are located on the plane. Any two given nodes are called neighbors if they are located within a certain distance (communication range) from one another. A given node can be directly connected to any one of its neighbors and picks its connections according to a unique topology control algorithm

Mina Nazari, Min Xi, Mark Aronson, Mi K. Hong

Pan-microbial inactivation technologies that do not require high temperatures, reactive chemical compounds, or UV radiation could address gaps in current infection control strategies and provide efficient sterilization of biologics in the biotechnological industry. Here, we demonstrate that femtosecond (fs) laser irradiation of resonant gold nanoparticles (N

Moshe A. Milevsky

Who {\em values} life annuities more? Is it the healthy retiree who expects to live long and might become a centenarian, or is the unhealthy retiree with a short life expectancy more likely to appreciate the pooling of longevity risk? What if the unhealthy retiree is pooled with someone who is much healthier and thus forced to pay an implicit loading? To ans

Danil Annenkov

We present three projects concerned with applications of proof assistants in the area of programming language theory and mathematics. The first project is about a certified compilation technique for a domain-specific programming language for financial contracts (the CL language). The code in CL is translated into a simple expression language well-suited for

Dwaipayan Mukherjee, Shashi Ranjan Kumar

This paper presents a finite-time heterogeneous cyclic pursuit scheme that ensures consensus among agents modelled as integrators. It is shown that for the proposed sliding mode control, even when the gains corresponding to each agent are non-identical, consensus results within a finite-time provided all the gains are positive. An algorithm is presented to c

Xueping Zhao, Qi Wang

We present a linear, second order fully discrete numerical scheme on a staggered grid for a thermodynamically consistent hydrodynamic phase field model of binary compressible fluid flow mixtures derived from the generalized Onsager Principle. The hydrodynamic model not only possesses the variational structure, but also warrants the mass, linear momentum cons

Christoph Reisinger, Zhenru Wang

In this article, we propose an implicit finite difference scheme for a two-dimensional parabolic stochastic partial differential equation (SPDE) of Zakai type. The scheme is based on a Milstein approximation to the stochastic integral and an alternating direction implicit (ADI) discretisation of the elliptic term. We prove its mean-square stability and conve

Yoshiaki Nakada

We analyze the effects of energy and commodity prices on commodity output using a three-factor, two-good general equilibrium trade model with three factors: capital, labor, and imported energy. We derive a sufficient condition for each sign pattern of each relationship to hold, which no other studies have derived. We assume factor-intensity ranking is consta

Tao Sun, Hao Jiang, Lizhi Cheng, Wei Zhu

In this paper, we consider the convergence of an abstract inexact nonconvex and nonsmooth algorithm. We promise a pseudo sufficient descent condition and a pseudo relative error condition, which are both related to an auxiliary sequence, for the algorithm; and a continuity condition is assumed to hold. In fact, a lot of classical inexact nonconvex and nonsmo

Marco Avella-Medina, Francesca Parise, Michael T. Schaub, Santiago Segarra

As relational datasets modeled as graphs keep increasing in size and their data-acquisition is permeated by uncertainty, graph-based analysis techniques can become computationally and conceptually challenging. In particular, node centrality measures rely on the assumption that the graph is perfectly known -- a premise not necessarily fulfilled for large, unc

Wuchen Li, Penghang Yin, Stanley Osher

We propose a fast algorithm to approximate the optimal transport distance. The main idea is to add a Fisher information regularization into the dynamical setting of the problem, originated by Benamou and Brenier. The regularized problem is shown to be smooth and strictly convex, thus many classical fast algorithms are available. In this paper, we adopt Newto

Corentin Briat

Co-design conditions for the design of a jumping-rule and a sampled-data control law for impulsive and impulsive switched systems subject to aperiodic sampled-data measurements are provided. Semi-infinite discrete-time Lyapunov-Metzler conditions are first obtained. As these conditions are difficult to check and generalize to more complex systems, an equival

Kevin McCloskey, Ankur Taly, Federico Monti, Michael P. Brenner

Deep neural networks have achieved state of the art accuracy at classifying molecules with respect to whether they bind to specific protein targets. A key breakthrough would occur if these models could reveal the fragment pharmacophores that are causally involved in binding. Extracting chemical details of binding from the networks could potentially lead to s

Biplab Dey

The electroweak sector of the Standard Model contains three generations of charged leptons $\ell^-\in\{e^-,μ^-,τ^-\}$ as exact replicas of each other, except for their Yukawa couplings to the Higgs that determine their masses. The Yukawas, and thereby, the masses, are not predicted but are parameters in the theory. A basic tenet in the formalism, known as le

Jose Risomar Sousa

This paper presents formulae for the sum of the terms of a harmonic progression of order $k$ with integer parameters, $\mathrm{HP}_k(n)$, and for the partial sums of its two associated Fourier series, $C^z_{k}(a,b,n)$ and $S^z_{k}(a,b,n)$. $\mathrm{HP}_k(n)$ is built from the ground up, with a power series for $1/(aj+b)^k$ that is summed over $j$ using Faulh

Ali Shafahi, Mahyar Najibi, Zheng Xu, John Dickerson

Standard adversarial attacks change the predicted class label of a selected image by adding specially tailored small perturbations to its pixels. In contrast, a universal perturbation is an update that can be added to any image in a broad class of images, while still changing the predicted class label. We study the efficient generation of universal adversari

Matthew Norton, Valentyn Khokhlov, Stan Uryasev

Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR), also called the superquantile and quantile, are frequently used to characterize the tails of probability distribution&#39;s and are popular measures of risk. Buffered Probability of Exceedance (bPOE) is a recently introduced characterization of the tail which is the inverse of CVaR, much like the CDF

Markus Rausch, Stefan Lämmer, Martin Treiber

We propose a novel self-organized traffic management strategy for incidents in traffic-light-controlled road networks. During incidents, it regulates the inflow into already congested road segments by restricting or skipping green times. Simultaneously, the remaining green times are used for the yet free turning directions. In this way, drivers can utilize u

Spyridon Kakaroumpas, Sergei Treil

For an $A_p$ weight $w$ the norm of the Hilbert Transform in $L^p(w)$, $1<p<\infty$ is estimated by $[w]_{A_p}^{s}$, where $[w]_{A_p}$ is the $A_p$ characteristic of the weight $w$ and $s = \max(1,1/(p-1))$; as simple examples with power weights show, these estimates are sharp. A natural question to ask, is whether it is possible to improve the exponent $s$

Arash Tavakoli, Vitaly Levdik, Riashat Islam, Christopher M. Smith

We consider the generic approach of using an experience memory to help exploration by adapting a restart distribution. That is, given the capacity to reset the state with those corresponding to the agent&#39;s past observations, we help exploration by promoting faster state-space coverage via restarting the agent from a more diverse set of initial states, as

Richard T. Marriott, Sami Romdhani, Liming Chen

Generative Adversarial Networks (GANs) are able to learn mappings between simple, relatively low-dimensional, random distributions and points on the manifold of realistic images in image-space. The semantics of this mapping, however, are typically entangled such that meaningful image properties cannot be controlled independently of one another. Conditional G

Maximilian Beikirch, Simon Cramer, Martin Frank, Philipp Otte

We study the qualitative and quantitative appearance of stylized facts in several agent-based computational economic market (ABCEM) models. We perform our simulations with the SABCEMM (Simulator for Agent-Based Computational Economic Market Models) tool recently introduced by the authors (Trimborn et al. 2019). Furthermore, we present novel ABCEM models crea

Ben Moews, J. Michael Herrmann, Gbenga Ibikunle

Trend change prediction in complex systems with a large number of noisy time series is a problem with many applications for real-world phenomena, with stock markets as a notoriously difficult to predict example of such systems. We approach predictions of directional trend changes via complex lagged correlations between them, excluding any information about t

Wang Yifan, Shihao Wu, Hui Huang, Daniel Cohen-Or

We present a detail-driven deep neural network for point set upsampling. A high-resolution point set is essential for point-based rendering and surface reconstruction. Inspired by the recent success of neural image super-resolution techniques, we progressively train a cascade of patch-based upsampling networks on different levels of detail end-to-end. We pro

Wen-Sheng Xu, Christopher N. Lam, Jan-Michael Y. Carrillo, Bobby G. Sumpter

The classical rheological theories of entangled polymeric liquids are built upon two pillars: Gaussian statistics of entanglement strands and the assumption that the stress arises exclusively from the change of intramolecular configuration entropy. We show that these two hypotheses are not supported by molecular dynamics simulations of polymer melts. Specifi

Raviteja Vemulapalli, Aseem Agarwala

Most of the existing work on automatic facial expression analysis focuses on discrete emotion recognition, or facial action unit detection. However, facial expressions do not always fall neatly into pre-defined semantic categories. Also, the similarity between expressions measured in the action unit space need not correspond to how humans perceive expression

Tim Brooks, Jonathan T. Barron

We present a technique for synthesizing a motion blurred image from a pair of unblurred images captured in succession. To build this system we motivate and design a differentiable &#34;line prediction&#34; layer to be used as part of a neural network architecture, with which we can learn a system to regress from image pairs to motion blurred images that span

Tian Xie, Guan-Hua Tu, Bangjie Yin, Chi-Yu Li

Since 2016, all of four major U.S. operators have rolled out nationwide Wi-Fi calling services. They are projected to surpass VoLTE (Voice over LTE) and other VoIP services in terms of mobile IP voice usage minutes in 2018. They enable mobile users to place cellular calls over Wi-Fi networks based on the 3GPP IMS (IP Multimedia Subsystem) technology. Compare

Henry Bendekgey

We present a method for encoding game logs as numeric features in the card game Dominion. We then run the manifold learning algorithm t-SNE on these encodings to visualize the landscape of player strategies. By quantifying game states as the relative prevalence of cards in a player&#39;s deck, we create visualizations that capture qualitative differences in

A. Bravo, S. Encinas, B. Pascual-Escudero

We study contact loci sets of arcs and the behavior of Hironaka&#39;s order function defined in constructive Resolution of singularities. We show that this function can be read in terms of the irreducible components of the contact loci sets at a singular point of an algebraic variety.

Leonardo A. Cano G, Pedro H. Zambrano

We remark that forcing on fiber bundles of structures of first order languages is not a compatible semantics with the pullback (of fiber bundles) and we describe a semantics which behaves well with respect to it. This new semantics uses parallel transport and allows to introduce two different types of extensions for the formulae: vertical and horizontal exte

Greg Olmschenk, Zhigang Zhu, Hao Tang

In this work, we generalize semi-supervised generative adversarial networks (GANs) from classification problems to regression problems. In the last few years, the importance of improving the training of neural networks using semi-supervised training has been demonstrated for classification problems. We present a novel loss function, called feature contrastin

Claudio Bellani, Damiano Brigo, Alex Done, Eyal Neuman

We compare optimal static and dynamic solutions in trade execution. An optimal trade execution problem is considered where a trader is looking at a short-term price predictive signal while trading. When the trader creates an instantaneous market impact, it is shown that transaction costs of optimal adaptive strategies are substantially lower than the corresp

Imre Bartos, Kyung-hwan Lee, Alessandra Corsi, Zsuzsa Marka

The multi-messenger observation of gamma-ray burst (GRB)\,170817A from the nearby binary neutron-star merger GW170817 demonstrated that low-energy $γ$-ray emission can be observed at relatively large angles from GRB jet axes. If such structured emission is typical, then the currently known sample of short GRBs with no distance measurements may contain multip

Sergey S. Sarkisov, Ilya Timofeyev, Robert Azencott

In this paper we develop and test algorithmic techniques to estimate genotypes fitnesses by analysis of observed daily frequency data monitoring the long-term evolution of bacterial populations. In particular, we develop a non-linear least squares approach to estimate selective advantages of emerging new mutant strains in locked-box stochastic models describ

Raj Prince

In this work, I have presented a multi-frequency variability and correlation study of the blazar Ton 599, which was observed first time in flaring state at the end of 2017. Data from \textit{Fermi}-LAT, Swift-XRT/UVOT, Steward Observatory, and OVRO (15 GHz) is used, and it is found that the source is more variable in $γ$-ray and optical/UV than X-ray and rad

Ariel Werle, Roberto Cid Fernandes, Natalia Vale Asari, Gustavo Bruzual

We combine data from the Sloan Digital Sky Survey and the Galaxy Evolution Explorer to simultaneously analyze optical spectra and ultraviolet photometry of 231643 galaxies with the STARLIGHT spectral synthesis code using state-of-the-art stellar population models. We present a new method to estimate GALEX photometry in the SDSS spectroscopic aperture, which

Juntang Zhuang, Junlin Yang, Lin Gu, Nicha Dvornek

In this paper, we present ShelfNet, a novel architecture for accurate fast semantic segmentation. Different from the single encoder-decoder structure, ShelfNet has multiple encoder-decoder branch pairs with skip connections at each spatial level, which looks like a shelf with multiple columns. The shelf-shaped structure can be viewed as an ensemble of multip

Yilun Zhang, Hyun Soo Park

This paper presents a semi-supervised learning framework to train a keypoint detector using multiview image streams given the limited labeled data (typically $<$4\%). We leverage the complementary relationship between multiview geometry and visual tracking to provide three types of supervisionary signals to utilize the unlabeled data: (1) keypoint detection

Jinlong Lei, Uday V. Shanbhag

This paper considers a stochastic Nash game in which each player minimizes an expectation valued composite objective. We make the following contributions. (I) Under suitable monotonicity assumptions on the concatenated gradient map, we derive optimal rate statements and oracle complexity bounds for the proposed variable sample-size proximal stochastic gradie

D. S. Akerib, S. Alsum, H. M. Araújo, X. Bai

The scattering of dark matter (DM) particles with sub-GeV masses off nuclei is difficult to detect using liquid xenon-based DM search instruments because the energy transfer during nuclear recoils is smaller than the typical detector threshold. However, the tree-level DM-nucleus scattering diagram can be accompanied by simultaneous emission of a Bremsstrahlu

Audace A. V. Dossou-Olory, Stephan Wagner

A subset of leaves of a rooted tree induces a new tree in a natural way. The density of a tree $D$ inside a larger tree $T$ is the proportion of such leaf-induced subtrees in $T$ that are isomorphic to $D$ among all those with the same number of leaves as $D$. The inducibility of $D$ measures how large this density can be as the size of $T$ tends to infinity

M. P. Garcia del Moral, C. Las Heras, P. Leon, J. M. Pena

We describe a compactified Supermembrane, or M2-brane, with 2-form fluxes generated by constant three-forms that are turned on a 2-torus of the target space $M_9\times T^2$. We compare this theory with the one describing a $11D$ M2-brane formulated on $M_9\times T^2$ target space subject to an irreducible wrapping condition. We show that the flux generated b

Sanjaye Ramgoolam, Mark C. Wilson, Ali Zahabi

The large N generating functions for the counting of chiral operators in $\mathcal{N}=1$, four-dimensional quiver gauge theories have previously been obtained in terms of the weighted adjacency matrix of the quiver diagram. We introduce the methods of multi-variate asymptotic analysis to study this counting in the limit of large charges. We describe a Hagedo

Yousheng Shi

In this paper, we study special cycles on the basic locus of certain unitary Shimura varieties over the ramified primes and their local analogues on the corresponding Rapoport-Zink spaces. We study the support and compute the dimension of these cycles.

Andrea Legramandi, Niall T. Macpherson

We complete the classification of Mink$_4$ solutions preserving $\mathcal{N}=2$ supersymmetry and SU(2) R-symmetry parameterised by a round $S^2$ factor. We consider eleven-dimensional supergravity and relax the assumptions of earlier works in type II theories. We show that, using chains of dualities, all solutions of this type can be generated from one of t

Diego Pérez Daroca, Pablo Roura-Bas, Armando A. Aligia

The zero-bias anomaly at low temperatures, originated by the Kondo effect when an electric current flows through a system formed by a spin-$1/2$ quantum dot and two metallic contacts is theoretically investigated. In particular, we compare the width of this anomaly $2T_{\rm NE}$ with that of the Kondo resonance in the spectral density of states $2T_{K}^ρ$, o

Tom Seccull, Wesley C. Fraser, Thomas H. Puzia, Alan Fitzsimmons

It has been suggested that centaurs may lose their red surfaces and become bluer due to the onset of cometary activity, but the way in which cometary outbursts affect the surface composition and albedo of active centaurs is poorly understood. We obtained consistent visual-near-infrared (VNIR) reflectance spectra of the sporadically active centaur 174P/Echecl

Berk Gulmezoglu, Andreas Zankl, M. Caner Tol, Saad Islam

Over the past years, literature has shown that attacks exploiting the microarchitecture of modern processors pose a serious threat to the privacy of mobile phone users. This is because applications leave distinct footprints in the processor, which can be used by malware to infer user activities. In this work, we show that these inference attacks are consider

Andrew J. Worthen, Shehab Alzobaidi, Vu Tran, Muhammad Iqbal

Whereas many studies have examined stabilization of emulsions and foams in low salinity aqueous phases with nanoparticles (NPs) with and without added surfactants, interest has grown recently in much higher salinities relevant to subsurface oil and gas applications. It is shown for the first time that NPs grafted with well-defined low molecular weight ligand

Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi, Dale Schuurmans

Entropy regularization is commonly used to improve policy optimization in reinforcement learning. It is believed to help with \emph{exploration} by encouraging the selection of more stochastic policies. In this work, we analyze this claim using new visualizations of the optimization landscape based on randomly perturbing the loss function. We first show that

Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic

Conditional GANs are at the forefront of natural image synthesis. The main drawback of such models is the necessity for labeled data. In this work we exploit two popular unsupervised learning techniques, adversarial training and self-supervision, and take a step towards bridging the gap between conditional and unconditional GANs. In particular, we allow the

Wentao Yuan, David Held, Christoph Mertz, Martial Hebert

3D point cloud is an efficient and flexible representation of 3D structures. Recently, neural networks operating on point clouds have shown superior performance on 3D understanding tasks such as shape classification and part segmentation. However, performance on such tasks is evaluated on complete shapes aligned in a canonical frame, while real world 3D data

Zhourong Chen, Yang Li, Samy Bengio, Si Si

The concept of conditional computation for deep nets has been proposed previously to improve model performance by selectively using only parts of the model conditioned on the sample it is processing. In this paper, we investigate input-dependent dynamic filter selection in deep convolutional neural networks (CNNs). The problem is interesting because the idea

Charlotte Chan, Alexander B. Ivanov

We initiate the study of affine Deligne-Lusztig varieties with arbitrarily deep level structure for general reductive groups over local fields. We prove that for GLn and its inner forms, Lusztig&#39;s semi-infinite Deligne-Lusztig construction is isomorphic to an affine Deligne-Lusztig variety at infinite level. We prove that their homology groups give geome

Erik Plauschinn

This review provides an introduction to non-geometric backgrounds in string theory. Starting from a discussion of T-duality, geometric and non-geometric torus-fibrations are reviewed, generalised geometry and its relation to non-geometric backgrounds are explained and compactifications of string theory with geometric and non-geometric fluxes are discussed. F