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Semi-Supervised Approaches to Efficient Evaluation of Model Prediction Performance
In many modern machine learning applications, the outcome is expensive or time-consuming to collect while the predictor information is easy to obtain. Semi-supervised learning (SSL) aims at utilizing large amounts of `unlabeled' data along with small amounts of `labeled' data to improve the efficiency of a classical ...
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Linearization of the box-ball system: an elementary approach
Kuniba, Okado, Takagi and Yamada have found that the time-evolution of the Takahashi-Satsuma box-ball system can be linearized by considering rigged configurations associated with states of the box-ball system. We introduce a simple way to understand the rigged configuration of $\mathfrak{sl}_2$-type, and give an ele...
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Controlling Sources of Inaccuracy in Stochastic Kriging
Scientists and engineers commonly use simulation models to study real systems for which actual experimentation is costly, difficult, or impossible. Many simulations are stochastic in the sense that repeated runs with the same input configuration will result in different outputs. For expensive or time-consuming simula...
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Implications of Decentralized Q-learning Resource Allocation in Wireless Networks
Reinforcement Learning is gaining attention by the wireless networking community due to its potential to learn good-performing configurations only from the observed results. In this work we propose a stateless variation of Q-learning, which we apply to exploit spatial reuse in a wireless network. In particular, we al...
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Exponential Ergodicity of the Bouncy Particle Sampler
Non-reversible Markov chain Monte Carlo schemes based on piecewise deterministic Markov processes have been recently introduced in applied probability, automatic control, physics and statistics. Although these algorithms demonstrate experimentally good performance and are accordingly increasingly used in a wide range...
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Analysis and X-ray tomography
These are lecture notes for the course "MATS4300 Analysis and X-ray tomography" given at the University of Jyväskylä in Fall 2017. The course is a broad overview of various tools in analysis that can be used to study X-ray tomography. The focus is on tools and ideas, not so much on technical details and minimal assum...
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Spatially Transformed Adversarial Examples
Recent studies show that widely used deep neural networks (DNNs) are vulnerable to carefully crafted adversarial examples. Many advanced algorithms have been proposed to generate adversarial examples by leveraging the $\mathcal{L}_p$ distance for penalizing perturbations. Researchers have explored different defense m...
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Arrow Categories of Monoidal Model Categories
We prove that the arrow category of a monoidal model category, equipped with the pushout product monoidal structure and the projective model structure, is a monoidal model category. This answers a question posed by Mark Hovey, and has the important consequence that it allows for the consideration of a monoidal produc...
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Differential-operator representations of Weyl group and singular vectors
Given a suitable ordering of the positive root system associated with a semisimple Lie algebra, there exists a natural correspondence between Verma modules and related polynomial algebras. With this, the Lie algebra action on a Verma module can be interpreted as a differential operator action on polynomials, and thus...
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Faithful Semitoric Systems
This paper consists of two parts. The first provides a review of the basic properties of integrable and almost-toric systems, with a particular emphasis on the integral affine structure associated to an integrable system. The second part introduces faithful semitoric systems, a generalization of semitoric systems (in...
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HoloScope: Topology-and-Spike Aware Fraud Detection
As online fraudsters invest more resources, including purchasing large pools of fake user accounts and dedicated IPs, fraudulent attacks become less obvious and their detection becomes increasingly challenging. Existing approaches such as average degree maximization suffer from the bias of including more nodes than n...
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On Approximation Guarantees for Greedy Low Rank Optimization
We provide new approximation guarantees for greedy low rank matrix estimation under standard assumptions of restricted strong convexity and smoothness. Our novel analysis also uncovers previously unknown connections between the low rank estimation and combinatorial optimization, so much so that our bounds are reminis...
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Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery
The topology of a power grid affects its dynamic operation and settlement in the electricity market. Real-time topology identification can enable faster control action following an emergency scenario like failure of a line. This article discusses a graphical model framework for topology estimation in bulk power grids...
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Wasserstein Introspective Neural Networks
We present Wasserstein introspective neural networks (WINN) that are both a generator and a discriminator within a single model. WINN provides a significant improvement over the recent introspective neural networks (INN) method by enhancing INN's generative modeling capability. WINN has three interesting properties: ...
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Convexity of level lines of Martin functions and applications
Let $\Omega$ be an unbounded domain in $\mathbb{R}\times\mathbb{R}^{d}.$ A positive harmonic function $u$ on $\Omega$ that vanishes on the boundary of $\Omega$ is called a Martin function. In this note, we show that, when $\Omega$ is convex, the superlevel sets of a Martin function are also convex. As a consequence w...
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New skein invariants of links
We introduce new skein invariants of links based on a procedure where we first apply the skein relation only to crossings of distinct components, so as to produce collections of unlinked knots. We then evaluate the resulting knots using a given invariant. A skein invariant can be computed on each link solely by the u...
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HSTREAM: A directive-based language extension for heterogeneous stream computing
Big data streaming applications require utilization of heterogeneous parallel computing systems, which may comprise multiple multi-core CPUs and many-core accelerating devices such as NVIDIA GPUs and Intel Xeon Phis. Programming such systems require advanced knowledge of several hardware architectures and device-spec...
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Faddeev-Jackiw approach of the noncommutative spacetime Podolsky electromagnetic theory
The interest in higher derivatives field theories has its origin mainly in their influence concerning the renormalization properties of physical models and to remove ultraviolet divergences. The noncommutative Podolsky theory is a constrained system that cannot by directly quantized by the canonical way. In this work...
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Spin Transport and Accumulation in 2D Weyl Fermion System
In this work, we study the spin Hall effect and Rashba-Edelstein effect of a 2D Weyl fermion system in the clean limit using the Kubo formalism. Spin transport is solely due to the spin-torque current in this strongly spin-orbit coupled (SOC) system, and chiral spin-flip scattering off non-SOC scalar impurities, with...
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Model-Based Control Using Koopman Operators
This paper explores the application of Koopman operator theory to the control of robotic systems. The operator is introduced as a method to generate data-driven models that have utility for model-based control methods. We then motivate the use of the Koopman operator towards augmenting model-based control. Specifical...
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Turbulence Hierarchy in a Random Fibre Laser
Turbulence is a challenging feature common to a wide range of complex phenomena. Random fibre lasers are a special class of lasers in which the feedback arises from multiple scattering in a one-dimensional disordered cavity-less medium. Here, we report on statistical signatures of turbulence in the distribution of in...
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Optimal Rates for Learning with Nyström Stochastic Gradient Methods
In the setting of nonparametric regression, we propose and study a combination of stochastic gradient methods with Nyström subsampling, allowing multiple passes over the data and mini-batches. Generalization error bounds for the studied algorithm are provided. Particularly, optimal learning rates are derived consider...
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Run Procrustes, Run! On the convergence of accelerated Procrustes Flow
In this work, we present theoretical results on the convergence of non-convex accelerated gradient descent in matrix factorization models. The technique is applied to matrix sensing problems with squared loss, for the estimation of a rank $r$ optimal solution $X^\star \in \mathbb{R}^{n \times n}$. We show that the ac...
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A note on the bijectivity of antipode of a Hopf algebra and its applications
Certain sufficient homological and ring-theoretical conditions are given for a Hopf algebra to have bijective antipode with applications to noetherian Hopf algebras regarding their homological behaviors.
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Perfect Edge Domination: Hard and Solvable Cases
Let $G$ be an undirected graph. An edge of $G$ dominates itself and all edges adjacent to it. A subset $E'$ of edges of $G$ is an edge dominating set of $G$, if every edge of the graph is dominated by some edge of $E'$. We say that $E'$ is a perfect edge dominating set of $G$, if every edge not in $E'$ is dominated b...
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On the presentation of Hecke-Hopf algebras for non-simply-laced type
Hecke-Hopf algebras were defined by A. Berenstein and D. Kazhdan. We give an explicit presentation of an Hecke-Hopf algebra when the parameter $m_{ij},$ associated to any two distinct vertices $i$ and $j$ in the presentation of a Coxeter group, equals $4,$ $5$ or $6$. As an application, we give a proof of a conjectur...
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ILP-based Alleviation of Dense Meander Segments with Prioritized Shifting and Progressive Fixing in PCB Routing
Length-matching is an important technique to bal- ance delays of bus signals in high-performance PCB routing. Existing routers, however, may generate very dense meander segments. Signals propagating along these meander segments exhibit a speedup effect due to crosstalk between the segments of the same wire, thus lead...
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Membrane Trafficking in the Yeast Saccharomyces cerevisiae Model
The yeast Saccharomyces cerevisiae is one of the best characterized eukaryotic models. The secretory pathway was the first trafficking pathway clearly understood mainly thanks to the work done in the laboratory of Randy Schekman in the 1980s. They have isolated yeast sec mutants unable to secrete an extracellular enz...
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Synthesizing Programs for Images using Reinforced Adversarial Learning
Advances in deep generative networks have led to impressive results in recent years. Nevertheless, such models can often waste their capacity on the minutiae of datasets, presumably due to weak inductive biases in their decoders. This is where graphics engines may come in handy since they abstract away low-level deta...
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A Correspondence Between Random Neural Networks and Statistical Field Theory
A number of recent papers have provided evidence that practical design questions about neural networks may be tackled theoretically by studying the behavior of random networks. However, until now the tools available for analyzing random neural networks have been relatively ad-hoc. In this work, we show that the distr...
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The nature of the progenitor of the M31 North-western stream: globular clusters as milestones of its orbit
We examine the nature, possible orbits and physical properties of the progenitor of the North-western stellar stream (NWS) in the halo of the Andromeda galaxy (M31). The progenitor is assumed to be an accreting dwarf galaxy with globular clusters (GCs). It is, in general, difficult to determine the progenitor's orbit...
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On codimension two flats in Fermat-type arrangements
In the present note we study certain arrangements of codimension $2$ flats in projective spaces, we call them "Fermat arrangements". We describe algebraic properties of their defining ideals. In particular, we show that they provide counterexamples to an expected containment relation between ordinary and symbolic pow...
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Invariant Causal Prediction for Sequential Data
We investigate the problem of inferring the causal predictors of a response $Y$ from a set of $d$ explanatory variables $(X^1,\dots,X^d)$. Classical ordinary least squares regression includes all predictors that reduce the variance of $Y$. Using only the causal predictors instead leads to models that have the advanta...
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Smoothing with Couplings of Conditional Particle Filters
In state space models, smoothing refers to the task of estimating a latent stochastic process given noisy measurements related to the process. We propose an unbiased estimator of smoothing expectations. The lack-of-bias property has methodological benefits: independent estimators can be generated in parallel, and con...
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Formation of High Pressure Gradients at the Free Surface of a Liquid Dielectric in a Tangential Electric Field
Nonlinear dynamics of the free surface of an ideal incompressible non-conducting fluid with high dielectric constant subjected by strong horizontal electric field is simulated on the base of the method of conformal transformations. It is demonstrated that interaction of counter-propagating waves leads to formation of...
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Subsampling for Ridge Regression via Regularized Volume Sampling
Given $n$ vectors $\mathbf{x}_i\in \mathbb{R}^d$, we want to fit a linear regression model for noisy labels $y_i\in\mathbb{R}$. The ridge estimator is a classical solution to this problem. However, when labels are expensive, we are forced to select only a small subset of vectors $\mathbf{x}_i$ for which we obtain the...
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Ab initio calculations of the concentration dependent band gap reduction in dilute nitrides
While being of persistent interest for the integration of lattice-matched laser devices with silicon circuits, the electronic structure of dilute nitride III/V-semiconductors has presented a challenge to ab initio computational approaches. The root of this lies in the strong distortion N atoms exert on most host mate...
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Outliers and related problems
We define outliers as a set of observations which contradicts the proposed mathematical (statistical) model and we discuss the frequently observed types of the outliers. Further we explore what changes in the model have to be made in order to avoid the occurance of the outliers. We observe that some variants of the o...
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On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions
We propose a DC proximal Newton algorithm for solving nonconvex regularized sparse learning problems in high dimensions. Our proposed algorithm integrates the proximal Newton algorithm with multi-stage convex relaxation based on the difference of convex (DC) programming, and enjoys both strong computational and stati...
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Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
In reinforcement learning, agents learn by performing actions and observing their outcomes. Sometimes, it is desirable for a human operator to \textit{interrupt} an agent in order to prevent dangerous situations from happening. Yet, as part of their learning process, agents may link these interruptions, that impact t...
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Heuristic Optimization for Automated Distribution System Planning in Network Integration Studies
Network integration studies try to assess the impact of future developments, such as the increase of Renewable Energy Sources or the introduction of Smart Grid Technologies, on large-scale network areas. Goals can be to support strategic alignment in the regulatory framework or to adapt the network planning principle...
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The Sizes and Depletions of the Dust and Gas Cavities in the Transitional Disk J160421.7-213028
We report ALMA Cycle 2 observations of 230 GHz (1.3 mm) dust continuum emission, and $^{12}$CO, $^{13}$CO, and C$^{18}$O J = 2-1 line emission, from the Upper Scorpius transitional disk [PZ99] J160421.7-213028, with an angular resolution of ~0".25 (35 AU). Armed with these data and existing H-band scattered light obs...
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Demystifying AlphaGo Zero as AlphaGo GAN
The astonishing success of AlphaGo Zero\cite{Silver_AlphaGo} invokes a worldwide discussion of the future of our human society with a mixed mood of hope, anxiousness, excitement and fear. We try to dymystify AlphaGo Zero by a qualitative analysis to indicate that AlphaGo Zero can be understood as a specially structur...
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Effects of pressure and magnetic field on the re-entrant superconductor Eu(Fe$_{0.93}$Rh$_{0.07}$)$_2$As$_2$
Electron-doped Eu(Fe$_{0.93}$Rh$_{0.07}$)$_2$As$_2$ has been systematically studied by high pressure investigations of the magnetic and electrical transport properties, in order to unravel the complex interplay of superconductivity and magnetism. The compound reveals an exceedingly broad re-entrant transition to the ...
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Commissioning and Operation
Chapter 16 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary Design Report. The Large Hadron Collider (LHC) is one of the largest scientific instruments ever built. Since opening up a new energy frontier for exploration in 2010, it has gathered a global user community of about 7,000 scientists working i...
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Only in the standard representation the Dirac theory is a quantum theory of a single fermion
It is shown that the relativistic quantum mechanics of a single fermion can be developed only on the basis of the standard representation of the Dirac bispinor. As in the nonrelativistic quantum mechanics, the arbitrariness in defining the bispinor, as a four-component wave function, is restricted by its multiplicati...
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Stable absorbing boundary conditions for molecular dynamics in general domains
A new type of absorbing boundary conditions for molecular dynamics simulations are presented. The exact boundary conditions for crystalline solids with harmonic approximation are expressed as a dynamic Dirichlet- to-Neumann (DtN) map. It connects the displacement of the atoms at the boundary to the traction on these ...
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Algebraic operads up to homotopy
This paper deals with the homotopy theory of differential graded operads. We endow the Koszul dual category of curved conilpotent cooperads, where the notion of quasi-isomorphism barely makes sense, with a model category structure Quillen equivalent to that of operads. This allows us to describe the homotopy properti...
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Nonlinear Kalman Filtering with Divergence Minimization
We consider the nonlinear Kalman filtering problem using Kullback-Leibler (KL) and $\alpha$-divergence measures as optimization criteria. Unlike linear Kalman filters, nonlinear Kalman filters do not have closed form Gaussian posteriors because of a lack of conjugacy due to the nonlinearity in the likelihood. In this...
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On Chern number inequality in dimension 3
We prove that if $X---> X^+$ is a threefold terminal flip, then $c_1(X).c_2(X)\leq c_1(X^+).c_2(X^+)$ where $c_1(X)$ and $c_2(X)$ denote the Chern classes. This gives the affirmative answer to a Question by Xie \cite{Xie2}. We obtain the similar but weaker result in the case of divisorial contraction to curves.
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Enhancing SDO/HMI images using deep learning
The Helioseismic and Magnetic Imager (HMI) provides continuum images and magnetograms with a cadence better than one per minute. It has been continuously observing the Sun 24 hours a day for the past 7 years. The obvious trade-off between full disk observations and spatial resolution makes HMI not enough to analyze t...
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Suppression of the superconductivity in ultrathin amorphous Mo$_{78}$Ge$_{22}$ thin films observed by STM
In contact with a superconductor, a normal metal modifies its properties due to Andreev reflection. In the current work, the local density of states (LDOS) of superconductor - normal metal Mo$_{78}$Ge$_{22}$ - Au bilayers are studied by means of STM applied from the Au side. Three bilayers have been prepared on silic...
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Functional data analysis in the Banach space of continuous functions
Functional data analysis is typically conducted within the $L^2$-Hilbert space framework. There is by now a fully developed statistical toolbox allowing for the principled application of the functional data machinery to real-world problems, often based on dimension reduction techniques such as functional principal co...
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Bayesian Recurrent Neural Networks
In this work we explore a straightforward variational Bayes scheme for Recurrent Neural Networks. Firstly, we show that a simple adaptation of truncated backpropagation through time can yield good quality uncertainty estimates and superior regularisation at only a small extra computational cost during training, also ...
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Cross-Correlation Redshift Calibration Without Spectroscopic Calibration Samples in DES Science Verification Data
Galaxy cross-correlations with high-fidelity redshift samples hold the potential to precisely calibrate systematic photometric redshift uncertainties arising from the unavailability of complete and representative training and validation samples of galaxies. However, application of this technique in the Dark Energy Su...
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Completely bounded bimodule maps and spectral synthesis
We initiate the study of the completely bounded multipliers of the Haagerup tensor product $A(G)\otimes_{\rm h} A(G)$ of two copies of the Fourier algebra $A(G)$ of a locally compact group $G$. If $E$ is a closed subset of $G$ we let $E^{\sharp} = \{(s,t) : st\in E\}$ and show that if $E^{\sharp}$ is a set of spectra...
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Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation
Black-box risk scoring models permeate our lives, yet are typically proprietary or opaque. We propose Distill-and-Compare, a model distillation and comparison approach to audit such models. To gain insight into black-box models, we treat them as teachers, training transparent student models to mimic the risk scores a...
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An influence-based fast preceding questionnaire model for elderly assessments
To improve the efficiency of elderly assessments, an influence-based fast preceding questionnaire model (FPQM) is proposed. Compared with traditional assessments, the FPQM optimizes questionnaires by reordering their attributes. The values of low-ranking attributes can be predicted by the values of the high-ranking a...
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A GPU Accelerated Discontinuous Galerkin Incompressible Flow Solver
We present a GPU-accelerated version of a high-order discontinuous Galerkin discretization of the unsteady incompressible Navier-Stokes equations. The equations are discretized in time using a semi-implicit scheme with explicit treatment of the nonlinear term and implicit treatment of the split Stokes operators. The ...
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The Auger Engineering Radio Array and multi-hybrid cosmic ray detection (TAUP 2015)
The Auger Engineering Radio Array (AERA) aims at the detection of air showers induced by high-energy cosmic rays. As an extension of the Pierre Auger Observatory, it measures complementary information to the particle detectors, fluorescence telescopes and to the muon scintillators of the Auger Muons and Infill for th...
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Historic Emergence of Diversity in Painting: Heterogeneity in Chromatic Distance in Images and Characterization of Massive Painting Data Set
Painting is an art form that has long functioned as a major channel for the creative expression and communication of humans, its evolution taking place under an interplay with the science, technology, and social environments of the times. Therefore, understanding the process based on comprehensive data could shed lig...
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Cage Size and Jump Precursors in Glass-Forming Liquids: Experiment and Simulations
Glassy dynamics is intermittent, as particles suddenly jump out of the cage formed by their neighbours, and heterogeneous, as these jumps are not uniformly distributed across the system. Relating these features of the dynamics to the diverse local environments explored by the particles is essential to rationalize the...
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A Comprehensive Survey on Bengali Phoneme Recognition
Hidden Markov model based various phoneme recognition methods for Bengali language is reviewed. Automatic phoneme recognition for Bengali language using multilayer neural network is reviewed. Usefulness of multilayer neural network over single layer neural network is discussed. Bangla phonetic feature table construct...
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Factorization of arithmetic automorphic periods
In this paper, we prove that the arithmetic automorphic periods for $GL_{n}$ over a CM field factorize through the infinite places. This generalizes a conjecture of Shimura in 1983, and is predicted by the Langlands correspondence between automorphic representations and motives.
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Multielectronic processes in particle and antiparticle collisions with rare gases
In this chapter we analyze the multiple ionization by impact of |Z|=1 projectiles: electrons, positrons, protons and antiprotons. Differences and similarities among the cross sections by these four projectiles allows us to have an insight on the physics involved. Mass and charge effects, energy thresholds, and relati...
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A Floating Cylinder on An Unbounded Bath
In this paper, we reconsider a circular cylinder horizontally floating on an unbounded reservoir in a gravitational field directed downwards, which was studied by Bhatnargar and Finn in 2006. We follow their approach but with some modifications. We establish the relation between the total energy relative to the undis...
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Switching between Limit Cycles in a Model of Running Using Exponentially Stabilizing Discrete Control Lyapunov Function
This paper considers the problem of switching between two periodic motions, also known as limit cycles, to create agile running motions. For each limit cycle, we use a control Lyapunov function to estimate the region of attraction at the apex of the flight phase. We switch controllers at the apex, only if the current...
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Locally Private Bayesian Inference for Count Models
As more aspects of social interaction are digitally recorded, there is a growing need to develop privacy-preserving data analysis methods. Social scientists will be more likely to adopt these methods if doing so entails minimal change to their current methodology. Toward that end, we present a general and modular met...
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Carrier Diffusion in Thin-Film CH3NH3PbI3 Perovskite Measured using Four-Wave Mixing
We report the application of femtosecond four-wave mixing (FWM) to the study of carrier transport in solution-processed CH3NH3PbI3. The diffusion coefficient was extracted through direct detection of the lateral diffusion of carriers utilizing the transient grating technique, coupled with simultaneous measurement of ...
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On effective Birkhoff's ergodic theorem for computable actions of amenable groups
We introduce computable actions of computable groups and prove the following versions of effective Birkhoff's ergodic theorem. Let $\Gamma$ be a computable amenable group, then there always exists a canonically computable tempered two-sided F{\o}lner sequence $(F_n)_{n \geq 1}$ in $\Gamma$. For a computable, measure-...
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Gender Differences in Participation and Reward on Stack Overflow
Programming is a valuable skill in the labor market, making the underrepresentation of women in computing an increasingly important issue. Online question and answer platforms serve a dual purpose in this field: they form a body of knowledge useful as a reference and learning tool, and they provide opportunities for ...
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Invariant surface area functionals and singular Yamabe problem in 3-dimensional CR geometry
We express two CR invariant surface area elements in terms of quantities in pseudohermitian geometry. We deduce the Euler-Lagrange equations of the associated energy functionals. Many solutions are given and discussed. In relation to the singular CR Yamabe problem, we show that one of the energy functionals appears a...
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Dynamic dipole polarizabilities of heteronuclear alkali dimers: optical response, trapping and control of ultracold molecules
In this article we address the general approach for calculating dynamical dipole polarizabilities of small quantum systems, based on a sum-over-states formula involving in principle the entire energy spectrum of the system. We complement this method by a few-parameter model involving a limited number of effective tra...
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Minor-free graphs have light spanners
We show that every $H$-minor-free graph has a light $(1+\epsilon)$-spanner, resolving an open problem of Grigni and Sissokho and proving a conjecture of Grigni and Hung. Our lightness bound is \[O\left(\frac{\sigma_H}{\epsilon^3}\log \frac{1}{\epsilon}\right)\] where $\sigma_H = |V(H)|\sqrt{\log |V(H)|}$ is the spars...
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Adversarial Generation of Natural Language
Generative Adversarial Networks (GANs) have gathered a lot of attention from the computer vision community, yielding impressive results for image generation. Advances in the adversarial generation of natural language from noise however are not commensurate with the progress made in generating images, and still lag fa...
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Likely Transiting Exocomets Detected by Kepler
We present the first good evidence for exocomet transits of a host star in continuum light in data from the Kepler mission. The Kepler star in question, KIC 3542116, is of spectral type F2V and is quite bright at K_p = 10. The transits have a distinct asymmetric shape with a steeper ingress and slower egress that can...
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Origins of bond and spin order in rare-earth nickelate bulk and heterostructures
We analyze the charge- and spin response functions of rare-earth nickelates RNiO3 and their heterostructures using random-phase approximation in a two-band Hubbard model. The inter-orbital charge fluctuation is found to be the driving mechanism for the rock-salt type bond order in bulk RNiO3, and good agreement of th...
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Canonical Truth
We introduce and study a notion of canonical set theoretical truth, which means truth in a `canonical model', i.e. a transitive class model that is uniquely characterized by some $\in$-formula. We show that this notion of truth is `informative', i.e. there are statements that hold in all canonical models but do not f...
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AACT: Application-Aware Cooperative Time Allocation for Internet of Things
As the number of Internet of Things (IoT) devices keeps increasing, data is required to be communicated and processed by these devices at unprecedented rates. Cooperation among wireless devices by exploiting Device-to-Device (D2D) connections is promising, where aggregated resources in a cooperative setup can be util...
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COPA: Constrained PARAFAC2 for Sparse & Large Datasets
PARAFAC2 has demonstrated success in modeling irregular tensors, where the tensor dimensions vary across one of the modes. An example scenario is modeling treatments across a set of patients with the varying number of medical encounters over time. Despite recent improvements on unconstrained PARAFAC2, its model facto...
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Effect of Composition Gradient on Magnetothermal Instability Modified by Shear and Rotation
We model the intracluster medium as a weakly collisional plasma that is a binary mixture of the hydrogen and the helium ions, along with free electrons. When, owing to the helium sedimentation, the gradient of the mean molecular weight (or equivalently, composition or helium ions' concentration) of the plasma is not ...
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A Verified Algorithm Enumerating Event Structures
An event structure is a mathematical abstraction modeling concepts as causality, conflict and concurrency between events. While many other mathematical structures, including groups, topological spaces, rings, abound with algorithms and formulas to generate, enumerate and count particular sets of their members, no alg...
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Missing Data as Part of the Social Behavior in Real-World Financial Complex Systems
Many real-world networks are known to exhibit facts that counter our knowledge prescribed by the theories on network creation and communication patterns. A common prerequisite in network analysis is that information on nodes and links will be complete because network topologies are extremely sensitive to missing info...
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Quantum Monte Carlo simulation of a two-dimensional Majorana lattice model
We study interacting Majorana fermions in two dimensions as a low-energy effective model of a vortex lattice in two-dimensional time-reversal-invariant topological superconductors. For that purpose, we implement ab-initio quantum Monte Carlo simulation to the Majorana fermion system in which the path-integral measure...
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Geometric Rescaling Algorithms for Submodular Function Minimization
We present a new class of polynomial-time algorithms for submodular function minimization (SFM), as well as a unified framework to obtain strongly polynomial SFM algorithms. Our new algorithms are based on simple iterative methods for the minimum-norm problem, such as the conditional gradient and the Fujishige-Wolfe ...
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Statistical PT-symmetric lasing in an optical fiber network
PT-symmetry in optics is a condition whereby the real and imaginary parts of the refractive index across a photonic structure are deliberately balanced. This balance can lead to a host of novel optical phenomena, such as unidirectional invisibility, loss-induced lasing, single-mode lasing from multimode resonators, a...
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Transforming Single Domain Magnetic CoFe2O4 Nanoparticles from Hydrophobic to Hydrophilic By Novel Mechanochemical Ligand Exchange
Single phase, uniform size (~9 nm) Cobalt Ferrite (CFO) nanoparticles have been synthesized by hydrothermal synthesis using oleic acid as a surfactant. The as synthesized oleic acid coated CFO (OA-CFO) nanoparticles were well dispersible in nonpolar solvents but not dispersible in water. The OA-CFO nanoparticles have...
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Probing the dusty stellar populations of the Local Volume Galaxies with JWST/MIRI
The Mid-Infrared Instrument (MIRI) for the {\em James Webb Space Telescope} (JWST) will revolutionize our understanding of infrared stellar populations in the Local Volume. Using the rich {\em Spitzer}-IRS spectroscopic data-set and spectral classifications from the Surveying the Agents of Galaxy Evolution (SAGE)-Spe...
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PythonRobotics: a Python code collection of robotics algorithms
This paper describes an Open Source Software (OSS) project: PythonRobotics. This is a collection of robotics algorithms implemented in the Python programming language. The focus of the project is on autonomous navigation, and the goal is for beginners in robotics to understand the basic ideas behind each algorithm. I...
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A Liouville theorem for the Euler equations in the plane
This paper is concerned with qualitative properties of bounded steady flows of an ideal incompressible fluid with no stagnation point in the two-dimensional plane R^2. We show that any such flow is a shear flow, that is, it is parallel to some constant vector. The proof of this Liouville-type result is firstly based ...
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First On-Site True Gamma-Ray Imaging-Spectroscopy of Contamination near Fukushima Plant
We have developed an Electron Tracking Compton Camera (ETCC), which provides a well-defined Point Spread Function (PSF) by reconstructing a direction of each gamma as a point and realizes simultaneous measurement of brightness and spectrum of MeV gamma-rays for the first time. Here, we present the results of our on-s...
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Weak Versus Strong Disorder Superfluid-Bose Glass Transition in One Dimension
Using large-scale simulations based on matrix product state and quantum Monte Carlo techniques, we study the superfluid to Bose glass-transition for one-dimensional attractive hard-core bosons at zero temperature, across the full regime from weak to strong disorder. As a function of interaction and disorder strength,...
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Quantum Structures in Human Decision-making: Towards Quantum Expected Utility
{\it Ellsberg thought experiments} and empirical confirmation of Ellsberg preferences pose serious challenges to {\it subjective expected utility theory} (SEUT). We have recently elaborated a quantum-theoretic framework for human decisions under uncertainty which satisfactorily copes with the Ellsberg paradox and oth...
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Fine-grained Event Learning of Human-Object Interaction with LSTM-CRF
Event learning is one of the most important problems in AI. However, notwithstanding significant research efforts, it is still a very complex task, especially when the events involve the interaction of humans or agents with other objects, as it requires modeling human kinematics and object movements. This study propo...
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Book Review Interferometry and Synthesis in Radio Astronomy - 3rd Ed
Review of the third edition of "Interferometry and Synthesis in Radio Astronomy" by Thompson, Moran and Swenson
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A Kernel Theory of Modern Data Augmentation
Data augmentation, a technique in which a training set is expanded with class-preserving transformations, is ubiquitous in modern machine learning pipelines. In this paper, we seek to establish a theoretical framework for understanding modern data augmentation techniques. We start by showing that for kernel classifie...
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Carrier driven coupling in ferromagnetic oxide heterostructures
Transition metal oxides are well known for their complex magnetic and electrical properties. When brought together in heterostructure geometries, they show particular promise for spintronics and colossal magnetoresistance applications. In this letter, we propose a new mechanism for the coupling between layers of itin...
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Data Dropout in Arbitrary Basis for Deep Network Regularization
An important problem in training deep networks with high capacity is to ensure that the trained network works well when presented with new inputs outside the training dataset. Dropout is an effective regularization technique to boost the network generalization in which a random subset of the elements of the given dat...
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Efficient algorithms to discover alterations with complementary functional association in cancer
Recent large cancer studies have measured somatic alterations in an unprecedented number of tumours. These large datasets allow the identification of cancer-related sets of genetic alterations by identifying relevant combinatorial patterns. Among such patterns, mutual exclusivity has been employed by several recent m...
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Laplace operators on holomorphic Lie algebroids
The paper introduces Laplace-type operators for functions defined on the tangent space of a Finsler Lie algebroid, using a volume form on the prolongation of the algebroid. It also presents the construction of a horizontal Laplace operator for forms defined on the prolongation of the algebroid. All of the Laplace ope...
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