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Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification
Deep neural networks (DNNs) have transformed several artificial intelligence research areas including computer vision, speech recognition, and natural language processing. However, recent studies demonstrated that DNNs are vulnerable to adversarial manipulations at testing time. Specifically, suppose we have a testin...
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Partition-free families of sets
Let $m(n)$ denote the maximum size of a family of subsets which does not contain two disjoint sets along with their union. In 1968 Kleitman proved that $m(n) = {n\choose m+1}+\ldots +{n\choose 2m+1}$ if $n=3m+1$. Confirming the conjecture of Kleitman, we establish the same equality for the cases $n=3m$ and $n=3m+2$, ...
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Measuring the Galactic Cosmic Ray Flux with the LISA Pathfinder Radiation Monitor
Test mass charging caused by cosmic rays will be a significant source of acceleration noise for space-based gravitational wave detectors like LISA. Operating between December 2015 and July 2017, the technology demonstration mission LISA Pathfinder included a bespoke monitor to help characterise the relationship betwe...
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Thread-Modular Static Analysis for Relaxed Memory Models
We propose a memory-model-aware static program analysis method for accurately analyzing the behavior of concurrent software running on processors with weak consistency models such as x86-TSO, SPARC-PSO, and SPARC-RMO. At the center of our method is a unified framework for deciding the feasibility of inter-thread inte...
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Bidirectional Evaluation with Direct Manipulation
We present an evaluation update (or simply, update) algorithm for a full-featured functional programming language, which synthesizes program changes based on output changes. Intuitively, the update algorithm retraces the steps of the original evaluation, rewriting the program as needed to reconcile differences betwee...
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Extreme Event Statistics in a Drifting Markov Chain
We analyse extreme event statistics of experimentally realized Markov chains with various drifts. Our Markov chains are individual trajectories of a single atom diffusing in a one dimensional periodic potential. Based on more than 500 individual atomic traces we verify the applicability of the Sparre Andersen theorem...
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On a Possibility of Self Acceleration of Electrons in a Plasma
The self-consistent nonlinear interaction of a monoenergetic bunch with cold plasma is considered. It is shown that under certain conditions a self-acceleration of the bunch tail electrons up to high energies is possible.
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An Adaptive Strategy for Active Learning with Smooth Decision Boundary
We present the first adaptive strategy for active learning in the setting of classification with smooth decision boundary. The problem of adaptivity (to unknown distributional parameters) has remained opened since the seminal work of Castro and Nowak (2007), which first established (active learning) rates for this se...
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Towards Adversarial Retinal Image Synthesis
Synthesizing images of the eye fundus is a challenging task that has been previously approached by formulating complex models of the anatomy of the eye. New images can then be generated by sampling a suitable parameter space. In this work, we propose a method that learns to synthesize eye fundus images directly from ...
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Tailoring the SiC surface - a morphology study on the epitaxial growth of graphene and its buffer layer
We investigate the growth of the graphene buffer layer and the involved step bunching behavior of the silicon carbide substrate surface using atomic force microscopy. The formation of local buffer layer domains are identified to be the origin of undesirably high step edges in excellent agreement with the predictions ...
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Polarization of the Vaccination Debate on Facebook
Vaccine hesitancy has been recognized as a major global health threat. Having access to any type of information in social media has been suggested as a potential powerful influence factor to hesitancy. Recent studies in other fields than vaccination show that access to a wide amount of content through the Internet wi...
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Predicting Demographics, Moral Foundations, and Human Values from Digital Behaviors
Personal electronic devices including smartphones give access to behavioural signals that can be used to learn about the characteristics and preferences of individuals. In this study, we explore the connection between demographic and psychological attributes and the digital behavioural records, for a cohort of 7,633 ...
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Isotonic regression in general dimensions
We study the least squares regression function estimator over the class of real-valued functions on $[0,1]^d$ that are increasing in each coordinate. For uniformly bounded signals and with a fixed, cubic lattice design, we establish that the estimator achieves the minimax rate of order $n^{-\min\{2/(d+2),1/d\}}$ in t...
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Extraction of Schottky barrier height insensitive to temperature via forward currentvoltage- temperature measurements
The thermal stability of most electronic and photo-electronic devices strongly depends on the relationship between Schottky Barrier Height (SBH) and temperature. In this paper, the possible of thermionic current depicted via correct and reliability relationship between forward current and voltage is consequently disc...
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Emergent Open-Endedness from Contagion of the Fittest
In this paper, we study emergent irreducible information in populations of randomly generated computable systems that are networked and follow a "Susceptible-Infected-Susceptible" contagion model of imitation of the fittest neighbor. We show that there is a lower bound for the stationary prevalence (or average densit...
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Incompressible Limit of isentropic Navier-Stokes equations with Navier-slip boundary
This paper concerns the low Mach number limit of weak solutions to the compressible Navier-Stokes equations for isentropic fluids in a bounded domain with a Navier-slip boundary condition. In \cite{DGLM99}, it has been proved that if the velocity is imposed the homogeneous Dirichlet boundary condition, as the Mach nu...
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On Some Exponential Sums Related to the Coulter's Polynomial
In this paper, the formulas of some exponential sums over finite field, related to the Coulter's polynomial, are settled based on the Coulter's theorems on Weil sums, which may have potential application in the construction of linear codes with few weights.
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Distribution-Preserving k-Anonymity
Preserving the privacy of individuals by protecting their sensitive attributes is an important consideration during microdata release. However, it is equally important to preserve the quality or utility of the data for at least some targeted workloads. We propose a novel framework for privacy preservation based on th...
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Using controlled disorder to probe the interplay between charge order and superconductivity in NbSe2
The interplay between superconductivity and charge density waves (CDW) in $H$-NbSe2 is not fully understood despite decades of study. Artificially introduced disorder can tip the delicate balance between two competing forms of long-range order, and reveal the underlying interactions that give rise to them. Here we in...
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A training process for improving the quality of software projects developed by a practitioner
Background: The quality of a software product depends on the quality of the software process followed in developing the product. Therefore, many higher education institutions (HEI) and software organizations have implemented software process improvement (SPI) training courses to improve the software quality. Objectiv...
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Gaia Data Release 1. Cross-match with external catalogues - Algorithm and results
Although the Gaia catalogue on its own will be a very powerful tool, it is the combination of this highly accurate archive with other archives that will truly open up amazing possibilities for astronomical research. The advanced interoperation of archives is based on cross-matching, leaving the user with the feeling ...
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Masses of Kepler-46b, c from Transit Timing Variations
We use 16 quarters of the \textit{Kepler} mission data to analyze the transit timing variations (TTVs) of the extrasolar planet Kepler-46b (KOI-872). Our dynamical fits confirm that the TTVs of this planet (period $P=33.648^{+0.004}_{-0.005}$ days) are produced by a non-transiting planet Kepler-46c ($P=57.325^{+0.116...
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Recovering water wave elevation from pressure measurements
The reconstruction of water wave elevation from bottom pressure measurements is an important issue for coastal applications, but corresponds to a difficult mathematical problem. In this paper we present the derivation of a method which allows the elevation reconstruction of water waves in intermediate and shallow wat...
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Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization
The Schatten quasi-norm was introduced to bridge the gap between the trace norm and rank function. However, existing algorithms are too slow or even impractical for large-scale problems. Motivated by the equivalence relation between the trace norm and its bilinear spectral penalty, we define two tractable Schatten no...
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Spectral Radii of Truncated Circular Unitary Matrices
Consider a truncated circular unitary matrix which is a $p_n$ by $p_n$ submatrix of an $n$ by $n$ circular unitary matrix by deleting the last $n-p_n$ columns and rows. Jiang and Qi (2017) proved that the maximum absolute value of the eigenvalues (known as spectral radius) of the truncated matrix, after properly norm...
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Information Assisted Dictionary Learning for fMRI data analysis
In this paper, the task-related fMRI problem is treated in its matrix factorization formulation. The focus of the reported work is on the dictionary learning (DL) matrix factorization approach. A major novelty of the paper lies in the incorporation of well-established assumptions associated with the GLM technique, wh...
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Efficient, Certifiably Optimal Clustering with Applications to Latent Variable Graphical Models
Motivated by the task of clustering either $d$ variables or $d$ points into $K$ groups, we investigate efficient algorithms to solve the Peng-Wei (P-W) $K$-means semi-definite programming (SDP) relaxation. The P-W SDP has been shown in the literature to have good statistical properties in a variety of settings, but r...
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Two- and three-dimensional wide-field weak lensing mass maps from the Hyper Suprime-Cam Subaru Strategic Program S16A data
We present wide-field (167 deg$^2$) weak lensing mass maps from the Hyper Supreme-Cam Subaru Strategic Program (HSC-SSP). We compare these weak lensing based dark matter maps with maps of the distribution of the stellar mass associated with luminous red galaxies. We find a strong correlation between these two maps wi...
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A Time-spectral Approach to Numerical Weather Prediction
Finite difference methods are traditionally used for modelling the time domain in numerical weather prediction (NWP). Time-spectral solution is an attractive alternative for reasons of accuracy and efficiency and because time step limitations associated with causal, CFL-like critera are avoided. In this work, the Lor...
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Trivial Constraints on Orbital-free Kinetic Energy Density Functionals
Kinetic energy density functionals (KEDFs) are central to orbital-free density functional theory. Limitations on the spatial derivative dependencies of KEDFs have been claimed from differential virial theorems. We point out a central defect in the argument: the relationships are not true for an arbitrary density but ...
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The Multi-layer Information Bottleneck Problem
The muti-layer information bottleneck (IB) problem, where information is propagated (or successively refined) from layer to layer, is considered. Based on information forwarded by the preceding layer, each stage of the network is required to preserve a certain level of relevance with regards to a specific hidden vari...
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A geometric approach to non-linear correlations with intrinsic scatter
We propose a new mathematical model for $n-k$-dimensional non-linear correlations with intrinsic scatter in $n$-dimensional data. The model is based on Riemannian geometry, and is naturally symmetric with respect to the measured variables and invariant under coordinate transformations. We combine the model with a Bay...
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Computing simplicial representatives of homotopy group elements
A central problem of algebraic topology is to understand the homotopy groups $\pi_d(X)$ of a topological space $X$. For the computational version of the problem, it is well known that there is no algorithm to decide whether the fundamental group $\pi_1(X)$ of a given finite simplicial complex $X$ is trivial. On the o...
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Multiobjective Optimization of Solar Powered Irrigation System with Fuzzy Type-2 Noise Modelling
Optimization is becoming a crucial element in industrial applications involving sustainable alternative energy systems. During the design of such systems, the engineer/decision maker would often encounter noise factors (e.g. solar insolation and ambient temperature fluctuations) when their system interacts with the e...
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Convergence Analysis of Gradient EM for Multi-component Gaussian Mixture
In this paper, we study convergence properties of the gradient Expectation-Maximization algorithm \cite{lange1995gradient} for Gaussian Mixture Models for general number of clusters and mixing coefficients. We derive the convergence rate depending on the mixing coefficients, minimum and maximum pairwise distances bet...
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The Gravitational-Wave Physics
The direct detection of gravitational wave by Laser Interferometer Gravitational-Wave Observatory indicates the coming of the era of gravitational-wave astronomy and gravitational-wave cosmology. It is expected that more and more gravitational-wave events will be detected by currently existing and planned gravitation...
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Multivariant Assertion-based Guidance in Abstract Interpretation
Approximations during program analysis are a necessary evil, as they ensure essential properties, such as soundness and termination of the analysis, but they also imply not always producing useful results. Automatic techniques have been studied to prevent precision loss, typically at the expense of larger resource co...
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An Experimental Comparison of Uncertainty Sets for Robust Shortest Path Problems
Through the development of efficient algorithms, data structures and preprocessing techniques, real-world shortest path problems in street networks are now very fast to solve. But in reality, the exact travel times along each arc in the network may not be known. This lead to the development of robust shortest path pr...
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An experimental comparison of velocities underneath focussed breaking waves
Nonlinear wave interactions affect the evolution of steep wave groups, their breaking and the associated kinematic field. Laboratory experiments are performed to investigate the effect of the underlying focussing mechanism on the shape of the breaking wave and its velocity field. In this regard, it is found that the ...
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Full Momentum and Energy Resolved Spectral Function of a 2D Electronic System
The single-particle spectral function measures the density of electronic states (DOS) in a material as a function of both momentum and energy, providing central insights into phenomena such as superconductivity and Mott insulators. While scanning tunneling microscopy (STM) and other tunneling methods have provided pa...
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Complete parallel mean curvature surfaces in two-dimensional complex space-forms
The purpose of this article is to determine explicitly the complete surfaces with parallel mean curvature vector, both in the complex projective plane and the complex hyperbolic plane. The main results are as follows: When the curvature of the ambient space is positive, there exists a unique such surface up to rigid ...
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Parallelized Linear Classification with Volumetric Chemical Perceptrons
In this work, we introduce a new type of linear classifier that is implemented in a chemical form. We propose a novel encoding technique which simultaneously represents multiple datasets in an array of microliter-scale chemical mixtures. Parallel computations on these datasets are performed as robotic liquid handling...
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Learning Spatial Regularization with Image-level Supervisions for Multi-label Image Classification
Multi-label image classification is a fundamental but challenging task in computer vision. Great progress has been achieved by exploiting semantic relations between labels in recent years. However, conventional approaches are unable to model the underlying spatial relations between labels in multi-label images, becau...
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The critical binary star separation for a planetary system origin of white dwarf pollution
The atmospheres of between one quarter and one half of observed single white dwarfs in the Milky Way contain heavy element pollution from planetary debris. The pollution observed in white dwarfs in binary star systems is, however, less clear, because companion star winds can generate a stream of matter which is accre...
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A quantum Mirković-Vybornov isomorphism
We present a quantization of an isomorphism of Mirković and Vybornov which relates the intersection of a Slodowy slice and a nilpotent orbit closure in $\mathfrak{gl}_N$ , to a slice between spherical Schubert varieties in the affine Grassmannian of $PGL_n$ (with weights encoded by the Jordan types of the nilpotent o...
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Portfolio diversification and model uncertainty: a robust dynamic mean-variance approach
This paper is concerned with a multi-asset mean-variance portfolio selection problem under model uncertainty. We develop a continuous time framework for taking into account ambiguity aversion about both expected return rates and correlation matrix of the assets, and for studying the effects on portfolio diversificati...
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TensorLayer: A Versatile Library for Efficient Deep Learning Development
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduous and complex, as it involves constructing neural network architectures, managing training/trained models, tuning optimization process, p...
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Effects of excess carriers on native defects in wide bandgap semiconductors: illumination as a method to enhance p-type doping
Undesired unintentional doping and doping limits in semiconductors are typically caused by compensating defects with low formation energies. Since the formation energy of a charged defect depends linearly on the Fermi level, doping limits can be especially pronounced in wide bandgap semiconductors where the Fermi lev...
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LATTE: Application Oriented Social Network Embedding
In recent years, many research works propose to embed the network structured data into a low-dimensional feature space, where each node is represented as a feature vector. However, due to the detachment of embedding process with external tasks, the learned embedding results by most existing embedding models can be in...
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Giant paramagnetism induced valley polarization of electrons in charge-tunable monolayer MoSe2
For applications exploiting the valley pseudospin degree of freedom in transition metal dichalcogenide monolayers, efficient preparation of electrons or holes in a single valley is essential. Here, we show that a magnetic field of 7 Tesla leads to a near-complete valley polarization of electrons in MoSe2 monolayer wi...
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Highrisk Prediction from Electronic Medical Records via Deep Attention Networks
Predicting highrisk vascular diseases is a significant issue in the medical domain. Most predicting methods predict the prognosis of patients from pathological and radiological measurements, which are expensive and require much time to be analyzed. Here we propose deep attention models that predict the onset of the h...
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Agent based simulation of the evolution of society as an alternate maximization problem
Understanding the evolution of human society, as a complex adaptive system, is a task that has been looked upon from various angles. In this paper, we simulate an agent-based model with a high enough population tractably. To do this, we characterize an entity called \textit{society}, which helps us reduce the complex...
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Can a heart rate variability biomarker identify the presence of autism spectrum disorder in eight year old children?
Autonomic nervous system (ANS) activity is altered in autism spectrum disorder (ASD). Heart rate variability (HRV) derived from electrocardiogram (ECG) has been a powerful tool to identify alterations in ANS due to a plethora of pathophysiological conditions, including psychological ones such as depression. ECG-deriv...
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Semantic Entity Retrieval Toolkit
Unsupervised learning of low-dimensional, semantic representations of words and entities has recently gained attention. In this paper we describe the Semantic Entity Retrieval Toolkit (SERT) that provides implementations of our previously published entity representation models. The toolkit provides a unified interfac...
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Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection
In the Best-$k$-Arm problem, we are given $n$ stochastic bandit arms, each associated with an unknown reward distribution. We are required to identify the $k$ arms with the largest means by taking as few samples as possible. In this paper, we make progress towards a complete characterization of the instance-wise samp...
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Dimensions of equilibrium measures on a class of planar self-affine sets
We study equilibrium measures (Käenmäki measures) supported on self-affine sets generated by a finite collection of diagonal and anti-diagonal matrices acting on the plane and satisfying the strong separation property. Our main result is that such measures are exact dimensional and the dimension satisfies the Ledrapp...
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Hubble PanCET: An isothermal day-side atmosphere for the bloated gas-giant HAT-P-32Ab
We present a thermal emission spectrum of the bloated hot Jupiter HAT-P-32Ab from a single eclipse observation made in spatial scan mode with the Wide Field Camera 3 (WFC3) aboard the Hubble Space Telescope (HST). The spectrum covers the wavelength regime from 1.123 to 1.644 microns which is binned into 14 eclipse de...
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One Model To Learn Them All
Deep learning yields great results across many fields, from speech recognition, image classification, to translation. But for each problem, getting a deep model to work well involves research into the architecture and a long period of tuning. We present a single model that yields good results on a number of problems ...
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Porcupine Neural Networks: (Almost) All Local Optima are Global
Neural networks have been used prominently in several machine learning and statistics applications. In general, the underlying optimization of neural networks is non-convex which makes their performance analysis challenging. In this paper, we take a novel approach to this problem by asking whether one can constrain n...
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Configuration Path Integral Monte Carlo Approach to the Static Density Response of the Warm Dense Electron Gas
Precise knowledge of the static density response function (SDRF) of the uniform electron gas (UEG) serves as key input for numerous applications, most importantly for density functional theory beyond generalized gradient approximations. Here we extend the configuration path integral Monte Carlo (CPIMC) formalism that...
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Superzone gap formation and low lying crystal electric field levels in PrPd$_2$Ge$_2$ single crystal
The magnetocrystalline anisotropy exhibited in PrPd$_2$Ge$_2$ single crystal has been investigated by measuring the magnetization, magnetic susceptibility, electrical resistivity and heat capacity. PrPd$_2$Ge$_2$ crystallizes in the well known ThCr$_2$Si$_2$\--type tetragonal structure. The antiferromagnetic ordering...
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Adaptive Real-Time Software Defined MIMO Visible Light Communications using Spatial Multiplexing and Spatial Diversity
In this paper, we experimentally demonstrate a real-time software defined multiple input multiple output (MIMO) visible light communication (VLC) system employing link adaptation of spatial multiplexing and spatial diversity. Real-time MIMO signal processing is implemented by using the Field Programmable Gate Array (...
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Maximum Principle Based Algorithms for Deep Learning
The continuous dynamical system approach to deep learning is explored in order to devise alternative frameworks for training algorithms. Training is recast as a control problem and this allows us to formulate necessary optimality conditions in continuous time using the Pontryagin's maximum principle (PMP). A modifica...
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Factorization Machines Leveraging Lightweight Linked Open Data-enabled Features for Top-N Recommendations
With the popularity of Linked Open Data (LOD) and the associated rise in freely accessible knowledge that can be accessed via LOD, exploiting LOD for recommender systems has been widely studied based on various approaches such as graph-based or using different machine learning models with LOD-enabled features. Many o...
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Wave propagation and homogenization in 2D and 3D lattices: a semi-analytical approach
Wave motion in two- and three-dimensional periodic lattices of beam members supporting longitudinal and flexural waves is considered. An analytic method for solving the Bloch wave spectrum is developed, characterized by a generalized eigenvalue equation obtained by enforcing the Floquet condition. The dynamic stiffne...
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Waring's problem for unipotent algebraic groups
In this paper, we formulate an analogue of Waring's problem for an algebraic group $G$. At the field level we consider a morphism of varieties $f\colon \mathbb{A}^1\to G$ and ask whether every element of $G(K)$ is the product of a bounded number of elements $f(\mathbb{A}^1(K)) = f(K)$. We give an affirmative answer w...
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Spreading of localized attacks in spatial multiplex networks
Many real-world multilayer systems such as critical infrastructure are interdependent and embedded in space with links of a characteristic length. They are also vulnerable to localized attacks or failures, such as terrorist attacks or natural catastrophes, which affect all nodes within a given radius. Here we study t...
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Greedy Sparse Signal Reconstruction Using Matching Pursuit Based on Hope-tree
The reconstruction of sparse signals requires the solution of an $\ell_0$-norm minimization problem in Compressed Sensing. Previous research has focused on the investigation of a single candidate to identify the support (index of nonzero elements) of a sparse signal. To ensure that the optimal candidate can be obtain...
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Attack-Aware Multi-Sensor Integration Algorithm for Autonomous Vehicle Navigation Systems
In this paper, we propose a fault detection and isolation based attack-aware multi-sensor integration algorithm for the detection of cyberattacks in autonomous vehicle navigation systems. The proposed algorithm uses an extended Kalman filter to construct robust residuals in the presence of noise, and then uses a para...
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Turbulence, cascade and singularity in a generalization of the Constantin-Lax-Majda equation
We study numerically a Constantin-Lax-Majda-De Gregorio model generalized by Okamoto, Sakajo and Wunsch, which is a model of fluid turbulence in one dimension with an inviscid conservation law. In the presence of the viscosity and two types of the large-scale forcings, we show that turbulent cascade of the inviscid i...
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Fitting phase--type scale mixtures to heavy--tailed data and distributions
We consider the fitting of heavy tailed data and distribution with a special attention to distributions with a non--standard shape in the "body" of the distribution. To this end we consider a dense class of heavy tailed distributions introduced recently, employing an EM algorithm for the the maximum likelihood estima...
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Deep Incremental Boosting
This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation. We draw inspiration from Transfer of Learning approaches to reduce the start-up time to training each in...
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Empirical Likelihood for Linear Structural Equation Models with Dependent Errors
We consider linear structural equation models that are associated with mixed graphs. The structural equations in these models only involve observed variables, but their idiosyncratic error terms are allowed to be correlated and non-Gaussian. We propose empirical likelihood (EL) procedures for inference, and suggest s...
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Grassmannian flows and applications to nonlinear partial differential equations
We show how solutions to a large class of partial differential equations with nonlocal Riccati-type nonlinearities can be generated from the corresponding linearized equations, from arbitrary initial data. It is well known that evolutionary matrix Riccati equations can be generated by projecting linear evolutionary f...
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The Reinhardt Conjecture as an Optimal Control Problem
In 1934, Reinhardt conjectured that the shape of the centrally symmetric convex body in the plane whose densest lattice packing has the smallest density is a smoothed octagon. This conjecture is still open. We formulate the Reinhardt Conjecture as a problem in optimal control theory. The smoothed octagon is a Pontrya...
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Deep submillimeter and radio observations in the SSA22 field. I. Powering sources and Lyα escape fraction of Lyα blobs
We study the heating mechanisms and Ly{\alpha} escape fractions of 35 Ly{\alpha} blobs (LABs) at z = 3.1 in the SSA22 field. Dust continuum sources have been identified in 11 of the 35 LABs, all with star formation rates (SFRs) above 100 Msun/yr. Likely radio counterparts are detected in 9 out of 29 investigated LABs...
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Modeling temporal constraints for a system of interactive scores
In this chapter we explain briefly the fundamentals of the interactive scores formalism. Then we develop a solution for implementing the ECO machine by mixing petri nets and constraints propagation. We also present another solution for implementing the ECO machine using concurrent constraint programming. Finally, we ...
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Electronic structure of ThRu2Si2 studied by angle-resolved photoelectron spectroscopy: Elucidating the contribution of U 5f states in URu2Si2
The electronic structure of ThRu2Si2 was studied by angle-resolved photoelectron spectroscopy (ARPES) with incident photon energies of hn=655-745 eV. Detailed band structure and the three-dimensional shapes of Fermi surfaces were derived experimentally, and their characteristic features were mostly explained by means...
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Non-zero constant curvature factorable surfaces in pseudo-Galilean space
Factorable surfaces, i.e. graphs associated with the product of two functions of one variable, constitute a wide class of surfaces. Such surfaces in the pseudo-Galilean space with zero Gaussian and mean curvature were obtained in [1]. In this study, we provide new classification results relating to the factorable sur...
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Darboux and Binary Darboux Transformations for Discrete Integrable Systems. II. Discrete Potential mKdV Equation
The paper presents two results. First it is shown how the discrete potential modified KdV equation and its Lax pairs in matrix form arise from the Hirota-Miwa equation by a 2-periodic reduction. Then Darboux transformations and binary Darboux transformations are derived for the discrete potential modified KdV equatio...
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Nearly second-order asymptotic optimality of sequential change-point detection with one-sample updates
Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential likelihood ratios with non-anticipating estimators constructed using on...
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Algorithms in the classical Néron Desingularization
We give algorithms to construct the Néron Desingularization and the easy case from \cite{KK} of the General Néron Desingularization.
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Recent Advances in Neural Program Synthesis
In recent years, deep learning has made tremendous progress in a number of fields that were previously out of reach for artificial intelligence. The successes in these problems has led researchers to consider the possibilities for intelligent systems to tackle a problem that humans have only recently themselves consi...
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Generator Reversal
We consider the problem of training generative models with deep neural networks as generators, i.e. to map latent codes to data points. Whereas the dominant paradigm combines simple priors over codes with complex deterministic models, we propose instead to use more flexible code distributions. These distributions are...
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Finite model reasoning over existential rules
Ontology-based query answering (OBQA) asks whether a Boolean conjunctive query is satisfied by all models of a logical theory consisting of a relational database paired with an ontology. The introduction of existential rules (i.e., Datalog rules extended with existential quantifiers in rule-heads) as a means to speci...
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On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization
Despite their popularity, the practical performance of asynchronous stochastic gradient descent methods (ASGD) for solving large scale machine learning problems are not as good as theoretical results indicate. We adopt and analyze a synchronous K-step averaging stochastic gradient descent algorithm which we call K-AV...
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Adversarial Neural Machine Translation
In this paper, we study a new learning paradigm for Neural Machine Translation (NMT). Instead of maximizing the likelihood of the human translation as in previous works, we minimize the distinction between human translation and the translation given by an NMT model. To achieve this goal, inspired by the recent succes...
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Surface group amalgams that (don't) act on 3-manifolds
We determine which amalgamated products of surface groups identified over multiples of simple closed curves are not fundamental groups of 3-manifolds. We prove each surface amalgam considered is virtually the fundamental group of a 3-manifold. We prove that each such surface group amalgam is abstractly commensurable ...
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Shading Annotations in the Wild
Understanding shading effects in images is critical for a variety of vision and graphics problems, including intrinsic image decomposition, shadow removal, image relighting, and inverse rendering. As is the case with other vision tasks, machine learning is a promising approach to understanding shading - but there is ...
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Koszul cycles and Golod rings
Let $S$ be the power series ring or the polynomial ring over a field $K$ in the variables $x_1,\ldots,x_n$, and let $R=S/I$, where $I$ is proper ideal which we assume to be graded if $S$ is the polynomial ring. We give an explicit description of the cycles of the Koszul complex whose homology classes generate the Kos...
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PacGAN: The power of two samples in generative adversarial networks
Generative adversarial networks (GANs) are innovative techniques for learning generative models of complex data distributions from samples. Despite remarkable recent improvements in generating realistic images, one of their major shortcomings is the fact that in practice, they tend to produce samples with little dive...
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Stein-like Estimators for Causal Mediation Analysis in Randomized Trials
Causal mediation analysis aims to estimate the natural direct and indirect effects under clearly specified assumptions. Traditional mediation analysis based on Ordinary Least Squares (OLS) relies on the absence of unmeasured causes of the putative mediator and outcome. When this assumption cannot be justified, Instru...
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Structure-Based Subspace Method for Multi-Channel Blind System Identification
In this work, a novel subspace-based method for blind identification of multichannel finite impulse response (FIR) systems is presented. Here, we exploit directly the impeded Toeplitz channel structure in the signal linear model to build a quadratic form whose minimization leads to the desired channel estimation up t...
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On Certain Analytical Representations of Cellular Automata
We extend a previously introduced semi-analytical representation of a decomposition of CA dynamics in arbitrary dimensions and neighborhood schemes via the use of certain universal maps in which CA rule vectors are derivable from the equivalent of superpotentials. The results justify the search for alternative analog...
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Strong consistency and optimality for generalized estimating equations with stochastic covariates
In this article we study the existence and strong consistency of GEE estimators, when the generalized estimating functions are martingales with random coefficients. Furthermore, we characterize estimating functions which are asymptotically optimal.
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Synthesis and electronic properties of Ruddlesden-Popper strontium iridate epitaxial thin films stabilized by control of growth kinetics
We report on the selective fabrication of high-quality Sr$_2$IrO$_4$ and SrIrO$_3$ epitaxial thin films from a single polycrystalline Sr$_2$IrO$_4$ target by pulsed laser deposition. Using a combination of X-ray diffraction and photoemission spectroscopy characterizations, we discover that within a relatively narrow ...
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A proof on energy gap for Yang-Mills connection
In this note, we prove an ${L^{\frac{n}{2}}}$-energy gap result for Yang-Mills connections on a principal $G$-bundle over a compact manifold without using Lojasiewicz-Simon gradient inequality (arXiv:1502.00668).
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Realisability of Pomsets via Communicating Automata
Pomsets are a model of concurrent computations introduced by Pratt. They can provide a syntax-oblivious description of semantics of coordination models based on asynchronous message-passing, such as Message Sequence Charts (MSCs). In this paper, we study conditions that ensure a specification expressed as a set of po...
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Complex pattern formation driven by the interaction of stable fronts in a competition-diffusion system
The ecological invasion problem in which a weaker exotic species invades an ecosystem inhabited by two strongly competing native species is modelled by a three-species competition-diffusion system. It is known that for a certain range of parameter values competitor-mediated coexistence occurs and complex spatio-tempo...
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Solitons with rings and vortex rings on solitons in nonlocal nonlinear media
Nonlocality is a key feature of many physical systems since it prevents a catastrophic collapse and a symmetry-breaking azimuthal instability of intense wave beams in a bulk self-focusing nonlinear media. This opens up an intriguing perspective for stabilization of complex topological structures such as higher-order ...
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