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Maximal fluctuations of confined actomyosin gels: dynamics of the cell nucleus
We investigate the effect of stress fluctuations on the stochastic dynamics of an inclusion embedded in a viscous gel. We show that, in non-equilibrium systems, stress fluctuations give rise to an effective attraction towards the boundaries of the confining domain, which is reminiscent of an active Casimir effect. We...
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Age-at-harvest models as monitoring and harvest management tools for Wisconsin carnivores
Quantifying and estimating wildlife population sizes is a foundation of wildlife management. However, many carnivore species are cryptic, leading to innate difficulties in estimating their populations. We evaluated the potential for using more rigorous statistical models to estimate the populations of black bears (Ur...
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Information Planning for Text Data
Information planning enables faster learning with fewer training examples. It is particularly applicable when training examples are costly to obtain. This work examines the advantages of information planning for text data by focusing on three supervised models: Naive Bayes, supervised LDA and deep neural networks. We...
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Development of Si-CMOS hybrid detectors towards electron tracking based Compton imaging in semiconductor detectors
Electron tracking based Compton imaging is a key technique to improve the sensitivity of Compton cameras by measuring the initial direction of recoiled electrons. To realize this technique in semiconductor Compton cameras, we propose a new detector concept, Si-CMOS hybrid detector. It is a Si detector bump-bonded to ...
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Sharp constant of an anisotropic Gagliardo-Nirenberg-type inequality and applications
In this paper we establish the best constant of an anisotropic Gagliardo-Nirenberg-type inequality related to the Benjamin-Ono-Zakharov-Kuznetsov equation. As an application of our results, we prove the uniform bound of solutions for such a equation in the energy space.
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Treatment Effect Quantification for Time-to-event Endpoints -- Estimands, Analysis Strategies, and beyond
A draft addendum to ICH E9 has been released for public consultation in August 2017. The addendum focuses on two topics particularly relevant for randomized confirmatory clinical trials: estimands and sensitivity analyses. The need to amend ICH E9 grew out of the realization of a lack of alignment between the objecti...
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A character of Siegel modular group of level 2 from theta constants
Given a characteristic, we define a character of the Siegel modular group of level 2, the computations of their values are also obtained. By using our theorems, some key theorems of Igusa [1] can be recovered.
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Antiferromagnetic Chern insulators in non-centrosymmetric systems
We investigate a new class of topological antiferromagnetic (AF) Chern insulators driven by electronic interactions in two-dimensional systems without inversion symmetry. Despite the absence of a net magnetization, AF Chern insulators (AFCI) possess a nonzero Chern number $C$ and exhibit the quantum anomalous Hall ef...
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The concentration-mass relation of clusters of galaxies from the OmegaWINGS survey
The relation between a cosmological halo concentration and its mass (cMr) is a powerful tool to constrain cosmological models of halo formation and evolution. On the scale of galaxy clusters the cMr has so far been determined mostly with X-ray and gravitational lensing data. The use of independent techniques is helpf...
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Effects of the structural distortion on the electronic band structure of {\boldmath $\rm Na Os O_3$} studied within density functional theory and a three-orbital model
Effects of the structural distortion associated with the $\rm OsO_6$ octahedral rotation and tilting on the electronic band structure and magnetic anisotropy energy for the $5d^3$ compound NaOsO$_3$ are investigated using the density functional theory (DFT) and within a three-orbital model. Comparison of the essentia...
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On the Joint Distribution Of $\mathrm{Sel}_ϕ(E/\mathbb{Q})$ and $\mathrm{Sel}_{\hatϕ}(E^\prime/\mathbb{Q})$ in Quadratic Twist Families
If $E$ is an elliptic curve with a point of order two, then work of Klagsbrun and Lemke Oliver shows that the distribution of $\dim_{\mathbb{F}_2}\mathrm{Sel}_\phi(E^d/\mathbb{Q}) - \dim_{\mathbb{F}_2} \mathrm{Sel}_{\hat\phi}(E^{\prime d}/\mathbb{Q})$ within the quadratic twist family tends to the discrete normal dis...
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Learning What Data to Learn
Machine learning is essentially the sciences of playing with data. An adaptive data selection strategy, enabling to dynamically choose different data at various training stages, can reach a more effective model in a more efficient way. In this paper, we propose a deep reinforcement learning framework, which we call \...
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Deformation estimation of an elastic object by partial observation using a neural network
Deformation estimation of elastic object assuming an internal organ is important for the computer navigation of surgery. The aim of this study is to estimate the deformation of an entire three-dimensional elastic object using displacement information of very few observation points. A learning approach with a neural n...
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Comparative analysis of two discretizations of Ricci curvature for complex networks
We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth noti...
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Zero-Shot Learning via Class-Conditioned Deep Generative Models
We present a deep generative model for learning to predict classes not seen at training time. Unlike most existing methods for this problem, that represent each class as a point (via a semantic embedding), we represent each seen/unseen class using a class-specific latent-space distribution, conditioned on class attri...
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On the vanishing viscosity approximation of a nonlinear model for tumor growth
We investigate the dynamics of a nonlinear system modeling tumor growth with drug application. The tumor is viewed as a mixture consisting of proliferating, quiescent and dead cells as well as a nutrient in the presence of a drug. The system is given by a multi-phase flow model: the densities of the different cells a...
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Noise-gating to clean astrophysical image data
I present a family of algorithms to reduce noise in astrophysical im- ages and image sequences, preserving more information from the original data than is retained by conventional techniques. The family uses locally adaptive filters ("noise gates") in the Fourier domain, to separate coherent image structure from back...
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Variational Bayesian dropout: pitfalls and fixes
Dropout, a stochastic regularisation technique for training of neural networks, has recently been reinterpreted as a specific type of approximate inference algorithm for Bayesian neural networks. The main contribution of the reinterpretation is in providing a theoretical framework useful for analysing and extending t...
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Deep Belief Networks Based Feature Generation and Regression for Predicting Wind Power
Wind energy forecasting helps to manage power production, and hence, reduces energy cost. Deep Neural Networks (DNN) mimics hierarchical learning in the human brain and thus possesses hierarchical, distributed, and multi-task learning capabilities. Based on aforementioned characteristics, we report Deep Belief Networ...
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Control Interpretations for First-Order Optimization Methods
First-order iterative optimization methods play a fundamental role in large scale optimization and machine learning. This paper presents control interpretations for such optimization methods. First, we give loop-shaping interpretations for several existing optimization methods and show that they are composed of basic...
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Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
Machine understanding of complex images is a key goal of artificial intelligence. One challenge underlying this task is that visual scenes contain multiple inter-related objects, and that global context plays an important role in interpreting the scene. A natural modeling framework for capturing such effects is struc...
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Identifying Similarities in Epileptic Patients for Drug Resistance Prediction
Currently, approximately 30% of epileptic patients treated with antiepileptic drugs (AEDs) remain resistant to treatment (known as refractory patients). This project seeks to understand the underlying similarities in refractory patients vs. other epileptic patients, identify features contributing to drug resistance a...
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Variational Inference of Disentangled Latent Concepts from Unlabeled Observations
Disentangled representations, where the higher level data generative factors are reflected in disjoint latent dimensions, offer several benefits such as ease of deriving invariant representations, transferability to other tasks, interpretability, etc. We consider the problem of unsupervised learning of disentangled r...
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Designing the color of hot-dip galvanized steel sheet through destructive light interference using a Zn-Ti liquid metallic bath
The color of hot-dip galvanized steel sheet was adjusted in a reproducible way using a liquid Zn-Ti metallic bath, air atmosphere, and controlling the bath temperature as the only experimental parameter. Coloring was found only for sample s cooled in air and dipped into Ti-containing liquid Zn. For samples dipped int...
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Counting Multiplicities in a Hypersurface over a Number Field
We fix a counting function of multiplicities of algebraic points in a projective hypersurface over a number field, and take the sum over all algebraic points of bounded height and fixed degree. An upper bound for the sum with respect to this counting function will be given in terms of the degree of the hypersurface, ...
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Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis
We consider the task of fine-grained sentiment analysis from the perspective of multiple instance learning (MIL). Our neural model is trained on document sentiment labels, and learns to predict the sentiment of text segments, i.e. sentences or elementary discourse units (EDUs), without segment-level supervision. We i...
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Eva-CiM: A System-Level Energy Evaluation Framework for Computing-in-Memory Architectures
Computing-in-Memory (CiM) architectures aim to reduce costly data transfers by performing arithmetic and logic operations in memory and hence relieve the pressure due to the memory wall. However, determining whether a given workload can really benefit from CiM, which memory hierarchy and what device technology should...
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Converging Shock Flows for a Mie-Grüneisen Equation of State
Previous work has shown that the one-dimensional (1D) inviscid compressible flow (Euler) equations admit a wide variety of scale-invariant solutions (including the famous Noh, Sedov, and Guderley shock solutions) when the included equation of state (EOS) closure model assumes a certain scale-invariant form. However, ...
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Robust estimation of tree structured Gaussian Graphical Model
Consider jointly Gaussian random variables whose conditional independence structure is specified by a graphical model. If we observe realizations of the variables, we can compute the covariance matrix, and it is well known that the support of the inverse covariance matrix corresponds to the edges of the graphical mod...
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What Propels Celebrity Follower Counts? Language Use or Social Connectivity
Follower count is a factor that quantifies the popularity of celebrities. It is a reflection of their power, prestige and overall social reach. In this paper we investigate whether the social connectivity or the language choice is more correlated to the future follower count of a celebrity. We collect data about twee...
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Monochromatic metrics are generalized Berwald
We show that monochromatic Finsler metrics, i.e., Finsler metrics such that each two tangent spaces are isomorphic as normed spaces, are generalized Berwald metrics, i.e., there exists an affine connection, possibly with torsion, that preserves the Finsler function
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CTCF Degradation Causes Increased Usage of Upstream Exons in Mouse Embryonic Stem Cells
Transcriptional repressor CTCF is an important regulator of chromatin 3D structure, facilitating the formation of topologically associating domains (TADs). However, its direct effects on gene regulation is less well understood. Here, we utilize previously published ChIP-seq and RNA-seq data to investigate the effects...
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The stability of tightly-packed, evenly-spaced systems of Earth-mass planets orbiting a Sun-like star
Many of the multi-planet systems discovered to date have been notable for their compactness, with neighbouring planets closer together than any in the Solar System. Interestingly, planet-hosting stars have a wide range of ages, suggesting that such compact systems can survive for extended periods of time. We have use...
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GPUQT: An efficient linear-scaling quantum transport code fully implemented on graphics processing units
We present GPUQT, a quantum transport code fully implemented on graphics processing units. Using this code, one can obtain intrinsic electronic transport properties of large systems described by a real-space tight-binding Hamiltonian together with one or more types of disorder. The DC Kubo conductivity is represented...
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Full-Duplex Cooperative Cognitive Radio Networks with Wireless Energy Harvesting
This paper proposes and analyzes a new full-duplex (FD) cooperative cognitive radio network with wireless energy harvesting (EH). We consider that the secondary receiver is equipped with a FD radio and acts as a FD hybrid access point (HAP), which aims to collect information from its associated EH secondary transmitt...
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Inkjet printing-based volumetric display projecting multiple full-colour 2D patterns
In this study, a method to construct a full-colour volumetric display is presented using a commercially available inkjet printer. Photoreactive luminescence materials are minutely and automatically printed as the volume elements, and volumetric displays are constructed with high resolution using easy-to-fabricate mea...
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Analysis of luminosity distributions of strong lensing galaxies: subtraction of diffuse lensed signal
Strong gravitational lensing gives access to the total mass distribution of galaxies. It can unveil a great deal of information about the lenses dark matter content when combined with the study of the lenses light profile. However, gravitational lensing galaxies, by definition, appear surrounded by point-like and dif...
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Support Estimation via Regularized and Weighted Chebyshev Approximations
We introduce a new framework for estimating the support size of an unknown distribution which improves upon known approximation-based techniques. Our main contributions include describing a rigorous new weighted Chebyshev polynomial approximation method and introducing regularization terms into the problem formulatio...
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Two-photon superbunching of pseudothermal light in a Hanbury Brown-Twiss interferometer
Two-photon superbunching of pseudothermal light is observed with single-mode continuous-wave laser light in a linear optical system. By adding more two-photon paths via three rotating ground glasses,g(2)(0) = 7.10 is experimentally observed. The second-order temporal coherence function of superbunching pseudothermal ...
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Non Relativistic Limit of Integrable QFT with fermionic excitations
The aim of this paper is to investigate the non-relativistic limit of integrable quantum field theories with fermionic fields, such as the O(N) Gross-Neveu model, the supersymmetric Sinh-Gordon and non-linear sigma models. The non-relativistic limit of these theories is implemented by a double scaling limit which con...
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Extensions of the Benson-Solomon fusion systems
The Benson-Solomon systems comprise the only known family of simple saturated fusion systems at the prime two that do not arise as the fusion system of any finite group. We determine the automorphism groups and the possible almost simple extensions of these systems and of their centric linking systems.
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Run-Wise Simulations for Imaging Atmospheric Cherenkov Telescope Arrays
We present a new paradigm for the simulation of arrays of Imaging Atmospheric Cherenkov Telescopes (IACTs) which overcomes limitations of current approaches. Up to now, all major IACT experiments rely on the same Monte-Carlo simulation strategy, using predefined observation and instrument settings. Simulations with v...
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Multi-party Poisoning through Generalized $p$-Tampering
In a poisoning attack against a learning algorithm, an adversary tampers with a fraction of the training data $T$ with the goal of increasing the classification error of the constructed hypothesis/model over the final test distribution. In the distributed setting, $T$ might be gathered gradually from $m$ data provide...
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Spectral edge behavior for eventually monotone Jacobi and Verblunsky coefficients
We consider Jacobi matrices with eventually increasing sequences of diagonal and off-diagonal Jacobi parameters. We describe the asymptotic behavior of the subordinate solution at the top of the essential spectrum, and the asymptotic behavior of the spectral density at the top of the essential spectrum. In particular...
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Web Video in Numbers - An Analysis of Web-Video Metadata
Web video is often used as a source of data in various fields of study. While specialized subsets of web video, mainly earmarked for dedicated purposes, are often analyzed in detail, there is little information available about the properties of web video as a whole. In this paper we present insights gained from the a...
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Bernoulli Correlations and Cut Polytopes
Given $n$ symmetric Bernoulli variables, what can be said about their correlation matrix viewed as a vector? We show that the set of those vectors $R(\mathcal{B}_n)$ is a polytope and identify its vertices. Those extreme points correspond to correlation vectors associated to the discrete uniform distributions on diag...
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Tensor products of NCDL-C*-algebras and the C*-algebra of the Heisenberg motion groups
We show that the tensor product $A\otimes B$ over $\mathbb{C}$ of two $C^* $-algebras satisfying the \textit{NCDL} conditions has again the same property. We use this result to describe the $C^* $-algebra of the Heisenberg motion groups $G_n = \mathbb{T}^n \ltimes \mathbb{H}_n$ as algebra of operator fields defined o...
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ViP-CNN: Visual Phrase Guided Convolutional Neural Network
As the intermediate level task connecting image captioning and object detection, visual relationship detection started to catch researchers' attention because of its descriptive power and clear structure. It detects the objects and captures their pair-wise interactions with a subject-predicate-object triplet, e.g. pe...
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Haantjes Algebras and Diagonalization
We propose the notion of Haantjes algebra, which consists of an assignment of a family of fields of operators over a differentiable manifold, with vanishing Haantjes torsion and satisfying suitable compatibility conditions among each others. Haantjes algebras naturally generalize several known interesting geometric s...
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Multipair Massive MIMO Relaying Systems with One-Bit ADCs and DACs
This paper considers a multipair amplify-and-forward massive MIMO relaying system with one-bit ADCs and one-bit DACs at the relay. The channel state information is estimated via pilot training, and then utilized by the relay to perform simple maximum-ratio combining/maximum-ratio transmission processing. Leveraging o...
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Bayesian Methods for Exoplanet Science
Exoplanet research is carried out at the limits of the capabilities of current telescopes and instruments. The studied signals are weak, and often embedded in complex systematics from instrumental, telluric, and astrophysical sources. Combining repeated observations of periodic events, simultaneous observations with ...
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Feature importance scores and lossless feature pruning using Banzhaf power indices
Understanding the influence of features in machine learning is crucial to interpreting models and selecting the best features for classification. In this work we propose the use of principles from coalitional game theory to reason about importance of features. In particular, we propose the use of the Banzhaf power in...
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Robust clustering of languages across Wikipedia growth
Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over five million articles, comparatively little is known about the behavior and growth of the remaining 283 smaller Wikipedias,...
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Attractive Heaviside-Maxwellian (Vector) Gravity from Special Relativity and Quantum Field Theory
Adopting two independent approaches (a) Lorentz-invariance of physical laws and (b) local phase invariance of quantum field theory applied to the Dirac Lagrangian for massive electrically neutral Dirac particles, we rediscovered the fundamental field equations of Heaviside Gravity (HG) of 1893 and Maxwellian Gravity ...
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Critical pairing fluctuations in the normal state of a superconductor: pseudogap and quasi-particle damping
We study the effect of critical pairing fluctuations on the electronic properties in the normal state of a clean superconductor in three dimensions. Using a functional renormalization group approach to take the non-Gaussian nature of critical fluctuations into account, we show microscopically that in the BCS regime, ...
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The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints
In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approach, which we call the Mixing method, is extremely simple to implement, has no free parameters, and typically attains an order of magnitude or better improvement in optimization ...
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GeoSeq2Seq: Information Geometric Sequence-to-Sequence Networks
The Fisher information metric is an important foundation of information geometry, wherein it allows us to approximate the local geometry of a probability distribution. Recurrent neural networks such as the Sequence-to-Sequence (Seq2Seq) networks that have lately been used to yield state-of-the-art performance on spee...
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Stochastic graph Voronoi tessellation reveals community structure
Given a network, the statistical ensemble of its graph-Voronoi diagrams with randomly chosen cell centers exhibits properties convertible into information on the network's large scale structures. We define a node-pair level measure called {\it Voronoi cohesion} which describes the probability for sharing the same Vor...
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Recursion for the smallest eigenvalue density of $β$-Wishart-Laguerre ensemble
The statistics of the smallest eigenvalue of Wishart-Laguerre ensemble is important from several perspectives. The smallest eigenvalue density is typically expressible in terms of determinants or Pfaffians. These results are of utmost significance in understanding the spectral behavior of Wishart-Laguerre ensembles a...
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Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation
Advances in image processing and computer vision in the latest years have brought about the use of visual features in artwork recommendation. Recent works have shown that visual features obtained from pre-trained deep neural networks (DNNs) perform very well for recommending digital art. Other recent works have shown...
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DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds
We propose DeepMapping, a novel registration framework using deep neural networks (DNNs) as auxiliary functions to align multiple point clouds from scratch to a globally consistent frame. We use DNNs to model the highly non-convex mapping process that traditionally involves hand-crafted data association, sensor pose ...
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The First Comparison Between Swarm-C Accelerometer-Derived Thermospheric Densities and Physical and Empirical Model Estimates
The first systematic comparison between Swarm-C accelerometer-derived thermospheric density and both empirical and physics-based model results using multiple model performance metrics is presented. This comparison is performed at the satellite's high temporal 10-s resolution, which provides a meaningful evaluation of...
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Gaussian Parsimonious Clustering Models with Covariates
We consider model-based clustering methods for continuous, correlated data that account for external information available in the presence of mixed-type fixed covariates by proposing the MoEClust suite of models. These allow covariates influence the component weights and/or component densities by modelling the parame...
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The Rice-Shapiro theorem in Computable Topology
We provide requirements on effectively enumerable topological spaces which guarantee that the Rice-Shapiro theorem holds for the computable elements of these spaces. We show that the relaxation of these requirements leads to the classes of effectively enumerable topological spaces where the Rice-Shapiro theorem does ...
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Multivariate Regression with Grossly Corrupted Observations: A Robust Approach and its Applications
This paper studies the problem of multivariate linear regression where a portion of the observations is grossly corrupted or is missing, and the magnitudes and locations of such occurrences are unknown in priori. To deal with this problem, we propose a new approach by explicitly consider the error source as well as i...
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A Deep Learning Approach for Population Estimation from Satellite Imagery
Knowing where people live is a fundamental component of many decision making processes such as urban development, infectious disease containment, evacuation planning, risk management, conservation planning, and more. While bottom-up, survey driven censuses can provide a comprehensive view into the population landscap...
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Trends in the Diffusion of Misinformation on Social Media
We measure trends in the diffusion of misinformation on Facebook and Twitter between January 2015 and July 2018. We focus on stories from 570 sites that have been identified as producers of false stories. Interactions with these sites on both Facebook and Twitter rose steadily through the end of 2016. Interactions th...
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SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications
We describe the SemEval task of extracting keyphrases and relations between them from scientific documents, which is crucial for understanding which publications describe which processes, tasks and materials. Although this was a new task, we had a total of 26 submissions across 3 evaluation scenarios. We expect the t...
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Well-posedness of the Two-dimensional Nonlinear Schrödinger Equation with Concentrated Nonlinearity
We consider a two-dimensional nonlinear Schrödinger equation with concentrated nonlinearity. In both the focusing and defocusing case we prove local well-posedness, i.e., existence and uniqueness of the solution for short times, as well as energy and mass conservation. In addition, we prove that this implies global e...
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The nilpotent variety of $W(1;n)_{p}$ is irreducible
In the late 1980s, Premet conjectured that the nilpotent variety of any finite dimensional restricted Lie algebra over an algebraically closed field of characteristic $p>0$ is irreducible. This conjecture remains open, but it is known to hold for a large class of simple restricted Lie algebras, e.g. for Lie algebras ...
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Solitons in Bose-Einstein Condensates with Helicoidal Spin-Orbit Coupling
We report on the existence and stability of freely moving solitons in a spatially inhomogeneous Bose- Einstein condensate with helicoidal spin-orbit (SO) coupling. In spite of the periodically varying parameters, the system allows for the existence of stable propagating solitons. Such states are found in the rotating...
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Possible heights of graph transformation groups
In the following text we prove that for all finite $p\geq0$ there exists a topological graph $X$ such that $\{p,p+1,p+2,\ldots\}\cup\{+\infty\}$ is the collection of all possible heights for transformation groups with phase space $X$. Moreover for all topological graph $X$ with $p$ as height of transformation group $...
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Dependencies: Formalising Semantic Catenae for Information Retrieval
Building machines that can understand text like humans is an AI-complete problem. A great deal of research has already gone into this, with astounding results, allowing everyday people to discuss with their telephones, or have their reading materials analysed and classified by computers. A prerequisite for processing...
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A New Pseudo-color Technique Based on Intensity Information Protection for Passive Sensor Imagery
Remote sensing image processing is so important in geo-sciences. Images which are obtained by different types of sensors might initially be unrecognizable. To make an acceptable visual perception in the images, some pre-processing steps (for removing noises and etc) are preformed which they affect the analysis of ima...
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Tunneling anisotropic magnetoresistance driven by magnetic phase transition
The independent control of two magnetic electrodes and spin-coherent transport in magnetic tunnel junctions are strictly required for tunneling magnetoresistance, while junctions with only one ferromagnetic electrode exhibit tunneling anisotropic magnetoresistance dependent on the anisotropic density of states with n...
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Finding Efficient Swimming Strategies in a Three Dimensional Chaotic Flow by Reinforcement Learning
We apply a reinforcement learning algorithm to show how smart particles can learn approximately optimal strategies to navigate in complex flows. In this paper we consider microswimmers in a paradigmatic three-dimensional case given by a stationary superposition of two Arnold-Beltrami-Childress flows with chaotic adve...
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Trapped imbalanced fermionic superfluids in one dimension: A variational approach
We propose and analyze a variational wave function for a population-imbalanced one-dimensional Fermi gas that allows for Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) type pairing correlations among the two fermion species, while also accounting for the harmonic confining potential. In the strongly interacting regime, we f...
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Prospects of dynamical determination of General Relativity parameter beta and solar quadrupole moment J2 with asteroid radar astronomy
We evaluated the prospects of quantifying the parameterized post-Newtonian parameter beta and solar quadrupole moment J2 with observations of near-Earth asteroids with large orbital precession rates (9 to 27 arcsec century$^{-1}$). We considered existing optical and radar astrometry, as well as radar astrometry that ...
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Modelling and Using Response Times in Online Courses
Each time a learner in a self-paced online course is trying to answer an assessment question, it takes some time to submit the answer, and if multiple attempts are allowed and the first answer was incorrect, it takes some time to submit the second attempt, and so on. Here we study the distribution of such "response t...
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Univalent Foundations and the UniMath Library
We give a concise presentation of the Univalent Foundations of mathematics outlining the main ideas, followed by a discussion of the UniMath library of formalized mathematics implementing the ideas of the Univalent Foundations (section 1), and the challenges one faces in attempting to design a large-scale library of ...
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Distributed methods for synchronization of orthogonal matrices over graphs
This paper addresses the problem of synchronizing orthogonal matrices over directed graphs. For synchronized transformations (or matrices), composite transformations over loops equal the identity. We formulate the synchronization problem as a least-squares optimization problem with nonlinear constraints. The synchron...
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Stochastic Model of SIR Epidemic Modelling
Threshold theorem is probably the most important development of mathematical epidemic modelling. Unfortunately, some models may not behave according to the threshold. In this paper, we will focus on the final outcome of SIR model with demography. The behaviour of the model approached by deteministic and stochastic mo...
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Parent Oriented Teacher Selection Causes Language Diversity
An evolutionary model for emergence of diversity in language is developed. We investigated the effects of two real life observations, namely, people prefer people that they communicate with well, and people interact with people that are physically close to each other. Clearly these groups are relatively small compare...
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Learning Role-based Graph Embeddings
Random walks are at the heart of many existing network embedding methods. However, such algorithms have many limitations that arise from the use of random walks, e.g., the features resulting from these methods are unable to transfer to new nodes and graphs as they are tied to vertex identity. In this work, we introdu...
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Quantum Emulation of Extreme Non-equilibrium Phenomena with Trapped Atoms
Ultracold atomic physics experiments offer a nearly ideal context for the investigation of quantum systems far from equilibrium. We describe three related emerging directions of research into extreme non-equilibrium phenomena in atom traps: quantum emulation of ultrafast atom-light interactions, coherent phasonic spe...
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A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
We consider solving convex-concave saddle point problems. We focus on two variants of gradient decent-ascent algorithms, Extra-gradient (EG) and Optimistic Gradient (OGDA) methods, and show that they admit a unified analysis as approximations of the classical proximal point method for solving saddle-point problems. T...
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Adaptive Multi-Step Prediction based EKF to Power System Dynamic State Estimation
Power system dynamic state estimation is essential to monitoring and controlling power system stability. Kalman filtering approaches are predominant in estimation of synchronous machine dynamic states (i.e. rotor angle and rotor speed). This paper proposes an adaptive multi-step prediction (AMSP) approach to improve ...
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Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality
A number of statistical estimation problems can be addressed by semidefinite programs (SDP). While SDPs are solvable in polynomial time using interior point methods, in practice generic SDP solvers do not scale well to high-dimensional problems. In order to cope with this problem, Burer and Monteiro proposed a non-co...
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Poisson-Nernst-Planck equations with steric effects - non-convexity and multiple stationary solutions
We study the existence and stability of stationary solutions of Poisson-Nernst- Planck equations with steric effects (PNP-steric equations) with two counter-charged species. These equations describe steady current through open ionic channels quite well. The current levels in open ionic channels are known to switch be...
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A Fast Noniterative Algorithm for Compressive Sensing Using Binary Measurement Matrices
In this paper we present a new algorithm for compressive sensing that makes use of binary measurement matrices and achieves exact recovery of ultra sparse vectors, in a single pass and without any iterations. Due to its noniterative nature, our algorithm is hundreds of times faster than $\ell_1$-norm minimization, an...
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Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
An important goal common to domain adaptation and causal inference is to make accurate predictions when the distributions for the source (or training) domain(s) and target (or test) domain(s) differ. In many cases, these different distributions can be modeled as different contexts of a single underlying system, in wh...
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Fitting ReLUs via SGD and Quantized SGD
In this paper we focus on the problem of finding the optimal weights of the shallowest of neural networks consisting of a single Rectified Linear Unit (ReLU). These functions are of the form $\mathbf{x}\rightarrow \max(0,\langle\mathbf{w},\mathbf{x}\rangle)$ with $\mathbf{w}\in\mathbb{R}^d$ denoting the weight vector...
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The meet operation in the imbalance lattice of maximal instantaneous codes: alternative proof of existence
An alternative proof is given of the existence of greatest lower bounds in the imbalance order of binary maximal instantaneous codes of a given size. These codes are viewed as maximal antichains of a given size in the infinite binary tree of 0-1 words. The proof proposed makes use of a single balancing operation inst...
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Approximating Partition Functions in Constant Time
We study approximations of the partition function of dense graphical models. Partition functions of graphical models play a fundamental role is statistical physics, in statistics and in machine learning. Two of the main methods for approximating the partition function are Markov Chain Monte Carlo and Variational Meth...
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Stability of a Volterra Integral Equation on Time Scales
In this paper, we study Hyers-Ulam stability for integral equation of Volterra type in time scale setting. Moreover we study the stability of the considered equation in Hyers-Ulam-Rassias sense. Our technique depends on successive approximation method, and we use time scale variant of induction principle to show that...
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Near-IR period-luminosity relations for pulsating stars in $ω$ Centauri (NGC 5139)
$\omega$ Centauri (NGC 5139) hosts hundreds of pulsating variable stars of different types, thus representing a treasure trove for studies of their corresponding period-luminosity (PL) relations. Our goal in this study is to obtain the PL relations for RR Lyrae, and SX Phoenicis stars in the field of the cluster, bas...
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Pseudo-deterministic Proofs
We introduce pseudo-deterministic interactive proofs (psdAM): interactive proof systems for search problems where the verifier is guaranteed with high probability to output the same output on different executions. As in the case with classical interactive proofs, the verifier is a probabilistic polynomial time algori...
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The Mechanism behind Erosive Bursts in Porous Media
Erosion and deposition during flow through porous media can lead to large erosive bursts that manifest as jumps in permeability and pressure loss. Here we reveal that the cause of these bursts is the re-opening of clogged pores when the pressure difference between two opposite sites of the pore surpasses a certain th...
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The Maximum Likelihood Degree of Toric Varieties
We study the maximum likelihood degree (ML degree) of toric varieties, known as discrete exponential models in statistics. By introducing scaling coefficients to the monomial parameterization of the toric variety, one can change the ML degree. We show that the ML degree is equal to the degree of the toric variety for...
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Low Mach number limit of a pressure correction MAC scheme for compressible barotropic flows
We study the incompressible limit of a pressure correction MAC scheme [3] for the unstationary compressible barotropic Navier-Stokes equations. Provided the initial data are well-prepared, the solution of the numerical scheme converges, as the Mach number tends to zero, towards the solution of the classical pressure ...
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