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MRA - Proof of Concept of a Multilingual Report Annotator Web Application
MRA (Multilingual Report Annotator) is a web application that translates Radiology text and annotates it with RadLex terms. Its goal is to explore the solution of translating non-English Radiology reports as a way to solve the problem of most of the Text Mining tools being developed for English. In this brief paper w...
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Contagions in Social Networks: Effects of Monophilic Contagion, Friendship Paradox and Reactive Networks
We consider SIS contagion processes over networks where, a classical assumption is that individuals' decisions to adopt a contagion are based on their immediate neighbors. However, recent literature shows that some attributes are more correlated between two-hop neighbors, a concept referred to as monophily. This moti...
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Derivation of a multilayer approach to model suspended sediment transport: application to hyperpycnal and hypopycnal plumes
We propose a multi-layer approach to simulate hyperpycnal and hypopycnal plumes in flows with free surface. The model allows to compute the vertical profile of the horizontal and the vertical components of the velocity of the fluid flow. The model can describe as well the vertical profile of the sediment concentratio...
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Continued fractions and conformal mappings for domains with angle points
Here we construct the conformal mappings with the help of continuous fractions approximations. These approximations converge to the algebraic roots $\sqrt[N]{z}$ for $N \in \mathbb{N}$ and $z$ from the right half-plane of the complex plane. We estimate both the convergence rate and the compact set of convergence. Als...
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Stochastic Activation Pruning for Robust Adversarial Defense
Neural networks are known to be vulnerable to adversarial examples. Carefully chosen perturbations to real images, while imperceptible to humans, induce misclassification and threaten the reliability of deep learning systems in the wild. To guard against adversarial examples, we take inspiration from game theory and ...
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Canonical bases of modules over one dimensional k-algebras
Let K be a field and denote by K[t], the polynomial ring with coefficients in K. Set A = K[f1,. .. , fs], with f1,. .. , fs $\in$ K[t]. We give a procedure to calculate the monoid of degrees of the K algebra M = F1A + $\times$ $\times$ $\times$ + FrA with F1,. .. , Fr $\in$ K[t]. We show some applications to the prob...
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Detecting Adversarial Samples from Artifacts
Deep neural networks (DNNs) are powerful nonlinear architectures that are known to be robust to random perturbations of the input. However, these models are vulnerable to adversarial perturbations--small input changes crafted explicitly to fool the model. In this paper, we ask whether a DNN can distinguish adversaria...
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Bots sustain and inflate striking opposition in online social systems
Societies are complex systems which tend to polarize into sub-groups of individuals with dramatically opposite perspectives. This phenomenon is reflected -- and often amplified -- in online social networks where, however, humans are no more the only players, and co-exist alongside with social bots, i.e. software-cont...
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Approximation of full-boundary data from partial-boundary electrode measurements
Measurements on a subset of the boundary are common in electrical impedance tomography, especially any electrode model can be interpreted as a partial boundary problem. The information obtained is different to full-boundary measurements as modeled by the ideal continuum model. In this study we discuss an approach to ...
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A Random Block-Coordinate Douglas-Rachford Splitting Method with Low Computational Complexity for Binary Logistic Regression
In this paper, we propose a new optimization algorithm for sparse logistic regression based on a stochastic version of the Douglas-Rachford splitting method. Our algorithm sweeps the training set by randomly selecting a mini-batch of data at each iteration, and it allows us to update the variables in a block coordina...
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Corrective Re-gridding Techniques for Non-Uniform Sampling in Time Domain Terahertz Spectroscopy
Time domain terahertz spectroscopy typically uses mechanical delay stages that inherently suffer from non-uniform sampling positions. We review, simulate, and experimentally test the ability of corrective cubic spline and Shannon re-gridding algorithms to mitigate the inherent sampling position noise. We present simu...
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Optimistic Robust Optimization With Applications To Machine Learning
Robust Optimization has traditionally taken a pessimistic, or worst-case viewpoint of uncertainty which is motivated by a desire to find sets of optimal policies that maintain feasibility under a variety of operating conditions. In this paper, we explore an optimistic, or best-case view of uncertainty and show that i...
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High Dimensional Time Series Generators
Multidimensional time series are sequences of real valued vectors. They occur in different areas, for example handwritten characters, GPS tracking, and gestures of modern virtual reality motion controllers. Within these areas, a common task is to search for similar time series. Dynamic Time Warping (DTW) is a common ...
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An isoperimetric inequality for Laplace eigenvalues on the sphere
We show that for any positive integer k, the k-th nonzero eigenvalue of the Laplace-Beltrami operator on the two-dimensional sphere endowed with a Riemannian metric of unit area, is maximized in the limit by a sequence of metrics converging to a union of k touching identical round spheres. This proves a conjecture po...
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Numerical solutions of an unsteady 2-D incompressible flow with heat and mass transfer at low, moderate, and high Reynolds numbers
In this paper, we have proposed a modified Marker-And-Cell (MAC) method to investigate the problem of an unsteady 2-D incompressible flow with heat and mass transfer at low, moderate, and high Reynolds numbers with no-slip and slip boundary conditions. We have used this method to solve the governing equations along w...
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A Dynamic Programming Solution to Bounded Dejittering Problems
We propose a dynamic programming solution to image dejittering problems with bounded displacements and obtain efficient algorithms for the removal of line jitter, line pixel jitter, and pixel jitter.
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Delayed pull-in transitions in overdamped MEMS devices
We consider the dynamics of overdamped MEMS devices undergoing the pull-in instability. Numerous previous experiments and numerical simulations have shown a significant increase in the pull-in time under DC voltages close to the pull-in voltage. Here the transient dynamics slow down as the device passes through a met...
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How ConvNets model Non-linear Transformations
In this paper, we theoretically address three fundamental problems involving deep convolutional networks regarding invariance, depth and hierarchy. We introduce the paradigm of Transformation Networks (TN) which are a direct generalization of Convolutional Networks (ConvNets). Theoretically, we show that TNs (and the...
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Volcano transition in a solvable model of oscillator glass
In 1992 a puzzling transition was discovered in simulations of randomly coupled limit-cycle oscillators. This so-called volcano transition has resisted analysis ever since. It was originally conjectured to mark the emergence of an oscillator glass, but here we show it need not. We introduce and solve a simpler model ...
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Recent advances and open questions on the susy structure of the chiral de Rham Complex
We review different constructions of the supersymmetry subalgebras of the chiral de Rham complex on special holonomy manifolds. We describe the difference between the holomorphic-anti-holomorphic sectors based on a local free ghost system vs the decomposition in left-right sectors from a local Boson-Fermion system. W...
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Toda maps, cocycles, and canonical systems
I present a discussion of the hierarchy of Toda flows that gives center stage to the associated cocycles and the maps they induce on the $m$ functions. In the second part, these ideas are then applied to canonical systems; an important feature of this discussion will be my proposal that the role of the shift on Jacob...
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The Gibbs paradox, the Landauer principle and the irreversibility associated with tilted observers
It is well known that, in the context of General Relativity, some spacetimes, when described by a congruence of comoving observers, may consist in a distribution of a perfect (non-dissipative) fluid, whereas the same spacetime as seen by a "tilted"' (Lorentz-boosted) congruence of observers, may exhibit the presence ...
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PlumX As a Potential Tool to Assess the Macroscopic Multidimensional Impact of Books
The main purpose of this macro-study is to shed light on the broad impact of books. For this purpose, the impact of a very large collection of books has been analyzed by using PlumX, an analytical tool providing a great number of different metrics provided by various tools.
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Action Robust Reinforcement Learning and Applications in Continuous Control
A policy is said to be robust if it maximizes the reward while considering a bad, or even adversarial, model. In this work we formalize two new criteria of robustness to action uncertainty. Specifically, we consider two scenarios in which the agent attempts to perform an action $\mathbf{a}$, and (i) with probability ...
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A characterization of finite vector bundles on Gauduchon astheno-Kahler manifolds
A vector bundle E on a projective variety X is called finite if it satisfies a nontrivial polynomial equation with integral coefficients. A theorem of Nori implies that E is finite if and only if the pullback of E to some finite etale Galois covering of X is trivial. We prove the same statement when X is a compact co...
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APSYNSIM: An Interactive Tool To Learn Interferometry
The APerture SYNthesis SIMulator is a simple interactive tool to help the students visualize and understand the basics of the Aperture Synthesis technique, applied to astronomical interferometers. The users can load many different interferometers and source models (and also create their own), change the observing par...
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The dimensionless dissipation rate and the Kolmogorov (1941) hypothesis of local stationarity in freely decaying isotropic turbulence
An expression for the dimensionless dissipation rate was derived from the Karman-Howarth equation by asymptotic expansion of the second- and third- order structure functions in powers of the inverse Reynolds number. The implications of the time-derivative term for the assumption of local stationarity (or local equili...
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Consistent estimation of the spectrum of trace class data augmentation algorithms
Markov chain Monte Carlo is widely used in a variety of scientific applications to generate approximate samples from intractable distributions. A thorough understanding of the convergence and mixing properties of these Markov chains can be obtained by studying the spectrum of the associated Markov operator. While sev...
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Balancing Selection Pressures, Multiple Objectives, and Neural Modularity to Coevolve Cooperative Agent Behavior
Previous research using evolutionary computation in Multi-Agent Systems indicates that assigning fitness based on team vs.\ individual behavior has a strong impact on the ability of evolved teams of artificial agents to exhibit teamwork in challenging tasks. However, such research only made use of single-objective ev...
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High-throughput nanofluidic device for one-dimensional confined detection of single fluorophores
Ensemble averaging experiments may conceal many fundamental molecular interactions. To overcome that, a high-throughput detection of single molecules or colloidal nanodots is crucial for biomedical, nanoelectronic, and solid-state applications. One-dimensional (1D) discrete flow of nanoscale objects is an efficient a...
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Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection
Joint analysis of data from multiple information repositories facilitates uncovering the underlying structure in heterogeneous datasets. Single and coupled matrix-tensor factorization (CMTF) has been widely used in this context for imputation-based recommendation from ratings, social network, and other user-item data...
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A computer algebra system for R: Macaulay2 and the m2r package
Algebraic methods have a long history in statistics. The most prominent manifestation of modern algebra in statistics can be seen in the field of algebraic statistics, which brings tools from commutative algebra and algebraic geometry to bear on statistical problems. Now over two decades old, algebraic statistics has...
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Transversal magnetoresistance and Shubnikov-de Haas oscillations in Weyl semimetals
We explore theoretically the magnetoresistance of Weyl semimetals in transversal magnetic fields away from charge neutrality. The analysis within the self-consistent Born approximation is done for the two different models of disorder: (i) short-range impurties and (ii) charged (Coulomb) impurities. For these models o...
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In Search of Lost (Mixing) Time: Adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p
The availability of data sets with large numbers of variables is rapidly increasing. The effective application of Bayesian variable selection methods for regression with these data sets has proved difficult since available Markov chain Monte Carlo methods do not perform well in typical problem sizes of interest. The ...
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Network growth models: A behavioural basis for attachment proportional to fitness
Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relati...
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On Convergence Property of Implicit Self-paced Objective
Self-paced learning (SPL) is a new methodology that simulates the learning principle of humans/animals to start learning easier aspects of a learning task, and then gradually take more complex examples into training. This new-coming learning regime has been empirically substantiated to be effective in various compute...
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Graphene quantum dots prevent alpha-synucleinopathy in Parkinson's disease
While the emerging evidence indicates that the pathogenesis of Parkinson's disease (PD) is strongly correlated to the accumulation of alpha-synuclein ({\alpha}-syn) aggregates, there has been no clinical success in anti-aggregation agents for the disease to date. Here we show that graphene quantum dots (GQDs) exhibit...
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Liu-Nagel phase diagrams in infinite dimension
We study Harmonic Soft Spheres as a model of thermal structural glasses in the limit of infinite dimensions. We show that cooling, compressing and shearing a glass lead to a Gardner transition and, hence, to a marginally stable amorphous solid as found for Hard Spheres systems. A general outcome of our results is tha...
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Networks of planar Hamiltonian systems
We introduce diffusively coupled networks where the dynamical system at each vertex is planar Hamiltonian. The problems we address are synchronisation and an analogue of diffusion-driven Turing instability for time-dependent homogeneous states. As a consequence of the underlying Hamiltonian structure there exist unus...
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Robust Tracking Using Region Proposal Networks
Recent advances in visual tracking showed that deep Convolutional Neural Networks (CNN) trained for image classification can be strong feature extractors for discriminative trackers. However, due to the drastic difference between image classification and tracking, extra treatments such as model ensemble and feature e...
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Recovering sparse graphs
We construct a fixed parameter algorithm parameterized by d and k that takes as an input a graph G' obtained from a d-degenerate graph G by complementing on at most k arbitrary subsets of the vertex set of G and outputs a graph H such that G and H agree on all but f(d,k) vertices. Our work is motivated by the first o...
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Remark on arithmetic topology
We formalize the arithmetic topology, i.e. a relationship between knots and primes. Namely, using the notion of a cluster C*-algebra we construct a functor from the category of 3-dimensional manifolds M to a category of algebraic number fields K, such that the prime ideals (ideals, resp.) in the ring of integers of K...
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Stable Architectures for Deep Neural Networks
Deep neural networks have become invaluable tools for supervised machine learning, e.g., classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such...
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Geometry and Arithmetic of Crystallographic Sphere Packings
We introduce the notion of a "crystallographic sphere packing," defined to be one whose limit set is that of a geometrically finite hyperbolic reflection group in one higher dimension. We exhibit for the first time an infinite family of conformally-inequivalent such with all radii being reciprocals of integers. We th...
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On the global convergence of the Jacobi method for symmetric matrices of order 4 under parallel strategies
The paper analyzes special cyclic Jacobi methods for symmetric matrices of order $4$. Only those cyclic pivot strategies that enable full parallelization of the method are considered. These strategies, unlike the serial pivot strategies, can force the method to be very slow or very fast within one cycle, depending on...
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Counting Motifs with Graph Sampling
Applied researchers often construct a network from a random sample of nodes in order to infer properties of the parent network. Two of the most widely used sampling schemes are subgraph sampling, where we sample each vertex independently with probability $p$ and observe the subgraph induced by the sampled vertices, a...
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Optimizing noise level for perturbing geo-location data
With the tremendous increase in the number of smart phones, app stores have been overwhelmed with applications requiring geo-location access in order to provide their users better services through personalization. Revealing a user's location to these third party apps, no matter at what frequency, is a severe privacy ...
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Hochschild Cohomology and Deformation Quantization of Affine Toric Varieties
For an affine toric variety $\mathrm{Spec}(A)$, we give a convex geometric description of the Hodge decomposition of its Hochschild cohomology. Under certain assumptions we compute the dimensions of the Hodge summands $T^1_{(i)}(A)$, generalizing the existing results about the Andre-Quillen cohomology group $T^1_{(1)...
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Adversarial Examples for Semantic Image Segmentation
Machine learning methods in general and Deep Neural Networks in particular have shown to be vulnerable to adversarial perturbations. So far this phenomenon has mainly been studied in the context of whole-image classification. In this contribution, we analyse how adversarial perturbations can affect the task of semant...
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Graphical virtual links and a polynomial of signed cyclic graphs
For a signed cyclic graph G, we can construct a unique virtual link L by taking the medial construction and convert 4-valent vertices of the medial graph to crossings according to the signs. If a virtual link can occur in this way then we say that the virtual link is graphical. In the article we shall prove that a vi...
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Exploring the Single-Particle Mobility Edge in a One-Dimensional Quasiperiodic Optical Lattice
A single-particle mobility edge (SPME) marks a critical energy separating extended from localized states in a quantum system. In one-dimensional systems with uncorrelated disorder, a SPME cannot exist, since all single-particle states localize for arbitrarily weak disorder strengths. However, if correlations are pres...
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Integral field observations of the blue compact galaxy Haro14. Star formation and feedback in dwarf galaxies
(Abridged) Low-luminosity, gas-rich blue compact galaxies (BCG) are ideal laboratories to investigate many aspects of the star formation in galaxies. We study the morphology, stellar content, kinematics, and the nebular excitation and ionization mechanism in the BCG Haro 14 by means of integral field observations wit...
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A Framework for Automated Cellular Network Tuning with Reinforcement Learning
Tuning cellular network performance against always occurring wireless impairments can dramatically improve reliability to end users. In this paper, we formulate cellular network performance tuning as a reinforcement learning (RL) problem and provide a solution to improve the signal to interference-plus-noise ratio (S...
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A Survey of Augmented Reality Navigation
Navigation has been a popular area of research in both academia and industry. Combined with maps, and different localization technologies, navigation systems have become robust and more usable. By combining navigation with augmented reality, it can be improved further to become realistic and user friendly. This paper...
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Strong Landau-quantization effects in high-magnetic-field superconductivity of a two-dimensional multiple-band metal near the Lifshitz transition
We investigate the onset of superconductivity in magnetic field for a clean two-dimensional multiple-band superconductor in the vicinity of the Lifshitz transition when one of the bands is very shallow. Due to small number of carriers in this band, the quasiclassical Werthamer-Helfand approximation breaks down and La...
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On boundary extension of mappings in metric spaces in terms of prime ends
We study the boundary behavior of the so-called ring $Q$-mappings obtained as a natural generalization of mappings with bounded distortion. We establish a series of conditions imposed on a function $Q(x)$ for the continuous extension of given mappings with respect to prime ends in domains with regular boundaries in m...
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Temporally Evolving Community Detection and Prediction in Content-Centric Networks
In this work, we consider the problem of combining link, content and temporal analysis for community detection and prediction in evolving networks. Such temporal and content-rich networks occur in many real-life settings, such as bibliographic networks and question answering forums. Most of the work in the literature...
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A Robust Utility Learning Framework via Inverse Optimization
In many smart infrastructure applications flexibility in achieving sustainability goals can be gained by engaging end-users. However, these users often have heterogeneous preferences that are unknown to the decision-maker tasked with improving operational efficiency. Modeling user interaction as a continuous game bet...
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Evaluating stochastic seeding strategies in networks
When trying to maximize the adoption of a behavior in a population connected by a social network, it is common to strategize about where in the network to seed the behavior, often with an element of randomness. Selecting seeds uniformly at random is a basic but compelling strategy in that it distributes seeds broadly...
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Flux noise in a superconducting transmission line
We study a superconducting transmission line (TL) formed by distributed LC oscillators and excited by external magnetic fluxes which are aroused from random magnetization (A) placed in substrate or (B) distributed at interfaces of a two-wire TL. Low-frequency dynamics of a random magnetic field is described based on ...
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Relativistic Newtonian Dynamics for Objects and Particles
Relativistic Newtonian Dynamics (RND) was introduced in a series of recent papers by the author, in partial cooperation with J. M. Steiner. RND was capable of describing non-classical behavior of motion under a central attracting force. RND incorporates the influence of potential energy on spacetime in Newtonian dyna...
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Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors
This paper introduces a new sparse spatio-temporal structured Gaussian process regression framework for online and offline Bayesian inference. This is the first framework that gives a time-evolving representation of the interdependencies between the components of the sparse signal of interest. A hierarchical Gaussian...
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Answer Set Solving with Bounded Treewidth Revisited
Parameterized algorithms are a way to solve hard problems more efficiently, given that a specific parameter of the input is small. In this paper, we apply this idea to the field of answer set programming (ASP). To this end, we propose two kinds of graph representations of programs to exploit their treewidth as a para...
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Community structure: A comparative evaluation of community detection methods
Discovering community structure in complex networks is a mature field since a tremendous number of community detection methods have been introduced in the literature. Nevertheless, it is still very challenging for practioners to determine which method would be suitable to get insights into the structural information ...
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Classification of isoparametric submanifolds admitting a reflective focal submanifold in symmetric spaces of non-compact type
In this paper, we assume that all isoparametric submanifolds have flat section. The main purpose of this paper is to prove that, if a full irreducible complete isoparametric submanifold of codimension greater than one in a symmetric space of non-compact type admits a reflective focal submanifold and if it of real ana...
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Training Group Orthogonal Neural Networks with Privileged Information
Learning rich and diverse representations is critical for the performance of deep convolutional neural networks (CNNs). In this paper, we consider how to use privileged information to promote inherent diversity of a single CNN model such that the model can learn better representations and offer stronger generalizatio...
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Antiunitary representations and modular theory
Antiunitary representations of Lie groups take values in the group of unitary and antiunitary operators on a Hilbert space H. In quantum physics, antiunitary operators implement time inversion or a PCT symmetry, and in the modular theory of operator algebras they arise as modular conjugations from cyclic separating v...
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ARTENOLIS: Automated Reproducibility and Testing Environment for Licensed Software
Motivation: Automatically testing changes to code is an essential feature of continuous integration. For open-source code, without licensed dependencies, a variety of continuous integration services exist. The COnstraint-Based Reconstruction and Analysis (COBRA) Toolbox is a suite of open-source code for computationa...
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Droplet states in quantum XXZ spin systems on general graphs
We study XXZ spin systems on general graphs. In particular, we describe the formation of droplet states near the bottom of the spectrum in the Ising phase of the model, where the Z-term dominates the XX-term. As key tools we use particle number conservation of XXZ systems and symmetric products of graphs with their a...
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Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning
There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of meta-algorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the Conditional Average Treatm...
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Counting triangles formula for the first Chern class of a circle bundle
We consider the problem of the combinatorial computation of the first Chern class of a circle bundle. N.Mnev found such a formula in terms of canonical shellings. It represents certain invariant of a triangulation computed by analyzing cyclic word in 3-character alphabet associated to the bundle. This curvature is a ...
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Probing homogeneity with standard candles
We show that standard candles can provide some valuable information about the density contrast, which could be particularly important at redshifts where other observations are not available. We use an inversion method to reconstruct the local radial density profile from luminosity distance observations assuming backg...
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Fabrication tolerant chalcogenide mid-infrared multimode interference coupler design with application for Bracewell nulling interferometry
Understanding exoplanet formation and finding potentially habitable exoplanets is vital to an enhanced understanding of the universe. The use of nulling interferometry to strongly attenuate the central starlight provides the opportunity to see objects closer to the star than ever before. Given that exoplanets are usu...
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Accurate Bayesian Data Classification without Hyperparameter Cross-validation
We extend the standard Bayesian multivariate Gaussian generative data classifier by considering a generalization of the conjugate, normal-Wishart prior distribution and by deriving the hyperparameters analytically via evidence maximization. The behaviour of the optimal hyperparameters is explored in the high-dimensio...
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Offline Biases in Online Platforms: a Study of Diversity and Homophily in Airbnb
How diverse are sharing economy platforms? Are they fair marketplaces, where all participants operate on a level playing field, or are they large-scale online aggregators of offline human biases? Often portrayed as easy-to-access digital spaces whose participants receive equal opportunities, such platforms have recen...
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Parameter Estimation for Thurstone Choice Models
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets...
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Quantitative modeling and analysis of bifurcation-induced bursting
Modeling and parameter estimation for neuronal dynamics are often challenging because many parameters can range over orders of magnitude and are difficult to measure experimentally. Moreover, selecting a suitable model complexity requires a sufficient understanding of the model's potential use, such as highlighting e...
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Uniqueness and radial symmetry of minimizers for a nonlocal variational problem
In this paper we prove the uniqueness and radial symmetry of minimizers for variational problems that model several phenomena. The uniqueness is a consequence of the convexity of the functional. The main technique is Fourier transform of tempered distributions.
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Improved Accounting for Differentially Private Learning
We consider the problem of differential privacy accounting, i.e. estimation of privacy loss bounds, in machine learning in a broad sense. We propose two versions of a generic privacy accountant suitable for a wide range of learning algorithms. Both versions are derived in a simple and principled way using well-known ...
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Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ
Scattertext is an open source tool for visualizing linguistic variation between document categories in a language-independent way. The tool presents a scatterplot, where each axis corresponds to the rank-frequency a term occurs in a category of documents. Through a tie-breaking strategy, the tool is able to display t...
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Tight contact structures on Seifert surface complements
We consider complements of standard Seifert surfaces of special alternating links. On these handlebodies, we use Honda's method to enumerate those tight contact structures whose dividing sets are isotopic to the link, and find their number to be the leading coefficient of the Alexander polynomial. The Euler classes o...
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Modular invariant representations of the $\mathcal{N}=2$ superconformal algebra
We compute the modular transformation formula of the characters for a certain family of (finitely or uncountably many) simple modules over the simple $\mathcal{N}=2$ vertex operator superalgebra of central charge $c_{p,p'}=3\left(1-\frac{2p'}{p}\right),$ where $(p,p')$ is a pair of coprime positive integers such that...
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The CODALEMA/EXTASIS experiment: Contributions to the 35th International Cosmic Ray Conference (ICRC 2017)
Contributions of the CODALEMA/EXTASIS experiment to the 35th International Cosmic Ray Conference, 12-20 July 2017, Busan, South Korea.
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Distributed Kernel K-Means for Large Scale Clustering
Clustering samples according to an effective metric and/or vector space representation is a challenging unsupervised learning task with a wide spectrum of applications. Among several clustering algorithms, k-means and its kernelized version have still a wide audience because of their conceptual simplicity and efficac...
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The Origin of Solar Filament Plasma Inferred from in situ Observations of Elemental Abundances
Solar filaments/prominences are one of the most common features in the corona, which may lead to energetic coronal mass ejections (CMEs) and flares when they erupt. Filaments are about one hundred times cooler and denser than the coronal material, and physical understanding of their material origin remains controvers...
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Distributed Stochastic Optimization via Adaptive SGD
Stochastic convex optimization algorithms are the most popular way to train machine learning models on large-scale data. Scaling up the training process of these models is crucial, but the most popular algorithm, Stochastic Gradient Descent (SGD), is a serial method that is surprisingly hard to parallelize. In this p...
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Bilipschitz Equivalence of Trees and Hyperbolic Fillings
We combine conditions found in [Wh] with results from [MPR] to show that quasi-isometries between uniformly discrete bounded geometry spaces that satisfy linear isoperimetric inequalities are within bounded distance to bilipschitz equivalences. We apply this result to regularly branching trees and hyperbolic fillings...
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On the contribution of thermal excitation to the total 630.0 nm emissions in the northern cusp ionosphere
Direct impact excitation by precipitating electrons is believed to be the main source of 630.0 nm emissions in the cusp ionosphere. However, this paper investigates a different source, 630.0 emissions caused by thermally excited atomic oxygen O$(^{1}$D) when high electron temperature prevail in the cusp. On 22 Januar...
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Dose finding for new vaccines: the role for immunostimulation/immunodynamic modelling
Current methods to optimize vaccine dose are purely empirically based, whereas in the drug development field, dosing determinations use far more advanced quantitative methodology to accelerate decision-making. Applying these established methods in the field of vaccine development may reduce the currently large clinic...
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On Learning Mixtures of Well-Separated Gaussians
We consider the problem of efficiently learning mixtures of a large number of spherical Gaussians, when the components of the mixture are well separated. In the most basic form of this problem, we are given samples from a uniform mixture of $k$ standard spherical Gaussians, and the goal is to estimate the means up to...
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Sylvester's Problem and Mock Heegner Points
We prove that if $p \equiv 4,7 \pmod{9}$ is prime and $3$ is not a cube modulo $p$, then both of the equations $x^3+y^3=p$ and $x^3+y^3=p^2$ have a solution with $x,y \in \mathbb{Q}$.
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Community Detection in the Network of German Princes in 1225: a Case Study
Many social networks exhibit some underlying community structure. In particular, in the context of historical research, clustering of different groups into warring or friendly factions can lead to a better understanding of how conflicts may arise, and whether they could be avoided or not. In this work we study the cr...
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Coupon Advertising in Online Social Systems: Algorithms and Sampling Techniques
Online social systems have become important platforms for viral marketing where the advertising of products is carried out with the communication of users. After adopting the product, the seed buyers may spread the information to their friends via online messages e.g. posts and tweets. In another issue, electronic co...
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Statistical study of auroral omega bands
The presence of very few statistical studies on auroral omega bands motivated us to test-use a semi-automatic method for identifying large-scale undulations of the diffuse aurora boundary and to investigate their occurrence. Five identical all-sky cameras with overlapping fields of view provided data for 438 auroral ...
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Efficient Lightweight Encryption Algorithm for Smart Video Applications
The future generation networks: Internet of things (IoT), in combination with the advanced computer vision techniques poses new challenges for securing videos for end-users. The visual devices generally have constrained resources in respects to their low computation power, small memory with limited power supply. Ther...
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Inter-site pair superconductivity: origins and recent validation experiments
The challenge of understanding high-temperature superconductivity has led to a plethora of ideas, but 30 years after its discovery in cuprates, very few have achieved convincing experimental validation. While Hubbard and t-J models were given a lot of attention, a number of recent experiments appear to give decisive ...
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Non-standard FDTD implementation of the Schrödinger equation
In this work, we apply the Cole's non-standard form of the FDTD to solve the time dependent Schrödinger equation. We deduce the equations for the non-standard FDTD considering an electronic wave function in the presence of potentials which can be higher or lower in comparison with the energy of the electron. The non-...
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The magnetic and electronic properties of Oxyselenides - influence of transition metal ions and lanthanides
Magnetic oxyselenides have been the topic of research for several decades being first of interest in the context of photoconductivity and thermoelectricity owing to their intrinsic semiconducting properties and ability to tune the energy gap through metal ion substitution. More recently, interest in the oxyselenides ...
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Localizing the Object Contact through Matching Tactile Features with Visual Map
This paper presents a novel framework for integration of vision and tactile sensing by localizing tactile readings in a visual object map. Intuitively, there are some correspondences, e.g., prominent features, between visual and tactile object identification. To apply it in robotics, we propose to localize tactile re...
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Scattering Cross Section in a Cylindrical anisotropic layered metamaterial
To design a uniaxial anisotropic metamaterial a layered cylindrical metamaterial is introduced for TE polarization. Unlike to the previous work, which the layers were in radial direction, here the layers are in azimuthal direction. Scattering efficiency for this metamaterial in different frequency is analyzed with so...
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