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Excitonic effects in third harmonic generation: the case of carbon nanotubes and nanoribbons
Linear and nonlinear optical properties of low dimensional nanostructures have attracted a large interest in the scientific community as tools to probe the strong confinement of the electrons and for possible applications in optoelectronic devices. In particular it has been shown that the linear optical response of c...
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A general family of congruences for Bernoulli numbers
We prove a general family of congruences for Bernoulli numbers whose index is a polynomial function of a prime, modulo a power of that prime. Our family generalizes many known results, including the von Staudt--Clausen theorem and Kummer's congruence.
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The Fourier algebra of a rigid $C^{\ast}$-tensor category
Completely positive and completely bounded mutlipliers on rigid $C^{\ast}$-tensor categories were introduced by Popa and Vaes. Using these notions, we define and study the Fourier-Stieltjes algebra, the Fourier algebra and the algebra of completely bounded multipliers of a rigid $C^{\ast}$-tensor category. The rich s...
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On lattice path matroid polytopes: integer points and Ehrhart polynomial
In this paper we investigate the number of integer points lying in dilations of lattice path matroid polytopes. We give a characterization of such points as polygonal paths in the diagram of the lattice path matroid. Furthermore, we prove that lattice path matroid polytopes are affinely equivalent to a family of dist...
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Quantum effects and magnetism in the spatially distributed DNA molecules
Electronic and magnetic properties of DNA structures doped by simple and transition d- and f-metal ions (Gd, La, Cu, Zn, Au) are reviewed. Both one- and two dimensional systems are considered. A particular attention is paid to gadolinium and copper doped DNA systems, their unusual magnetism being treated. The problem...
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A Stochastic Model for Short-Term Probabilistic Forecast of Solar Photo-Voltaic Power
In this paper, a stochastic model with regime switching is developed for solar photo-voltaic (PV) power in order to provide short-term probabilistic forecasts. The proposed model for solar PV power is physics inspired and explicitly incorporates the stochasticity due to clouds using different parameters addressing th...
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Stability and elasticity of metastable solid solutions and superlattices in the MoN-TaN system: a first-principles study
Employing ab initio calculations, we discuss chemical, mechanical, and dynamical stability of MoN-TaN solid solutions together with cubic-like MoN/TaN superlattices, as another materials design concept. Hexagonal-type structures based on low-energy modifications of MoN and TaN are the most stable ones over the whole ...
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High Accuracy Classification of Parkinson's Disease through Shape Analysis and Surface Fitting in $^{123}$I-Ioflupane SPECT Imaging
Early and accurate identification of parkinsonian syndromes (PS) involving presynaptic degeneration from non-degenerative variants such as Scans Without Evidence of Dopaminergic Deficit (SWEDD) and tremor disorders, is important for effective patient management as the course, therapy and prognosis differ substantiall...
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End-to-End Learning for Structured Prediction Energy Networks
Structured Prediction Energy Networks (SPENs) are a simple, yet expressive family of structured prediction models (Belanger and McCallum, 2016). An energy function over candidate structured outputs is given by a deep network, and predictions are formed by gradient-based optimization. This paper presents end-to-end le...
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Self-compression of spatially limited laser pulses in a system of coupled light-guides
The self-action features of wave packets propagating in a two-dimensional system of equidistantly arranged fibers are studied analytically and numerically on the basis of the discrete nonlinear Schrödinger equation. Self-consistent equations for the characteristic scales of a Gaussian wave packet are derived on the b...
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A Hand-Held Multimedia Translation and Interpretation System with Application to Diet Management
We propose a network independent, hand-held system to translate and disambiguate foreign restaurant menu items in real-time. The system is based on the use of a portable multimedia device, such as a smartphones or a PDA. An accurate and fast translation is obtained using a Machine Translation engine and a context-spe...
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Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees
In this paper, we show how controllers created using data driven designs, such as neural networks, can be used together with model based controllers in a way that combines the performance guarantees of the model based controllers with the efficiency of the data driven controllers. The considered performance guarantee...
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Drop pattern resulting from the breakup of a bidimensional grid of liquid filaments
A rectangular grid formed by liquid filaments on a partially wetting substrate evolves in a series of breakups leading to arrays of drops with different shapes distributed in a rather regular bidimensional pattern. Our study is focused on the configuration produced when two long parallel filaments of silicone oil, wh...
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FIRED: Frequent Inertial Resets with Diversification for Emerging Commodity Cyber-Physical Systems
A Cyber-Physical System (CPS) is defined by its unique characteristics involving both the cyber and physical domains. Their hybrid nature introduces new attack vectors, but also provides an opportunity to design new security defenses. In this paper, we present a new domain-specific security mechanism, FIRED, that lev...
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Modelling of Dictyostelium Discoideum Movement in Linear Gradient of Chemoattractant
Chemotaxis is a ubiquitous biological phenomenon in which cells detect a spatial gradient of chemoattractant, and then move towards the source. Here we present a position-dependent advection-diffusion model that quantitatively describes the statistical features of the chemotactic motion of the social amoeba {\it Dict...
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Cycles of Activity in the Jovian Atmosphere
Jupiter's banded appearance may appear unchanging to the casual observer, but closer inspection reveals a dynamic, ever-changing system of belts and zones with distinct cycles of activity. Identification of these long-term cycles requires access to datasets spanning multiple jovian years, but explaining them requires...
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Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
This paper offers a methodological contribution at the intersection of machine learning and operations research. Namely, we propose a methodology to quickly predict tactical solutions to a given operational problem. In this context, the tactical solution is less detailed than the operational one but it has to be comp...
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Consistent Approval-Based Multi-Winner Rules
This paper is an axiomatic study of consistent approval-based multi-winner rules, i.e., voting rules that select a fixed-size group of candidates based on approval ballots. We introduce the class of counting rules, provide an axiomatic characterization of this class and, in particular, show that counting rules are co...
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Bridge functional for the molecular density functional theory with consistent pressure and surface tension and its importance for solvation in water
We address the problem of predicting the solvation free energy and equilibrium solvent density profile in fews minutes from the molecular density functional theory beyond the usual hypernetted-chain approximation. We introduce a bridge functional of a coarse-grained, weighted solvent density. In few minutes at most, ...
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Fourier multiplier theorems for Triebel-Lizorkin spaces
In this paper we study sharp generalizations of $\dot{F}_p^{0,q}$ multiplier theorem of Mikhlin-Hörmander type. The class of multipliers that we consider involves Herz spaces $K_u^{s,t}$. Plancherel's theorem proves $\widehat{L_s^2}=K_2^{s,2}$ and we study the optimal triple $(u,t,s)$ for which $\sup_{k\in\mathbb{Z}}...
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Individual dynamic predictions using landmarking and joint modelling: validation of estimators and robustness assessment
After the diagnosis of a disease, one major objective is to predict cumulative probabilities of events such as clinical relapse or death from the individual information collected up to a prediction time, including usually biomarker repeated measurements. Several competing estimators have been proposed to calculate th...
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A partial converse to the Andreotti-Grauert theorem
Let $X$ be a smooth projective manifold with $\dim_\mathbb{C} X=n$. We show that if a line bundle $L$ is $(n-1)$-ample, then it is $(n-1)$-positive. This is a partial converse to the Andreotti-Grauert theorem. As an application, we show that a projective manifold $X$ is uniruled if and only if there exists a Hermitia...
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Ab initio study of magnetocrystalline anisotropy, magnetostriction, and Fermi surface of L10 FeNi (tetrataenite)
The ordered L1$_0$ FeNi phase (tetrataenite) is recently considered as a promising candidate for the rare-earth free permanent magnets applications. In this work we calculate several characteristics of the L1$_0$ FeNi, where most of the results come form the fully relativistic full potential FPLO method with the gene...
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Modular groups, Hurwitz classes and dynamic portraits of NET maps
An orientation-preserving branched covering $f: S^2 \to S^2$ is a nearly Euclidean Thurston (NET) map if each critical point is simple and its postcritical set has exactly four points. Inspired by classical, non-dynamical notions such as Hurwitz equivalence of branched covers of surfaces, we develop invariants for su...
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Proximal Planar Shape Signatures. Homology Nerves and Descriptive Proximity
This article introduces planar shape signatures derived from homology nerves, which are intersecting 1-cycles in a collection of homology groups endowed with a proximal relator (set of nearness relations) that includes a descriptive proximity. A 1-cycle is a closed, connected path with a zero boundary in a simplicial...
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Asymptotic analysis of a 2D overhead crane with input delays in the boundary control
The paper investigates the asymptotic behavior of a 2D overhead crane with input delays in the boundary control. A linear boundary control is proposed. The main feature of such a control lies in the facts that it solely depends on the velocity but under the presence of time-delays. We end-up with a closed-loop system...
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Abrupt disappearance and reemergence of the SU(2) and SU(4) Kondo effects due to population inversion
The interplay of almost degenerate levels in quantum dots and molecular junctions with possibly different couplings to the reservoirs has lead to many observable phenomena, such as the Fano effect, transmission phase slips and the SU(4) Kondo effect. Here we predict a dramatic repeated disappearance and reemergence o...
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Stochastic Global Optimization Algorithms: A Systematic Formal Approach
As we know, some global optimization problems cannot be solved using analytic methods, so numeric/algorithmic approaches are used to find near to the optimal solutions for them. A stochastic global optimization algorithm (SGoal) is an iterative algorithm that generates a new population (a set of candidate solutions) ...
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A complete characterization of optimal dictionaries for least squares representation
Dictionaries are collections of vectors used for representations of elements in Euclidean spaces. While recent research on optimal dictionaries is focussed on providing sparse (i.e., $\ell_0$-optimal,) representations, here we consider the problem of finding optimal dictionaries such that representations of samples o...
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Least Square Variational Bayesian Autoencoder with Regularization
In recent years Variation Autoencoders have become one of the most popular unsupervised learning of complicated distributions.Variational Autoencoder (VAE) provides more efficient reconstructive performance over a traditional autoencoder. Variational auto enocders make better approximaiton than MCMC. The VAE defines ...
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Rational points of rationally simply connected varieties over global function fields
A complex projective manifold is rationally connected, resp. rationally simply connected, if finite subsets are connected by a rational curve, resp. the spaces parameterizing these connecting rational curves are themselves rationally connected. We prove that a projective scheme over a global function field with vanis...
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A Koszul sign map
We define a Koszul sign map encoding the Koszul sign convention. A cohomological interpretation is given.
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Combining low- to high-resolution transit spectroscopy of HD 189733b. Linking the troposphere and the thermosphere of a hot gas giant
Space-borne low-to medium-resolution (R~10^2-10^3) transmission spectroscopy of atmospheres detect the broadest spectral features (alkali doublets, molecular bands, scattering), while high-resolution (R~10^5), ground-based observations probe the sharpest features (cores of the alkali lines, molecular lines).The two t...
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Factorizations in Modules and Splitting Multiplicatively Closed Subsets
We introduce the concept of multiplicatively closed subsets of a commutative ring $R$ which split an $R$-module $M$ and study factorization properties of elements of $M$ with respect to such a set. Also we demonstrate how one can utilize this concept to investigate factorization properties of $R$ and deduce some Naga...
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ROPPERI - A TPC readout with GEMs, pads and Timepix
The concept of a hybrid readout of a time projection chamber is presented. It combines a GEM-based amplification and a pad-based anode plane with a pixel chip as readout electronics. This way, a high granularity enabling to identify electron clusters from the primary ionisation is achieved as well as flexibility and ...
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A Shared Task on Bandit Learning for Machine Translation
We introduce and describe the results of a novel shared task on bandit learning for machine translation. The task was organized jointly by Amazon and Heidelberg University for the first time at the Second Conference on Machine Translation (WMT 2017). The goal of the task is to encourage research on learning machine t...
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Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction
Learning with Reproducing Kernel Hilbert Spaces (RKHS) has been widely used in many scientific disciplines. Because a RKHS can be very flexible, it is common to impose a regularization term in the optimization to prevent overfitting. Standard RKHS learning employs the squared norm penalty of the learning function. De...
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Controlling of blow-up responses by a nonlinear $\cal{PT}$ symmetric coupling
We investigate the dynamics of a coupled waveguide system with competing linear and nonlinear loss-gain profiles which can facilitate power saturation. We show the usefulness of the model in achieving unidirectional beam propagation. In this regard, the considered type of coupled waveguide system has two drawbacks, (...
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Text Extraction From Texture Images Using Masked Signal Decomposition
Text extraction is an important problem in image processing with applications from optical character recognition to autonomous driving. Most of the traditional text segmentation algorithms consider separating text from a simple background (which usually has a different color from texts). In this work we consider sepa...
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Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting
Long-lead forecasting for spatio-temporal systems can often entail complex nonlinear dynamics that are difficult to specify it a priori. Current statistical methodologies for modeling these processes are often highly parameterized and thus, challenging to implement from a computational perspective. One potential pars...
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Using Convex Optimization of Autocorrelation with Constrained Support and Windowing for Improved Phase Retrieval Accuracy
In imaging modalities recording diffraction data, the original image can be reconstructed assuming known phases. When phases are unknown, oversampling and a constraint on the support region in the original object can be used to solve a non-convex optimization problem. Such schemes are ill-suited to find the optimum s...
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Parametrizations, weights, and optimal prediction: Part 1
We consider the problem of the annual mean temperature prediction. The years taken into account and the corresponding annual mean temperatures are denoted by $0,\ldots, n$ and $t_0$, $\ldots$, $t_n$, respectively. We propose to predict the temperature $t_{n+1}$ using the data $t_0$, $\ldots$, $t_n$. For each $0\leq l...
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Time irreversibility from symplectic non-squeezing
The issue of how time reversible microscopic dynamics gives rise to macroscopic irreversible processes has been a recurrent issue in Physics since the time of Boltzmann whose ideas shaped, and essentially resolved, such an apparent contradiction. Following Boltzmann's spirit and ideas, but employing Gibbs's approach,...
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On Optimal Weighted-Delay Scheduling in Input-Queued Switches
Motivated by relatively few delay-optimal scheduling results, in comparison to results on throughput optimality, we investigate an input-queued switch scheduling problem in which the objective is to minimize a linear function of the queue-length vector. Theoretical properties of variants of the well-known MaxWeight s...
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Hausdorff dimension, projections, intersections, and Besicovitch sets
This is a survey on recent developments on the Hausdorff dimension of projections and intersections for general subsets of Euclidean spaces, with an emphasis on estimates of the Hausdorff dimension of exceptional sets and on restricted projection families. We shall also discuss relations between projections and Hausd...
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Interpolating between matching and hedonic pricing models
We consider the theoretical properties of a model which encompasses bi-partite matching under transferable utility on the one hand, and hedonic pricing on the other. This framework is intimately connected to tripartite matching problems (known as multi-marginal optimal transport problems in the mathematical literatur...
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Modeling and predicting the short term evolution of the Geomagnetic field
The coupled evolution of the magnetic field and the flow at the Earth's core mantle boundary is modeled within the 1900.0-2014.0 time period. To constraint the dynamical behavior of the system with a core field model deriving from direct measurements of the Earth's magnetic field we used an Ensemble Kalman filter alg...
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Analysing the Potential of BLE to Support Dynamic Broadcasting Scenarios
In this paper, we present a novel approach for broadcasting information based on a Bluetooth Low Energy (BLE) ibeacon technology. We propose a dynamic method that uses a combination of Wi-Fi and BLE technology where every technology plays a part in a user discovery and broadcasting process. In such system, a specific...
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$\texttt{PyTranSpot}$ - A tool for multiband light curve modeling of planetary transits and stellar spots
Several studies have shown that stellar activity features, such as occulted and non-occulted starspots, can affect the measurement of transit parameters biasing studies of transit timing variations and transmission spectra. We present $\texttt{PyTranSpot}$, which we designed to model multiband transit light curves sh...
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Interplay of spatial dynamics and local adaptation shapes species lifetime distributions and species-area relationships
The distributions of species lifetimes and species in space are related, since species with good local survival chances have more time to colonize new habitats and species inhabiting large areas have higher chances to survive local disturbances. Yet, both distributions have been discussed in mostly separate communiti...
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Routing Symmetric Demands in Directed Minor-Free Graphs with Constant Congestion
The problem of routing in graphs using node-disjoint paths has received a lot of attention and a polylogarithmic approximation algorithm with constant congestion is known for undirected graphs [Chuzhoy and Li 2016] and [Chekuri and Ene 2013]. However, the problem is hard to approximate within polynomial factors on di...
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Fast sampling of parameterised Gaussian random fields
Gaussian random fields are popular models for spatially varying uncertainties, arising for instance in geotechnical engineering, hydrology or image processing. A Gaussian random field is fully characterised by its mean function and covariance operator. In more complex models these can also be partially unknown. In th...
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Universal Scalable Robust Solvers from Computational Information Games and fast eigenspace adapted Multiresolution Analysis
We show how the discovery of robust scalable numerical solvers for arbitrary bounded linear operators can be automated as a Game Theory problem by reformulating the process of computing with partial information and limited resources as that of playing underlying hierarchies of adversarial information games. When the ...
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Preliminary Experiments using Subjective Logic for the Polyrepresentation of Information Needs
According to the principle of polyrepresentation, retrieval accuracy may improve through the combination of multiple and diverse information object representations about e.g. the context of the user, the information sought, or the retrieval system. Recently, the principle of polyrepresentation was mathematically expr...
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General Robust Bayes Pseudo-Posterior: Exponential Convergence results with Applications
Although Bayesian inference is an immensely popular paradigm among a large segment of scientists including statisticians, most of the applications consider the objective priors and need critical investigations (Efron, 2013, Science). And although it has several optimal properties, one major drawback of Bayesian infer...
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The $H_0$ tension in light of vacuum dynamics in the Universe
Despite the outstanding achievements of modern cosmology, the classical dispute on the precise value of $H_0$, which is the first ever parameter of modern cosmology and one of the prime parameters in the field, still goes on and on after over half a century of measurements. Recently the dispute came to the spotlight ...
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On certain type of difference polynomials of meromorphic functions
In this paper, we investigate zeros of difference polynomials of the form $f(z)^nH(z, f)-s(z)$, where $f(z)$ is a meromorphic function, $H(z, f)$ is a difference polynomial of $f(z)$ and $s(z)$ is a small function. We first obtain some inequalities for the relationship of the zero counting function of $f(z)^nH(z, f)-...
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Teaching methods are erroneous: approaches which lead to erroneous end-user computing
If spreadsheets are not erroneous then who, or what, is? Research has found that end-users are. If end-users are erroneous then why are they? Research has found that responsibility lies with human beings' fast and slow thinking modes and the inappropriate way they use them. If we are aware of this peculiarity of huma...
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Modulational Instability in Linearly Coupled Asymmetric Dual-Core Fibers
We investigate modulational instability (MI) in asymmetric dual-core nonlinear directional couplers incorporating the effects of the differences in effective mode areas and group velocity dispersions, as well as phase- and group-velocity mismatches. Using coupled-mode equations for this system, we identify MI conditi...
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Discovering Visual Concept Structure with Sparse and Incomplete Tags
Discovering automatically the semantic structure of tagged visual data (e.g. web videos and images) is important for visual data analysis and interpretation, enabling the machine intelligence for effectively processing the fast-growing amount of multi-media data. However, this is non-trivial due to the need for joint...
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GALILEO: A Generalized Low-Entropy Mixture Model
We present a new method of generating mixture models for data with categorical attributes. The keys to this approach are an entropy-based density metric in categorical space and annealing of high-entropy/low-density components from an initial state with many components. Pruning of low-density components using the ent...
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Approximation by mappings with singular Hessian minors
Let $\Omega\subset\mathbb R^n$ be a Lipschitz domain. Given $1\leq p<k\leq n$ and any $u\in W^{2,p}(\Omega)$ belonging to the little Hölder class $c^{1,\alpha}$, we construct a sequence $u_j$ in the same space with $\operatorname{rank}D^2u_j<k$ almost everywhere such that $u_j\to u$ in $C^{1,\alpha}$ and weakly in $W...
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Adaptive Cardinality Estimation
In this paper we address cardinality estimation problem which is an important subproblem in query optimization. Query optimization is a part of every relational DBMS responsible for finding the best way of the execution for the given query. These ways are called plans. The execution time of different plans may differ...
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Non-stationary Stochastic Optimization under $L_{p,q}$-Variation Measures
We consider a non-stationary sequential stochastic optimization problem, in which the underlying cost functions change over time under a variation budget constraint. We propose an $L_{p,q}$-variation functional to quantify the change, which yields less variation for dynamic function sequences whose changes are constr...
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Spin conductance of YIG thin films driven from thermal to subthermal magnons regime by large spin-orbit torque
We report a study on spin conductance in ultra-thin films of Yttrium Iron Garnet (YIG), where spin transport is provided by propagating spin waves, that are generated and detected by direct and inverse spin Hall effects in two Pt wires deposited on top. While at low current the spin conductance is dominated by transp...
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Mathematical renormalization in quantum electrodynamics via noncommutative generating series
In this work, we focus on on the approach by noncommutative formal power series to study the combinatorial aspects of the renormalization at the singularities in $\{0,1,+\infty\}$ of the solutions of nonlinear differential equations involved in quantum electrodynamics.
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Inference in Deep Networks in High Dimensions
Deep generative networks provide a powerful tool for modeling complex data in a wide range of applications. In inverse problems that use these networks as generative priors on data, one must often perform inference of the inputs of the networks from the outputs. Inference is also required for sampling during stochast...
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Differentially Private Variational Dropout
Deep neural networks with their large number of parameters are highly flexible learning systems. The high flexibility in such networks brings with some serious problems such as overfitting, and regularization is used to address this problem. A currently popular and effective regularization technique for controlling t...
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Persistent Currents in Ferromagnetic Condensates
Persistent currents in Bose condensates with a scalar order parameter are stabilized by the topology of the order parameter manifold. In condensates with multicomponent order parameters it is topologically possible for supercurrents to `unwind' without leaving the manifold. We study the energetics of this process in ...
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Parameter Adaptation and Criticality in Particle Swarm Optimization
Generality is one of the main advantages of heuristic algorithms, as such, multiple parameters are exposed to the user with the objective of allowing them to shape the algorithms to their specific needs. Parameter selection, therefore, becomes an intrinsic problem of every heuristic algorithm. Selecting good paramete...
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Model Predictive Control meets robust Kalman filtering
Model Predictive Control (MPC) is the principal control technique used in industrial applications. Although it offers distinguishable qualities that make it ideal for industrial applications, it can be questioned its robustness regarding model uncertainties and external noises. In this paper we propose a robust MPC c...
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Election forensic analysis of the Turkish Constitutional Referendum 2017
With a majority of 'Yes' votes in the Constitutional Referendum of 2017, Turkey continues its transition from democracy to autocracy. By the will of the Turkish people, this referendum transferred practically all executive power to president Erdogan. However, the referendum was confronted with a substantial number of...
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Efficient Bayesian inference for multivariate factor stochastic volatility models with leverage
This paper discusses the efficient Bayesian estimation of a multivariate factor stochastic volatility (Factor MSV) model with leverage. We propose a novel approach to construct the sampling schemes that converges to the posterior distribution of the latent volatilities and the parameters of interest of the Factor MSV...
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Next Steps for the Colorado Risk-Limiting Audit (CORLA) Program
Colorado conducted risk-limiting tabulation audits (RLAs) across the state in 2017, including both ballot-level comparison audits and ballot-polling audits. Those audits only covered contests restricted to a single county; methods to efficiently audit contests that cross county boundaries and combine ballot polling a...
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HD 202206 : A Circumbinary Brown Dwarf System
With Hubble Space Telescope Fine Guidance Sensor astrometry and previously published radial velocity measures we explore the exoplanetary system HD 202206. Our modeling results in a parallax, $\pi_{abs} = 21.96\pm0.12$ milliseconds of arc, a mass for HD 202206 B of M$_B = 0.089^{ +0.007}_{-0.006}$ Msun, and a mass fo...
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On Optimal Group Claims at Voting in a Stochastic Environment
There is a paradox in the model of social dynamics determined by voting in a stochastic environment (the ViSE model) called "pit of losses." It consists in the fact that a series of democratic decisions may systematically lead the society to the states unacceptable for all the voters. The paper examines how this para...
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Exploring many body localization and thermalization using semiclassical method
The Discrete Truncated Wigner Approximation (DTWA) is a semi-classical phase space method useful for the exploration of Many-body quantum dynamics. In this work we investigate Many-Body Localization (MBL) and thermalization using DTWA and compare its performance to exact numerical solutions. By taking as a benchmark ...
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An FPTAS for the Knapsack Problem with Parametric Weights
In this paper, we investigate the parametric weight knapsack problem, in which the item weights are affine functions of the form $w_i(\lambda) = a_i + \lambda \cdot b_i$ for $i \in \{1,\ldots,n\}$ depending on a real-valued parameter $\lambda$. The aim is to provide a solution for all values of the parameter. It is w...
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Mellin and Wiener-Hopf operators in a non-classical boundary value problem describing a Lévy process
Markov processes are well understood in the case when they take place in the whole Euclidean space. However, the situation becomes much more complicated if a Markov process is restricted to a domain with a boundary, and then a satisfactory theory only exists for processes with continuous trajectories. This research, ...
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Long-term photometric behavior of the eclipsing cataclysmic variable V729 Sgr
We present the analysis results of an eclipsing cataclysmic variable (CV) V729 Sgr, based on our observations and AAVSO data. Some outburst parameters were determined such as outburst amplitude ($A_{n}$) and recurrence time ($T_{n}$), and then the relationship between $A_{n}$ and $T_{n}$ is discussed. A cursory exami...
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SPUX: Scalable Particle Markov Chain Monte Carlo for uncertainty quantification in stochastic ecological models
Calibration of individual based models (IBMs), successful in modeling complex ecological dynamical systems, is often performed only ad-hoc. Bayesian inference can be used for both parameter estimation and uncertainty quantification, but its successful application to realistic scenarios has been hindered by the comple...
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A Social Network Analysis Framework for Modeling Health Insurance Claims Data
Health insurance companies in Brazil have their data about claims organized having the view only for providers. In this way, they loose the physician view and how they share patients. Partnership between physicians can view as a fruitful work in most of the cases but sometimes this could be a problem for health insur...
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Congruences for Restricted Plane Overpartitions Modulo 4 and 8
In 2009, Corteel, Savelief and Vuletić generalized the concept of overpartitions to a new object called plane overpartitions. In recent work, the author considered a restricted form of plane overpartitions called $k$-rowed plane overpartions and proved a method to obtain congruences for these and other types of combi...
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AndroVault: Constructing Knowledge Graph from Millions of Android Apps for Automated Analysis
Data driven research on Android has gained a great momentum these years. The abundance of data facilitates knowledge learning, however, also increases the difficulty of data preprocessing. Therefore, it is non-trivial to prepare a demanding and accurate set of data for research. In this work, we put forward AndroVaul...
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Universal and generalizable restoration strategies for degraded ecological networks
Humans are increasingly stressing ecosystems via habitat destruction, climate change and global population movements leading to the widespread loss of biodiversity and the disruption of key ecological services. Ecosystems characterized primarily by mutualistic relationships between species such as plant-pollinator in...
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Information transmission and signal permutation in active flow networks
Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propa...
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Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis
When analyzing empirical data, we often find that global linear models overestimate the number of parameters required. In such cases, we may ask whether the data lies on or near a manifold or a set of manifolds (a so-called multi-manifold) of lower dimension than the ambient space. This question can be phrased as a (...
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Kitting in the Wild through Online Domain Adaptation
Technological developments call for increasing perception and action capabilities of robots. Among other skills, vision systems that can adapt to any possible change in the working conditions are needed. Since these conditions are unpredictable, we need benchmarks which allow to assess the generalization and robustne...
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Event Analysis of Pulse-reclosers in Distribution Systems Through Sparse Representation
The pulse-recloser uses pulse testing technology to verify that the line is clear of faults before initiating a reclose operation, which significantly reduces stress on the system components (e.g. substation transformers) and voltage sags on adjacent feeders. Online event analysis of pulse-reclosers are essential to ...
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Projected Power Iteration for Network Alignment
The network alignment problem asks for the best correspondence between two given graphs, so that the largest possible number of edges are matched. This problem appears in many scientific problems (like the study of protein-protein interactions) and it is very closely related to the quadratic assignment problem which ...
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3D mean Projective Shape Difference for Face Differentiation from Multiple Digital Camera Images
We give a nonparametric methodology for hypothesis testing for equality of extrinsic mean objects on a manifold embedded in a numerical spaces. The results obtained in the general setting are detailed further in the case of 3D projective shapes represented in a space of symmetric matrices via the quadratic Veronese-W...
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Video Highlight Prediction Using Audience Chat Reactions
Sports channel video portals offer an exciting domain for research on multimodal, multilingual analysis. We present methods addressing the problem of automatic video highlight prediction based on joint visual features and textual analysis of the real-world audience discourse with complex slang, in both English and tr...
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Effects of Interactions on Dynamic Correlations of Hard-Core Bosons at Finite Temperatures
We investigate how dynamic correlations of hard-core bosonic excitation at finite temperature are affected by additional interactions besides the hard-core repulsion which prevents them from occupying the same site. We focus especially on dimerized spin systems, where these additional interactions between the element...
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The Frechet distribution: Estimation and Application an Overview
In this article, we consider the problem of estimating the parameters of the Fréchet distribution from both frequentist and Bayesian points of view. First we briefly describe different frequentist approaches, namely, maximum likelihood, method of moments, percentile estimators, L-moments, ordinary and weighted least ...
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Prediction of Sea Surface Temperature using Long Short-Term Memory
This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series r...
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An Operational Framework for Specifying Memory Models using Instantaneous Instruction Execution
There has been great progress recently in formally specifying the memory model of microprocessors like ARM and POWER. These specifications are, however, too complicated for reasoning about program behaviors, verifying compilers etc., because they involve microarchitectural details like the reorder buffer (ROB), parti...
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Efficient Algorithms for Moral Lineage Tracing
Lineage tracing, the joint segmentation and tracking of living cells as they move and divide in a sequence of light microscopy images, is a challenging task. Jug et al. have proposed a mathematical abstraction of this task, the moral lineage tracing problem (MLTP), whose feasible solutions define both a segmentation ...
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Interpolating between $k$-Median and $k$-Center: Approximation Algorithms for Ordered $k$-Median
We consider a generalization of $k$-median and $k$-center, called the {\em ordered $k$-median} problem. In this problem, we are given a metric space $(\mathcal{D},\{c_{ij}\})$ with $n=|\mathcal{D}|$ points, and a non-increasing weight vector $w\in\mathbb{R}_+^n$, and the goal is to open $k$ centers and assign each po...
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Statistical Challenges in Modeling Big Brain Signals
Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.
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Injective and Automorphism-Invariant Non-Singular Modules
Every automorphism-invariant right non-singular $A$-module is injective if and only if the factor ring of the ring $A$ with respect to its right Goldie radical is a right strongly semiprime ring.
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