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On the generalized nonlinear Camassa-Holm equation
In this paper, a generalized nonlinear Camassa-Holm equation with time- and space-dependent coefficients is considered. We show that the control of the higher order dispersive term is possible by using an adequate weight function to define the energy. The existence and uniqueness of solutions are obtained via a Picar...
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802.11 Wireless Simulation and Anomaly Detection using HMM and UBM
Despite the growing popularity of 802.11 wireless networks, users often suffer from connectivity problems and performance issues due to unstable radio conditions and dynamic user behavior among other reasons. Anomaly detection and distinction are in the thick of major challenges that network managers encounter. Compl...
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Early MFCC And HPCP Fusion for Robust Cover Song Identification
While most schemes for automatic cover song identification have focused on note-based features such as HPCP and chord profiles, a few recent papers surprisingly showed that local self-similarities of MFCC-based features also have classification power for this task. Since MFCC and HPCP capture complementary informatio...
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Optimally Gathering Two Robots
We present an algorithm that ensures in finite time the gathering of two robots in the non-rigid ASYNC model. To circumvent established impossibility results, we assume robots are equipped with 2-colors lights and are able to measure distances between one another. Aside from its light, a robot has no memory of its pa...
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On Grauert-Riemenschneider type criterions
Let $(X,\omega)$ be a compact Hermitian manifold of complex dimension $n$. In this article, we first survey recent progress towards Grauert-Riemenschneider type criterions. Secondly, we give a simplified proof of Boucksom's conjecture given by the author under the assumption that the Hermitian metric $\omega$ satisfi...
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P-Governance Technology: Using Big Data for Political Party Management
Information and Communication Technology (ICT) has been playing a pivotal role since the last decade in developing countries that brings citizen services to the doorsteps and connecting people. With this aspiration ICT has introduced several technologies of citizen services towards all categories of people. The purpo...
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The Forgettable-Watcher Model for Video Question Answering
A number of visual question answering approaches have been proposed recently, aiming at understanding the visual scenes by answering the natural language questions. While the image question answering has drawn significant attention, video question answering is largely unexplored. Video-QA is different from Image-QA s...
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Analogues of the $p^n$th Hilbert symbol in characteristic $p$ (updated)
The $p$th degree Hilbert symbol $(\cdot,\cdot )_p:K^\times/K^{\times p}\times K^\times/K^{\times p}\to{}_p{\rm Br}(K)$ from characteristic $\neq p$ has two analogues in characteristic $p$, $$[\cdot,\cdot )_p:K/\wp (K)\times K^\times/K^{\times p}\to{}_p{\rm Br}(K),$$ where $\wp$ is the Artin-Schreier map $x\mapsto x^p...
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GAMER-2: a GPU-accelerated adaptive mesh refinement code -- accuracy, performance, and scalability
We present GAMER-2, a GPU-accelerated adaptive mesh refinement (AMR) code for astrophysics. It provides a rich set of features, including adaptive time-stepping, several hydrodynamic schemes, magnetohydrodynamics, self-gravity, particles, star formation, chemistry and radiative processes with GRACKLE, data analysis w...
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Partition algebras $\mathsf{P}_k(n)$ with $2k>n$ and the fundamental theorems of invariant theory for the symmetric group $\mathsf{S}_n$
Assume $\mathsf{M}_n$ is the $n$-dimensional permutation module for the symmetric group $\mathsf{S}_n$, and let $\mathsf{M}_n^{\otimes k}$ be its $k$-fold tensor power. The partition algebra $\mathsf{P}_k(n)$ maps surjectively onto the centralizer algebra $\mathsf{End}_{\mathsf{S}_n}(\mathsf{M}_n^{\otimes k})$ for al...
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Distributed sub-optimal resource allocation over weight-balanced graph via singular perturbation
In this paper, we consider distributed optimization design for resource allocation problems over weight-balanced graphs. With the help of singular perturbation analysis, we propose a simple sub-optimal continuous-time optimization algorithm. Moreover, we prove the existence and uniqueness of the algorithm equilibrium...
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Decentralized P2P Energy Trading under Network Constraints in a Low-Voltage Network
The increasing uptake of distributed energy resources (DERs) in distribution systems and the rapid advance of technology have established new scenarios in the operation of low-voltage networks. In particular, recent trends in cryptocurrencies and blockchain have led to a proliferation of peer-to-peer (P2P) energy tra...
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Fictitious GAN: Training GANs with Historical Models
Generative adversarial networks (GANs) are powerful tools for learning generative models. In practice, the training may suffer from lack of convergence. GANs are commonly viewed as a two-player zero-sum game between two neural networks. Here, we leverage this game theoretic view to study the convergence behavior of t...
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Suppression of Hall number due to charge density wave order in high-$T_c$ cuprates
Understanding the pseudogap phase in hole-doped high temperature cuprate superconductors remains a central challenge in condensed matter physics. From a host of recent experiments there is now compelling evidence of translational symmetry breaking charge density wave (CDW) order in a wide range of doping inside this ...
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The Wavefunction of the Collapsing Bose-Einstein Condensate
Bose-Einstein condensates with tunable interatomic interactions have been studied intensely in recent experiments. The investigation of the collapse of a condensate following a sudden change in the nature of the interaction from repulsive to attractive has led to the observation of a remnant condensate that did not u...
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Not-So-Random Features
We propose a principled method for kernel learning, which relies on a Fourier-analytic characterization of translation-invariant or rotation-invariant kernels. Our method produces a sequence of feature maps, iteratively refining the SVM margin. We provide rigorous guarantees for optimality and generalization, interpr...
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Dual-Primal Graph Convolutional Networks
In recent years, there has been a surge of interest in developing deep learning methods for non-Euclidean structured data such as graphs. In this paper, we propose Dual-Primal Graph CNN, a graph convolutional architecture that alternates convolution-like operations on the graph and its dual. Our approach allows to le...
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CLEAR: Coverage-based Limiting-cell Experiment Analysis for RNA-seq
Direct cDNA preamplification protocols developed for single-cell RNA-seq (scRNA-seq) have enabled transcriptome profiling of rare cells without having to pool multiple samples or to perform RNA extraction. We term this approach limiting-cell RNA-seq (lcRNA-seq). Unlike scRNA-seq, which focuses on 'cell-atlasing', lcR...
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Training Deep AutoEncoders for Collaborative Filtering
This paper proposes a novel model for the rating prediction task in recommender systems which significantly outperforms previous state-of-the art models on a time-split Netflix data set. Our model is based on deep autoencoder with 6 layers and is trained end-to-end without any layer-wise pre-training. We empirically ...
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Unit circle rectification of the MVDR beamformer
The sample matrix inversion (SMI) beamformer implements Capon's minimum variance distortionless (MVDR) beamforming using the sample covariance matrix (SCM). In a snapshot limited environment, the SCM is poorly conditioned resulting in a suboptimal performance from the SMI beamformer. Imposing structural constraints o...
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Reducing Storage of Global Wind Ensembles with Stochastic Generators
Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at re...
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Jackknife Empirical Likelihood-based inference for S-Gini indices
Widely used income inequality measure, Gini index is extended to form a family of income inequality measures known as Single-Series Gini (S-Gini) indices. In this study, we develop empirical likelihood (EL) and jackknife empirical likelihood (JEL) based inference for S-Gini indices. We prove that the limiting distrib...
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Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network Simulation Expansion and STDP Convergence Predictions
This paper presents a constructive algorithm that achieves successful one-shot learning of hidden spike-patterns in a competitive detection task. It has previously been shown (Masquelier et al., 2008) that spike-timing-dependent plasticity (STDP) and lateral inhibition can result in neurons competitively tuned to rep...
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Interpretable High-Dimensional Inference Via Score Projection with an Application in Neuroimaging
In the fields of neuroimaging and genetics, a key goal is testing the association of a single outcome with a very high-dimensional imaging or genetic variable. Often, summary measures of the high-dimensional variable are created to sequentially test and localize the association with the outcome. In some cases, the re...
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A maximum principle for free boundary minimal varieties of arbitrary codimension
We establish a boundary maximum principle for free boundary minimal submanifolds in a Riemannian manifold with boundary, in any dimension and codimension. Our result holds more generally in the context of varifolds.
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Drawing Big Graphs using Spectral Sparsification
Spectral sparsification is a general technique developed by Spielman et al. to reduce the number of edges in a graph while retaining its structural properties. We investigate the use of spectral sparsification to produce good visual representations of big graphs. We evaluate spectral sparsification approaches on real...
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Optimal paths on the road network as directed polymers
We analyze the statistics of the shortest and fastest paths on the road network between randomly sampled end points. To a good approximation, these optimal paths are found to be directed in that their lengths (at large scales) are linearly proportional to the absolute distance between them. This motivates comparisons...
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Optimal proportional reinsurance and investment for stochastic factor models
In this work we investigate the optimal proportional reinsurance-investment strategy of an insurance company which wishes to maximize the expected exponential utility of its terminal wealth in a finite time horizon. Our goal is to extend the classical Cramer-Lundberg model introducing a stochastic factor which affect...
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Formal Black-Box Analysis of Routing Protocol Implementations
The Internet infrastructure relies entirely on open standards for its routing protocols. However, the majority of routers on the Internet are closed-source. Hence, there is no straightforward way to analyze them. Specifically, one cannot easily identify deviations of a router's routing functionality from the routing ...
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Finding polynomial loop invariants for probabilistic programs
Quantitative loop invariants are an essential element in the verification of probabilistic programs. Recently, multivariate Lagrange interpolation has been applied to synthesizing polynomial invariants. In this paper, we propose an alternative approach. First, we fix a polynomial template as a candidate of a loop inv...
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Active Decision Boundary Annotation with Deep Generative Models
This paper is on active learning where the goal is to reduce the data annotation burden by interacting with a (human) oracle during training. Standard active learning methods ask the oracle to annotate data samples. Instead, we take a profoundly different approach: we ask for annotations of the decision boundary. We ...
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Multifrequency Excitation and Detection Scheme in Apertureless Scattering Near Field Scanning Optical Microscopy
We theoretically and experimentally demonstrate a multifrequency excitation and detection scheme in apertureless near field optical microscopy, that exceeds current state of the art sensitivity and background suppression. By exciting the AFM tip at its two first flexural modes, and demodulating the detected signal at...
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Extended Kitaev chain with longer-range hopping and pairing
We consider the Kitaev chain model with finite and infinite range in the hopping and pairing parameters, looking in particular at the appearance of Majorana zero energy modes and massive edge modes. We study the system both in the presence and in the absence of time reversal symmetry, by means of topological invarian...
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Global entropy solutions to the compressible Euler equations in the isentropic nozzle flow for large data: Application of the modified Godunov scheme and the generalized invariant regions
We study the motion of isentropic gas in nozzles. This is a major subject in fluid dynamics. In fact, the nozzle is utilized to increase the thrust of rocket engines. Moreover, the nozzle flow is closely related to astrophysics. These phenomena are governed by the compressible Euler equation, which is one of crucial ...
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Effects of atrial fibrillation on the arterial fluid dynamics: a modelling perspective
Atrial fibrillation (AF) is the most common form of arrhythmia with accelerated and irregular heart rate (HR), leading to both heart failure and stroke and being responsible for an increase in cardiovascular morbidity and mortality. In spite of its importance, the direct effects of AF on the arterial hemodynamic patt...
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Controllability and optimal control of the transport equation with a localized vector field
We study controllability of a Partial Differential Equation of transport type, that arises in crowd models. We are interested in controlling such system with a control being a Lipschitz vector field on a fixed control set $\omega$. We prove that, for each initial and final configuration, one can steer one to another ...
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Gravitational instabilities in a protosolar-like disc II: continuum emission and mass estimates
Gravitational instabilities (GIs) are most likely a fundamental process during the early stages of protoplanetary disc formation. Recently, there have been detections of spiral features in young, embedded objects that appear consistent with GI-driven structure. It is crucial to perform hydrodynamic and radiative tran...
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Information Processing by Networks of Quantum Decision Makers
We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the generalization of quantum decision theory, developed earlier for single decision makers rea...
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The Value of Sharing Intermittent Spectrum
Recent initiatives by regulatory agencies to increase spectrum resources available for broadband access include rules for sharing spectrum with high-priority incumbents. We study a model in which wireless Service Providers (SPs) charge for access to their own exclusive-use (licensed) band along with access to an addi...
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Origin of layer dependence in band structures of two-dimensional materials
We study the origin of layer dependence in band structures of two-dimensional materials. We find that the layer dependence, at the density functional theory (DFT) level, is a result of quantum confinement and the non-linearity of the exchange-correlation functional. We use this to develop an efficient scheme for perf...
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From Strings to Sets
A complete proof is given of relative interpretability of Adjunctive Set Theory with Extensionality in an elementary concatenation theory.
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Sharp measure contraction property for generalized H-type Carnot groups
We prove that H-type Carnot groups of rank $k$ and dimension $n$ satisfy the $\mathrm{MCP}(K,N)$ if and only if $K\leq 0$ and $N \geq k+3(n-k)$. The latter integer coincides with the geodesic dimension of the Carnot group. The same result holds true for the larger class of generalized H-type Carnot groups introduced ...
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Twisted Quantum Double Model of Topological Orders with Boundaries
We generalize the twisted quantum double model of topological orders in two dimensions to the case with boundaries by systematically constructing the boundary Hamiltonians. Given the bulk Hamiltonian defined by a gauge group $G$ and a three-cocycle in the third cohomology group of $G$ over $U(1)$, a boundary Hamilton...
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Evolutionary game of coalition building under external pressure
We study the fragmentation-coagulation (or merging and splitting) evolutionary control model as introduced recently by one of the authors, where $N$ small players can form coalitions to resist to the pressure exerted by the principal. It is a Markov chain in continuous time and the players have a common reward to opt...
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Nearly resolution V plans on blocks of small size
In Bagchi (2010) main effect plans "orthogonal through the block factor" (POTB) have been constructed. The main advantages of a POTB are that (a) it may exist in a set up where an "usual" orthogonal main effect plan (OMEP) cannot exist and (b) the data analysis is nearly as simple as an OMEP. In the present paper we ...
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Graphene-based electron transport layers in perovskite solar cells: a step-up for an efficient carrier collection
The electron transport layer (ETL) plays a fundamental role in perovskite solar cells. Recently, graphene-based ETLs have been proved to be good candidate for scalable fabrication processes and to achieve higher carrier injection with respect to most commonly used ETLs. In this work we experimentally study the effect...
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Learning and Transferring IDs Representation in E-commerce
Many machine intelligence techniques are developed in E-commerce and one of the most essential components is the representation of IDs, including user ID, item ID, product ID, store ID, brand ID, category ID etc. The classical encoding based methods (like one-hot encoding) are inefficient in that it suffers sparsity ...
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Differentiable Supervector Extraction for Encoding Speaker and Phrase Information in Text Dependent Speaker Verification
In this paper, we propose a new differentiable neural network alignment mechanism for text-dependent speaker verification which uses alignment models to produce a supervector representation of an utterance. Unlike previous works with similar approaches, we do not extract the embedding of an utterance from the mean re...
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In situ accretion of gaseous envelopes on to planetary cores embedded in evolving protoplanetary discs
The core accretion hypothesis posits that planets with significant gaseous envelopes accreted them from their protoplanetary discs after the formation of rocky/icy cores. Observations indicate that such exoplanets exist at a broad range of orbital radii, but it is not known whether they accreted their envelopes in si...
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New Two Step Laplace Adam-Bashforth Method for Integer an Non integer Order Partial Differential Equations
This paper presents a novel method that allows to generalise the use of the Adam-Bashforth to Partial Differential Equations with local and non local operator. The Method derives a two step Adam-Bashforth numerical scheme in Laplace space and the solution is taken back into the real space via inverse Laplace transfor...
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The Impact of Alternation
Alternating automata have been widely used to model and verify systems that handle data from finite domains, such as communication protocols or hardware. The main advantage of the alternating model of computation is that complementation is possible in linear time, thus allowing to concisely encode trace inclusion pro...
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Partial-wave Coulomb t-matrices for like-charged particles at ground-state energy
We study a special case at which the analytical solution of the Lippmann-Schwinger integral equation for the partial wave two-body Coulomb transition matrix for likely charged particles at negative energy is possible. With the use of the Fock's method of the stereographic projection of the momentum space onto the fou...
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Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness
Causal effect estimation from observational data is an important and much studied research topic. The instrumental variable (IV) and local causal discovery (LCD) patterns are canonical examples of settings where a closed-form expression exists for the causal effect of one variable on another, given the presence of a ...
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The Cross-section of a Spherical Double Cone
We show that the poset of $SL(n)$-orbit closures in the product of two partial flag varieties is a lattice if the action of $SL(n)$ is spherical.
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Understanding looping kinetics of a long polymer molecule in solution. Exact solution for delocalized sink model
The fundamental understanding of loop formation of long polymer chains in solution has been an important thread of research for several theoretical and experimental studies. Loop formations are important phenomenological parameters in many important biological processes. Here we give a general method for finding an e...
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SESA: Supervised Explicit Semantic Analysis
In recent years supervised representation learning has provided state of the art or close to the state of the art results in semantic analysis tasks including ranking and information retrieval. The core idea is to learn how to embed items into a latent space such that they optimize a supervised objective in that late...
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High-Level Concepts for Affective Understanding of Images
This paper aims to bridge the affective gap between image content and the emotional response of the viewer it elicits by using High-Level Concepts (HLCs). In contrast to previous work that relied solely on low-level features or used convolutional neural network (CNN) as a black-box, we use HLCs generated by pretraine...
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A Network of Networks Approach to Interconnected Power Grids
We present two different approaches to model power grids as interconnected networks of networks. Both models are derived from a model for spatially embedded mono-layer networks and are generalised to handle an arbitrary number of network layers. The two approaches are distinguished by their use case. The static glue ...
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A Nonparametric Method for Producing Isolines of Bivariate Exceedance Probabilities
We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence framework widely used for extremes. This framework enables drawing isolines corresponding to very low exceedance probabilities and these ...
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Finite element error analysis for measure-valued optimal control problems governed by a 1D wave equation with variable coefficients
This work is concerned with the optimal control problems governed by a 1D wave equation with variable coefficients and the control spaces $\mathcal M_T$ of either measure-valued functions $L_{w^*}^2(I,\mathcal M(\Omega))$ or vector measures $\mathcal M(\Omega,L^2(I))$. The cost functional involves the standard quadra...
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Marked points on translation surfaces
We show that all GL(2,R) equivariant point markings over orbit closures of translation surfaces arise from branched covering constructions and periodic points, completely classify such point markings over strata of quadratic differentials, and give applications to the finite blocking problem.
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Multitask Learning for Fundamental Frequency Estimation in Music
Fundamental frequency (f0) estimation from polyphonic music includes the tasks of multiple-f0, melody, vocal, and bass line estimation. Historically these problems have been approached separately, and only recently, using learning-based approaches. We present a multitask deep learning architecture that jointly estima...
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Real eigenvalues of a non-self-adjoint perturbation of the self-adjoint Zakharov-Shabat operator
We study the eigenvalues of the self-adjoint Zakharov-Shabat operator corresponding to the defocusing nonlinear Schrodinger equation in the inverse scattering method. Real eigenvalues exist when the square of the potential has a simple well. We derive two types of quantization condition for the eigenvalues by using t...
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Planning with Multiple Biases
Recent work has considered theoretical models for the behavior of agents with specific behavioral biases: rather than making decisions that optimize a given payoff function, the agent behaves inefficiently because its decisions suffer from an underlying bias. These approaches have generally considered an agent who ex...
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Zhu reduction for Jacobi $n$-point functions and applications
We establish precise Zhu reduction formulas for Jacobi $n$-point functions which show the absence of any possible poles arising in these formulas. We then exploit this to produce results concerning the structure of strongly regular vertex operator algebras, and also to motivate new differential operators acting on Ja...
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Fourier-like multipliers and applications for integral operators
Timelimited functions and bandlimited functions play a fundamental role in signal and image processing. But by the uncertainty principles, a signal cannot be simultaneously time and bandlimited. A natural assumption is thus that a signal is almost time and almost bandlimited. The aim of this paper is to prove that th...
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Inferring Properties of the ISM from Supernova Remnant Size Distributions
We model the size distribution of supernova remnants to infer the surrounding ISM density. Using simple, yet standard SNR evolution models, we find that the distribution of ambient densities is remarkably narrow; either the standard assumptions about SNR evolution are wrong, or observable SNRs are biased to a narrow ...
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Mining Target Attribute Subspace and Set of Target Communities in Large Attributed Networks
Community detection provides invaluable help for various applications, such as marketing and product recommendation. Traditional community detection methods designed for plain networks may not be able to detect communities with homogeneous attributes inside on attributed networks with attribute information. Most of r...
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Achieving rental harmony with a secretive roommate
Given the subjective preferences of n roommates in an n-bedroom apartment, one can use Sperner's lemma to find a division of the rent such that each roommate is content with a distinct room. At the given price distribution, no roommate has a strictly stronger preference for a different room. We give a new elementary ...
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A Channel-Based Perspective on Conjugate Priors
A desired closure property in Bayesian probability is that an updated posterior distribution be in the same class of distributions --- say Gaussians --- as the prior distribution. When the updating takes place via a statistical model, one calls the class of prior distributions the `conjugate priors' of the model. Thi...
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Cascaded Coded Distributed Computing on Heterogeneous Networks
Coded distributed computing (CDC) introduced by Li et al. in 2015 offers an efficient approach to trade computing power to reduce the communication load in general distributed computing frameworks such as MapReduce. For the more general cascaded CDC, Map computations are repeated at $r$ nodes to significantly reduce ...
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A FEL Based on a Superlattice
The motion and photon emission of electrons in a superlattice may be described as in an undulator. Therefore, there is a close analogy between ballistic electrons in a superlattice and electrons in a free electron laser (FEL). Touching upon this analogy the intensity of photon emission in the IR region and the gain a...
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Thermal and non-thermal emission from the cocoon of a gamma-ray burst jet
We present hydrodynamic simulations of the hot cocoon produced when a relativistic jet passes through the gamma-ray burst (GRB) progenitor star and its environment, and we compute the lightcurve and spectrum of the radiation emitted by the cocoon. The radiation from the cocoon has a nearly thermal spectrum with a pea...
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Least Squares Polynomial Chaos Expansion: A Review of Sampling Strategies
As non-institutive polynomial chaos expansion (PCE) techniques have gained growing popularity among researchers, we here provide a comprehensive review of major sampling strategies for the least squares based PCE. Traditional sampling methods, such as Monte Carlo, Latin hypercube, quasi-Monte Carlo, optimal design of...
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Efficient Dense Labeling of Human Activity Sequences from Wearables using Fully Convolutional Networks
Recognizing human activities in a sequence is a challenging area of research in ubiquitous computing. Most approaches use a fixed size sliding window over consecutive samples to extract features---either handcrafted or learned features---and predict a single label for all samples in the window. Two key problems emana...
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Higher Tetrahedral Algebras
We introduce and study the higher tetrahedral algebras, an exotic family of finite-dimensional tame symmetric algebras over an algebraically closed field. The Gabriel quiver of such an algebra is the triangulation quiver associated to the coherent orientation of the tetrahedron. Surprisingly, these algebras occurred ...
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Adaptive multi-penalty regularization based on a generalized Lasso path
For many algorithms, parameter tuning remains a challenging and critical task, which becomes tedious and infeasible in a multi-parameter setting. Multi-penalty regularization, successfully used for solving undetermined sparse regression of problems of unmixing type where signal and noise are additively mixed, is one ...
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Shape Generation using Spatially Partitioned Point Clouds
We propose a method to generate 3D shapes using point clouds. Given a point-cloud representation of a 3D shape, our method builds a kd-tree to spatially partition the points. This orders them consistently across all shapes, resulting in reasonably good correspondences across all shapes. We then use PCA analysis to de...
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Open Vocabulary Scene Parsing
Recognizing arbitrary objects in the wild has been a challenging problem due to the limitations of existing classification models and datasets. In this paper, we propose a new task that aims at parsing scenes with a large and open vocabulary, and several evaluation metrics are explored for this problem. Our proposed ...
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Parameter Estimation in Mean Reversion Processes with Periodic Functional Tendency
This paper describes the procedure to estimate the parameters in mean reversion processes with functional tendency defined by a periodic continuous deterministic function, expressed as a series of truncated Fourier. Two phases of estimation are defined, in the first phase through Gaussian techniques using the Euler-M...
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User Interface (UI) Design Issues for the Multilingual Users: A Case Study
A multitude of web and desktop applications are now widely available in diverse human languages. This paper explores the design issues that are specifically relevant for multilingual users. It reports on the continued studies of Information System (IS) issues and users' behaviour across cross-cultural and transnation...
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NetSpam: a Network-based Spam Detection Framework for Reviews in Online Social Media
Nowadays, a big part of people rely on available content in social media in their decisions (e.g. reviews and feedback on a topic or product). The possibility that anybody can leave a review provide a golden opportunity for spammers to write spam reviews about products and services for different interests. Identifyin...
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Proving Non-Deterministic Computations in Agda
We investigate proving properties of Curry programs using Agda. First, we address the functional correctness of Curry functions that, apart from some syntactic and semantic differences, are in the intersection of the two languages. Second, we use Agda to model non-deterministic functions with two distinct and competi...
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NeuroRule: A Connectionist Approach to Data Mining
Classification, which involves finding rules that partition a given data set into disjoint groups, is one class of data mining problems. Approaches proposed so far for mining classification rules for large databases are mainly decision tree based symbolic learning methods. The connectionist approach based on neural n...
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Contextual Explanation Networks
Modern learning algorithms excel at producing accurate but complex models of the data. However, deploying such models in the real-world requires extra care: we must ensure their reliability, robustness, and absence of undesired biases. This motivates the development of models that are equally accurate but can be also...
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Inference for Differential Equation Models using Relaxation via Dynamical Systems
Statistical regression models whose mean functions are represented by ordinary differential equations (ODEs) can be used to describe phenomenons dynamical in nature, which are abundant in areas such as biology, climatology and genetics. The estimation of parameters of ODE based models is essential for understanding i...
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Joint Trajectory and Communication Design for UAV-Enabled Multiple Access
Unmanned aerial vehicles (UAVs) have attracted significant interest recently in wireless communication due to their high maneuverability, flexible deployment, and low cost. This paper studies a UAV-enabled wireless network where the UAV is employed as an aerial mobile base station (BS) to serve a group of users on th...
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Imaging the Schwarzschild-radius-scale Structure of M87 with the Event Horizon Telescope using Sparse Modeling
We propose a new imaging technique for radio and optical/infrared interferometry. The proposed technique reconstructs the image from the visibility amplitude and closure phase, which are standard data products of short-millimeter very long baseline interferometers such as the Event Horizon Telescope (EHT) and optical...
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The process of purely event-driven programs
Using process algebra, this paper describes the formalisation of the process/semantics behind the purely event-driven programming language.
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Partial dust obscuration in active galactic nuclei as a cause of broad-line profile and lag variability, and apparent accretion disc inhomogeneities
The profiles of the broad emission lines of active galactic nuclei (AGNs) and the time delays in their response to changes in the ionizing continuum ("lags") give information about the structure and kinematics of the inner regions of AGNs. Line profiles are also our main way of estimating the masses of the supermassi...
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From Plants to Landmarks: Time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields
Agricultural robots are expected to increase yields in a sustainable way and automate precision tasks, such as weeding and plant monitoring. At the same time, they move in a continuously changing, semi-structured field environment, in which features can hardly be found and reproduced at a later time. Challenges for L...
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There's more to the multimedia effect than meets the eye: is seeing pictures believing?
Textbooks in applied mathematics often use graphs to explain the meaning of formulae, even though their benefit is still not fully explored. To test processes underlying this assumed multimedia effect we collected performance scores, eye movements, and think-aloud protocols from students solving problems in vector ca...
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Methods of Enumerating Two Vertex Maps of Arbitrary Genus
This paper provides an alternate proof to parts of the Goulden-Slofstra formula for enumerating two vertex maps by genus, which is an extension of the famous Harer-Zagier formula that computes the Euler characteristic of the moduli space of curves. This paper also shows a further simplification to the Goulden-Slofstr...
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Higher Theory and the Three Problems of Physics
According to the Butterfield--Isham proposal, to understand quantum gravity we must revise the way we view the universe of mathematics. However, this paper demonstrates that the current elaborations of this programme neglect quantum interactions. The paper then introduces the Faddeev--Mickelsson anomaly which obstruc...
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Light emission by accelerated electric, toroidal and anapole dipolar sources
Emission of electromagnetic radiation by accelerated particles with electric, toroidal and anapole dipole moments is analyzed. It is shown that ellipticity of the emitted light can be used to differentiate between electric and toroidal dipole sources, and that anapoles, elementary neutral non-radiating configurations...
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Bayesian Approaches to Distribution Regression
Distribution regression has recently attracted much interest as a generic solution to the problem of supervised learning where labels are available at the group level, rather than at the individual level. Current approaches, however, do not propagate the uncertainty in observations due to sampling variability in the ...
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Atomic-Scale Structure Relaxation, Chemistry and Charge Distribution of Dislocation Cores in SrTiO3
By using the state-of-the-art microscopy and spectroscopy in aberration-corrected scanning transmission electron microscopes, we determine the atomic arrangements, occupancy, elemental distribution, and the electronic structures of dislocation cores in the 10°tilted SrTiO3 bicrystal. We identify that there are two di...
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Transição de fase no sistema de Hénon-Heiles (Phase transition in the Henon-Heiles system)
The Henon-Heiles system was originally proposed to describe the dynamical behavior of galaxies, but this system has been widely applied in dynamical systems by exhibit great details in phase space. This work presents the formalism to describe Henon-Heiles system and a qualitative approach of dynamics behavior. The gr...
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Self-similar solutions of fragmentation equations revisited
We study the large time behaviour of the mass (size) of particles described by the fragmentation equation with homogeneous breakup kernel. We give necessary and sufficient conditions for the convergence of solutions to the unique self-similar solution.
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Refining Source Representations with Relation Networks for Neural Machine Translation
Although neural machine translation (NMT) with the encoder-decoder framework has achieved great success in recent times, it still suffers from some drawbacks: RNNs tend to forget old information which is often useful and the encoder only operates through words without considering word relationship. To solve these pro...
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