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K-closedness of weighted Hardy spaces on the two-dimensional torus
It is proved that, under certain restrictions on weights, a pair of weighted Hardy spaces on the two-dimensional torus is K-closed in the pair of the corresponding weighted Lebesgue spaces. By now, K-closedness of Hardy spaces on the two-dimensional torus was considered either in the case of no weights or in the case...
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Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Tissue characterization has long been an important component of Computer Aided Diagnosis (CAD) systems for automatic lesion detection and further clinical planning. Motivated by the superior performance of deep learning methods on various computer vision problems, there has been increasing work applying deep learning...
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PS-DBSCAN: An Efficient Parallel DBSCAN Algorithm Based on Platform Of AI (PAI)
We present PS-DBSCAN, a communication efficient parallel DBSCAN algorithm that combines the disjoint-set data structure and Parameter Server framework in Platform of AI (PAI). Since data points within the same cluster may be distributed over different workers which result in several disjoint-sets, merging them incurs...
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Non-singular spacetimes with a negative cosmological constant: IV. Stationary black hole solutions with matter fields
We use an elliptic system of equations with complex coefficients for a set of complex-valued tensor fields as a tool to construct infinite-dimensional families of non-singular stationary black holes, real-valued Lorentzian solutions of the Einstein-Maxwell-dilaton-scalar fields-Yang-Mills-Higgs-Chern-Simons-$f(R)$ eq...
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Non-Negative Matrix Factorization Test Cases
Non-negative matrix factorization (NMF) is a prob- lem with many applications, ranging from facial recognition to document clustering. However, due to the variety of algorithms that solve NMF, the randomness involved in these algorithms, and the somewhat subjective nature of the problem, there is no clear "correct an...
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Inequalities for the fundamental Robin eigenvalue of the Laplacian for box-shaped domains
This document consists of two papers, both submitted, and supplementary material. The submitted papers are here given as Parts I and II. Part I establishes results, used in Part II, 'on functions and inverses, both positive, decreasing and convex'. Part II uses results from Part I to extablish 'inequalities for the f...
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Non-Hamiltonian isotopic Lagrangians on the one-point blow-up of CP^2
We show that two Hamiltonian isotopic Lagrangians in (CP^2,\omega_\textup{FS}) induce two Lagrangian submanifolds in the one-point blow-up (\widetilde{CP}^2,\widetilde{\omega}_\rho) that are not Hamiltonian isotopic. Furthermore, we show that for any integer k>1 there are k Hamiltonian isotopic Lagrangians in (CP^2,\...
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Berezinskii-Kosterlitz-Thouless Type Scenario in Molecular Spin Liquid $A$Cr$_2$O$_4$
The spin relaxation in chromium spinel oxides $A$Cr$_{2}$O$_{4}$ ($A=$ Mg, Zn, Cd) is investigated in the paramagnetic regime by electron spin resonance (ESR). The temperature dependence of the ESR linewidth indicates an unconventional spin-relaxation behavior, similar to spin-spin relaxation in the two-dimensional (...
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Continuum percolation theory of epimorphic regeneration
A biophysical model of epimorphic regeneration based on a continuum percolation process of fully penetrable disks in two dimensions is proposed. All cells within a randomly chosen disk of the regenerating organism are assumed to receive a signal in the form of a circular wave as a result of the action/reconfiguration...
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Multiplicity of solutions for a nonhomogeneous quasilinear elliptic problem with critical growth
It is established some existence and multiplicity of solution results for a quasilinear elliptic problem driven by $\Phi$-Laplacian operator. One of these solutions is built as a ground state solution. In order to prove our main results we apply the Nehari method combined with the concentration compactness theorem in...
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Mahonian STAT on rearrangement class of words
In 2000, Babson and Steingrímsson generalized the notion of permutation patterns to the so-called vincular patterns, and they showed that many Mahonian statistics can be expressed as sums of vincular pattern occurrence statistics. STAT is one of such Mahonian statistics discoverd by them. In 2016, Kitaev and the thir...
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A bibliometric approach to Systematic Mapping Studies: The case of the evolution and perspectives of community detection in complex networks
Critical analysis of the state of the art is a necessary task when identifying new research lines worthwhile to pursue. To such an end, all the available work related to the field of interest must be taken into account. The key point is how to organize, analyze, and make sense of the huge amount of scientific literat...
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SPEW: Synthetic Populations and Ecosystems of the World
Agent-based models (ABMs) simulate interactions between autonomous agents in constrained environments over time. ABMs are often used for modeling the spread of infectious diseases. In order to simulate disease outbreaks or other phenomena, ABMs rely on "synthetic ecosystems," or information about agents and their env...
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Bayesian hierarchical weighting adjustment and survey inference
We combine Bayesian prediction and weighted inference as a unified approach to survey inference. The general principles of Bayesian analysis imply that models for survey outcomes should be conditional on all variables that affect the probability of inclusion. We incorporate the weighting variables under the framework...
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Comparison of the h-index for Different Fields of Research Using Bootstrap Methodology
An important disadvantage of the h-index is that typically it cannot take into account the specific field of research of a researcher. Usually sample point estimates of the average and median h-index values for the various fields are reported that are highly variable and dependent of the specific samples and it would...
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Impact of Intervals on the Emotional Effect in Western Music
Every art form ultimately aims to invoke an emotional response over the audience, and music is no different. While the precise perception of music is a highly subjective topic, there is an agreement in the "feeling" of a piece of music in broad terms. Based on this observation, in this study, we aimed to determine th...
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Nonlocal Pertubations of Fractional Choquard Equation
We study the equation \begin{equation} (-\Delta)^{s}u+V(x)u= (I_{\alpha}*|u|^{p})|u|^{p-2}u+\lambda(I_{\beta}*|u|^{q})|u|^{q-2}u \quad\mbox{ in } \R^{N}, \end{equation} where $I_\gamma(x)=|x|^{-\gamma}$ for any $\gamma\in (0,N)$, $p, q >0$, $\alpha,\beta\in (0,N)$, $N\geq 3$ and $ \lambda \in R$. First, the existence...
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Clustering Patients with Tensor Decomposition
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such a...
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Posterior distribution existence and error control in Banach spaces in the Bayesian approach to UQ in inverse problems
We generalize the results of \cite{Capistran2016} on expected Bayes factors (BF) to control the numerical error in the posterior distribution to an infinite dimensional setting when considering Banach functional spaces and now in a prior setting. The main result is a bound on the absolute global error to be tolerated...
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High-$T_c$ mechanism through analysis of diverging effective mass for YaBa$_2$Cu$_3$O$_{6+x}$ and pairing symmetry in cuprate superconductors
In order to clarify the high-$T_c$ mechanism in inhomogeneous cuprate layer superconductors, we deduce and find the correlation strength not revealed before, contributing to the formation of the Cooper pair and the 2-D density of state, and demonstrate the pairing symmetry in the superconductors still controversial. ...
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The Long Term Fréchet distribution: Estimation, Properties and its Application
In this paper a new long-term survival distribution is proposed. The so called long term Fréchet distribution allows us to fit data where a part of the population is not susceptible to the event of interest. This model may be used, for example, in clinical studies where a portion of the population can be cured during...
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Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space
Many engineering problems require identifying feasible domains under implicit constraints. One example is finding acceptable car body styling designs based on constraints like aesthetics and functionality. Current active-learning based methods learn feasible domains for bounded input spaces. However, we usually lack ...
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On diagrams of simplified trisections and mapping class groups
A simplified trisection is a trisection map on a 4-manifold such that, in its critical value set, there is no double point and cusps only appear in triples on innermost fold circles. We give a necessary and sufficient condition for a 3-tuple of systems of simple closed curves in a surface to be a diagram of a simplif...
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Look No Further: Adapting the Localization Sensory Window to the Temporal Characteristics of the Environment
Many localization algorithms use a spatiotemporal window of sensory information in order to recognize spatial locations, and the length of this window is often a sensitive parameter that must be tuned to the specifics of the application. This letter presents a general method for environment-driven variation of the le...
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The Gaia-ESO Survey: Dynamical models of flattened, rotating globular clusters
We present a family of self-consistent axisymmetric rotating globular cluster models which are fitted to spectroscopic data for NGC 362, NGC 1851, NGC 2808, NGC 4372, NGC 5927 and NGC 6752 to provide constraints on their physical and kinematic properties, including their rotation signals. They are constructed by flat...
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A two-dimensional data-driven model for traffic flow on highways
Based on experimental traffic data obtained from German and US highways, we propose a novel two-dimensional first-order macroscopic traffic flow model. The goal is to reproduce a detailed description of traffic dynamics for the real road geometry. In our approach both the dynamic along the road and across the lanes i...
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Cut Finite Element Methods for Elliptic Problems on Multipatch Parametric Surfaces
We develop a finite element method for the Laplace--Beltrami operator on a surface described by a set of patchwise parametrizations. The patches provide a partition of the surface and each patch is the image by a diffeomorphism of a subdomain of the unit square which is bounded by a number of smooth trim curves. A pa...
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The rationality problem for forms of $\overline{M_{0, n}}$
Let $X$ be a del Pezzo surface of degree $5$ defined over a field $F$. A theorem of Yu. I. Manin and P. Swinnerton-Dyer asserts that every Del Pezzo surface of degree $5$ is rational. In this paper we generalize this result as follows. Recall that del Pezzo surfaces of degree $5$ over a field $F$ are precisely the tw...
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The p-adic Kummer-Leopoldt constant - Normalized p-adic regulator
The p-adic Kummer--Leopoldt constant kappa\_K of a number field K is (assuming the Leopoldt conjecture) the least integer c such that for all n \textgreater{}\textgreater{} 0, any global unit of K, which is locally a p^(n+c)th power at the p-places, is necessarily the p^nth power of a global unit of K. This constant ...
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Regularization Learning Networks: Deep Learning for Tabular Datasets
Despite their impressive performance, Deep Neural Networks (DNNs) typically underperform Gradient Boosting Trees (GBTs) on many tabular-dataset learning tasks. We propose that applying a different regularization coefficient to each weight might boost the performance of DNNs by allowing them to make more use of the mo...
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Numerical dimension and locally ample curves
In the paper \cite{Lau16}, it was shown that the restriction of a pseudoeffective divisor $D$ to a subvariety $Y$ with nef normal bundle is pseudoeffective. Assuming the normal bundle is ample and that $D|_Y$ is not big, we prove that the numerical dimension of $D$ is bounded above by that of its restriction, i.e. $\...
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Local-global principles in circle packings
We generalize work of Bourgain-Kontorovich and Zhang, proving an almost local-to-global property for the curvatures of certain circle packings, to a large class of Kleinian groups. Specifically, we associate in a natural way an infinite family of integral packings of circles to any Kleinian group $\mathcal A\leq\text...
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Underscreening in concentrated electrolytes
Screening of a surface charge by electrolyte and the resulting interaction energy between charged objects is of fundamental importance in scenarios from bio-molecular interactions to energy storage. The conventional wisdom is that the interaction energy decays exponentially with object separation and the decay length...
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Asymptotics for Small Nonlinear Price Impact: a PDE Approach to the Multidimensional Case
We provide an asymptotic expansion of the value function of a multidimensional utility maximization problem from consumption with small non-linear price impact. In our model cross-impacts between assets are allowed. In the limit for small price impact, we determine the asymptotic expansion of the value function aroun...
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Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation
Probabilistic atlases provide essential spatial contextual information for image interpretation, Bayesian modeling, and algorithmic processing. Such atlases are typically constructed by grouping subjects with similar demographic information. Importantly, use of the same scanner minimizes inter-group variability. Howe...
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Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems
We present a machine learning framework for multi-agent systems to learn both the optimal policy for maximizing the rewards and the encoding of the high dimensional visual observation. The encoding is useful for sharing local visual observations with other agents under communication resource constraints. The actor-en...
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Optimal investment-consumption problem post-retirement with a minimum guarantee
We study the optimal investment-consumption problem for a member of defined contribution plan during the decumulation phase. For a fixed annuitization time, to achieve higher final annuity, we consider a variable consumption rate. Moreover, to eliminate the ruin possibilities and having a minimum guarantee for the fi...
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Parametrices for the light ray transform on Minkowski spacetime
We consider restricted light ray transforms arising from an inverse problem of finding cosmic strings. We construct a relative left parametrix for the transform on two tensors, which recovers the space-like and some light-like singularities of the two tensor.
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Derivative Principal Component Analysis for Representing the Time Dynamics of Longitudinal and Functional Data
We propose a nonparametric method to explicitly model and represent the derivatives of smooth underlying trajectories for longitudinal data. This representation is based on a direct Karhunen--Loève expansion of the unobserved derivatives and leads to the notion of derivative principal component analysis, which comple...
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Stokes phenomenon and confluence in non-autonomous Hamiltonian systems
This article studies a confluence of a pair of regular singular points to an irregular one in a generic family of time-dependent Hamiltonian systems in dimension 2. This is a general setting for the understanding of the degeneration of the sixth Painleve equation to the fifth one. The main result is a theorem of sect...
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A General Sequential Delay-Doppler Estimation Scheme for Sub-Nyquist Pulse-Doppler Radar
Sequential estimation of the delay and Doppler parameters for sub-Nyquist radars by analog-to-information conversion (AIC) systems has received wide attention recently. However, the estimation methods reported are AIC-dependent and have poor performance for off-grid targets. This paper develops a general estimation s...
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The independence number of the Birkhoff polytope graph, and applications to maximally recoverable codes
Maximally recoverable codes are codes designed for distributed storage which combine quick recovery from single node failure and optimal recovery from catastrophic failure. Gopalan et al [SODA 2017] studied the alphabet size needed for such codes in grid topologies and gave a combinatorial characterization for it. Co...
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Spin Angular Momentum of Proton Spin Puzzle in Complex Octonion Spaces
The paper focuses on considering some special precessional motions as the spin motions, separating the octonion angular momentum of a proton into six components, elucidating the proton angular momentum in the proton spin puzzle, especially the proton spin, decomposition, quarks and gluons, and polarization and so for...
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Physics-Informed Regularization of Deep Neural Networks
This paper presents a novel physics-informed regularization method for training of deep neural networks (DNNs). In particular, we focus on the DNN representation for the response of a physical or biological system, for which a set of governing laws are known. These laws often appear in the form of differential equati...
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Gradient-based Filter Design for the Dual-tree Wavelet Transform
The wavelet transform has seen success when incorporated into neural network architectures, such as in wavelet scattering networks. More recently, it has been shown that the dual-tree complex wavelet transform can provide better representations than the standard transform. With this in mind, we extend our previous me...
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Assimilated LVEF: A Bayesian technique combining human intuition with machine measurement for sharper estimates of left ventricular ejection fraction and stronger association with outcomes
The cardiologist's main tool for measuring systolic heart failure is left ventricular ejection fraction (LVEF). Trained cardiologist's report both a visual and machine-guided measurement of LVEF, but only use this machine-guided measurement in analysis. We use a Bayesian technique to combine visual and machine-guided...
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DBSCAN: Optimal Rates For Density Based Clustering
We study the problem of optimal estimation of the density cluster tree under various assumptions on the underlying density. Building up from the seminal work of Chaudhuri et al. [2014], we formulate a new notion of clustering consistency which is better suited to smooth densities, and derive minimax rates of consiste...
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Steganographic Generative Adversarial Networks
Steganography is collection of methods to hide secret information ("payload") within non-secret information ("container"). Its counterpart, Steganalysis, is the practice of determining if a message contains a hidden payload, and recovering it if possible. Presence of hidden payloads is typically detected by a binary ...
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Minimal Sum Labeling of Graphs
A graph $G$ is called a sum graph if there is a so-called sum labeling of $G$, i.e. an injective function $\ell: V(G) \rightarrow \mathbb{N}$ such that for every $u,v\in V(G)$ it holds that $uv\in E(G)$ if and only if there exists a vertex $w\in V(G)$ such that $\ell(u)+\ell(v) = \ell(w)$. We say that sum labeling $\...
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Provably efficient RL with Rich Observations via Latent State Decoding
We study the exploration problem in episodic MDPs with rich observations generated from a small number of latent states. Under certain identifiability assumptions, we demonstrate how to estimate a mapping from the observations to latent states inductively through a sequence of regression and clustering steps---where ...
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Markov Chain Lifting and Distributed ADMM
The time to converge to the steady state of a finite Markov chain can be greatly reduced by a lifting operation, which creates a new Markov chain on an expanded state space. For a class of quadratic objectives, we show an analogous behavior where a distributed ADMM algorithm can be seen as a lifting of Gradient Desce...
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Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis
Generating versatile and appropriate synthetic speech requires control over the output expression separate from the spoken text. Important non-textual speech variation is seldom annotated, in which case output control must be learned in an unsupervised fashion. In this paper, we perform an in-depth study of methods f...
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Fast failover of multicast sessions in software-defined networks
With the rapid growth of services that stream to groups of users comes an increased importance of and demand for reliable multicast. In this paper, we turn to software-defined networking and develop a novel general-purpose multi-failure protection algorithm to provide quick failure recovery, via Fast Failover (FF) gr...
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AI Safety Gridworlds
We present a suite of reinforcement learning environments illustrating various safety properties of intelligent agents. These problems include safe interruptibility, avoiding side effects, absent supervisor, reward gaming, safe exploration, as well as robustness to self-modification, distributional shift, and adversa...
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Maximality of Galois actions for abelian varieties
Let $\{\rho_\ell\}_\ell$ be the system of $\ell$-adic representations arising from the $i$th $\ell$-adic cohomology of a complete smooth variety $X$ defined over a number field $K$. Denote the image of $\rho_\ell$ by $\Gamma_\ell$ and its Zariski closure, which is a linear algebraic group over $\mathbb{Q}_\ell$, by $...
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An Application of Multi-band Forced Photometry to One Square Degree of SERVS: Accurate Photometric Redshifts and Implications for Future Science
We apply The Tractor image modeling code to improve upon existing multi-band photometry for the Spitzer Extragalactic Representative Volume Survey (SERVS). SERVS consists of post-cryogenic Spitzer observations at 3.6 and 4.5 micron over five well-studied deep fields spanning 18 square degrees. In concert with data fr...
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Stacked Structure Learning for Lifted Relational Neural Networks
Lifted Relational Neural Networks (LRNNs) describe relational domains using weighted first-order rules which act as templates for constructing feed-forward neural networks. While previous work has shown that using LRNNs can lead to state-of-the-art results in various ILP tasks, these results depended on hand-crafted ...
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Spec-QP: Speculative Query Planning for Joins over Knowledge Graphs
Organisations store huge amounts of data from multiple heterogeneous sources in the form of Knowledge Graphs (KGs). One of the ways to query these KGs is to use SPARQL queries over a database engine. Since SPARQL follows exact match semantics, the queries may return too few or no results. Recent works have proposed q...
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SurfClipse: Context-Aware Meta Search in the IDE
Despite various debugging supports of the existing IDEs for programming errors and exceptions, software developers often look at web for working solutions or any up-to-date information. Traditional web search does not consider the context of the problems that they search solutions for, and thus it often does not help...
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Chomp on numerical semigroups
We consider the two-player game chomp on posets associated to numerical semigroups and show that the analysis of strategies for chomp is strongly related to classical properties of semigroups. We characterize, which player has a winning-strategy for symmetric semigroups, semigroups of maximal embedding dimension and ...
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Single Index Latent Variable Models for Network Topology Inference
A semi-parametric, non-linear regression model in the presence of latent variables is applied towards learning network graph structure. These latent variables can correspond to unmodeled phenomena or unmeasured agents in a complex system of interacting entities. This formulation jointly estimates non-linearities in t...
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Quadratically-Regularized Optimal Transport on Graphs
Optimal transportation provides a means of lifting distances between points on a geometric domain to distances between signals over the domain, expressed as probability distributions. On a graph, transportation problems can be used to express challenging tasks involving matching supply to demand with minimal shipment...
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Discussion on "Random-projection ensemble classification" by T. Cannings and R. Samworth
Discussion on "Random-projection ensemble classification" by T. Cannings and R. Samworth. We believe that the proposed approach can find many applications in economics such as credit scoring (e.g. Altman (1968)) and can be extended to more general type of classifiers. In this discussion we would like to draw authors ...
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Deep Asymmetric Multi-task Feature Learning
We propose Deep Asymmetric Multitask Feature Learning (Deep-AMTFL) which can learn deep representations shared across multiple tasks while effectively preventing negative transfer that may happen in the feature sharing process. Specifically, we introduce an asymmetric autoencoder term that allows reliable predictors ...
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Sub-nanometre resolution of atomic motion during electronic excitation in phase-change materials
Phase-change materials based on Ge-Sb-Te alloys are widely used in industrial applications such as nonvolatile memories, but reaction pathways for crystalline-to-amorphous phase-change on picosecond timescales remain unknown. Femtosecond laser excitation and an ultrashort x-ray probe is used to show the temporal sepa...
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A Density Result for Real Hyperelliptic Curves
Let $\{\infty^+, \infty^-\}$ be the two points above $\infty$ on the real hyperelliptic curve $H: y^2 = (x^2 - 1) \prod_{i=1}^{2g} (x - a_i)$. We show that the divisor $([\infty^+] - [\infty^-])$ is torsion in $\operatorname{Jac} J$ for a dense set of $(a_1, a_2, \ldots, a_{2g}) \in (-1, 1)^{2g}$. In fact, we prove b...
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On a class of integrable systems of Monge-Ampère type
We investigate a class of multi-dimensional two-component systems of Monge-Ampère type that can be viewed as generalisations of heavenly-type equations appearing in self-dual Ricci-flat geometry. Based on the Jordan-Kronecker theory of skew-symmetric matrix pencils, a classification of normal forms of such systems is...
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When is the mode functional the Bayes classifier?
In classification problems, the mode of the conditional probability distribution, i.e., the most probable category, is the Bayes classifier under zero-one or misclassification loss. Under any other cost structure, the mode fails to persist.
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Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity Data
One of the main benefits of a wrist-worn computer is its ability to collect a variety of physiological data in a minimally intrusive manner. Among these data, electrodermal activity (EDA) is readily collected and provides a window into a person's emotional and sympathetic responses. EDA data collected using a wearabl...
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CredSaT: Credibility Ranking of Users in Big Social Data incorporating Semantic Analysis and Temporal Factor
The widespread use of big social data has pointed the research community in several significant directions. In particular, the notion of social trust has attracted a great deal of attention from information processors | computer scientists and information consumers | formal organizations. This is evident in various a...
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On singular Finsler foliation
In this paper we introduce the concept of singular Finsler foliation, which generalizes the concepts of Finsler actions, Finsler submersions and (regular) Finsler foliations. We show that if $\mathcal{F}$ is a singular Finsler foliation on a Randers manifold $(M,Z)$ with Zermelo data $(\mathtt{h},W),$ then $\mathcal{...
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Early Experiences with Crowdsourcing Airway Annotations in Chest CT
Measuring airways in chest computed tomography (CT) images is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotated data to perform well. We investigate whether crowdsourcing can be...
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Convergent Iteration in Sobolev Space for Time Dependent Closed Quantum Systems
Time dependent quantum systems have become indispensable in science and its applications, particularly at the atomic and molecular levels. Here, we discuss the approximation of closed time dependent quantum systems on bounded domains, via iterative methods in Sobolev space based upon evolution operators. Recently, ex...
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Prototyping and Experimentation of a Closed-Loop Wireless Power Transmission with Channel Acquisition and Waveform Optimization
A systematic design of adaptive waveform for Wireless Power Transfer (WPT) has recently been proposed and shown through simulations to lead to significant performance benefits compared to traditional non-adaptive and heuristic waveforms. In this study, we design the first prototype of a closed-loop wireless power tra...
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Image-based immersed boundary model of the aortic root
Each year, approximately 300,000 heart valve repair or replacement procedures are performed worldwide, including approximately 70,000 aortic valve replacement surgeries in the United States alone. This paper describes progress in constructing anatomically and physiologically realistic immersed boundary (IB) models of...
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Large-Scale Cox Process Inference using Variational Fourier Features
Gaussian process modulated Poisson processes provide a flexible framework for modelling spatiotemporal point patterns. So far this had been restricted to one dimension, binning to a pre-determined grid, or small data sets of up to a few thousand data points. Here we introduce Cox process inference based on Fourier fe...
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Buildings-to-Grid Integration Framework
This paper puts forth a mathematical framework for Buildings-to-Grid (BtG) integration in smart cities. The framework explicitly couples power grid and building's control actions and operational decisions, and can be utilized by buildings and power grids operators to simultaneously optimize their performance. Simplif...
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Oxygen Partial Pressure during Pulsed Laser Deposition: Deterministic Role on Thermodynamic Stability of Atomic Termination Sequence at SrRuO3/BaTiO3 Interface
With recent trends on miniaturizing oxide-based devices, the need for atomic-scale control of surface/interface structures by pulsed laser deposition (PLD) has increased. In particular, realizing uniform atomic termination at the surface/interface is highly desirable. However, a lack of understanding on the surface f...
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A Data-Driven Analysis of the Influence of Care Coordination on Trauma Outcome
OBJECTIVE: To test the hypothesis that variation in care coordination is related to LOS. DESIGN We applied a spectral co-clustering methodology to simultaneously infer groups of patients and care coordination patterns, in the form of interaction networks of health care professionals, from electronic medical record (E...
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Construction of Non-asymptotic Confidence Sets in 2-Wasserstein Space
In this paper, we consider a probabilistic setting where the probability measures are considered to be random objects. We propose a procedure of construction non-asymptotic confidence sets for empirical barycenters in 2-Wasserstein space and develop the idea further to construction of a non-parametric two-sample test...
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Limits on statistical anisotropy from BOSS DR12 galaxies using bipolar spherical harmonics
We measure statistically anisotropic signatures imprinted in three-dimensional galaxy clustering using bipolar spherical harmonics (BipoSHs) in both Fourier space and configuration space. We then constrain a well-known quadrupolar anisotropy parameter $g_{2M}$ in the primordial power spectrum, parametrized by $P(\vec...
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A Central Limit Theorem for Wasserstein type distances between two different laws
This article is dedicated to the estimation of Wasserstein distances and Wasserstein costs between two distinct continuous distributions $F$ and $G$ on $\mathbb R$. The estimator is based on the order statistics of (possibly dependent) samples of $F$ resp. $G$. We prove the consistency and the asymptotic normality of...
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Confidence Intervals for Stochastic Arithmetic
Quantifying errors and losses due to the use of Floating-Point (FP) calculations in industrial scientific computing codes is an important part of the Verification, Validation and Uncertainty Quantification (VVUQ) process. Stochastic Arithmetic is one way to model and estimate FP losses of accuracy, which scales well ...
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Contaminated speech training methods for robust DNN-HMM distant speech recognition
Despite the significant progress made in the last years, state-of-the-art speech recognition technologies provide a satisfactory performance only in the close-talking condition. Robustness of distant speech recognition in adverse acoustic conditions, on the other hand, remains a crucial open issue for future applicat...
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Co-segmentation for Space-Time Co-located Collections
We present a co-segmentation technique for space-time co-located image collections. These prevalent collections capture various dynamic events, usually by multiple photographers, and may contain multiple co-occurring objects which are not necessarily part of the intended foreground object, resulting in ambiguities fo...
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Speaker Diarization with LSTM
For many years, i-vector based audio embedding techniques were the dominant approach for speaker verification and speaker diarization applications. However, mirroring the rise of deep learning in various domains, neural network based audio embeddings, also known as d-vectors, have consistently demonstrated superior s...
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Almost h-conformal semi-invariant submersions from almost quaternionic Hermitian manifolds
As a generalization of Riemannian submersions, horizontally conformal submersions, semi-invariant submersions, h-semi-invariant submersions, almost h-semi-invariant submersions, conformal semi-invariant submersions, we introduce h-conformal semi-invariant submersions and almost h-conformal semi-invariant submersions ...
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Use of Source Code Similarity Metrics in Software Defect Prediction
In recent years, defect prediction has received a great deal of attention in the empirical software engineering world. Predicting software defects before the maintenance phase is very important not only to decrease the maintenance costs but also increase the overall quality of a software product. There are different ...
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Connecting pairwise spheres by depth: DCOPS
We extend the classical notion of the spherical depth in \mathbb{R}^k, to the important setup of data on a Riemannian manifold. We show that this notion of depth satisfies a set of desirable properties. For the empirical version of this depth function both uniform consistency and the asymptotic distribution are studi...
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Estimating the spectral gap of a trace-class Markov operator
The utility of a Markov chain Monte Carlo algorithm is, in large part, determined by the size of the spectral gap of the corresponding Markov operator. However, calculating (and even approximating) the spectral gaps of practical Monte Carlo Markov chains in statistics has proven to be an extremely difficult and often...
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Tidal synchronization of an anelastic multi-layered body: Titan's synchronous rotation
This paper presents one analytical tidal theory for a viscoelastic multi-layered body with an arbitrary number of homogeneous layers. Starting with the static equilibrium figure, modified to include tide and differential rotation, and using the Newtonian creep approach, we find the dynamical equilibrium figure of the...
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On Lie algebras responsible for zero-curvature representations of multicomponent (1+1)-dimensional evolution PDEs
Zero-curvature representations (ZCRs) are one of the main tools in the theory of integrable $(1+1)$-dimensional PDEs. According to the preprint arXiv:1212.2199, for any given $(1+1)$-dimensional evolution PDE one can define a sequence of Lie algebras $F^p$, $p=0,1,2,3,\dots$, such that representations of these algebr...
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TRAMP: Tracking by a Real-time AMbisonic-based Particle filter
This article presents a multiple sound source localization and tracking system, fed by the Eigenmike array. The First Order Ambisonics (FOA) format is used to build a pseudointensity-based spherical histogram, from which the source position estimates are deduced. These instantaneous estimates are processed by a wellk...
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Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity
In this paper we present a scalable approach for robustly computing a 3D surface mesh from multi-scale multi-view stereo point clouds that can handle extreme jumps of point density (in our experiments three orders of magnitude). The backbone of our approach is a combination of octree data partitioning, local Delaunay...
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General Bounds for Incremental Maximization
We propose a theoretical framework to capture incremental solutions to cardinality constrained maximization problems. The defining characteristic of our framework is that the cardinality/support of the solution is bounded by a value $k\in\mathbb{N}$ that grows over time, and we allow the solution to be extended one e...
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Arrangements of pseudocircles on surfaces
A pseudocircle is a simple closed curve on some surface. Arrangements of pseudocircles were introduced by Grünbaum, who defined them as collections of pseudocircles that pairwise intersect in exactly two points, at which they cross. There are several variations on this notion in the literature, one of which requires ...
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Scalable methods for Bayesian selective inference
Modeled along the truncated approach in Panigrahi (2016), selection-adjusted inference in a Bayesian regime is based on a selective posterior. Such a posterior is determined together by a generative model imposed on data and the selection event that enforces a truncation on the assumed law. The effective difference b...
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Modified Recursive Cholesky (Rchol) Algorithm: An Explicit Estimation and Pseudo-inverse of Correlation Matrices
The Cholesky decomposition plays an important role in finding the inverse of the correlation matrices. As it is a fast and numerically stable for linear system solving, inversion, and factorization compared to singular valued decomposition (SVD), QR factorization and LU decomposition. As different methods exist to fi...
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A Utility-Driven Multi-Queue Admission Control Solution for Network Slicing
The combination of recent emerging technologies such as network function virtualization (NFV) and network programmability (SDN) gave birth to the Network Slicing revolution. 5G networks consist of multi-tenant infrastructures capable of offering leased network "slices" to new customers (e.g., vertical industries) ena...
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Statistical inference for network samples using subgraph counts
We consider that a network is an observation, and a collection of observed networks forms a sample. In this setting, we provide methods to test whether all observations in a network sample are drawn from a specified model. We achieve this by deriving, under the null of the graphon model, the joint asymptotic properti...
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