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Hermitian-Yang-Mills connections on collapsing elliptically fibered $K3$ surfaces
Let $X\rightarrow {\mathbb P}^1$ be an elliptically fibered $K3$ surface with a section, admitting a sequence of Ricci-flat metrics collapsing the fibers. Let $\mathcal E$ be a generic, holomoprhic $SU(n)$ bundle over $X$ such that the restriction of $\mathcal E$ to each fiber is semi-stable. Given a sequence $\Xi_i$...
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Highly Efficient Human Action Recognition with Quantum Genetic Algorithm Optimized Support Vector Machine
In this paper we propose the use of quantum genetic algorithm to optimize the support vector machine (SVM) for human action recognition. The Microsoft Kinect sensor can be used for skeleton tracking, which provides the joints' position data. However, how to extract the motion features for representing the dynamics of...
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The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI
We present a vision-only model for gaming AI which uses a late integration deep convolutional network architecture trained in a purely supervised imitation learning context. Although state-of-the-art deep learning models for video game tasks generally rely on more complex methods such as deep-Q learning, we show that...
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Differential relations for almost Belyi maps
Several kinds of differential relations for polynomial components of almost Belyi maps are presented. Saito's theory of free divisors give particularly interesting (yet conjectural) logarithmic action of vector fields. The differential relations implied by Kitaev's construction of algebraic Painleve VI solutions thro...
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Non-commutative holomorphic semicocycles
This paper studies holomorphic semicocycles over semigroups in the unit disk, which take values in an arbitrary unital Banach algebra. We prove that every such semicocycle is a solution to a corresponding evolution problem. We then investigate the linearization problem: which semicocycles are cohomologous to constant...
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Comparative Study of Virtual Machines and Containers for DevOps Developers
In this work, we plan to develop a system to compare virtual machines with container technology. We would devise ways to measure the administrator effort of containers vs. Virtual Machines (VMs). Metrics that will be tested against include human efforts required, ease of migration, resource utilization and ease of us...
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Developmental tendencies in the Academic Field of Intellectual Property through the Identification of Invisible Colleges
The emergence of intellectual property as an academic issue opens a big gate to a cross-disciplinary field. Different disciplines start a dialogue in the framework of the international multilateral treaties in the early 90's. As global economy demands new knowledge on intellectual property, Science grows at its own p...
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Periodic fourth-order cubic NLS: Local well-posedness and Non-squeezing property
In this paper, we consider the cubic fourth-order nonlinear Schrödinger equation (4NLS) under the periodic boundary condition. We prove two results. One is the local well-posedness in $H^s$ with $-1/3 \le s < 0$ for the Cauchy problem of the Wick ordered 4NLS. The other one is the non-squeezing property for the flow ...
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Feature Learning for Meta-Paths in Knowledge Graphs
In this thesis, we study the problem of feature learning on heterogeneous knowledge graphs. These features can be used to perform tasks such as link prediction, classification and clustering on graphs. Knowledge graphs provide rich semantics encoded in the edge and node types. Meta-paths consist of these types and ab...
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Closed-Form Exact Inverses of the Weakly Singular and Hypersingular Operators On Disks
We introduce new boundary integral operators which are the exact inverses of the weakly singular and hypersingular operators for the Laplacian on flat disks. Moreover, we provide explicit closed forms for them and prove the continuity and ellipticity of their corresponding bilinear forms in the natural Sobolev trace ...
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Focus on Imaging Methods in Granular Physics
Granular materials are complex multi-particle ensembles in which macroscopic properties are largely determined by inter-particle interactions between their numerous constituents. In order to understand and to predict their macroscopic physical behavior, it is necessary to analyze the composition and interactions at t...
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The Stochastic Matching Problem: Beating Half with a Non-Adaptive Algorithm
In the stochastic matching problem, we are given a general (not necessarily bipartite) graph $G(V,E)$, where each edge in $E$ is realized with some constant probability $p > 0$ and the goal is to compute a bounded-degree (bounded by a function depending only on $p$) subgraph $H$ of $G$ such that the expected maximum ...
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Measuring the unmeasurable - a project of domestic violence risk prediction and management
The prevention of domestic violence (DV) have aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported DV cases that doubled over the past decade and the scarcity of social workers. Additionally, a large amount of data was collected when social workers use the predominant ...
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Attaining Capacity with Algebraic Geometry Codes through the $(U|U+V)$ Construction and Koetter-Vardy Soft Decoding
In this paper we show how to attain the capacity of discrete symmetric channels with polynomial time decoding complexity by considering iterated $(U|U+V)$ constructions with Reed-Solomon code or algebraic geometry code components. These codes are decoded with a recursive computation of the {\em a posteriori} probabil...
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Embedded real-time monitoring using SystemC in IMA network
Avionics is one kind of domain where prevention prevails. Nonetheless fails occur. Sometimes due to pilot misreacting, flooded in information. Sometimes information itself would be better verified than trusted. To avoid some kind of failure, it has been thought to add,in midst of the ARINC664 aircraft data network, a...
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One pixel attack for fooling deep neural networks
Recent research has revealed that the output of Deep Neural Networks (DNN) can be easily altered by adding relatively small perturbations to the input vector. In this paper, we analyze an attack in an extremely limited scenario where only one pixel can be modified. For that we propose a novel method for generating on...
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A computer simulation of the Volga River hydrological regime: a problem of water-retaining dam optimal location
We investigate of a special dam optimal location at the Volga river in area of the Akhtuba left sleeve beginning (7 \, km to the south of the Volga Hydroelectric Power Station dam). We claim that a new water-retaining dam can resolve the key problem of the Volga-Akhtuba floodplain related to insufficient water amount...
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Multi-proton bunch driven hollow plasma wakefield acceleration in the nonlinear regime
Proton-driven plasma wakefield acceleration has been demonstrated in simulations to be capable of accelerating particles to the energy frontier in a single stage, but its potential is hindered by the fact that currently available proton bunches are orders of magnitude longer than the plasma wavelength. Fortunately, p...
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Self corrective Perturbations for Semantic Segmentation and Classification
Convolutional Neural Networks have been a subject of great importance over the past decade and great strides have been made in their utility for producing state of the art performance in many computer vision problems. However, the behavior of deep networks is yet to be fully understood and is still an active area of ...
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Large-Scale Mapping of Human Activity using Geo-Tagged Videos
This paper is the first work to perform spatio-temporal mapping of human activity using the visual content of geo-tagged videos. We utilize a recent deep-learning based video analysis framework, termed hidden two-stream networks, to recognize a range of activities in YouTube videos. This framework is efficient and ca...
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Structure of a Parabolic Partial Differential Equation on Graphs and Digital spaces. Solution of PDE on Digital Spaces: a Klein Bottle, a Projective Plane, a 4D Sphere and a Moebius Band
This paper studies the structure of a parabolic partial differential equation on graphs and digital n-dimensional manifolds, which are digital models of continuous n-manifolds. Conditions for the existence of solutions of equations are determined and investigated. Numerical solutions of the equation on a Klein bottle...
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GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks
In this paper, we generally formulate the dynamics prediction problem of various network systems (e.g., the prediction of mobility, traffic and topology) as the temporal link prediction task. Different from conventional techniques of temporal link prediction that ignore the potential non-linear characteristics and th...
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Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs
Graphs are an important tool to model data in different domains, including social networks, bioinformatics and the world wide web. Most of the networks formed in these domains are directed graphs, where all the edges have a direction and they are not symmetric. Betweenness centrality is an important index widely used...
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A multi-instrument non-parametric reconstruction of the electron pressure profile in the galaxy cluster CLJ1226.9+3332
Context: In the past decade, sensitive, resolved Sunyaev-Zel'dovich (SZ) studies of galaxy clusters have become common. Whereas many previous SZ studies have parameterized the pressure profiles of galaxy clusters, non-parametric reconstructions will provide insights into the thermodynamic state of the intracluster me...
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Recognizing Union-Find trees built up using union-by-rank strategy is NP-complete
Disjoint-Set forests, consisting of Union-Find trees, are data structures having a widespread practical application due to their efficiency. Despite them being well-known, no exact structural characterization of these trees is known (such a characterization exists for Union trees which are constructed without using p...
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A Competitive Algorithm for Online Multi-Robot Exploration of a Translating Plume
In this paper, we study the problem of exploring a translating plume with a team of aerial robots. The shape and the size of the plume are unknown to the robots. The objective is to find a tour for each robot such that they collectively explore the plume. Specifically, the tours must be such that each point in the pl...
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Warped Riemannian metrics for location-scale models
The present paper shows that warped Riemannian metrics, a class of Riemannian metrics which play a prominent role in Riemannian geometry, are also of fundamental importance in information geometry. Precisely, the paper features a new theorem, which states that the Rao-Fisher information metric of any location-scale m...
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Admissibility of solution estimators for stochastic optimization
We look at stochastic optimization problems through the lens of statistical decision theory. In particular, we address admissibility, in the statistical decision theory sense, of the natural sample average estimator for a stochastic optimization problem (which is also known as the empirical risk minimization (ERM) ru...
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Min-Max Regret Scheduling To Minimize the Total Weight of Late Jobs With Interval Uncertainty
We study the single machine scheduling problem with the objective to minimize the total weight of late jobs. It is assumed that the processing times of jobs are not exactly known at the time when a complete schedule must be dispatched. Instead, only interval bounds for these parameters are given. In contrast to the s...
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Correcting rural building annotations in OpenStreetMap using convolutional neural networks
Rural building mapping is paramount to support demographic studies and plan actions in response to crisis that affect those areas. Rural building annotations exist in OpenStreetMap (OSM), but their quality and quantity are not sufficient for training models that can create accurate rural building maps. The problems w...
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Closed-form Harmonic Contrast Control with Surface Impedance Coatings for Conductive Objects
The problem of suppressing the scattering from conductive objects is addressed in terms of harmonic contrast reduction. A unique compact closed-form solution for a surface impedance $Z_s(m,kr)$ is found in a straightforward manner and without any approximation as a function of the harmonic index $m$ (scattering mode ...
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Numerical methods to prevent pressure oscillations in transcritical flows
The accurate and robust simulation of transcritical real-fluid effects is crucial for many engineering applications, such as fuel injection in internal combustion engines, rocket engines and gas turbines. For example, in diesel engines, the liquid fuel is injected into the ambient gas at a pressure that exceeds its c...
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Shape Convergence for Aggregate Tiles in Conformal Tilings
Given a substitution tiling $T$ of the plane with subdivision operator $\tau$, we study the conformal tilings $\mathcal{T}_n$ associated with $\tau^n T$. We prove that aggregate tiles within $\mathcal{T}_n$ converge in shape as $n\rightarrow \infty$ to their associated Euclidean tiles in $T$.
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Performance and sensitivity of vortex coronagraphs on segmented space telescopes
The detection of molecular species in the atmospheres of earth-like exoplanets orbiting nearby stars requires an optical system that suppresses starlight and maximizes the sensitivity to the weak planet signals at small angular separations. Achieving sufficient contrast performance on a segmented aperture space teles...
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Classical Spacetime Structure
I discuss several issues related to "classical" spacetime structure. I review Galilean, Newtonian, and Leibnizian spacetimes, and briefly describe more recent developments. The target audience is undergraduates and early graduate students in philosophy; the presentation avoids mathematical formalism as much as possib...
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Fractal curves from prime trigonometric series
We study the convergence of the parameter family of series $$V_{\alpha,\beta}(t)=\sum_{p}p^{-\alpha}\exp(2\pi i p^{\beta}t),\quad \alpha,\beta \in \mathbb{R}_{>0},\; t \in [0,1)$$ defined over prime numbers $p$, and subsequently, their differentiability properties. The visible fractal nature of the graphs as a functi...
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Facets on the convex hull of $d$-dimensional Brownian and Lévy motion
For stationary, homogeneous Markov processes (viz., Lévy processes, including Brownian motion) in dimension $d\geq 3$, we establish an exact formula for the average number of $(d-1)$-dimensional facets that can be defined by $d$ points on the process's path. This formula defines a universality class in that it is ind...
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Local systems on complements of arrangements of smooth, complex algebraic hypersurfaces
We consider smooth, complex quasi-projective varieties $U$ which admit a compactification with a boundary which is an arrangement of smooth algebraic hypersurfaces. If the hypersurfaces intersect locally like hyperplanes, and the relative interiors of the hypersurfaces are Stein manifolds, we prove that the cohomolog...
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Some Open Problems in Random Matrix Theory and the Theory of Integrable Systems. II
We describe a list of open problems in random matrix theory and the theory of integrable systems that was presented at the conference Asymptotics in Integrable Systems, Random Matrices and Random Processes and Universality, Centre de Recherches Mathematiques, Montreal, June 7-11, 2015. We also describe progress that ...
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A semi-parametric estimation for max-mixture spatial processes
We proposed a semi-parametric estimation procedure in order to estimate the parameters of a max-mixture model and also of a max-stable model (inverse max-stable model) as an alternative to composite likelihood. A good estimation by the proposed estimator required the dependence measure to detect all dependence struct...
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Spectroscopic Observation and Analysis of HII regions in M33 with MMT: Temperatures and Oxygen Abundances
The spectra of 413 star-forming (or HII) regions in M33 (NGC 598) were observed by using the multifiber spectrograph of Hectospec at the 6.5-m Multiple Mirror Telescope (MMT). By using this homogeneous spectra sample, we measured the intensities of emission lines and some physical parameters, such as electron tempera...
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Output-only parameter identification of a colored-noise-driven Van der Pol oscillator -- Thermoacoustic instabilities as an example
The problem of output-only parameter identification for nonlinear oscillators forced by colored noise is considered. In this context, it is often assumed that the forcing noise is white, since its actual spectral content is unknown. The impact of this white noise forcing assumption upon parameter identification is qu...
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Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manually intensive delineation of radiosensitive organs at risk (OARs). This planning process can delay treatment commencement. While auto-segm...
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Anomaly Detection in Hierarchical Data Streams under Unknown Models
We consider the problem of detecting a few targets among a large number of hierarchical data streams. The data streams are modeled as random processes with unknown and potentially heavy-tailed distributions. The objective is an active inference strategy that determines, sequentially, which data stream to collect samp...
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Intelligent Parameter Tuning in Optimization-based Iterative CT Reconstruction via Deep Reinforcement Learning
A number of image-processing problems can be formulated as optimization problems. The objective function typically contains several terms specifically designed for different purposes. Parameters in front of these terms are used to control the relative weights among them. It is of critical importance to tune these par...
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Adversarial Examples that Fool Detectors
An adversarial example is an example that has been adjusted to produce a wrong label when presented to a system at test time. To date, adversarial example constructions have been demonstrated for classifiers, but not for detectors. If adversarial examples that could fool a detector exist, they could be used to (for e...
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FLUX: Progressive State Estimation Based on Zakai-type Distributed Ordinary Differential Equations
We propose a homotopy continuation method called FLUX for approximating complicated probability density functions. It is based on progressive processing for smoothly morphing a given density into the desired one. Distributed ordinary differential equations (DODEs) with an artificial time $\gamma \in [0,1]$ are derive...
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Direct and mediating influences of user-developer perception gaps in requirements understanding on user participation
User participation is considered an effective way to conduct requirements engineering, but user-developer perception gaps in requirements understanding occur frequently. Since user participation in practice is not as active as we expect and the requirements perception gap has been recognized as a risk that negatively...
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Equivariant Schrödinger maps from two dimensional hyperbolic space
In this article, we consider the equivariant Schrödinger map from $\Bbb H^2$ to $\Bbb S^2$ which converges to the north pole of $\Bbb S^2$ at the origin and spatial infinity of the hyperbolic space. If the energy of the data is less than $4\pi$, we show that the local existence of Schrödinger map. Furthermore, if the...
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A fast numerical method for ideal fluid flow in domains with multiple stirrers
A collection of arbitrarily-shaped solid objects, each moving at a constant speed, can be used to mix or stir ideal fluid, and can give rise to interesting flow patterns. Assuming these systems of fluid stirrers are two-dimensional, the mathematical problem of resolving the flow field - given a particular distributio...
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A Short Survey on Probabilistic Reinforcement Learning
A reinforcement learning agent tries to maximize its cumulative payoff by interacting in an unknown environment. It is important for the agent to explore suboptimal actions as well as to pick actions with highest known rewards. Yet, in sensitive domains, collecting more data with exploration is not always possible, b...
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Modification of low-temperature silicon dioxide films under the influence of technology factors
The structure, composition and electrophysical characteristics of low-temperature silicon dioxide films under influence of various technology factors, such as ion implantation, laser irradiation, thermal and photonic annealing, have been studied. Silicon dioxide films have been obtained by monosilane oxidation using ...
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GelSlim: A High-Resolution, Compact, Robust, and Calibrated Tactile-sensing Finger
This work describes the development of a high-resolution tactile-sensing finger for robot grasping. This finger, inspired by previous GelSight sensing techniques, features an integration that is slimmer, more robust, and with more homogeneous output than previous vision-based tactile sensors. To achieve a compact int...
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The Muon g-2 experiment at Fermilab
The upcoming Fermilab E989 experiment will measure the muon anomalous magnetic moment $a_{\mu}$ . This measurement is motivated by the previous measurement performed in 2001 by the BNL E821 experiment that reported a 3-4 standard deviation discrepancy between the measured value and the Standard Model prediction. The ...
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Ringel duality as an instance of Koszul duality
In their previous work, S. Koenig, S. Ovsienko and the second author showed that every quasi-hereditary algebra is Morita equivalent to the right algebra, i.e. the opposite algebra of the left dual, of a coring. Let $A$ be an associative algebra and $V$ an $A$-coring whose right algebra $R$ is quasi-hereditary. In th...
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Bypass Fraud Detection: Artificial Intelligence Approach
Telecom companies are severely damaged by bypass fraud or SIM boxing. However, there is a shortage of published research to tackle this problem. The traditional method of Test Call Generating is easily overcome by fraudsters and the need for more sophisticated ways is inevitable. In this work, we are developing intel...
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Absence of cyclotron resonance in the anomalous metallic phase in InO$_x$
It is observed that many thin superconducting films with not too high disorder level (generally R$_N/\Box \leq 2000 \Omega$) placed in magnetic field show an anomalous metallic phase where the resistance is low but still finite as temperature goes to zero. Here we report in weakly disordered amorphous InO$_x$ thin fi...
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Scenario Reduction Revisited: Fundamental Limits and Guarantees
The goal of scenario reduction is to approximate a given discrete distribution with another discrete distribution that has fewer atoms. We distinguish continuous scenario reduction, where the new atoms may be chosen freely, and discrete scenario reduction, where the new atoms must be chosen from among the existing on...
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Testing the science/technology relationship by analysis of patent citations of scientific papers after decomposition of both science and technology
The relationship of scientific knowledge development to technological development is widely recognized as one of the most important and complex aspects of technological evolution. This paper adds to our understanding of the relationship through use of a more rigorous structure for differentiating among technologies b...
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The Informativeness of $k$-Means and Dimensionality Reduction for Learning Mixture Models
The learning of mixture models can be viewed as a clustering problem. Indeed, given data samples independently generated from a mixture of distributions, we often would like to find the correct target clustering of the samples according to which component distribution they were generated from. For a clustering proble...
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A Mention-Ranking Model for Abstract Anaphora Resolution
Resolving abstract anaphora is an important, but difficult task for text understanding. Yet, with recent advances in representation learning this task becomes a more tangible aim. A central property of abstract anaphora is that it establishes a relation between the anaphor embedded in the anaphoric sentence and its (...
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Harmonic density interpolation methods for high-order evaluation of Laplace layer potentials in 2D and 3D
We present an effective harmonic density interpolation method for the numerical evaluation of singular and nearly singular Laplace boundary integral operators and layer potentials in two and three spatial dimensions. The method relies on the use of Green's third identity and local Taylor-like interpolations of densit...
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Stochastic Low-Rank Bandits
Many problems in computer vision and recommender systems involve low-rank matrices. In this work, we study the problem of finding the maximum entry of a stochastic low-rank matrix from sequential observations. At each step, a learning agent chooses pairs of row and column arms, and receives the noisy product of their...
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Temporal resolution of a pre-maximum halt in a Classical Nova: V5589 Sgr observed with STEREO HI-1B
Classical novae show a rapid rise in optical brightness over a few hours. Until recently the rise phase, particularly the phenomenon of a pre-maximum halt, was observed sporadically. Solar observation satellites observing Coronal Mass Ejections enable us to observe the pre-maximum phase in unprecedented temporal reso...
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The Thermophysical Properties of the Bagnold Dunes, Mars: Ground-truthing Orbital Data
In this work, we compare the thermophysical properties and particle sizes derived from the Mars Science Laboratory (MSL) rover's Ground Temperature Sensor (GTS) of the Bagnold dunes, specifically Namib dune, to those derived orbitally from Thermal Emission Imaging System (THEMIS), ultimately linking these measurement...
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Entrywise Eigenvector Analysis of Random Matrices with Low Expected Rank
Recovering low-rank structures via eigenvector perturbation analysis is a common problem in statistical machine learning, such as in factor analysis, community detection, ranking, matrix completion, among others. While a large variety of results provide tight bounds on the average errors between empirical and populat...
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Algorithmic Trading with Fitted Q Iteration and Heston Model
We present the use of the fitted Q iteration in algorithmic trading. We show that the fitted Q iteration helps alleviate the dimension problem that the basic Q-learning algorithm faces in application to trading. Furthermore, we introduce a procedure including model fitting and data simulation to enrich training data ...
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Superrigidity of actions on finite rank median spaces
Finite rank median spaces are a simultaneous generalisation of finite dimensional CAT(0) cube complexes and real trees. If $\Gamma$ is an irreducible lattice in a product of rank one simple Lie groups, we show that every action of $\Gamma$ on a complete, finite rank median space has a global fixed point. This is in s...
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Detecting and Explaining Causes From Text For a Time Series Event
Explaining underlying causes or effects about events is a challenging but valuable task. We define a novel problem of generating explanations of a time series event by (1) searching cause and effect relationships of the time series with textual data and (2) constructing a connecting chain between them to generate an ...
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Mailbox Types for Unordered Interactions
We propose a type system for reasoning on protocol conformance and deadlock freedom in networks of processes that communicate through unordered mailboxes. We model these networks in the mailbox calculus, a mild extension of the asynchronous {\pi}-calculus with first-class mailboxes and selective input. The calculus s...
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The Complexity of Counting Surjective Homomorphisms and Compactions
A homomorphism from a graph G to a graph H is a function from the vertices of G to the vertices of H that preserves edges. A homomorphism is surjective if it uses all of the vertices of H and it is a compaction if it uses all of the vertices of H and all of the non-loop edges of H. Hell and Nesetril gave a complete c...
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A recursive algorithm and a series expansion related to the homogeneous Boltzmann equation for hard potentials with angular cutoff
We consider the spatially homogeneous Boltzmann equation for hard potentials with angular cutoff. This equation has a unique conservative weak solution $(f_t)_{t\geq 0}$, once the initial condition $f_0$ with finite mass and energy is fixed. Taking advantage of the energy conservation, we propose a recursive algorith...
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Periodic auxetics: Structure and design
Materials science has adopted the term of auxetic behavior for structural deformations where stretching in some direction entails lateral widening, rather than lateral shrinking. Most studies, in the last three decades, have explored repetitive or cellular structures and used the notion of negative Poisson's ratio as...
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Asymptotics of maximum likelihood estimation for stable law with $(M)$ parameterization
Asymptotics of maximum likelihood estimation for $\alpha$-stable law are analytically investigated with $(M)$ parameterization. The consistency and asymptotic normality are shown on the interior of the whole parameter space. Although these asymptotics have been proved with $(B)$ parameterization, there are several ga...
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Enabling Massive Deep Neural Networks with the GraphBLAS
Deep Neural Networks (DNNs) have emerged as a core tool for machine learning. The computations performed during DNN training and inference are dominated by operations on the weight matrices describing the DNN. As DNNs incorporate more stages and more nodes per stage, these weight matrices may be required to be sparse...
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Univariate and Bivariate Geometric Discrete Generalized Exponential Distributions
Marshall and Olkin (1997, Biometrika, 84, 641 - 652) introduced a very powerful method to introduce an additional parameter to a class of continuous distribution functions and hence it brings more flexibility to the model. They have demonstrated their method for the exponential and Weibull classes. In the same paper ...
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What Can Machine Learning Teach Us about Communications?
Rapid improvements in machine learning over the past decade are beginning to have far-reaching effects. For communications, engineers with limited domain expertise can now use off-the-shelf learning packages to design high-performance systems based on simulations. Prior to the current revolution in machine learning, ...
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Global stability of a network-based SIRS epidemic model with nonmonotone incidence rate
This paper studies the dynamics of a network-based SIRS epidemic model with vaccination and a nonmonotone incidence rate. This type of nonlinear incidence can be used to describe the psychological or inhibitory effect from the behavioral change of the susceptible individuals when the number of infective individuals o...
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Slicewise definability in first-order logic with bounded quantifier rank
For every $q\in \mathbb N$ let $\textrm{FO}_q$ denote the class of sentences of first-order logic FO of quantifier rank at most $q$. If a graph property can be defined in $\textrm{FO}_q$, then it can be decided in time $O(n^q)$. Thus, minimizing $q$ has favorable algorithmic consequences. Many graph properties amount...
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The efficiency of community detection by most similar node pairs
Community analysis is an important way to ascertain whether or not a complex system consists of sub-structures with different properties. In this paper, we give a two level community structure analysis for the SSCI journal system by most similar co-citation pattern. Five different strategies for the selection of most...
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Composite Adaptive Control for Bilateral Teleoperation Systems without Persistency of Excitation
Composite adaptive control schemes, which use both the system tracking errors and the prediction error to drive the update laws, have become widespread in achieving an improvement of system performance. However, a strong persistent-excitation (PE) condition should be satisfied to guarantee the parameter convergence. ...
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Infinitely many periodic orbits just above the Mañé critical value on the 2-sphere
We introduce a new critical value $c_\infty(L)$ for Tonelli Lagrangians $L$ on the tangent bundle of the 2-sphere without minimizing measures supported on a point. We show that $c_\infty(L)$ is strictly larger than the Mañé critical value $c(L)$, and on every energy level $e\in(c(L),c_\infty(L))$ there exist infinite...
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Decentralized Random Walk-Based Data Collection in Networks
We analyze a decentralized random walk-based algorithm for data collection at the sink in a multi-hop sensor network. Our algorithm, Random-Collect, which involves data packets being passed to random neighbors in the network according to a random walk mechanism, requires no configuration and incurs no routing overhea...
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The Fan Region at 1.5 GHz. I: Polarized synchrotron emission extending beyond the Perseus Arm
The Fan Region is one of the dominant features in the polarized radio sky, long thought to be a local (distance < 500 pc) synchrotron feature. We present 1.3-1.8 GHz polarized radio continuum observations of the region from the Global Magneto-Ionic Medium Survey (GMIMS) and compare them to maps of Halpha and polarize...
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The redshift distribution of cosmological samples: a forward modeling approach
Determining the redshift distribution $n(z)$ of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global $n(z)$ of cosmol...
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DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks
In this paper we develop a novel computational sensing framework for sensing and recovering structured signals. When trained on a set of representative signals, our framework learns to take undersampled measurements and recover signals from them using a deep convolutional neural network. In other words, it learns a t...
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Robotic frameworks, architectures and middleware comparison
Nowadays, the construction of a complex robotic system requires a high level of specialization in a large number of diverse scientific areas. It is reasonable that a single researcher cannot create from scratch the entirety of this system, as it is impossible for him to have the necessary skills in the necessary fiel...
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Analysis of equivalence relation in joint sparse recovery
The joint sparse recovery problem is a generalization of the single measurement vector problem which is widely studied in Compressed Sensing and it aims to recovery a set of jointly sparse vectors. i.e. have nonzero entries concentrated at common location. Meanwhile l_p-minimization subject to matrices is widely used...
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The Stochastic Firefighter Problem
The dynamics of infectious diseases spread is crucial in determining their risk and offering ways to contain them. We study sequential vaccination of individuals in networks. In the original (deterministic) version of the Firefighter problem, a fire breaks out at some node of a given graph. At each time step, b nodes...
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The phase space structure of the oligopoly dynamical system by means of Darboux integrability
We investigate the dynamical complexity of Cournot oligopoly dynamics of three firms by using the qualitative methods of dynamical systems to study the phase structure of this model. The phase space is organized with one-dimensional and two-dimensional invariant submanifolds (for the monopoly and duopoly) and unique ...
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Generalizations of the 'Linear Chain Trick': Incorporating more flexible dwell time distributions into mean field ODE models
Mathematical modelers have long known of a "rule of thumb" referred to as the Linear Chain Trick (LCT; aka the Gamma Chain Trick): a technique used to construct mean field ODE models from continuous-time stochastic state transition models where the time an individual spends in a given state (i.e., the dwell time) is ...
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Life and work of Egbert Brieskorn (1936 - 2013)
Egbert Brieskorn died on July 11, 2013, a few days after his 77th birthday. He was an impressive personality who has left a lasting impression on all who knew him, whether inside or outside of mathematics. Brieskorn was a great mathematician, but his interests, his knowledge, and activities ranged far beyond mathemat...
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Resource Allocation for a Full-Duplex Base Station Aided OFDMA System
Exploiting full-duplex (FD) technology on base stations (BSs) is a promising solution to enhancing the system performance. Motivated by this, we revisit a full-duplex base station (FD-BS) aided OFDMA system, which consists of one BS, several uplink/downlink users and multiple subcarriers. A joint 3-dimensional (3D) m...
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Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments
We consider task and motion planning in complex dynamic environments for problems expressed in terms of a set of Linear Temporal Logic (LTL) constraints, and a reward function. We propose a methodology based on reinforcement learning that employs deep neural networks to learn low-level control policies as well as tas...
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BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition
Recently, deep neural networks (DNNs) have been regarded as the state-of-the-art classification methods in a wide range of applications, especially in image classification. Despite the success, the huge number of parameters blocks its deployment to situations with light computing resources. Researchers resort to the ...
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Resampling Strategy in Sequential Monte Carlo for Constrained Sampling Problems
Sequential Monte Carlo (SMC) methods are a class of Monte Carlo methods that are used to obtain random samples of a high dimensional random variable in a sequential fashion. Many problems encountered in applications often involve different types of constraints. These constraints can make the problem much more challen...
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Transverse Shift in Andreev Reflection
An incoming electron is reflected back as a hole at a normal-metal-superconductor interface, a process known as Andreev reflection. We predict that there exists a universal transverse shift in this process due to the effect of spin-orbit coupling in the normal metal. Particularly, using both the scattering approach a...
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Production of Entanglement Entropy by Decoherence
We examine the dynamics of entanglement entropy of all parts in an open system consisting of a two-level dimer interacting with an environment of oscillators. The dimer-environment interaction is almost energy conserving. We find the precise link between decoherence and production of entanglement entropy. We show tha...
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Aggressive Economic Incentives and Physical Activity: The Role of Choice and Technology Decision Aids
Aggressive incentive schemes that allow individuals to impose economic punishment on themselves if they fail to meet health goals present a promising approach for encouraging healthier behavior. However, the element of choice inherent in these schemes introduces concerns that only non-representative sectors of the po...
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Dynamics of resonances and equilibria of Low Earth Objects
The nearby space surrounding the Earth is densely populated by artificial satellites and instruments, whose orbits are distributed within the Low-Earth-Orbit region (LEO), ranging between 90 and 2 000 $km$ of altitude. As a consequence of collisions and fragmentations, many space debris of different sizes are left in...
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