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On the incorporation of interval-valued fuzzy sets into the Bousi-Prolog system: declarative semantics, implementation and applications
In this paper we analyse the benefits of incorporating interval-valued fuzzy sets into the Bousi-Prolog system. A syntax, declarative semantics and im- plementation for this extension is presented and formalised. We show, by using potential applications, that fuzzy logic programming frameworks enhanced with them can ...
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Characterization of Thermal Neutron Beam Monitors
Neutron beam monitors with high efficiency, low gamma sensitivity, high time and space resolution are required in neutron beam experiments to continuously diagnose the delivered beam. In this work, commercially available neutron beam monitors have been characterized using the R2D2 beamline at IFE (Norway) and using a...
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Detecting Galaxy-Filament Alignments in the Sloan Digital Sky Survey III
Previous studies have shown the filamentary structures in the cosmic web influence the alignments of nearby galaxies. We study this effect in the LOWZ sample of the Sloan Digital Sky Survey using the "Cosmic Web Reconstruction" filament catalogue of Chen et al. (2016). We find that LOWZ galaxies exhibit a small but s...
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Pandeia: A Multi-mission Exposure Time Calculator for JWST and WFIRST
Pandeia is the exposure time calculator (ETC) system developed for the James Webb Space Telescope (JWST) that will be used for creating JWST proposals. It includes a simulation-hybrid Python engine that calculates the two-dimensional pixel-by-pixel signal and noise properties of the JWST instruments. This allows for ...
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The numbers of edges of 5-polytopes with a given number of vertices
A basic combinatorial invariant of a convex polytope $P$ is its $f$-vector $f(P)=(f_0,f_1,\dots,f_{\dim P-1})$, where $f_i$ is the number of $i$-dimensional faces of $P$. Steinitz characterized all possible $f$-vectors of $3$-polytopes and Grünbaum characterized the pairs given by the first two entries of the $f$-vec...
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MapExif: an image scanning and mapping tool for investigators
Recently, the integration of geographical coordinates into a picture has become more and more popular. Indeed almost all smartphones and many cameras today have a built-in GPS receiver that stores the location information in the Exif header when a picture is taken. Although the automatic embedding of geotags in pictu...
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Fitch-Style Modal Lambda Calculi
Fitch-style modal deduction, in which modalities are eliminated by opening a subordinate proof, and introduced by shutting one, were investigated in the 1990s as a basis for lambda calculi. We show that such calculi have good computational properties for a variety of intuitionistic modal logics. Semantics are given i...
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Hot Stuff for One Year (HSOY) - A 583 million star proper motion catalogue derived from Gaia DR1 and PPMXL
Recently, the first installment of data from ESA's Gaia astrometric satellite mission (Gaia-DR1) was released, containing positions of more than 1 billion stars with unprecedented precision, as well as only proper motions and parallaxes, however only for a subset of 2 million objects. The second release, due in late ...
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Asymptotic behaviour of ground states for mixtures of ferromagnetic and antiferromagnetic interactions in a dilute regime
We consider randomly distributed mixtures of bonds of ferromagnetic and antiferromagnetic type in a two-dimensional square lattice with probability $1-p$ and $p$, respectively, according to an i.i.d. random variable. We study minimizers of the corresponding nearest-neighbour spin energy on large domains in ${\mathbb ...
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Extended Reduced-Form Framework for Non-Life Insurance
In this paper we propose a general framework for modeling an insurance claims' information flow in continuous time, by generalizing the reduced-form framework for credit risk and life insurance. In particular, we assume a nontrivial dependence structure between the reference filtration and the insurance internal filt...
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Overview of Recent Studies and Design Changes for the FNAL Magnetron Ion Source
This paper will cover several studies and design changes that will eventually be implemented to the Fermi National Accelerator Laboratory (FNAL) magnetron ion source. The topics include tungsten cathode insert, solenoid gas valves, current controlled arc pulser, cesium boiler redesign, gas mixtures of hydrogen and ni...
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Complete algebraic solution of multidimensional optimization problems in tropical semifield
We consider multidimensional optimization problems that are formulated in the framework of tropical mathematics to minimize functions defined on vectors over a tropical semifield (a semiring with idempotent addition and invertible multiplication). The functions, given by a matrix and calculated through multiplicative...
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Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back
A graph is a powerful concept for representation of relations between pairs of entities. Data with underlying graph structure can be found across many disciplines and there is a natural desire for understanding such data better. Deep learning (DL) has achieved significant breakthroughs in a variety of machine learnin...
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Supermodular Optimization for Redundant Robot Assignment under Travel-Time Uncertainty
This paper considers the assignment of multiple mobile robots to goal locations under uncertain travel time estimates. Our aim is to produce optimal assignments, such that the average waiting time at destinations is minimized. Our premise is that time is the most valuable asset in the system. Hence, we make use of re...
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Several classes of optimal ternary cyclic codes
Cyclic codes have efficient encoding and decoding algorithms over finite fields, so that they have practical applications in communication systems, consumer electronics and data storage systems. The objective of this paper is to give eight new classes of optimal ternary cyclic codes with parameters $[3^m-1,3^m-1-2m,4...
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$Σ$-pure-injective modules for string algebras and linear relations
We prove that indecomposable $\Sigma$-pure-injective modules for a string algebra are string or band modules. The key step in our proof is a splitting result for infinite-dimensional linear relations.
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Continuous Optimization of Adaptive Quadtree Structures
We present a novel continuous optimization method to the discrete problem of quadtree optimization. The optimization aims at achieving a quadtree structure with the highest mechanical stiffness, where the edges in the quadtree are interpreted as structural elements carrying mechanical loads. We formulate quadtree opt...
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Machine Learning Meets Microeconomics: The Case of Decision Trees and Discrete Choice
We provide a microeconomic framework for decision trees: a popular machine learning method. Specifically, we show how decision trees represent a non-compensatory decision protocol known as disjunctions-of-conjunctions and how this protocol generalizes many of the non-compensatory rules used in the discrete choice lit...
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Structured Control Nets for Deep Reinforcement Learning
In recent years, Deep Reinforcement Learning has made impressive advances in solving several important benchmark problems for sequential decision making. Many control applications use a generic multilayer perceptron (MLP) for non-vision parts of the policy network. In this work, we propose a new neural network archit...
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PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
We consider the problem of identifying any $k$ out of the best $m$ arms in an $n$-armed stochastic multi-armed bandit. Framed in the PAC setting, this particular problem generalises both the problem of `best subset selection' and that of selecting `one out of the best m' arms [arcsk 2017]. In applications such as cro...
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Collaborative Filtering using Denoising Auto-Encoders for Market Basket Data
Recommender systems (RS) help users navigate large sets of items in the search for "interesting" ones. One approach to RS is Collaborative Filtering (CF), which is based on the idea that similar users are interested in similar items. Most model-based approaches to CF seek to train a machine-learning/data-mining model...
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Stein's Method for Stationary Distributions of Markov Chains and Application to Ising Models
We develop a new technique, based on Stein's method, for comparing two stationary distributions of irreducible Markov Chains whose update rules are `close enough'. We apply this technique to compare Ising models on $d$-regular expander graphs to the Curie-Weiss model (complete graph) in terms of pairwise correlations...
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Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages
In this paper, we propose a novel and elegant solution to "Multi-Source Neural Machine Translation" (MSNMT) which only relies on preprocessing a N-way multilingual corpus without modifying the Neural Machine Translation (NMT) architecture or training procedure. We simply concatenate the source sentences to form a sin...
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Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods
The literature on Inverse Reinforcement Learning (IRL) typically assumes that humans take actions in order to minimize the expected value of a cost function, i.e., that humans are risk neutral. Yet, in practice, humans are often far from being risk neutral. To fill this gap, the objective of this paper is to devise a...
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QRT maps and related Laurent systems
In recent work it was shown how recursive factorisation of certain QRT maps leads to Somos-4 and Somos-5 recurrences with periodic coefficients, and to a fifth-order recurrence with the Laurent property. Here we recursively factorise the 12-parameter symmetric QRT map, given by a second-order recurrence, to obtain a ...
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Model-based reinforcement learning in differential graphical games
This paper seeks to combine differential game theory with the actor-critic-identifier architecture to determine forward-in-time, approximate optimal controllers for formation tracking in multi-agent systems, where the agents have uncertain heterogeneous nonlinear dynamics. A continuous control strategy is proposed, u...
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The depth of a finite simple group
We introduce the notion of the depth of a finite group $G$, defined as the minimal length of an unrefinable chain of subgroups from $G$ to the trivial subgroup. In this paper we investigate the depth of (non-abelian) finite simple groups. We determine the simple groups of minimal depth, and show, somewhat surprisingl...
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TRAGALDABAS. First results on cosmic ray studies and their relation with the solar activity, the Earth magnetic field and the atmospheric properties
Cosmic rays originating from extraterrestrial sources are permanently arriving at Earth atmosphere, where they produce up to billions of secondary particles. The analysis of the secondary particles reaching to the surface of the Earth may provide a very valuable information about the Sun activity, changes in the geom...
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Approximation of solutions of SDEs driven by a fractional Brownian motion, under pathwise uniqueness
Our aim in this paper is to establish some strong stability properties of a solution of a stochastic differential equation driven by a fractional Brownian motion for which the pathwise uniqueness holds. The results are obtained using Skorokhod's selection theorem.
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Smoothed GMM for quantile models
This paper develops theory for feasible estimators of finite-dimensional parameters identified by general conditional quantile restrictions, under much weaker assumptions than previously seen in the literature. This includes instrumental variables nonlinear quantile regression as a special case. More specifically, we...
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Multi-district preference modelling
Generating realistic artificial preference distributions is an important part of any simulation analysis of electoral systems. While this has been discussed in some detail in the context of a single electoral district, many electoral systems of interest are based on multiple districts. Neither treating preferences be...
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Orientability of the moduli space of Spin(7)-instantons
Let $(M,\Omega)$ be a closed $8$-dimensional manifold equipped with a generically non-integrable $\mathrm{Spin}(7)$-structure $\Omega$. We prove that if $\mathrm{Hom}(H^{3}(M,\mathbb{Z}), \mathbb{Z}_{2}) = 0$ then the moduli space of irreducible $\mathrm{Spin}(7)$-instantons on $(M,\Omega)$ with gauge group $\mathrm{...
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Neural Text Generation: A Practical Guide
Deep learning methods have recently achieved great empirical success on machine translation, dialogue response generation, summarization, and other text generation tasks. At a high level, the technique has been to train end-to-end neural network models consisting of an encoder model to produce a hidden representation...
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Context Prediction for Unsupervised Deep Learning on Point Clouds
Point clouds provide a flexible and natural representation usable in countless applications such as robotics or self-driving cars. Recently, deep neural networks operating on raw point cloud data have shown promising results on supervised learning tasks such as object classification and semantic segmentation. While m...
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A core-set approach for distributed quadratic programming in big-data classification
A new challenge for learning algorithms in cyber-physical network systems is the distributed solution of big-data classification problems, i.e., problems in which both the number of training samples and their dimension is high. Motivated by several problem set-ups in Machine Learning, in this paper we consider a spec...
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On the Erasure Robustness Property of Random Matrices
The study of the restricted isometry property (RIP) for corrupted random matrices is particularly important in the field of compressed sensing (CS) with corruptions. If a matrix still satisfy RIP after a certain portion of rows are erased, then we say that the matrix has the strong restricted isometry property (SRIP....
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The Weighted Kendall and High-order Kernels for Permutations
We propose new positive definite kernels for permutations. First we introduce a weighted version of the Kendall kernel, which allows to weight unequally the contributions of different item pairs in the permutations depending on their ranks. Like the Kendall kernel, we show that the weighted version is invariant to re...
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Synchronizing automata and the language of minimal reset words
We study a connection between synchronizing automata and its set $M$ of minimal reset words, i.e., such that no proper factor is a reset word. We first show that any synchronizing automaton having the set of minimal reset words whose set of factors does not contain a word of length at most $\frac{1}{4}\min\{|u|: u\in...
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Peephole: Predicting Network Performance Before Training
The quest for performant networks has been a significant force that drives the advancements of deep learning in recent years. While rewarding, improving network design has never been an easy journey. The large design space combined with the tremendous cost required for network training poses a major obstacle to this ...
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Optimization Landscape and Expressivity of Deep CNNs
We analyze the loss landscape and expressiveness of practical deep convolutional neural networks (CNNs) with shared weights and max pooling layers. We show that such CNNs produce linearly independent features at a "wide" layer which has more neurons than the number of training samples. This condition holds e.g. for t...
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A new cosine series antialiasing function and its application to aliasing-free glottal source models for speech and singing synthesis
We formulated and implemented a procedure to generate aliasing-free excitation source signals. It uses a new antialiasing filter in the continuous time domain followed by an IIR digital filter for response equalization. We introduced a cosine-series-based general design procedure for the new antialiasing function. We...
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Defining Equations of Nilpotent Orbits for Borel Subgroups of Modality Zero in Type $A_{n}$
Let $G$ be a quasi-simple algebraic group defined over an algebraically closed field $k$ and $B$ a Borel subgroup of $G$ acting on the nilradical $\mathfrak{n}$ of its Lie algebra $\mathfrak{b}$ via the Adjoint representation. It is known that $B$ has only finitely many orbits in only five cases: when $G$ is of type ...
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Quadratically Tight Relations for Randomized Query Complexity
Let $f:\{0,1\}^n \rightarrow \{0,1\}$ be a Boolean function. The certificate complexity $C(f)$ is a complexity measure that is quadratically tight for the zero-error randomized query complexity $R_0(f)$: $C(f) \leq R_0(f) \leq C(f)^2$. In this paper we study a new complexity measure that we call expectational certifi...
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Parabolic subgroup orbits on finite root systems
Oshima's Lemma describes the orbits of parabolic subgroups of irreducible finite Weyl groups on crystallographic root systems. This note generalises that result to all root systems of finite Coxeter groups, and provides a self contained proof, independent of the representation theory of semisimple complex Lie algebra...
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User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction
In human-in-the-loop machine learning, the user provides information beyond that in the training data. Many algorithms and user interfaces have been designed to optimize and facilitate this human--machine interaction; however, fewer studies have addressed the potential defects the designs can cause. Effective interac...
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A note on the asymptotics of the modified Bessel functions on the Stokes lines
We employ the exponentially improved asymptotic expansions of the confluent hypergeometric functions on the Stokes lines discussed by the author [Appl. Math. Sci. {\bf 7} (2013) 6601--6609] to give the analogous expansions of the modified Bessel functions $I_\nu(z)$ and $K_\nu(z)$ for large $z$ and finite $\nu$ on $\...
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Fair k-Center Clustering for Data Summarization
In data summarization we want to choose k prototypes in order to summarize a data set. We study a setting where the data set comprises several demographic groups and we are restricted to choose k_i prototypes belonging to group i. A common approach to the problem without the fairness constraint is to optimize a centr...
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Advanced Bayesian Multilevel Modeling with the R Package brms
The brms package allows R users to easily specify a wide range of Bayesian single-level and multilevel models, which are fitted with the probabilistic programming language Stan behind the scenes. Several response distributions are supported, of which all parameters (e.g., location, scale, and shape) can be predicted ...
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$W$-entropy, super Perelman Ricci flows and $(K, m)$-Ricci solitons
In this paper, we prove the characterization of the $(K, \infty)$-super Perelman Ricci flows by various functional inequalities and gradient estimate for the heat semigroup generated by the Witten Laplacian on manifolds equipped with time dependent metrics and potentials. As a byproduct, we derive the Hamilton type d...
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Stellar energetic particle ionization in protoplanetary disks around T Tauri stars
Anomalies in the abundance measurements of short lived radionuclides in meteorites indicate that the protosolar nebulae was irradiated by a high amount of energetic particles (E$\gtrsim$10 MeV). The particle flux of the contemporary Sun cannot explain these anomalies. However, similar to T Tauri stars the young Sun w...
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Extended Trust-Region Problems with One or Two Balls: Exact Copositive and Lagrangian Relaxations
We establish a geometric condition guaranteeing exact copositive relaxation for the nonconvex quadratic optimization problem under two quadratic and several linear constraints, and present sufficient conditions for global optimality in terms of generalized Karush-Kuhn-Tucker multipliers. The copositive relaxation is ...
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Weighted batch means estimators in Markov chain Monte Carlo
This paper proposes a family of weighted batch means variance estimators, which are computationally efficient and can be conveniently applied in practice. The focus is on Markov chain Monte Carlo simulations and estimation of the asymptotic covariance matrix in the Markov chain central limit theorem, where conditions...
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Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
Gradient-based optimization is the foundation of deep learning and reinforcement learning. Even when the mechanism being optimized is unknown or not differentiable, optimization using high-variance or biased gradient estimates is still often the best strategy. We introduce a general framework for learning low-varianc...
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Truncation-free Hybrid Inference for DPMM
Dirichlet process mixture models (DPMM) are a cornerstone of Bayesian non-parametrics. While these models free from choosing the number of components a-priori, computationally attractive variational inference often reintroduces the need to do so, via a truncation on the variational distribution. In this paper we pres...
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Functors and morphisms determined by subcategories
We study the existence and uniqueness of minimal right determiners in various categories. Particularly in a Hom-finite hereditary abelian category with enough projectives, we prove that the Auslander-Reiten-Smal{\o}-Ringel formula of the minimal right determiner still holds. As an application, we give a formula of mi...
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Collective Effects in Nanolasers Explained by Generalized Rate Equations
We study the stationary photon output and statistics of small lasers. Our closed-form expressions clarify the contribution of collective effects due to the interaction between quantum emitters. We generalize laser rate equations and explain photon trapping: a decrease of the photon number output below the lasing thre...
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The Risk of Machine Learning
Many applied settings in empirical economics involve simultaneous estimation of a large number of parameters. In particular, applied economists are often interested in estimating the effects of many-valued treatments (like teacher effects or location effects), treatment effects for many groups, and prediction models ...
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Agatha: disentangling periodic signals from correlated noise in a periodogram framework
Periodograms are used as a key significance assessment and visualisation tool to display the significant periodicities in unevenly sampled time series. We introduce a framework of periodograms, called "Agatha", to disentangle periodic signals from correlated noise and to solve the 2-dimensional model selection proble...
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A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome
In this work, we consider the problem of predicting the course of a progressive disease, such as cancer or Alzheimer's. Progressive diseases often start with mild symptoms that might precede a diagnosis, and each patient follows their own trajectory. Patient trajectories exhibit wild variability, which can be associa...
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On the generation of the quarks through spontaneous symmetry breaking
In this paper we present the state of the art about the quarks: group SU(3), Lie algebra, the electric charge and mass. The quarks masses are generated in the same way as the lepton masses. It is constructed a term in the Lagrangian that couples the Higgs doublet to the fermion fields.
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Distributed Holistic Clustering on Linked Data
Link discovery is an active field of research to support data integration in the Web of Data. Due to the huge size and number of available data sources, efficient and effective link discovery is a very challenging task. Common pairwise link discovery approaches do not scale to many sources with very large entity sets...
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A branch-and-bound algorithm for the minimum radius $k$-enclosing ball problem
The minimum $k$-enclosing ball problem seeks the ball with smallest radius that contains at least~$k$ of~$m$ given points in a general $n$-dimensional Euclidean space. This problem is NP-hard. We present a branch-and-bound algorithm on the tree of the subsets of~$k$ points to solve this problem. The nodes on the tree...
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Dependency Parsing with Dilated Iterated Graph CNNs
Dependency parses are an effective way to inject linguistic knowledge into many downstream tasks, and many practitioners wish to efficiently parse sentences at scale. Recent advances in GPU hardware have enabled neural networks to achieve significant gains over the previous best models, these models still fail to lev...
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Motion Planning in Irreducible Path Spaces
The motion of a mechanical system can be defined as a path through its configuration space. Computing such a path has a computational complexity scaling exponentially with the dimensionality of the configuration space. We propose to reduce the dimensionality of the configuration space by introducing the irreducible p...
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Learning Neural Networks with Two Nonlinear Layers in Polynomial Time
We give a polynomial-time algorithm for learning neural networks with one layer of sigmoids feeding into any Lipschitz, monotone activation function (e.g., sigmoid or ReLU). We make no assumptions on the structure of the network, and the algorithm succeeds with respect to {\em any} distribution on the unit ball in $n...
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Sample-Derived Disjunctive Rules for Secure Power System Operation
Machine learning techniques have been used in the past using Monte Carlo samples to construct predictors of the dynamic stability of power systems. In this paper we move beyond the task of prediction and propose a comprehensive approach to use predictors, such as Decision Trees (DT), within a standard optimization fr...
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Satellite altimetry reveals spatial patterns of variations in the Baltic Sea wave climate
The main properties of the climate of waves in the seasonally ice-covered Baltic Sea and its decadal changes since 1990 are estimated from satellite altimetry data. The data set of significant wave heights (SWH) from all existing nine satellites, cleaned and cross-validated against in situ measurements, shows overall...
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Estimation of Covariance Matrices for Portfolio Optimization using Gaussian Processes
Estimating covariances between financial assets plays an important role in risk management and optimal portfolio allocation. In practice, when the sample size is small compared to the number of variables, i.e. when considering a wide universe of assets over just a few years, this poses considerable challenges and the...
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Zeeman interaction and Jahn-Teller effect in $Γ_8$ multiplet
We present a thorough analysis of the interplay of magnetic moment and the Jahn-Teller effect in the $\Gamma_8$ cubic multiplet. We find that in the presence of dynamical Jahn-Teller effect, the Zeeman interaction remains isotropic, whereas the $g$ and $G$ factors can change their signs. The static Jahn-Teller distor...
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Measuring the Declared SDK Versions and Their Consistency with API Calls in Android Apps
Android has been the most popular smartphone system, with multiple platform versions (e.g., KITKAT and Lollipop) active in the market. To manage the application's compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper...
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The Design and Implementation of Modern Online Programming Competitions
This paper presents a framework for the implementation of online programming competitions, including a set of principles for the design of the multiplayer game and a practical framework for the construction of the competition environment. The paper presents a successful example competition, the 2016-17 Halite challen...
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Emergence of a spectral gap in a class of random matrices associated with split graphs
Motivated by the intriguing behavior displayed in a dynamic network that models a population of extreme introverts and extroverts (XIE), we consider the spectral properties of ensembles of random split graph adjacency matrices. We discover that, in general, a gap emerges in the bulk spectrum between -1 and 0 that con...
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Helping News Editors Write Better Headlines: A Recommender to Improve the Keyword Contents & Shareability of News Headlines
We present a software tool that employs state-of-the-art natural language processing (NLP) and machine learning techniques to help newspaper editors compose effective headlines for online publication. The system identifies the most salient keywords in a news article and ranks them based on both their overall populari...
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ParaGraphE: A Library for Parallel Knowledge Graph Embedding
Knowledge graph embedding aims at translating the knowledge graph into numerical representations by transforming the entities and relations into continuous low-dimensional vectors. Recently, many methods [1, 5, 3, 2, 6] have been proposed to deal with this problem, but existing single-thread implementations of them a...
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The Globular Cluster - Dark Matter Halo Connection
I present a simple phenomenological model for the observed linear scaling of the stellar mass in old globular clusters (GCs) with $z=0$ halo mass in which the stellar mass in GCs scales linearly with progenitor halo mass at $z=6$ above a minimum halo mass for GC formation. This model reproduces the observed $M_{\rm G...
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NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many state-of-the-art (SOA) visual processing tasks. Even though Graphical Processing Units (GPUs) are most often used in training and deploying CNNs, their power efficiency is less than 10 GOp/s/W for single-frame r...
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Platooning in the Presence of a Speed Drop: A Generalized Control Model
The positive impacts of platooning on travel time reliability, congestion, emissions, and energy consumption have been shown for homogeneous roadway segments. However, speed limit changes frequently throughout the transportation network, due to either safety-related considerations (e.g., workzone operations) or conge...
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Koszul duality for Lie algebroids
This paper studies the role of dg-Lie algebroids in derived deformation theory. More precisely, we provide an equivalence between the homotopy theories of formal moduli problems and dg-Lie algebroids over a commutative dg-algebra of characteristic zero. At the level of linear objects, we show that the category of rep...
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Semi-Semantic Line-Cluster Assisted Monocular SLAM for Indoor Environments
This paper presents a novel method to reduce the scale drift for indoor monocular simultaneous localization and mapping (SLAM). We leverage the prior knowledge that in the indoor environment, the line segments form tight clusters, e.g. many door frames in a straight corridor are of the same shape, size and orientatio...
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Direct visualization of vortex ice in a nanostructured superconductor
Artificial ice systems have unique physical properties promising for potential applications. One of the most challenging issues in this field is to find novel ice systems that allows a precise control over the geometries and many-body interactions. Superconducting vortex matter has been proposed as a very suitable ca...
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Statistical Mechanics of Node-perturbation Learning with Noisy Baseline
Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the p...
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New Generalized Fixed Point Results on $S_{b}$-Metric Spaces
Recently $S_{b}$-metric spaces have been introduced as the generalizations of metric and $S$-metric spaces. In this paper we investigate some basic properties of this new space. We generalize the classical Banach's contraction principle using the theory of a complete $S_{b}$-metric space. Also we give an application ...
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A Decentralized Optimization Framework for Energy Harvesting Devices
Designing decentralized policies for wireless communication networks is a crucial problem, which has only been partially solved in the literature so far. In this paper, we propose the Decentralized Markov Decision Process (Dec-MDP) framework to analyze a wireless sensor network with multiple users which access a comm...
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Inf-sup stable finite-element methods for the Landau--Lifshitz--Gilbert and harmonic map heat flow equation
In this paper we propose and analyze a finite element method for both the harmonic map heat and Landau--Lifshitz--Gilbert equation, the time variable remaining continuous. Our starting point is to set out a unified saddle point approach for both problems in order to impose the unit sphere constraint at the nodes sinc...
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Power Control and Relay Selection in Full-Duplex Cognitive Relay Networks: Coherent versus Non-coherent Scenarios
This paper investigates power control and relay selection in Full Duplex Cognitive Relay Networks (FDCRNs), where the secondary-user (SU) relays can simultaneously receive and forward the signal from the SU source. We study both non-coherent and coherent scenarios. In the non-coherent case, the SU relay forwards the ...
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Ternary and $n$-ary $f$-distributive Structures
We introduce and study ternary $f$-distributive structures, Ternary $f$-quandles and more generally their higher $n$-ary analogues. A classification of ternary $f$-quandles is provided in low dimensions. Moreover, we study extension theory and introduce a cohomology theory for ternary, and more generally $n$-ary, $f$...
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Deformations of infinite-dimensional Lie algebras, exotic cohomology, and integrable nonlinear partial differential equations
The important unsolved problem in theory of integrable systems is to find conditions guaranteeing existence of a Lax representation for a given PDE. The use of the exotic cohomology of the symmetry algebras opens a way to formulate such conditions in internal terms of the PDEs under the study. In this paper we consid...
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Tunable high-harmonic generation by chromatic focusing of few-cycle laser pulses
In this work we study the impact of chromatic focusing of few-cycle laser pulses on high-order harmonic generation (HHG) through analysis of the emitted extreme ultraviolet (XUV) radiation. Chromatic focusing is usually avoided in the few-cycle regime, as the pulse spatio-temporal structure may be highly distorted by...
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Gate Switchable Transport and Optical Anisotropy in 90° Twisted Bilayer Black Phosphorus
Anisotropy describes the directional dependence of a material's properties such as transport and optical response. In conventional bulk materials, anisotropy is intrinsically related to the crystal structure, and thus not tunable by the gating techniques used in modern electronics. Here we show that, in bilayer black...
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MM Algorithms for Variance Component Estimation and Selection in Logistic Linear Mixed Model
Logistic linear mixed model is widely used in experimental designs and genetic analysis with binary traits. Motivated by modern applications, we consider the case with many groups of random effects and each group corresponds to a variance component. When the number of variance components is large, fitting the logisti...
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Settling the query complexity of non-adaptive junta testing
We prove that any non-adaptive algorithm that tests whether an unknown Boolean function $f: \{0, 1\}^n\to \{0, 1\}$ is a $k$-junta or $\epsilon$-far from every $k$-junta must make $\widetilde{\Omega}(k^{3/2} / \epsilon)$ many queries for a wide range of parameters $k$ and $\epsilon$. Our result dramatically improves ...
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Investigation of Language Understanding Impact for Reinforcement Learning Based Dialogue Systems
Language understanding is a key component in a spoken dialogue system. In this paper, we investigate how the language understanding module influences the dialogue system performance by conducting a series of systematic experiments on a task-oriented neural dialogue system in a reinforcement learning based setting. Th...
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String stability and a delay-based spacing policy for vehicle platoons subject to disturbances
A novel delay-based spacing policy for the control of vehicle platoons is introduced together with a notion of disturbance string stability. The delay-based spacing policy specifies the desired inter-vehicular distance between vehicles and guarantees that all vehicles track the same spatially varying reference veloci...
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Reidemeister spectra for solvmanifolds in low dimensions
The Reidemeister number of an endomorphism of a group is the number of twisted conjugacy classes determined by that endomorphism. The collection of all Reidemeister numbers of all automorphisms of a group $G$ is called the Reidemeister spectrum of $G$. In this paper, we determine the Reidemeister spectra of all funda...
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Cross-layer Optimization for Ultra-reliable and Low-latency Radio Access Networks
In this paper, we propose a framework for cross-layer optimization to ensure ultra-high reliability and ultra-low latency in radio access networks, where both transmission delay and queueing delay are considered. With short transmission time, the blocklength of channel codes is finite, and the Shannon Capacity cannot...
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Network Inference via the Time-Varying Graphical Lasso
Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different ...
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Construction of dynamical semigroups by a functional regularisation à la Kato
A functional version of the Kato one-parametric regularisation for the construction of a dynamical semigroup generator of a relative bound one perturbation is introduced. It does not require that the minus generator of the unperturbed semigroup is a positivity preserving operator. The regularisation is illustrated by...
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Visual Reasoning with Multi-hop Feature Modulation
Recent breakthroughs in computer vision and natural language processing have spurred interest in challenging multi-modal tasks such as visual question-answering and visual dialogue. For such tasks, one successful approach is to condition image-based convolutional network computation on language via Feature-wise Linea...
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Behavioral-clinical phenotyping with type 2 diabetes self-monitoring data
Objective: To evaluate unsupervised clustering methods for identifying individual-level behavioral-clinical phenotypes that relate personal biomarkers and behavioral traits in type 2 diabetes (T2DM) self-monitoring data. Materials and Methods: We used hierarchical clustering (HC) to identify groups of meals with simi...
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Ultrahigh capacitive energy storage in highly oriented BaZr(x)Ti(1-x)O3 thin films prepared by pulsed laser deposition
We report structural, optical, temperature and frequency dependent dielectric, and energy storage properties of pulsed laser deposited (100) highly textured BaZr(x)Ti(1-x)O3 (x = 0.3, 0.4 and 0.5) relaxor ferroelectric thin films on La0.7Sr0.3MnO3/MgO substrates which make this compound as a potential lead-free capac...
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