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Poincaré profiles of groups and spaces
We introduce a spectrum of monotone coarse invariants for metric measure spaces called Poincaré profiles. The two extremes of this spectrum determine the growth of the space, and the separation profile as defined by Benjamini--Schramm--Timár. In this paper we focus on properties of the Poincaré profiles of groups wit...
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NMR Study of the New Magnetic Superconductor CaK(Fe$0.951Ni0.049)4As4: Microscopic Coexistence of Hedgehog Spin-vortex Crystal and Superconductivity
Coexistence of a new-type antiferromagnetic (AFM) state, the so-called hedgehog spin-vortex crystal (SVC), and superconductivity (SC) is evidenced by $^{75}$As nuclear magnetic resonance study on single-crystalline CaK(Fe$_{0.951}$Ni$_{0.049}$)$_4$As$_4$. The hedgehog SVC order is clearly demonstrated by the direct o...
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Light spanners for bounded treewidth graphs imply light spanners for $H$-minor-free graphs
Grigni and Hung~\cite{GH12} conjectured that H-minor-free graphs have $(1+\epsilon)$-spanners that are light, that is, of weight $g(|H|,\epsilon)$ times the weight of the minimum spanning tree for some function $g$. This conjecture implies the {\em efficient} polynomial-time approximation scheme (PTAS) of the traveli...
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Modeling Daily Seasonality of Mexico City Ozone using Nonseparable Covariance Models on Circles Cross Time
Mexico City tracks ground-level ozone levels to assess compliance with national ambient air quality standards and to prevent environmental health emergencies. Ozone levels show distinct daily patterns, within the city, and over the course of the year. To model these data, we use covariance models over space, circular...
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Huygens-Fresnel Picture for Electron-Molecule Elastic Scattering
The elastic scattering cross sections for a slow electron by C2 and H2 molecules have been calculated within the framework of the non-overlapping atomic potential model. For the amplitudes of the multiple electron scattering by a target the wave function of the molecular continuum is represented as a combination of a...
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When Point Process Meets RNNs: Predicting Fine-Grained User Interests with Mutual Behavioral Infectivity
Predicting fine-grained interests of users with temporal behavior is important to personalization and information filtering applications. However, existing interest prediction methods are incapable of capturing the subtle degreed user interests towards particular items, and the internal time-varying drifting attentio...
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Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer
Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk assessment and the quantification of intratumoural heterogeneity. In this work, 1615 radiomic features (quantifying tumour image intensit...
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Normalization of zero-inflated data: An empirical analysis of a new indicator family and its use with altmetrics data
Recently, two new indicators (Equalized Mean-based Normalized Proportion Cited, EMNPC; Mean-based Normalized Proportion Cited, MNPC) were proposed which are intended for sparse scientometrics data. The indicators compare the proportion of mentioned papers (e.g. on Facebook) of a unit (e.g., a researcher or institutio...
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Gravity Formality
We show that Willwacher's cyclic formality theorem can be extended to preserve natural Gravity operations on cyclic multivector fields and cyclic multidifferential operators. We express this in terms of a homotopy Gravity quasi-isomorphism with explicit local formulas. For this, we develop operadic tools related to m...
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On the Feasibility of Distinguishing Between Process Disturbances and Intrusions in Process Control Systems Using Multivariate Statistical Process Control
Process Control Systems (PCSs) are the operating core of Critical Infrastructures (CIs). As such, anomaly detection has been an active research field to ensure CI normal operation. Previous approaches have leveraged network level data for anomaly detection, or have disregarded the existence of process disturbances, t...
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Quantum hydrodynamic approximations to the finite temperature trapped Bose gases
For the quantum kinetic system modelling the Bose-Einstein Condensate that accounts for interactions between condensate and excited atoms, we use the Chapman-Enskog expansion to derive its hydrodynamic approximations, include both Euler and Navier-Stokes approximations. The hydrodynamic approximations describe not on...
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Game-theoretic dynamic investment model with incomplete information: futures contracts
Over the past few years, the futures market has been successfully developing in the North-West region. Futures markets are one of the most effective and liquid-visible trading mechanisms. A large number of buyers are forced to compete with each other and raise their prices. A large number of sellers make them reduce ...
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Deep Collaborative Learning for Visual Recognition
Deep neural networks are playing an important role in state-of-the-art visual recognition. To represent high-level visual concepts, modern networks are equipped with large convolutional layers, which use a large number of filters and contribute significantly to model complexity. For example, more than half of the wei...
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Co-location Epidemic Tracking on London Public Transports Using Low Power Mobile Magnetometer
The public transports provide an ideal means to enable contagious diseases transmission. This paper introduces a novel idea to detect co-location of people in such environment using just the ubiquitous geomagnetic field sensor on the smart phone. Essentially, given that all passengers must share the same journey betw...
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Waring-Goldbach Problem: One Square, Four Cubes and Higher Powers
Let $\mathcal{P}_r$ denote an almost-prime with at most $r$ prime factors, counted according to multiplicity. In this paper, it is proved that, for $12\leqslant b\leqslant 35$ and for every sufficiently large odd integer $N$, the equation \begin{equation*} N=x^2+p_1^3+p_2^3+p_3^3+p_4^3+p_5^4+p_6^b \end{equation*} is ...
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Realizability of tropical canonical divisors
We use recent results by Bainbridge-Chen-Gendron-Grushevsky-Moeller on compactifications of strata of abelian differentials to give a comprehensive solution to the realizability problem for effective tropical canonical divisors in equicharacteristic zero. Given a pair $(\Gamma, D)$ consisting of a stable tropical cur...
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Causal inference for interfering units with cluster and population level treatment allocation programs
Interference arises when an individual's potential outcome depends on the individual treatment level, but also on the treatment level of others. A common assumption in the causal inference literature in the presence of interference is partial interference, implying that the population can be partitioned in clusters o...
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A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation
We present a unifying framework to solve several computer vision problems with event cameras: motion, depth and optical flow estimation. The main idea of our framework is to find the point trajectories on the image plane that are best aligned with the event data by maximizing an objective function: the contrast of an...
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TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
Machine learning models are notoriously difficult to interpret and debug. This is particularly true of neural networks. In this work, we introduce automated software testing techniques for neural networks that are well-suited to discovering errors which occur only for rare inputs. Specifically, we develop coverage-gu...
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Inferring directed climatic interactions with renormalized partial directed coherence and directed partial correlation
Inferring interactions between processes promises deeper insight into mechanisms underlying network phenomena. Renormalised partial directed coherence (rPDC) is a frequency-domain representation of the concept of Granger causality while directed partial correlation (DPC) is an alternative approach for quantifying Gra...
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Conditions for the invertibility of dual energy data
The Alvarez-Macovski method [Alvarez, R. E and Macovski, A., "Energy-selective reconstructions in X-ray computerized tomography", Phys. Med. Biol. (1976), 733--44] requires the inversion of the transformation from the line integrals of the basis set coefficients to measurements with multiple x-ray spectra. Analytical...
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Examples of lattice-polarized K3 surfaces with automorphic discriminant, and Lorentzian Kac--Moody algebras
Using our results about Lorentzian Kac--Moody algebras and arithmetic mirror symmetry, we give six series of examples of lattice-polarized K3 surfaces with automorphic discriminant.
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Quantum ferrofluid turbulence
We study the elementary characteristics of turbulence in a quantum ferrofluid through the context of a dipolar Bose gas condensing from a highly non-equilibrium thermal state. Our simulations reveal that the dipolar interactions drive the emergence of polarized turbulence and density corrugations. The superfluid vort...
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Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book
An extensive empirical literature documents a generally negative correlation, named the "leverage effect," between asset returns and changes of volatility. It is more challenging to establish such a return-volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and tes...
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Group representations that resist worst-case sampling
Motivated by expansion in Cayley graphs, we show that there exist infinitely many groups $G$ with a nontrivial irreducible unitary representation whose average over every set of $o(\log\log|G|)$ elements of $G$ has operator norm $1 - o(1)$. This answers a question of Lovett, Moore, and Russell, and strengthens their ...
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On the nearly smooth complex spaces
We introduce a class of normal complex spaces having only mild sin-gularities (close to quotient singularities) for which we generalize the notion of a (analytic) fundamental class for an analytic cycle and also the notion of a relative fundamental class for an analytic family of cycles. We also generalize to these s...
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Semi-supervised learning of hierarchical representations of molecules using neural message passing
With the rapid increase of compound databases available in medicinal and material science, there is a growing need for learning representations of molecules in a semi-supervised manner. In this paper, we propose an unsupervised hierarchical feature extraction algorithm for molecules (or more generally, graph-structur...
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Tracy-Widom at each edge of real covariance and MANOVA estimators
We study the sample covariance matrix for real-valued data with general population covariance, as well as MANOVA-type covariance estimators in variance components models under null hypotheses of global sphericity. In the limit as matrix dimensions increase proportionally, the asymptotic spectra of such estimators may...
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Multi-stage Neural Networks with Single-sided Classifiers for False Positive Reduction and its Evaluation using Lung X-ray CT Images
Lung nodule classification is a class imbalanced problem because nodules are found with much lower frequency than non-nodules. In the class imbalanced problem, conventional classifiers tend to be overwhelmed by the majority class and ignore the minority class. We therefore propose cascaded convolutional neural networ...
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Monochromatic knots and other unusual electromagnetic disturbances: light localised in 3D
We introduce and examine a collection of unusual electromagnetic disturbances. Each of these is an exact, monochromatic solution of Maxwell's equations in free space with looped electric and magnetic field lines of finite extent and a localised appearance in all three spatial dimensions. Included are the first explic...
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Zero-cycles of degree one on Skorobogatov's bielliptic surface
Skorobogatov constructed a bielliptic surface which is a counterexample to the Hasse principle not explained by the Brauer-Manin obstruction. We show that this surface has a $0$-cycle of degree 1, as predicted by a conjecture of Colliot-Thélène.
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Locally Nameless Permutation Types
We define "Locally Nameless Permutation Types", which fuse permutation types as used in Nominal Isabelle with the locally nameless representation. We show that this combination is particularly useful when formalizing programming languages where bound names may become free during execution ("extrusion"), common in pro...
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On dimension-free variational inequalities for averaging operators in $\mathbb R^d$
We study dimension-free $L^p$ inequalities for $r$-variations of the Hardy--Littlewood averaging operators defined over symmetric convex bodies in $\mathbb R^d$.
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One-particle density matrix of trapped one-dimensional impenetrable bosons from conformal invariance
The one-particle density matrix of the one-dimensional Tonks-Girardeau gas with inhomogeneous density profile is calculated, thanks to a recent observation that relates this system to a two-dimensional conformal field theory in curved space. The result is asymptotically exact in the limit of large particle density an...
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Image Analysis Using a Dual-Tree $M$-Band Wavelet Transform
We propose a 2D generalization to the $M$-band case of the dual-tree decomposition structure (initially proposed by N. Kingsbury and further investigated by I. Selesnick) based on a Hilbert pair of wavelets. We particularly address (\textit{i}) the construction of the dual basis and (\textit{ii}) the resulting direct...
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Nonlinear Cauchy-Riemann Equations and Liouville Equation For Conformal Metrics
We introduce the Nonlinear Cauchy-Riemann equations as Bäcklund transformations for several nonlinear and linear partial differential equations. From these equations we treat in details the Laplace and the Liouville equations by deriving general solution for the nonlinear Liouville equation. By Möbius transformation ...
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SmartPaste: Learning to Adapt Source Code
Deep Neural Networks have been shown to succeed at a range of natural language tasks such as machine translation and text summarization. While tasks on source code (ie, formal languages) have been considered recently, most work in this area does not attempt to capitalize on the unique opportunities offered by its kno...
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An Outcome Model Approach to Translating a Randomized Controlled Trial Results to a Target Population
Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to translate RCT results to target populations has focused on weighting RCT data to look like the target data. Simulation work, however, has suggested that an outcome model approac...
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Influence of parameterized small-scale gravity waves on the migrating diurnal tide in Earth's thermosphere
Effects of subgrid-scale gravity waves (GWs) on the diurnal migrating tides are investigated from the mesosphere to the upper thermosphere for September equinox conditions, using a general circulation model coupled with the extended spectral nonlinear GW parameterization of Yiğit et al (2008). Simulations with GW eff...
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A Statistical Model for Ideal Team Selection for A National Cricket Squad
Cricket is a game played between two teams which consists of eleven players each. Nowadays cricket game is becoming more and more popular in Bangladesh and other South Asian Countries. Before a match people are very enthusiastic about team squads and "Which players are playing today?", "How well will MR. X perform to...
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The geometry of some generalized affine Springer fibers
We study basic geometric properties of some group analogue of affine Springer fibers and compare with the classical Lie algebra affine Springer fibers. The main purpose is to formulate a conjecture that relates the number of irreducible components of such varieties for a reductive group $G$ to certain weight multipli...
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Modelling of a Permanent Magnet Synchronous Machine Using Isogeometric Analysis
Isogeometric analysis (IGA) is used to simulate a permanent magnet synchronous machine. IGA uses non-uniform rational B-splines to parametrise the domain and to approximate the solution space, thus allowing for the exact description of the geometries even on the coarsest level of mesh refinement. Given the properties...
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Learning and Trust in Auction Markets
In this paper, we study behavior of bidders in an experimental launch of a new advertising auction platform by Zillow, as Zillow switched from negotiated contracts to using auctions in several geographically isolated markets. A unique feature of this experiment is that the bidders in this market are real estate agent...
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Like trainer, like bot? Inheritance of bias in algorithmic content moderation
The internet has become a central medium through which `networked publics' express their opinions and engage in debate. Offensive comments and personal attacks can inhibit participation in these spaces. Automated content moderation aims to overcome this problem using machine learning classifiers trained on large corp...
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Holographic Neural Architectures
Representation learning is at the heart of what makes deep learning effective. In this work, we introduce a new framework for representation learning that we call "Holographic Neural Architectures" (HNAs). In the same way that an observer can experience the 3D structure of a holographed object by looking at its holog...
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An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists
Topological Data Analysis (tda) is a recent and fast growing eld providing a set of new topological and geometric tools to infer relevant features for possibly complex data. This paper is a brief introduction, through a few selected topics, to basic fundamental and practical aspects of tda for non experts. 1 Introduc...
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Machine Learning by Two-Dimensional Hierarchical Tensor Networks: A Quantum Information Theoretic Perspective on Deep Architectures
The resemblance between the methods used in quantum-many body physics and in machine learning has drawn considerable attention. In particular, tensor networks (TNs) and deep learning architectures bear striking similarities to the extent that TNs can be used for machine learning. Previous results used one-dimensional...
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Hierarchical Imitation and Reinforcement Learning
We study how to effectively leverage expert feedback to learn sequential decision-making policies. We focus on problems with sparse rewards and long time horizons, which typically pose significant challenges in reinforcement learning. We propose an algorithmic framework, called hierarchical guidance, that leverages t...
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Social learning in a simple task allocation game
We investigate the effects of social interactions in task al- location using Evolutionary Game Theory (EGT). We propose a simple task-allocation game and study how different learning mechanisms can give rise to specialised and non- specialised colonies under different ecological conditions. By combining agent-based s...
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Guided projections for analysing the structure of high-dimensional data
A powerful data transformation method named guided projections is proposed creating new possibilities to reveal the group structure of high-dimensional data in the presence of noise variables. Utilising projections onto a space spanned by a selection of a small number of observations allows measuring the similarity o...
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Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caused by such failure...
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Strong electron-hole symmetric Rashba spin-orbit coupling in graphene/monolayer transition metal dichalcogenide heterostructures
Despite its extremely weak intrinsic spin-orbit coupling (SOC), graphene has been shown to acquire considerable SOC by proximity coupling with exfoliated transition metal dichalcogenides (TMDs). Here we demonstrate strong induced Rashba SOC in graphene that is proximity coupled to a monolayer TMD film, MoS2 or WSe2, ...
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Robust Statistics for Image Deconvolution
We present a blind multiframe image-deconvolution method based on robust statistics. The usual shortcomings of iterative optimization of the likelihood function are alleviated by minimizing the M-scale of the residuals, which achieves more uniform convergence across the image. We focus on the deconvolution of astrono...
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Nash and Wardrop equilibria in aggregative games with coupling constraints
We consider the framework of aggregative games, in which the cost function of each agent depends on his own strategy and on the average population strategy. As first contribution, we investigate the relations between the concepts of Nash and Wardrop equilibrium. By exploiting a characterization of the two equilibria ...
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Magnetoresistance in the superconducting state at the (111) LaAlO$_3$/SrTiO$_3$ interface
Condensed matter systems that simultaneously exhibit superconductivity and ferromagnetism are rare due the antagonistic relationship between conventional spin-singlet superconductivity and ferromagnetic order. In materials in which superconductivity and magnetic order is known to coexist (such as some heavy-fermion m...
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Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data
The paper presents the application of Variational Autoencoders (VAE) for data dimensionality reduction and explorative analysis of mass spectrometry imaging data (MSI). The results confirm that VAEs are capable of detecting the patterns associated with the different tissue sub-types with performance than standard app...
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Learning General Latent-Variable Graphical Models with Predictive Belief Propagation and Hilbert Space Embeddings
In this paper, we propose a new algorithm for learning general latent-variable probabilistic graphical models using the techniques of predictive state representation, instrumental variable regression, and reproducing-kernel Hilbert space embeddings of distributions. Under this new learning framework, we first convert...
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Can interacting dark energy solve the $H_0$ tension?
The answer is Yes! We indeed find that interacting dark energy can alleviate the current tension on the value of the Hubble constant $H_0$ between the Cosmic Microwave Background anisotropies constraints obtained from the Planck satellite and the recent direct measurements reported by Riess et al. 2016. The combinati...
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Fast Switching Dual Fabry-Perot Cavity Optical Refractometry - Methodologies for Accurate Assessment of Gas Density
Dual Fabry-Perot cavity based optical refractometry (DFPC-OR) has a high potential for assessments of gas density. However, drifts of the FP cavity often limit its performance. We show that by the use of two narrow-linewidth fiber lasers locked to two high finesse cavities and Allan-Werle plots that drift-free DFPC-O...
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A Large Self-Annotated Corpus for Sarcasm
We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for sarcasm research and for training and evaluating systems for sarcasm detection. The corpus has 1.3 million sarcastic statements -- 10 times more than any previous dataset -- and many times more instances of non-sarcastic statements, allowing for...
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Aerosol properties in the atmospheres of extrasolar giant planets
We use a model of aerosol microphysics to investigate the impact of high-altitude photochemical aerosols on the transmission spectra and atmospheric properties of close-in exoplanets, such as HD209458b and HD189733b. The results depend strongly on the temperature profiles in the middle and upper atmosphere that are p...
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Influence of random opinion change in complex networks
Opinion formation in the population has attracted extensive research interest. Various models have been introduced and studied, including the ones with individuals' free will allowing them to change their opinions. Such models, however, have not taken into account the fact that individuals with different opinions may...
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We Are Not Your Real Parents: Telling Causal from Confounded using MDL
Given data over variables $(X_1,...,X_m, Y)$ we consider the problem of finding out whether $X$ jointly causes $Y$ or whether they are all confounded by an unobserved latent variable $Z$. To do so, we take an information-theoretic approach based on Kolmogorov complexity. In a nutshell, we follow the postulate that fi...
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Evolution of eccentricity and inclination of hot protoplanets embedded in radiative discs
We study the evolution of the eccentricity and inclination of protoplanetary embryos and low-mass protoplanets (from a fraction of an Earth mass to a few Earth masses) embedded in a protoplanetary disc, by means of three dimensional hydrodynamics calculations with radiative transfer in the diffusion limit. When the p...
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Definitions in mathematics
We discuss various forms of definitions in mathematics and describe rules governing them.
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Excellence in prime characteristic
Fix any field $K$ of characteristic $p$ such that $[K:K^p]$ is finite. We discuss excellence for Noetherian domains whose fraction field is $K$, showing for example, that $R$ is excellent if and only if the Frobenius map is finite on $R$. Furthermore, we show $R$ is excellent if and only if it admits some non-zero $p...
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Asymptotically optimal private estimation under mean square loss
We consider the minimax estimation problem of a discrete distribution with support size $k$ under locally differential privacy constraints. A privatization scheme is applied to each raw sample independently, and we need to estimate the distribution of the raw samples from the privatized samples. A positive number $\e...
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Coulomb repulsion of holes and competition between d_{x^2-y^2}-wave and s-wave parings in cuprate superconductors
The effect of the Coulomb repulsion of holes on the Cooper instability in an ensemble of spin-polaron quasiparticles has been analyzed, taking into account the peculiarities of the crystallographic structure of the CuO$_2$ plane, which are associated with the presence of two oxygen ions and one copper ion in the unit...
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Modeling Game Avatar Synergy and Opposition through Embedding in Multiplayer Online Battle Arena Games
Multiplayer Online Battle Arena (MOBA) games have received increasing worldwide popularity recently. In such games, players compete in teams against each other by controlling selected game avatars, each of which is designed with different strengths and weaknesses. Intuitively, putting together game avatars that compl...
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Design and Development of Effective Transmission Mechanisms on a Tendon Driven Hand Orthosis for Stroke Patients
Tendon-driven hand orthoses have advantages over exoskeletons with respect to wearability and safety because of their low-profile design and ability to fit a range of patients without requiring custom joint alignment. However, no existing study on a wearable tendon-driven hand orthosis for stroke patients presents ev...
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eXpose: A Character-Level Convolutional Neural Network with Embeddings For Detecting Malicious URLs, File Paths and Registry Keys
For years security machine learning research has promised to obviate the need for signature based detection by automatically learning to detect indicators of attack. Unfortunately, this vision hasn't come to fruition: in fact, developing and maintaining today's security machine learning systems can require engineerin...
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A Software Reuse Approach and Its Effect On Software Quality, An Empirical Study for The Software Industry
Software reusability has become much interesting because of increased quality and reduce cost. A good process of software reuse leads to enhance the reliability, productivity, quality and the reduction of time and cost. Current reuse techniques focuses on the reuse of software artifact which grounded on anticipated f...
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Portfolio Optimization with Nondominated Priors and Unbounded Parameters
We consider classical Merton problem of terminal wealth maximization in finite horizon. We assume that the drift of the stock is following Ornstein-Uhlenbeck process and the volatility of it is following GARCH(1) process. In particular, both mean and volatility are unbounded. We assume that there is Knightian uncerta...
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Measuring heterogeneity in urban expansion via spatial entropy
The lack of efficiency in urban diffusion is a debated issue, important for biologists, urban specialists, planners and statisticians, both in developed and new developing countries. Many approaches have been considered to measure urban sprawl, i.e. chaotic urban expansion; such idea of chaos is here linked to the co...
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Bayesian Cluster Enumeration Criterion for Unsupervised Learning
We derive a new Bayesian Information Criterion (BIC) by formulating the problem of estimating the number of clusters in an observed data set as maximization of the posterior probability of the candidate models. Given that some mild assumptions are satisfied, we provide a general BIC expression for a broad class of da...
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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Combinatorial interaction testing is an important software testing technique that has seen lots of recent interest. It can reduce the number of test cases needed by considering interactions between combinations of input parameters. Empirical evidence shows that it effectively detects faults, in particular, for highly...
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Is Life Most Likely Around Sun-like Stars?
We consider the habitability of Earth-analogs around stars of different masses, which is regulated by the stellar lifetime, stellar wind-induced atmospheric erosion, and biologically active ultraviolet (UV) irradiance. By estimating the timescales associated with each of these processes, we show that they collectivel...
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Maximum Entropy Generators for Energy-Based Models
Unsupervised learning is about capturing dependencies between variables and is driven by the contrast between the probable vs. improbable configurations of these variables, often either via a generative model that only samples probable ones or with an energy function (unnormalized log-density) that is low for probabl...
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A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols
Convolutional neural networks (CNNs) have shown promising results on several segmentation tasks in magnetic resonance (MR) images. However, the accuracy of CNNs may degrade severely when segmenting images acquired with different scanners and/or protocols as compared to the training data, thus limiting their practical...
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Hybrid Kinematic Control for Rigid Body Pose Stabilization using Dual Quaternions
In this paper, we address the rigid body pose stabilization problem using dual quaternion formalism. We propose a hybrid control strategy to design a switching control law with hysteresis in such a way that the global asymptotic stability of the closed-loop system is guaranteed and such that the global attractivity o...
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On 2d-4d motivic wall-crossing formulas
In this paper we propose definitions and examples of categorical enhancements of the data involved in the $2d$-$4d$ wall-crossing formulas which generalize both Cecotti-Vafa and Kontsevich-Soibelman motivic wall-crossing formulas.
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On Quitting: Performance and Practice in Online Game Play
We study the relationship between performance and practice by analyzing the activity of many players of a casual online game. We find significant heterogeneity in the improvement of player performance, given by score, and address this by dividing players into similar skill levels and segmenting each player's activity...
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Video Labeling for Automatic Video Surveillance in Security Domains
Beyond traditional security methods, unmanned aerial vehicles (UAVs) have become an important surveillance tool used in security domains to collect the required annotated data. However, collecting annotated data from videos taken by UAVs efficiently, and using these data to build datasets that can be used for learnin...
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On density of subgraphs of Cartesian products
In this paper, we extend two classical results about the density of subgraphs of hypercubes to subgraphs $G$ of Cartesian products $G_1\times\cdots\times G_m$ of arbitrary connected graphs. Namely, we show that $\frac{|E(G)|}{|V(G)|}\le \lceil 2\max\{ \text{dens}(G_1),\ldots,\text{dens}(G_m)\} \rceil\log|V(G)|$, wher...
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Replica Analysis for Maximization of Net Present Value
In this paper, we use replica analysis to determine the investment strategy that can maximize the net present value for portfolios containing multiple development projects. Replica analysis was developed in statistical mechanical informatics and econophysics to evaluate disordered systems, and here we use it to formu...
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On some properties of weak solutions to elliptic equations with divergence-free drifts
We discuss the local properties of weak solutions to the equation $-\Delta u + b\cdot\nabla u=0$. The corresponding theory is well-known in the case $b\in L_n$, where $n$ is the dimension of the space. Our main interest is focused on the case $b\in L_2$. In this case the structure assumption $\operatorname{div} b=0$ ...
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The heptagon-wheel cocycle in the Kontsevich graph complex
The real vector space of non-oriented graphs is known to carry a differential graded Lie algebra structure. Cocycles in the Kontsevich graph complex, expressed using formal sums of graphs on $n$ vertices and $2n-2$ edges, induce -- under the orientation mapping -- infinitesimal symmetries of classical Poisson structu...
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Maneuver Regulation for Accelerating Bodies in Atmospheric Environments
In order to address the need for an affordable reduced gravity test platform, this work focuses on the analysis and implementation of atmospheric acceleration tracking with an autonomous aerial vehicle. As proof of concept, the vehicle is designed with the objective of flying accurate reduced-gravity parabolas. Sugge...
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A Hybrid Deep Learning Approach for Texture Analysis
Texture classification is a problem that has various applications such as remote sensing and forest species recognition. Solutions tend to be custom fit to the dataset used but fails to generalize. The Convolutional Neural Network (CNN) in combination with Support Vector Machine (SVM) form a robust selection between ...
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Accounting Noise and the Pricing of CoCos
Contingent Convertible bonds (CoCos) are debt instruments that convert into equity or are written down in times of distress. Existing pricing models assume conversion triggers based on market prices and on the assumption that markets can always observe all relevant firm information. But all Cocos issued so far have t...
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An Improved Algorithm for E-Generalization
E-generalization computes common generalizations of given ground terms w.r.t. a given equational background theory E. In 2005 [arXiv:1403.8118], we had presented a computation approach based on standard regular tree grammar algorithms, and a Prolog prototype implementation. In this report, we present algorithmic impr...
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On quartic double fivefolds and the matrix factorizations of exceptional quaternionic representations
We study quartic double fivefolds from the perspective of Fano manifolds of Calabi-Yau type and that of exceptional quaternionic representations. We first prove that the generic quartic double fivefold can be represented, in a finite number of ways, as a double cover of P^5 ramified along a linear section of the Sp 1...
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Atmospheric thermal tides and planetary spin I. The complex interplay between stratification and rotation
Thermal atmospheric tides can torque telluric planets away from spin-orbit synchronous rotation, as observed in the case of Venus. They thus participate to determine the possible climates and general circulations of the atmospheres of these planets. In this work, we write the equations governing the dynamics of therm...
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Inferring Generative Model Structure with Static Analysis
Obtaining enough labeled data to robustly train complex discriminative models is a major bottleneck in the machine learning pipeline. A popular solution is combining multiple sources of weak supervision using generative models. The structure of these models affects training label quality, but is difficult to learn wi...
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Maslov, Chern-Weil and Mean Curvature
We provide an integral formula for the Maslov index of a pair $(E,F)$ over a surface $\Sigma$, where $E\rightarrow\Sigma$ is a complex vector bundle and $F\subset E_{|\partial\Sigma}$ is a totally real subbundle. As in Chern-Weil theory, this formula is written in terms of the curvature of $E$ plus a boundary contrib...
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Tuning Goodness-of-Fit Tests
As modern precision cosmological measurements continue to show agreement with the broad features of the standard $\Lambda$-Cold Dark Matter ($\Lambda$CDM) cosmological model, we are increasingly motivated to look for small departures from the standard model's predictions which might not be detected with standard appr...
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The Lubin-Tate stack and Gross-Hopkins duality
Morava $E$-theory $E$ is an $E_\infty$-ring with an action of the Morava stabilizer group $\Gamma$. We study the derived stack $\operatorname{Spf} E/\Gamma$. Descent-theoretic techniques allow us to deduce a theorem of Hopkins-Mahowald-Sadofsky on the $K(n)$-local Picard group, as well as a recent result of Barthel-B...
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Generalized Probabilistic Bisection for Stochastic Root-Finding
We consider numerical schemes for root finding of noisy responses through generalizing the Probabilistic Bisection Algorithm (PBA) to the more practical context where the sampling distribution is unknown and location-dependent. As in standard PBA, we rely on a knowledge state for the approximate posterior of the root...
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Towards Proof Synthesis Guided by Neural Machine Translation for Intuitionistic Propositional Logic
Inspired by the recent evolution of deep neural networks (DNNs) in machine learning, we explore their application to PL-related topics. This paper is the first step towards this goal; we propose a proof-synthesis method for the negation-free propositional logic in which we use a DNN to obtain a guide of proof search....
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Fibonacci words in hyperbolic Pascal triangles
The hyperbolic Pascal triangle ${\cal HPT}_{4,q}$ $(q\ge5)$ is a new mathematical construction, which is a geometrical generalization of Pascal's arithmetical triangle. In the present study we show that a natural pattern of rows of ${\cal HPT}_{4,5}$ is almost the same as the sequence consisting of every second term ...
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