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Robust Adversarial Reinforcement Learning
Deep neural networks coupled with fast simulation and improved computation have led to recent successes in the field of reinforcement learning (RL). However, most current RL-based approaches fail to generalize since: (a) the gap between simulation and real world is so large that policy-learning approaches fail to tra...
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Dynamic behaviour of Multilamellar Vesicles under Poiseuille flow
Surfactant solutions exhibit multilamellar surfactant vesicles (MLVs) under flow conditions and in concentration ranges which are found in a large number of industrial applications. MLVs are typically formed from a lamellar phase and play an important role in determining the rheological properties of surfactant solut...
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Approximate fixed points and B-amenable groups
A topological group $G$ is B-amenable if and only if every continuous affine action of $G$ on a bounded convex subset of a locally convex space has an approximate fixed point. Similar results hold more generally for slightly uniformly continuous semigroup actions.
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Radiation hardness of small-pitch 3D pixel sensors up to HL-LHC fluences
A new generation of 3D silicon pixel detectors with a small pixel size of 50$\times$50 and 25$\times$100 $\mu$m$^{2}$ is being developed for the HL-LHC tracker upgrades. The radiation hardness of such detectors was studied in beam tests after irradiation to HL-LHC fluences up to $1.4\times10^{16}$ n$_{\mathrm{eq}}$/c...
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Simulating Cosmic Microwave Background anisotropy measurements for Microwave Kinetic Inductance Devices
Microwave Kinetic Inductance Devices (MKIDs) are poised to allow for massively and natively multiplexed photon detectors arrays and are a natural choice for the next-generation CMB-Stage 4 experiment which will require 105 detectors. In this proceed- ing we discuss what noise performance of present generation MKIDs i...
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Optimized State Space Grids for Abstractions
The practical impact of abstraction-based controller synthesis methods is currently limited by the immense computational effort for obtaining abstractions. In this note we focus on a recently proposed method to compute abstractions whose state space is a cover of the state space of the plant by congruent hyper-interv...
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Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
We propose a novel denoising framework for task functional Magnetic Resonance Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the brain functional connectivity via dictionary learning and sparse coding (DLSC). In order to address the limitations of the unsupervised DLSC-based fMRI studies, we...
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Optimal control of a Vlasov-Poisson plasma by an external magnetic field - The basics for variational calculus
We consider the three dimensional Vlasov-Poisson system that is equipped with an external magnetic field to describe a plasma. The aim of various concrete applications is to control a plasma in a desired fashion. This can be modeled by an optimal control problem. For that reason the basics for calculus of variations ...
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Lensless Photography with only an image sensor
Photography usually requires optics in conjunction with a recording device (an image sensor). Eliminating the optics could lead to new form factors for cameras. Here, we report a simple demonstration of imaging using a bare CMOS sensor that utilizes computation. The technique relies on the space variant point-spread ...
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Truth-Telling Mechanism for Secure Two-Way Relay Communications with Energy-Harvesting Revenue
This paper brings the novel idea of paying the utility to the winning agents in terms of some physical entity in cooperative communications. Our setting is a secret two-way communication channel where two transmitters exchange information in the presence of an eavesdropper. The relays are selected from a set of inter...
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Prediction of Individual Outcomes for Asthma Sufferers
We consider the problem of individual-specific medication level recommendation (initiation, removal, increase, or decrease) for asthma sufferers. Asthma is one of the most common chronic diseases in both adults and children, affecting 8% of the US population and costing $37-63 billion/year in the US. Asthma is a comp...
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Bayesian Probabilistic Numerical Methods
The emergent field of probabilistic numerics has thus far lacked clear statistical principals. This paper establishes Bayesian probabilistic numerical methods as those which can be cast as solutions to certain inverse problems within the Bayesian framework. This allows us to establish general conditions under which B...
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The evolution of the temperature field during cavity collapse in liquid nitromethane. Part II: Reactive case
We study effect of cavity collapse in non-ideal explosives as a means of controlling their sensitivity. The main aim is to understand the origin of localised temperature peaks (hot spots) that play a leading order role at early ignition stages. Thus, we perform 2D and 3D numerical simulations of shock induced single ...
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Quantile Regression for Qualifying Match of GEFCom2017 Probabilistic Load Forecasting
We present a simple quantile regression-based forecasting method that was applied in a probabilistic load forecasting framework of the Global Energy Forecasting Competition 2017 (GEFCom2017). The hourly load data is log transformed and split into a long-term trend component and a remainder term. The key forecasting e...
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Strong Local Nondeterminism of Spherical Fractional Brownian Motion
Let $B = \left\{ B\left( x\right),\, x\in \mathbb{S}^{2}\right\} $ be the fractional Brownian motion indexed by the unit sphere $\mathbb{S}^{2}$ with index $0<H\leq \frac{1}{2}$, introduced by Istas \cite{IstasECP05}. We establish optimal estimates for its angular power spectrum $\{d_\ell, \ell = 0, 1, 2, \ldots\}$, ...
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Sparse Named Entity Classification using Factorization Machines
Named entity classification is the task of classifying text-based elements into various categories, including places, names, dates, times, and monetary values. A bottleneck in named entity classification, however, is the data problem of sparseness, because new named entities continually emerge, making it rather diffi...
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Exploration of Large Networks with Covariates via Fast and Universal Latent Space Model Fitting
Latent space models are effective tools for statistical modeling and exploration of network data. These models can effectively model real world network characteristics such as degree heterogeneity, transitivity, homophily, etc. Due to their close connection to generalized linear models, it is also natural to incorpor...
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Distant Supervision for Topic Classification of Tweets in Curated Streams
We tackle the challenge of topic classification of tweets in the context of analyzing a large collection of curated streams by news outlets and other organizations to deliver relevant content to users. Our approach is novel in applying distant supervision based on semi-automatically identifying curated streams that a...
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Relationship Maintenance in Software Language Repositories
The context of this research is testing and building software systems and, specifically, software language repositories (SLRs), i.e., repositories with components for language processing (interpreters, translators, analyzers, transformers, pretty printers, etc.). SLRs are typically set up for developing and using met...
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The Emptiness Problem for Valence Automata over Graph Monoids
This work studies which storage mechanisms in automata permit decidability of the emptiness problem. The question is formalized using valence automata, an abstract model of automata in which the storage mechanism is given by a monoid. For each of a variety of storage mechanisms, one can choose a (typically infinite) ...
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On the Optimization Landscape of Tensor Decompositions
Non-convex optimization with local search heuristics has been widely used in machine learning, achieving many state-of-art results. It becomes increasingly important to understand why they can work for these NP-hard problems on typical data. The landscape of many objective functions in learning has been conjectured t...
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Estimate of Joule Heating in a Flat Dechirper
We have performed Joule power loss calculations for a flat dechirper. We have considered the configurations of the beam on-axis between the two plates---for chirp control---and for the beam especially close to one plate---for use as a fast kicker. Our calculations use a surface impedance approach, one that is valid w...
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Accurate Kernel Learning for Linear Gaussian Markov Processes using a Scalable Likelihood Computation
We report an exact likelihood computation for Linear Gaussian Markov processes that is more scalable than existing algorithms for complex models and sparsely sampled signals. Better scaling is achieved through elimination of repeated computations in the Kalman likelihood, and by using the diagonalized form of the sta...
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Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach
The experimental design problem concerns the selection of k points from a potentially large design pool of p-dimensional vectors, so as to maximize the statistical efficiency regressed on the selected k design points. Statistical efficiency is measured by optimality criteria, including A(verage), D(eterminant), T(rac...
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Positive semi-definite embedding for dimensionality reduction and out-of-sample extensions
In machine learning or statistics, it is often desirable to reduce the dimensionality of high dimensional data. We propose to obtain the low dimensional embedding coordinates as the eigenvectors of a positive semi-definite kernel matrix. This kernel matrix is the solution of a semi-definite program promoting a low ra...
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Bounded Projective Functions and Hyperbolic Metrics with Isolated Singularities
We establish a correspondence on a Riemann surface between hyperbolic metrics with isolated singularities and bounded projective functions whose Schwarzian derivatives have at most double poles and whose monodromies lie in ${\rm PSU}(1,\,1)$. As an application, we construct explicitly a new class of hyperbolic metric...
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A State-Space Approach to Dynamic Nonnegative Matrix Factorization
Nonnegative matrix factorization (NMF) has been actively investigated and used in a wide range of problems in the past decade. A significant amount of attention has been given to develop NMF algorithms that are suitable to model time series with strong temporal dependencies. In this paper, we propose a novel state-sp...
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Active Inductive Logic Programming for Code Search
Modern search techniques either cannot efficiently incorporate human feedback to refine search results or to express structural or semantic properties of desired code. The key insight of our interactive code search technique ALICE is that user feedback could be actively incorporated to allow users to easily express a...
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Dense families of modular curves, prime numbers and uniform symmetric tensor rank of multiplication in certain finite fields
We obtain new uniform bounds for the symmetric tensor rank of multiplication in finite extensions of any finite field Fp or Fp2 where p denotes a prime number greater or equal than 5. In this aim, we use the symmetric Chudnovsky-type generalized algorithm applied on sufficiently dense families of modular curves defin...
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Continued fraction algorithms and Lagrange's theorem in ${\mathbb Q}_p$
We present several continued fraction algorithms, each of which gives an eventually periodic expansion for every quadratic element of ${\mathbb Q}_p$ over ${\mathbb Q}$ and gives a finite expansion for every rational number. We also give, for each of our algorithms, the complete characterization of elements having pu...
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Scaling and bias codes for modeling speaker-adaptive DNN-based speech synthesis systems
Most neural-network based speaker-adaptive acoustic models for speech synthesis can be categorized into either layer-based or input-code approaches. Although both approaches have their own pros and cons, most existing works on speaker adaptation focus on improving one or the other. In this paper, after we first syste...
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Bayesian Network Regularized Regression for Modeling Urban Crime Occurrences
This paper considers the problem of statistical inference and prediction for processes defined on networks. We assume that the network is known and measures similarity, and our goal is to learn about an attribute associated with its vertices. Classical regression methods are not immediately applicable to this setting...
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Similarity forces and recurrent components in human face-to-face interaction networks
We show that the social dynamics responsible for the formation of connected components that appear recurrently in face-to-face interaction networks, find a natural explanation in the assumption that the agents of the temporal network reside in a hidden similarity space. Distances between the agents in this space act ...
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CELLO-3D: Estimating the Covariance of ICP in the Real World
The fusion of Iterative Closest Point (ICP) reg- istrations in existing state estimation frameworks relies on an accurate estimation of their uncertainty. In this paper, we study the estimation of this uncertainty in the form of a covariance. First, we scrutinize the limitations of existing closed-form covariance est...
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Projection Theorems Using Effective Dimension
In this paper we use the theory of computing to study fractal dimensions of projections in Euclidean spaces. A fundamental result in fractal geometry is Marstrand's projection theorem, which shows that for every analytic set E, for almost every line L, the Hausdorff dimension of the orthogonal projection of E onto L ...
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Exotic pairing symmetry of interacting Dirac fermions on a $π$ flux lattice
The pairing symmetry of interacting Dirac fermions on the $\pi$-flux lattice is studied with the determinant quantum Monte Carlo and numerical linked cluster expansion methods. The extended $s^*$- (i.e. extended $s$-) and d-wave pairing symmetries, which are distinct in the conventional square lattice, are degenerate...
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Learning Causal Structures Using Regression Invariance
We study causal inference in a multi-environment setting, in which the functional relations for producing the variables from their direct causes remain the same across environments, while the distribution of exogenous noises may vary. We introduce the idea of using the invariance of the functional relations of the va...
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Linear Exponential Comonads without Symmetry
The notion of linear exponential comonads on symmetric monoidal categories has been used for modelling the exponential modality of linear logic. In this paper we introduce linear exponential comonads on general (possibly non-symmetric) monoidal categories, and show some basic results on them.
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Multi-speaker Recognition in Cocktail Party Problem
This paper proposes an original statistical decision theory to accomplish a multi-speaker recognition task in cocktail party problem. This theory relies on an assumption that the varied frequencies of speakers obey Gaussian distribution and the relationship of their voiceprints can be represented by Euclidean distanc...
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A DIRT-T Approach to Unsupervised Domain Adaptation
Domain adaptation refers to the problem of leveraging labeled data in a source domain to learn an accurate model in a target domain where labels are scarce or unavailable. A recent approach for finding a common representation of the two domains is via domain adversarial training (Ganin & Lempitsky, 2015), which attem...
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Robust valley polarization of helium ion modified atomically thin MoS$_{2}$
Atomically thin semiconductors have dimensions that are commensurate with critical feature sizes of future optoelectronic devices defined using electron/ion beam lithography. Robustness of their emergent optical and valleytronic properties is essential for typical exposure doses used during fabrication. Here, we expl...
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Sustained sensorimotor control as intermittent decisions about prediction errors: Computational framework and application to ground vehicle steering
A conceptual and computational framework is proposed for modelling of human sensorimotor control, and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency, and extends on existing models by suggesting that the nervous system implements intermittent control using a...
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COLOSSUS: A python toolkit for cosmology, large-scale structure, and dark matter halos
This paper introduces Colossus, a public, open-source python package for calculations related to cosmology, the large-scale structure (LSS) of matter in the universe, and the properties of dark matter halos. The code is designed to be fast and easy to use, with a coherent, well-documented user interface. The cosmolog...
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Generalized Similarity U: A Non-parametric Test of Association Based on Similarity
Second generation sequencing technologies are being increasingly used for genetic association studies, where the main research interest is to identify sets of genetic variants that contribute to various phenotype. The phenotype can be univariate disease status, multivariate responses and even high-dimensional outcome...
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Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS
Many modern video processing pipelines rely on edge-aware (EA) filtering methods. However, recent high-quality methods are challenging to run in real-time on embedded hardware due to their computational load. To this end, we propose an area-efficient and real-time capable hardware implementation of a high quality EA ...
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Non-Convex Weighted Lp Nuclear Norm based ADMM Framework for Image Restoration
Since the matrix formed by nonlocal similar patches in a natural image is of low rank, the nuclear norm minimization (NNM) has been widely used in various image processing studies. Nonetheless, nuclear norm based convex surrogate of the rank function usually over-shrinks the rank components and makes different compon...
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A Contextual Bandit Approach for Stream-Based Active Learning
Contextual bandit algorithms -- a class of multi-armed bandit algorithms that exploit the contextual information -- have been shown to be effective in solving sequential decision making problems under uncertainty. A common assumption adopted in the literature is that the realized (ground truth) reward by taking the s...
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Localization of ions within one-, two- and three-dimensional Coulomb crystals by a standing wave optical potential
We demonstrate light-induced localization of Coulomb-interacting particles in multi-dimensional structures. Subwavelength localization of ions within small multi-dimensional Coulomb crystals by an intracavity optical standing wave field is evidenced by measuring the difference in scattering inside symmetrically red- ...
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Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks
A variety of real-world processes (over networks) produce sequences of data whose complex temporal dynamics need to be studied. More especially, the event timestamps can carry important information about the underlying network dynamics, which otherwise are not available from the time-series evenly sampled from contin...
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Low Auto-correlation Binary Sequences explored using Warning Propagation
The search of binary sequences with low auto-correlations (LABS) is a discrete combinatorial optimization problem contained in the NP-hard computational complexity class. We study this problem using Warning Propagation (WP) , a message passing algorithm, and compare the performance of the algorithm in the original pr...
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Estimation of the marginal expected shortfall under asymptotic independence
We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positive associated, which is modeled by the so-called tail dependent coefficient. We construct an estimator of the marginal expected shortfall which is shown to be asymptotically normal. T...
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Downgrade Attack on TrustZone
Security-critical tasks require proper isolation from untrusted software. Chip manufacturers design and include trusted execution environments (TEEs) in their processors to secure these tasks. The integrity and security of the software in the trusted environment depend on the verification process of the system. We fi...
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Robust Inference under the Beta Regression Model with Application to Health Care Studies
Data on rates, percentages or proportions arise frequently in many different applied disciplines like medical biology, health care, psychology and several others. In this paper, we develop a robust inference procedure for the beta regression model which is used to describe such response variables taking values in $(0...
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PageRank in Undirected Random Graphs
PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning. In this paper, we study PageRank in undirected random graphs with an expansion property. The Chung-Lu random graph is an example of such a graph. We show that in the limit, as the size of the gra...
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Room temperature line lists for CO\2 symmetric isotopologues with \textit{ab initio} computed intensities
Remote sensing experiments require high-accuracy, preferably sub-percent, line intensities and in response to this need we present computed room temperature line lists for six symmetric isotopologues of carbon dioxide: $^{13}$C$^{16}$O$_2$, $^{14}$C$^{16}$O$_2$, $^{12}$C$^{17}$O$_2$, $^{12}$C$^{18}$O$_2$, $^{13}$C$^{...
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The GIT moduli of semistable pairs consisting of a cubic curve and a line on ${\mathbb P}^{2}$
We discuss the GIT moduli of semistable pairs consisting of a cubic curve and a line on the projective plane. We study in some detail this moduli and compare it with another moduli suggested by Alexeev. It is the moduli of pairs (with no specified semi-abelian action) consisting of a cubic curve with at worst nodal s...
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On the Genus of the Moonshine Module
We provide a novel and simple description of Schellekens' seventy-one affine Kac-Moody structures of self-dual vertex operator algebras of central charge 24 by utilizing cyclic subgroups of the glue codes of the Niemeier lattices with roots. We also discuss a possible uniform construction procedure of the self-dual v...
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A Deep Learning-based Reconstruction of Cosmic Ray-induced Air Showers
We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detector's responses to traversing shower particles are signal amplitudes as a function of time...
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The unexpected resurgence of Weyl geometry in late 20-th century physics
Weyl's original scale geometry of 1918 ("purely infinitesimal geometry") was withdrawn by its author from physical theorizing in the early 1920s. It had a comeback in the last third of the 20th century in different contexts: scalar tensor theories of gravity, foundations of gravity, foundations of quantum mechanics, ...
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Discrete Dynamic Causal Modeling and Its Relationship with Directed Information
This paper explores the discrete Dynamic Causal Modeling (DDCM) and its relationship with Directed Information (DI). We prove the conditional equivalence between DDCM and DI in characterizing the causal relationship between two brain regions. The theoretical results are demonstrated using fMRI data obtained under bot...
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Two-step approach to scheduling quantum circuits
As the effort to scale up existing quantum hardware proceeds, it becomes necessary to schedule quantum gates in a way that minimizes the number of operations. There are three constraints that have to be satisfied: the order or dependency of the quantum gates in the specific algorithm, the fact that any qubit may be i...
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A Study of the Allan Variance for Constant-Mean Non-Stationary Processes
The Allan Variance (AV) is a widely used quantity in areas focusing on error measurement as well as in the general analysis of variance for autocorrelated processes in domains such as engineering and, more specifically, metrology. The form of this quantity is widely used to detect noise patterns and indications of st...
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Foresight: Recommending Visual Insights
Current tools for exploratory data analysis (EDA) require users to manually select data attributes, statistical computations and visual encodings. This can be daunting for large-scale, complex data. We introduce Foresight, a system that helps the user rapidly discover visual insights from large high-dimensional datas...
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Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization
We consider the stochastic composition optimization problem proposed in \cite{wang2017stochastic}, which has applications ranging from estimation to statistical and machine learning. We propose the first ADMM-based algorithm named com-SVR-ADMM, and show that com-SVR-ADMM converges linearly for strongly convex and Lip...
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Hierarchical Behavioral Repertoires with Unsupervised Descriptors
Enabling artificial agents to automatically learn complex, versatile and high-performing behaviors is a long-lasting challenge. This paper presents a step in this direction with hierarchical behavioral repertoires that stack several behavioral repertoires to generate sophisticated behaviors. Each repertoire of this a...
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Indirect Image Registration with Large Diffeomorphic Deformations
The paper adapts the large deformation diffeomorphic metric mapping framework for image registration to the indirect setting where a template is registered against a target that is given through indirect noisy observations. The registration uses diffeomorphisms that transform the template through a (group) action. Th...
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Morphological estimators on Sunyaev--Zel'dovich maps of MUSIC clusters of galaxies
The determination of the morphology of galaxy clusters has important repercussion on their cosmological and astrophysical studies. In this paper we address the morphological characterisation of synthetic maps of the Sunyaev--Zel'dovich (SZ) effect produced for a sample of 258 massive clusters ($M_{vir}>5\times10^{14}...
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Hierarchy of exchange interactions in the triangular-lattice spin-liquid YbMgGaO$_{4}$
The spin-1/2 triangular lattice antiferromagnet YbMgGaO$_{4}$ has attracted recent attention as a quantum spin-liquid candidate with the possible presence of off-diagonal anisotropic exchange interactions induced by spin-orbit coupling. Whether a quantum spin-liquid is stabilized or not depends on the interplay of va...
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Pulsar braking and the P-Pdot diagram
The location of radio pulsars in the period-period derivative (P-Pdot) plane has been a key diagnostic tool since the early days of pulsar astronomy. Of particular importance is how pulsars evolve through the P-Pdot diagram with time. Here we show that the decay of the inclination angle (alpha-dot) between the magnet...
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Uniqueness of stable capillary hypersurfaces in a ball
In this paper we prove that any immersed stable capillary hypersurfaces in a ball in space forms are totally umbilical. This solves completely a long-standing open problem. In the proof one of crucial ingredients is a new Minkowski type formula. We also prove a Heintze-Karcher-Ros type inequality for hypersurfaces in...
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A Potential Recoiling Supermassive Black Hole CXO J101527.2+625911
We have carried out a systematic search for recoiling supermassive black holes (rSMBH) using the Chandra Source and SDSS Cross Matched Catalog. From the survey, we have detected a potential rSMBH, 'CXO J101527.2+625911' at z=0.3504. The CXO J101527.2+625911 has a spatially offset (1.26$\pm$0.05 kpc) active SMBH and k...
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WLAN Performance Analysis Ibrahim Group of industries Faisalabad Pakistan
Now a days several organizations are moving their LAN foundation towards remote LAN frame work. The purpose for this is extremely straight forward multinational organizations needs their clients surprise about their office surroundings and they additionally need to make wire free environment in their workplaces. Much...
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Archetypes for Representing Data about the Brazilian Public Hospital Information System and Outpatient High Complexity Procedures System
The Brazilian Ministry of Health has selected the openEHR model as a standard for electronic health record systems. This paper presents a set of archetypes to represent the main data from the Brazilian Public Hospital Information System and the High Complexity Procedures Module of the Brazilian public Outpatient Heal...
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Global linear convergent algorithm to compute the minimum volume enclosing ellipsoid
The minimum volume enclosing ellipsoid (MVEE) problem is an optimization problem in the basis of many practical problems. This paper describes some new properties of this model and proposes a first-order oracle algorithm, the Adjusted Coordinate Descent (ACD) algorithm, to address the MVEE problem. The ACD algorithm ...
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Asymptotic behavior of memristive circuits and combinatorial optimization
The interest in memristors has risen due to their possible application both as memory units and as computational devices in combination with CMOS. This is in part due to their nonlinear dynamics and a strong dependence on the circuit topology. We provide evidence that also purely memristive circuits can be employed f...
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Contrasting information theoretic decompositions of modulatory and arithmetic interactions in neural information processing systems
Biological and artificial neural systems are composed of many local processors, and their capabilities depend upon the transfer function that relates each local processor's outputs to its inputs. This paper uses a recent advance in the foundations of information theory to study the properties of local processors that...
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Recommendations for Marketing Campaigns in Telecommunication Business based on the footprint analysis
A major investment made by a telecom operator goes into the infrastructure and its maintenance, while business revenues are proportional to how big and good the customer base is. We present a data-driven analytic strategy based on combinatorial optimization and analysis of historical data. The data cover historical m...
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Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
We consider the problem of detecting out-of-distribution images in neural networks. We propose ODIN, a simple and effective method that does not require any change to a pre-trained neural network. Our method is based on the observation that using temperature scaling and adding small perturbations to the input can sep...
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Two-fermion Bethe-Salpeter Equation in Minkowski Space: the Nakanishi Way
The possibility of solving the Bethe-Salpeter Equation in Minkowski space, even for fermionic systems, is becoming actual, through the applications of well-known tools: i) the Nakanishi integral representation of the Bethe-Salpeter amplitude and ii) the light-front projection onto the null-plane. The theoretical back...
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Fractional Laplacians on the sphere, the Minakshisundaram zeta function and semigroups
In this paper we show novel underlying connections between fractional powers of the Laplacian on the unit sphere and functions from analytic number theory and differential geometry, like the Hurwitz zeta function and the Minakshisundaram zeta function. Inspired by Minakshisundaram's ideas, we find a precise pointwise...
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Nef partitions for codimension 2 weighted complete intersections
We prove that a smooth well formed Fano weighted complete intersection of codimension 2 has a nef partition. We discuss applications of this fact to Mirror Symmetry. In particular we list all nef partitions for smooth well formed Fano weighted complete intersections of dimensions 4 and 5 and present weak Landau--Ginz...
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Integrating sentiment and social structure to determine preference alignments: The Irish Marriage Referendum
We examine the relationship between social structure and sentiment through the analysis of a large collection of tweets about the Irish Marriage Referendum of 2015. We obtain the sentiment of every tweet with the hashtags #marref and #marriageref that was posted in the days leading to the referendum, and construct ne...
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Tailoring symmetric metallic and magnetic edge states of nanoribbon in semiconductive monolayer PtS2
Fabrication of atomic scale of metallic wire remains challenging. In present work, a nanoribbon with two parallel symmetric metallic and magnetic edges was designed from semiconductive monolayer PtS2 by employing first-principles calculations based on density functional theory. Edge energy, bonding charge density, ba...
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The Ramsey theory of the universal homogeneous triangle-free graph
The universal homogeneous triangle-free graph, constructed by Henson and denoted $\mathcal{H}_3$, is the triangle-free analogue of the Rado graph. While the Ramsey theory of the Rado graph has been completely established, beginning with Erdős-Hajnal-Posá and culminating in work of Sauer and Laflamme-Sauer-Vuksanovic,...
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Restriction of representations of metaplectic $GL_{2}(F)$ to tori
Let $F$ be a non-Archimedean local field. We study the restriction of an irreducible admissible genuine representations of the two fold metaplectic cover $\widetilde{GL}_{2}(F)$ of $GL_{2}(F)$ to the inverse image in $\widetilde{GL}_{2}(F)$ of a maximal torus in $GL_{2}(F)$.
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Five-dimensional Perfect Simplices
Let $Q_n=[0,1]^n$ be the unit cube in ${\mathbb R}^n$, $n \in {\mathbb N}$. For a nondegenerate simplex $S\subset{\mathbb R}^n$, consider the value $\xi(S)=\min \{\sigma>0: Q_n\subset \sigma S\}$. Here $\sigma S$ is a homothetic image of $S$ with homothety center at the center of gravity of $S$ and coefficient of hom...
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Quantum Fluctuations in Mesoscopic Systems
Recent experimental results point to the existence of coherent quantum phenomena in systems made of a large number of particles, despite the fact that for many-body systems the presence of decoherence is hardly negligible and emerging classicality is expected. This behaviour hinges on collective observables, named qu...
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Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks
Sensors are present in various forms all around the world such as mobile phones, surveillance cameras, smart televisions, intelligent refrigerators and blood pressure monitors. Usually, most of the sensors are a part of some other system with similar sensors that compose a network. One of such networks is composed of...
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EmbedJoin: Efficient Edit Similarity Joins via Embeddings
We study the problem of edit similarity joins, where given a set of strings and a threshold value $K$, we want to output all pairs of strings whose edit distances are at most $K$. Edit similarity join is a fundamental problem in data cleaning/integration, bioinformatics, collaborative filtering and natural language p...
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Construction of curve pairs and their applications
In this study, we introduce a new approach to curve pairs by using integral curves. We consider the direction curve and donor curve to study curve couples such as involute-evolute curves, Mannheim partner curves and Bertrand partner curves. We obtain new methods to construct partner curves of a unit speed curve and g...
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Solution of linear ill-posed problems by model selection and aggregation
We consider a general statistical linear inverse problem, where the solution is represented via a known (possibly overcomplete) dictionary that allows its sparse representation. We propose two different approaches. A model selection estimator selects a single model by minimizing the penalized empirical risk over all ...
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Simulation studies for dielectric wakefield programme at CLARA facility
Short, high charge electron bunches can drive high magnitude electric fields in dielectric lined structures. The interaction of the electron bunch with this field has several applications including high gradient dielectric wakefield acceleration (DWA) and passive beam manipulation. The simulations presented provide a...
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Long-range dynamical magnetic order and spin tunneling in the cooperative paramagnetic states of the pyrochlore analogous spinel antiferromagnets CdYb2X4 (X = S, Se)
Magnetic systems with spins sitting on a lattice of corner sharing regular tetrahedra have been particularly prolific for the discovery of new magnetic states for the last two decades. The pyrochlore compounds have offered the playground for these studies, while little attention has been comparatively devoted to othe...
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The Frobenius morphism in invariant theory
Let $R$ be the homogeneous coordinate ring of the Grassmannian $\mathbb{G}=\operatorname{Gr}(2,n)$ defined over an algebraically closed field of characteristic $p>0$. In this paper we give a completely characteristic free description of the decomposition of $R$, considered as a graded $R^p$-module, into indecomposabl...
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A General Probabilistic Approach for Quantitative Assessment of LES Combustion Models
The Wasserstein metric is introduced as a probabilistic method to enable quantitative evaluations of LES combustion models. The Wasserstein metric can directly be evaluated from scatter data or statistical results using probabilistic reconstruction against experimental data. The method is derived and generalized for ...
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Sentiment Analysis by Joint Learning of Word Embeddings and Classifier
Word embeddings are representations of individual words of a text document in a vector space and they are often use- ful for performing natural language pro- cessing tasks. Current state of the art al- gorithms for learning word embeddings learn vector representations from large corpora of text documents in an unsu- ...
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Normal-state Properties of a Unitary Bose-Fermi Mixture: A Combined Strong-coupling Approach with Universal Thermodynamics
We theoretically investigate normal-state properties of a unitary Bose-Fermi mixture. Including strong hetero-pairing fluctuations, we evaluate the Bose and Fermi chemical potential, internal energy, pressure, entropy, as well as specific heat at constant volume $C_V$, within the framework of a combined strong-coupli...
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A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
The goal of Machine Learning to automatically learn from data, extract knowledge and to make decisions without any human intervention. Such automatic (aML) approaches show impressive success. Recent results even demonstrate intriguingly that deep learning applied for automatic classification of skin lesions is on par...
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Verification Studies for the Noh Problem using Non-ideal Equations of State and Finite Strength Shocks
The Noh verification test problem is extended beyond the commonly studied ideal gamma-law gas to more realistic equations of state (EOSs) including the stiff gas, the Noble-Abel gas, and the Carnahan-Starling EOS for hard-sphere fluids. Self-similarity methods are used to solve the Euler compressible flow equations, ...
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Motivic zeta functions and infinite cyclic covers
We associate with an infinite cyclic cover of a punctured neighborhood of a simple normal crossing divisor on a complex quasi-projective manifold (assuming certain finiteness conditions are satisfied) a rational function in $K_0({\rm Var}^{\hat \mu}_{\mathbb{C}})[\mathbb{L}^{-1}]$, which we call {\it motivic infinite...
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