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Yangian Symmetry and Integrability of Planar N=4 Super-Yang-Mills Theory
In this letter we establish Yangian symmetry of planar N=4 super-Yang-Mills theory. We prove that the classical equations of motion of the model close onto themselves under the action of Yangian generators. Moreover we propose an off-shell extension of our statement which is equivalent to the invariance of the action...
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DaMaSCUS: The Impact of Underground Scatterings on Direct Detection of Light Dark Matter
Conventional dark matter direct detection experiments set stringent constraints on dark matter by looking for elastic scattering events between dark matter particles and nuclei in underground detectors. However these constraints weaken significantly in the sub-GeV mass region, simply because light dark matter does no...
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Allocation strategies for high fidelity models in the multifidelity regime
We propose a novel approach to allocating resources for expensive simulations of high fidelity models when used in a multifidelity framework. Allocation decisions that distribute computational resources across several simulation models become extremely important in situations where only a small number of expensive hi...
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Simplicial Closure and higher-order link prediction
Networks provide a powerful formalism for modeling complex systems by using a model of pairwise interactions. But much of the structure within these systems involves interactions that take place among more than two nodes at once; for example, communication within a group rather than person-to person, collaboration am...
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Basic concepts and tools for the Toki Pona minimal and constructed language: description of the language and main issues; analysis of the vocabulary; text synthesis and syntax highlighting; Wordnet synsets
A minimal constructed language (conlang) is useful for experiments and comfortable for making tools. The Toki Pona (TP) conlang is minimal both in the vocabulary (with only 14 letters and 124 lemmas) and in the (about) 10 syntax rules. The language is useful for being a used and somewhat established minimal conlang w...
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Spectral Methods for Nonparametric Models
Nonparametric models are versatile, albeit computationally expensive, tool for modeling mixture models. In this paper, we introduce spectral methods for the two most popular nonparametric models: the Indian Buffet Process (IBP) and the Hierarchical Dirichlet Process (HDP). We show that using spectral methods for the ...
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Setting the threshold for high throughput detectors: A mathematical approach for ensembles of dynamic, heterogeneous, probabilistic anomaly detectors
Anomaly detection (AD) has garnered ample attention in security research, as such algorithms complement existing signature-based methods but promise detection of never-before-seen attacks. Cyber operations manage a high volume of heterogeneous log data; hence, AD in such operations involves multiple (e.g., per IP, pe...
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Photonic Loschmidt echo in binary waveguide lattices
Time reversal is one of the most intriguing yet elusive wave phenomenon of major interest in different areas of classical and quantum physics. Time reversal requires in principle to flip the sign of the Hamiltonian of the system, leading to a revival of the initial state (Loschmidt echo). Here it is shown that Loschm...
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Proof Reduction of Fair Stuttering Refinement of Asynchronous Systems and Applications
We present a series of definitions and theorems demonstrating how to reduce the requirements for proving system refinements ensuring containment of fair stuttering runs. A primary result of the work is the ability to reduce the requisite proofs on runs of a system of interacting state machines to a set of definitions...
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Steady Galactic Dynamos and Observational Consequences I: Halo Magnetic Fields
We study the global consequences in the halos of spiral galaxies of the steady, axially symmetric, mean field dynamo. We use the classical theory but add the possibility of using the velocity field components as parameters in addition to the helicity and diffusivity. The analysis is based on the simplest version of t...
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Efficient Decision Trees for Multi-class Support Vector Machines Using Entropy and Generalization Error Estimation
We propose new methods for Support Vector Machines (SVMs) using tree architecture for multi-class classi- fication. In each node of the tree, we select an appropriate binary classifier using entropy and generalization error estimation, then group the examples into positive and negative classes based on the selected c...
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Semiclassical measures on hyperbolic surfaces have full support
We show that each limiting semiclassical measure obtained from a sequence of eigenfunctions of the Laplacian on a compact hyperbolic surface is supported on the entire cosphere bundle. The key new ingredient for the proof is the fractal uncertainty principle, first formulated in [arXiv:1504.06589] and proved for poro...
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Assessment of algorithms for computing moist available potential energy
Atmospheric moist available potential energy (MAPE) has been traditionally defined as the potential energy of a moist atmosphere relative to that of the adiabatically sorted reference state defining a global potential energy minimum. Finding such a reference state was recently shown to be a linear assignment problem,...
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A Zero Knowledge Sumcheck and its Applications
Many seminal results in Interactive Proofs (IPs) use algebraic techniques based on low-degree polynomials, the study of which is pervasive in theoretical computer science. Unfortunately, known methods for endowing such proofs with zero knowledge guarantees do not retain this rich algebraic structure. In this work, we...
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Exact diagonalization and cluster mean-field study of triangular-lattice XXZ antiferromagnets near saturation
Quantum magnetic phases near the magnetic saturation of triangular-lattice antiferromagnets with XXZ anisotropy have been attracting renewed interest since it has been suggested that a nontrivial coplanar phase, called the $\pi$-coplanar or $\Psi$ phase, could be stabilized by quantum effects in a certain range of an...
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Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions
We consider the problem of finding local minimizers in non-convex and non-smooth optimization. Under the assumption of strict saddle points, positive results have been derived for first-order methods. We present the first known results for the non-smooth case, which requires different analysis and a different algorit...
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Don't Panic! Better, Fewer, Syntax Errors for LR Parsers
Syntax errors are generally easy to fix for humans, but not for parsers, in general, and LR parsers, in particular. Traditional 'panic mode' error recovery, though easy to implement and applicable to any grammar, often leads to a cascading chain of errors that drown out the original. More advanced error recovery tech...
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Predicting Tomorrow's Headline using Today's Twitter Deliberations
Predicting the popularity of news article is a challenging task. Existing literature mostly focused on article contents and polarity to predict popularity. However, existing research has not considered the users' preference towards a particular article. Understanding users' preference is an important aspect for predi...
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On a problem of Bharanedhar and Ponnusamy involving planar harmonic mappings
In this paper, we give a negative answer to a problem presented by Bharanedhar and Ponnusamy (Rocky Mountain J. Math. 44: 753--777, 2014) concerning univalency of a class of harmonic mappings. More precisely, we show that for all values of the involved parameter, this class contains a non-univalent function. Moreover...
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Projecting UK Mortality using Bayesian Generalised Additive Models
Forecasts of mortality provide vital information about future populations, with implications for pension and health-care policy as well as for decisions made by private companies about life insurance and annuity pricing. Stochastic mortality forecasts allow the uncertainty in mortality predictions to be taken into co...
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The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning
Machine learning is usually defined in behaviourist terms, where external validation is the primary mechanism of learning. In this paper, I argue for a more holistic interpretation in which finding more probable, efficient and abstract representations is as central to learning as performance. In other words, machine ...
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Bulk viscosity model for near-equilibrium acoustic wave attenuation
Acoustic wave attenuation due to vibrational and rotational molecular relaxation, under simplifying assumptions of near-thermodynamic equilibrium and absence of molecular dissociations, can be accounted for by specifying a bulk viscosity coefficient $\mu_B$. In this paper, we propose a simple frequency-dependent bulk...
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A Lagrangian fluctuation-dissipation relation for scalar turbulence, III. Turbulent Rayleigh-Bénard convection
A Lagrangian fluctuation-dissipation relation has been derived in a previous work to describe the dissipation rate of advected scalars, both passive and active, in wall-bounded flows. We apply this relation here to develop a Lagrangian description of thermal dissipation in turbulent Rayleigh-Bénard convection in a ri...
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Model Selection for Explosive Models
This paper examines the limit properties of information criteria (such as AIC, BIC, HQIC) for distinguishing between the unit root model and the various kinds of explosive models. The explosive models include the local-to-unit-root model, the mildly explosive model and the regular explosive model. Initial conditions ...
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Deep Energy Estimator Networks
Density estimation is a fundamental problem in statistical learning. This problem is especially challenging for complex high-dimensional data due to the curse of dimensionality. A promising solution to this problem is given here in an inference-free hierarchical framework that is built on score matching. We revisit t...
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A Scale Free Algorithm for Stochastic Bandits with Bounded Kurtosis
Existing strategies for finite-armed stochastic bandits mostly depend on a parameter of scale that must be known in advance. Sometimes this is in the form of a bound on the payoffs, or the knowledge of a variance or subgaussian parameter. The notable exceptions are the analysis of Gaussian bandits with unknown mean a...
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An Asynchronous Parallel Approach to Sparse Recovery
Asynchronous parallel computing and sparse recovery are two areas that have received recent interest. Asynchronous algorithms are often studied to solve optimization problems where the cost function takes the form $\sum_{i=1}^M f_i(x)$, with a common assumption that each $f_i$ is sparse; that is, each $f_i$ acts only...
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Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples
State-of-the-art neural networks are vulnerable to adversarial examples; they can easily misclassify inputs that are imperceptibly different than their training and test data. In this work, we establish that the use of cross-entropy loss function and the low-rank features of the training data have responsibility for ...
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Parametrizing modified gravity for cosmological surveys
One of the challenges in testing gravity with cosmology is the vast freedom opened when extending General Relativity. For linear perturbations, one solution consists in using the Effective Field Theory of Dark Energy (EFT of DE). Even then, the theory space is described in terms of a handful of free functions of time...
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Inductive Freeness of Ziegler's Canonical Multiderivations for Reflection Arrangements
Let $A$ be a free hyperplane arrangement. In 1989, Ziegler showed that the restriction $A''$ of $A$ to any hyperplane endowed with the natural multiplicity is then a free multiarrangement. We initiate a study of the stronger freeness property of inductive freeness for these canonical free multiarrangements and invest...
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Toward III-V/Si co-integration by controlling biatomic steps on hydrogenated Si(001)
The integration of III-V on silicon is still a hot topic as it will open up a way to co-integrate Si CMOS logic with photonic vices. To reach this aim, several hurdles should be solved, and more particularly the generation of antiphase boundaries (APBs) at the III-V/Si(001) interface. Density functional theory (DFT) ...
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Proceedings XVI Jornadas sobre Programación y Lenguajes
This volume contains a selection of the papers presented at the XVI Jornadas sobre Programación y Lenguajes (PROLE 2016), held at Salamanca, Spain, during September 14th-15th, 2016. Previous editions of the workshop were held in Santander (2015), Cádiz (2014), Madrid (2013), Almería (2012), A Coruña (2011), València ...
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The proximal point algorithm in geodesic spaces with curvature bounded above
We investigate the asymptotic behavior of sequences generated by the proximal point algorithm for convex functions in complete geodesic spaces with curvature bounded above. Using the notion of resolvents of such functions, which was recently introduced by the authors, we show the existence of minimizers of convex fun...
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Spatio-temporal canards in neural field equations
Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially-extended s...
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Counterfactuals, indicative conditionals, and negation under uncertainty: Are there cross-cultural differences?
In this paper we study selected argument forms involving counterfactuals and indicative conditionals under uncertainty. We selected argument forms to explore whether people with an Eastern cultural background reason differently about conditionals compared to Westerners, because of the differences in the location of n...
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Efficient Convolutional Network Learning using Parametric Log based Dual-Tree Wavelet ScatterNet
We propose a DTCWT ScatterNet Convolutional Neural Network (DTSCNN) formed by replacing the first few layers of a CNN network with a parametric log based DTCWT ScatterNet. The ScatterNet extracts edge based invariant representations that are used by the later layers of the CNN to learn high-level features. This impro...
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The $r$th moment of the divisor function: an elementary approach
Let $\tau(n)$ be the number of divisors of $n$. We give an elementary proof of the fact that $$ \sum_{n\le x} \tau(n)^r =xC_{r} (\log x)^{2^r-1}+O(x(\log x)^{2^r-2}), $$ for any integer $r\ge 2$. Here, $$ C_{r}=\frac{1}{(2^r-1)!} \prod_{p\ge 2}\left( \left(1-\frac{1}{p}\right)^{2^r} \left(\sum_{\alpha\ge 0} \frac{(\a...
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Liu-type Shrinkage Estimations in Linear Models
In this study, we present the preliminary test, Stein-type and positive part Liu estimators in the linear models when the parameter vector $\boldsymbol{\beta}$ is partitioned into two parts, namely, the main effects $\boldsymbol{\beta}_1$ and the nuisance effects $\boldsymbol{\beta}_2$ such that $\boldsymbol{\beta}=\...
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Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds
We present an efficient coresets-based neural network compression algorithm that provably sparsifies the parameters of a trained fully-connected neural network in a manner that approximately preserves the network's output. Our approach is based on an importance sampling scheme that judiciously defines a sampling dist...
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Active Galactic Nuclei: what's in a name?
Active Galactic Nuclei (AGN) are energetic astrophysical sources powered by accretion onto supermassive black holes in galaxies, and present unique observational signatures that cover the full electromagnetic spectrum over more than twenty orders of magnitude in frequency. The rich phenomenology of AGN has resulted i...
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Fixed points of Legendre-Fenchel type transforms
A recent result characterizes the fully order reversing operators acting on the class of lower semicontinuous proper convex functions in a real Banach space as certain linear deformations of the Legendre-Fenchel transform. Motivated by the Hilbert space version of this result and by the well-known result saying that ...
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High-Dimensional Materials and Process Optimization using Data-driven Experimental Design with Well-Calibrated Uncertainty Estimates
The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and error, and luck. We propose a methodology that can accelerate this process by fitting data-driven models to experimental data as it is co...
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Two Posets of Noncrossing Partitions Coming From Undesired Parking Spaces
Consider the noncrossing set partitions of an $n$-element set which either do not contain the block $\{n-1,n\}$, or which do not contain the singleton block $\{n\}$ whenever $1$ and $n-1$ are in the same block. In this article we study the subposet of the noncrossing partition lattice induced by these elements, and s...
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Semi-supervised model-based clustering with controlled clusters leakage
In this paper, we focus on finding clusters in partially categorized data sets. We propose a semi-supervised version of Gaussian mixture model, called C3L, which retrieves natural subgroups of given categories. In contrast to other semi-supervised models, C3L is parametrized by user-defined leakage level, which contr...
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Local White Matter Architecture Defines Functional Brain Dynamics
Large bundles of myelinated axons, called white matter, anatomically connect disparate brain regions together and compose the structural core of the human connectome. We recently proposed a method of measuring the local integrity along the length of each white matter fascicle, termed the local connectome. If communic...
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An upper bound on tricolored ordered sum-free sets
We present a strengthening of the lemma on the lower bound of the slice rank by Tao (2016) motivated by the Croot-Lev-Pach-Ellenberg-Gijswijt bound on cap sets (2017, 2017). The Croot-Lev-Pach-Ellenberg-Gijswijt method and the lemma of Tao are based on the fact that the rank of a diagonal matrix is equal to the numbe...
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The effect of the spatial domain in FANOVA models with ARH(1) error term
Functional Analysis of Variance (FANOVA) from Hilbert-valued correlated data with spatial rectangular or circular supports is analyzed, when Dirichlet conditions are assumed on the boundary. Specifically, a Hilbert-valued fixed effect model with error term defined from an Autoregressive Hilbertian process of order on...
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Audio to Body Dynamics
We present a method that gets as input an audio of violin or piano playing, and outputs a video of skeleton predictions which are further used to animate an avatar. The key idea is to create an animation of an avatar that moves their hands similarly to how a pianist or violinist would do, just from audio. Aiming for ...
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Detecting causal associations in large nonlinear time series datasets
Identifying causal relationships from observational time series data is a key problem in disciplines such as climate science or neuroscience, where experiments are often not possible. Data-driven causal inference is challenging since datasets are often high-dimensional and nonlinear with limited sample sizes. Here we...
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Controlling a remotely located Robot using Hand Gestures in real time: A DSP implementation
Telepresence is a necessity for present time as we can't reach everywhere and also it is useful in saving human life at dangerous places. A robot, which could be controlled from a distant location, can solve these problems. This could be via communication waves or networking methods. Also controlling should be in rea...
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Hybrid Machine Learning Approach to Popularity Prediction of Newly Released Contents for Online Video Streaming Service
In the industry of video content providers such as VOD and IPTV, predicting the popularity of video contents in advance is critical not only from a marketing perspective but also from a network optimization perspective. By predicting whether the content will be successful or not in advance, the content file, which is...
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Vaught's Two-Cardinal Theorem and Quasi-Minimality in Continuous Logic
We prove the following continuous analogue of Vaught's Two-Cardinal Theorem: if for some $\kappa>\lambda\geq \aleph_0$, a continuous theory $T$ has a model with density character $\kappa$ which has a definable subset of density character $\lambda$, then $T$ has a model with density character $\aleph_1$ which has a se...
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Spectral Calibration of the Fluorescence Telescopes of the Pierre Auger Observatory
We present a novel method to measure precisely the relative spectral response of the fluorescence telescopes of the Pierre Auger Observatory. We used a portable light source based on a xenon flasher and a monochromator to measure the relative spectral efficiencies of eight telescopes in steps of 5 nm from 280 nm to 4...
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Two properties of Müntz spaces
We show that Müntz spaces, as subspaces of $C[0,1]$, contain asymptotically isometric copies of $c_0$ and that their dual spaces are octahedral.
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Rational approximations to the zeta function
This article describes a sequence of rational functions which converges locally uniformly to the zeta function. The numerators (and denominators) of these rational functions can be expressed as characteristic polynomials of matrices that are on the face of it very simple. As a consequence, the Riemann hypothesis can ...
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The COS-Halos Survey: Metallicities in the Low-Redshift Circumgalactic Medium
We analyze new far-ultraviolet spectra of 13 quasars from the z~0.2 COS-Halos survey that cover the HI Lyman limit of 14 circumgalactic medium (CGM) systems. These data yield precise estimates or more constraining limits than previous COS-Halos measurements on the HI column densities NHI. We then apply a Monte-Carlo ...
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On Quaternionic Tori and their Moduli Spaces
Quaternionic tori are defined as quotients of the skew field $\mathbb{H}$ of quaternions by rank-4 lattices. Using slice regular functions, these tori are endowed with natural structures of quaternionic manifolds (in fact quaternionic curves), and a fundamental region in a $12$-dimensional real subspace is then const...
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GIER: A Danish computer from 1961 with a role in the modern revolution of astronomy
A Danish computer, GIER, from 1961 played a vital role in the development of a new method for astrometric measurement. This method, photon counting astrometry, ultimately led to two satellites with a significant role in the modern revolution of astronomy. A GIER was installed at the Hamburg Observatory in 1964 where ...
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Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study
Several recent papers investigate Active Learning (AL) for mitigating the data dependence of deep learning for natural language processing. However, the applicability of AL to real-world problems remains an open question. While in supervised learning, practitioners can try many different methods, evaluating each agai...
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Analogy and duality between random channel coding and lossy source coding
Here we write in a unified fashion (using "R(P, Q, D)") the random coding exponents in channel coding and lossy source coding. We derive their explicit forms and show, that, for a given random codebook distribution Q, the channel decoding error exponent can be viewed as an encoding success exponent in lossy source co...
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Towards Bursting Filter Bubble via Contextual Risks and Uncertainties
A rising topic in computational journalism is how to enhance the diversity in news served to subscribers to foster exploration behavior in news reading. Despite the success of preference learning in personalized news recommendation, their over-exploitation causes filter bubble that isolates readers from opposing view...
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Nonlinear Loewy Factorizable Algebraic ODEs and Hayman's Conjecture
In this paper, we introduce certain $n$-th order nonlinear Loewy factorizable algebraic ordinary differential equations for the first time and study the growth of their meromorphic solutions in terms of the Nevanlinna characteristic function. It is shown that for generic cases all their meromorphic solutions are elli...
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Grounding Symbols in Multi-Modal Instructions
As robots begin to cohabit with humans in semi-structured environments, the need arises to understand instructions involving rich variability---for instance, learning to ground symbols in the physical world. Realistically, this task must cope with small datasets consisting of a particular users' contextual assignment...
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Morphometric analysis in gamma-ray astronomy using Minkowski functionals: II. Joint structure quantification
We pursue a novel morphometric analysis to detect sources in very-high-energy gamma-ray counts maps by structural deviations from the background noise. Because the Minkowski functionals from integral geometry quantify the shape of the counts map itself, the morphometric analysis includes unbiased structure informatio...
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An Event-based Fast Movement Detection Algorithm for a Positioning Robot Using POWERLINK Communication
This work develops a tracking system based on an event-based camera. A bioinspired filtering algorithm to reduce noise and transmitted data while keeping the main features at the scene is implemented in FPGA which also serves as a network node. POWERLINK IEEE 61158 industrial network is used to communicate the FPGA w...
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$\textsf{S}^3T$: An Efficient Score-Statistic for Spatio-Temporal Surveillance
We present an efficient score statistic, called the $\textsf{S}^3 \textsf{T}$ statistic, to detect the emergence of a spatially and temporally correlated signal from either fixed-sample or sequential data. The signal may cause a men shift and/or a change in the covariance structure. The score statistic can capture bo...
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Relaxing Integrity Requirements for Attack-Resilient Cyber-Physical Systems
The increase in network connectivity has also resulted in several high-profile attacks on cyber-physical systems. An attacker that manages to access a local network could remotely affect control performance by tampering with sensor measurements delivered to the controller. Recent results have shown that with network-...
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Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content
With the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks. The multimedia information usually makes rumors look more convincing. Therefore, finding an automatic approach to verify rumors with multimedia content is a pressing task. Previous rumor ver...
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Convergence of the Kähler-Ricci iteration
The Ricci iteration is a discrete analogue of the Ricci flow. According to Perelman, the Ricci flow converges to a Kahler-Einstein metric whenever one exists, and it has been conjectured that the Ricci iteration should behave similarly. This article confirms this conjecture. As a special case, this gives a new method...
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Joint estimation of genetic and parent-of-origin effects using RNA-seq data from human
RNA sequencing allows one to study allelic imbalance of gene expression, which may be due to genetic factors or genomic imprinting. It is desirable to model both genetic and parent-of-origin effects simultaneously to avoid confounding and to improve the power to detect either effect. In a study of experimental cross,...
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Consistency Analysis for Massively Inconsistent Datasets in Bound-to-Bound Data Collaboration
Bound-to-Bound Data Collaboration (B2BDC) provides a natural framework for addressing both forward and inverse uncertainty quantification problems. In this approach, QOI (quantity of interest) models are constrained by related experimental observations with interval uncertainty. A collection of such models and observ...
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Hydra: a C++11 framework for data analysis in massively parallel platforms
Hydra is a header-only, templated and C++11-compliant framework designed to perform the typical bottleneck calculations found in common HEP data analyses on massively parallel platforms. The framework is implemented on top of the C++11 Standard Library and a variadic version of the Thrust library and is designed to r...
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Analysis of dropout learning regarded as ensemble learning
Deep learning is the state-of-the-art in fields such as visual object recognition and speech recognition. This learning uses a large number of layers, huge number of units, and connections. Therefore, overfitting is a serious problem. To avoid this problem, dropout learning is proposed. Dropout learning neglects some...
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Spatially-resolved Brillouin spectroscopy reveals biomechanical changes in early ectatic corneal disease and post-crosslinking in vivo
Mounting evidence connects the biomechanical properties of tissues to the development of eye diseases such as keratoconus, a common disease in which the cornea thins and bulges into a conical shape. However, measuring biomechanical changes in vivo with sufficient sensitivity for disease detection has proved challengi...
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Combining Symbolic Execution and Model Checking to Verify MPI Programs
Message Passing Interface (MPI) is the standard paradigm of programming in high performance computing. MPI programming takes significant effort, and is error-prone. Thus, effective tools for analyzing MPI programs are much needed. On the other hand, analyzing MPI programs itself is challenging because of non-determin...
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An Improved Modified Cholesky Decomposition Method for Inverse Covariance Matrix Estimation
The modified Cholesky decomposition is commonly used for inverse covariance matrix estimation given a specified order of random variables. However, the order of variables is often not available or cannot be pre-determined. Hence, we propose a novel estimator to address the variable order issue in the modified Cholesk...
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Self-exciting Point Processes: Infections and Implementations
This is a comment on Reinhart's "Review of Self-Exciting Spatio-Temporal Point Processes and Their Applications" (arXiv:1708.02647v1). I contribute some experiences from modelling the spread of infectious diseases. Furthermore, I try to complement the review with regard to the availability of software for the describ...
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Magnetism and charge density waves in RNiC$_2$ (R = Ce, Pr, Nd)
We have compared the magnetic, transport, galvanomagnetic and specific heat properties of CeNiC$_2$, PrNiC$_2$ and NdNiC$_2$ to study the interplay between charge density waves and magnetism in these compounds. The negative magnetoresistance in NdNiC$_2$ is discussed in terms of the partial destruction of charge dens...
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Conjoined constraints on modified gravity from the expansion history and cosmic growth
In this paper we present conjoined constraints on several cosmological models from the expansion history $H(z)$ and cosmic growth $f\sigma_8(z)$. The models we study include the CPL $w_0w_a$ parametrization, the Holographic Dark Energy (HDE) model, the Time varying vacuum ($\Lambda_t$CDM) model, the Dvali, Gabadadze ...
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Coaxial collisions of a vortex ring and a sphere in an inviscid incompressible fluid
The dynamics of a circular thin vortex ring and a sphere moving along the symmetry axis of the ring in an inviscid incompressible fluid is studied on the basis of Euler's equations of motion. The equations of motion for position and radius of the vortex ring and those for position and velocity of the sphere are coupl...
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Cosmic viscosity as a remedy for tension between PLANCK and LSS data
Measurements of $\sigma_8$ from large scale structure observations show a discordance with the extrapolated $\sigma_8$ from Planck CMB parameters using $\Lambda$CDM cosmology. Similar discordance is found in the value of $H_0$ and $\Omega_m$. In this paper, we show that the presence of viscosity in cold dark matter, ...
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A probabilistic approach to emission-line galaxy classification
We invoke a Gaussian mixture model (GMM) to jointly analyse two traditional emission-line classification schemes of galaxy ionization sources: the Baldwin-Phillips-Terlevich (BPT) and $\rm W_{H\alpha}$ vs. [NII]/H$\alpha$ (WHAN) diagrams, using spectroscopic data from the Sloan Digital Sky Survey Data Release 7 and S...
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Quantum repeaters with individual rare-earth ions at telecommunication wavelengths
We present a quantum repeater scheme that is based on individual erbium and europium ions. Erbium ions are attractive because they emit photons at telecommunication wavelength, while europium ions offer exceptional spin coherence for long-term storage. Entanglement between distant erbium ions is created by photon det...
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Questions and dependency in intuitionistic logic
In recent years, the logic of questions and dependencies has been investigated in the closely related frameworks of inquisitive logic and dependence logic. These investigations have assumed classical logic as the background logic of statements, and added formulas expressing questions and dependencies to this classica...
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Translations: generalizing relative expressiveness between logics
There is a strong demand for precise means for the comparison of logics in terms of expressiveness both from theoretical and from application areas. The aim of this paper is to propose a sufficiently general and reasonable formal criterion for expressiveness, so as to apply not only to model-theoretic logics, but als...
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Learning Aided Optimization for Energy Harvesting Devices with Outdated State Information
This paper considers utility optimal power control for energy harvesting wireless devices with a finite capacity battery. The distribution information of the underlying wireless environment and harvestable energy is unknown and only outdated system state information is known at the device controller. This scenario sh...
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Absence of long range order in the frustrated magnet SrDy$_2$O$_4$ due to trapped defects from a dimensionality crossover
Magnetic frustration and low dimensionality can prevent long range magnetic order and lead to exotic correlated ground states. SrDy$_2$O$_4$ consists of magnetic Dy$^{3+}$ ions forming magnetically frustrated zig-zag chains along the c-axis and shows no long range order to temperatures as low as $T=60$ mK. We carried...
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A class of multi-resolution approximations for large spatial datasets
Gaussian processes are popular and flexible models for spatial, temporal, and functional data, but they are computationally infeasible for large datasets. We discuss Gaussian-process approximations that use basis functions at multiple resolutions to achieve fast inference and that can (approximately) represent any sp...
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Origin of Operating Voltage Increase in InGaN-based Light-emitting Diodes under High Injection: Phase Space Filling Effect on Forward Voltage Characteristics
As an attempt to further elucidate the operating voltage increase in InGaN-based light-emitting diodes (LEDs), the radiative and nonradiative current components are separately analyzed in combination with the Shockley diode equation. Through the analyses, we have shown that the increase in operating voltage is caused...
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Emergence of Selective Invariance in Hierarchical Feed Forward Networks
Many theories have emerged which investigate how in- variance is generated in hierarchical networks through sim- ple schemes such as max and mean pooling. The restriction to max/mean pooling in theoretical and empirical studies has diverted attention away from a more general way of generating invariance to nuisance t...
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Virtual retraction and Howson's theorem in pro-$p$ groups
We show that for every finitely generated closed subgroup $K$ of a non-solvable Demushkin group $G$, there exists an open subgroup $U$ of $G$ containing $K$, and a continuous homomorphism $\tau \colon U \to K$ satisfying $\tau(k) = k$ for every $k \in K$. We prove that the intersection of a pair of finitely generated...
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Convolutional Dictionary Learning: A Comparative Review and New Algorithms
Convolutional sparse representations are a form of sparse representation with a dictionary that has a structure that is equivalent to convolution with a set of linear filters. While effective algorithms have recently been developed for the convolutional sparse coding problem, the corresponding dictionary learning pro...
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Replication Ethics
Suppose some future technology enables the same consciously experienced human life to be repeated, identically or nearly so, N times, in series or in parallel. Is this roughly N times as valuable as enabling the same life once, because each life has value and values are additive? Or is it of roughly equal value as en...
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PSYM-WIDE: a survey for large-separation planetary-mass companions to late spectral type members of young moving groups
We present the results of a direct-imaging survey for very large separation ($>$100 au), companions around 95 nearby young K5-L5 stars and brown dwarfs. They are high-likelihood candidates or confirmed members of the young ($\lessapprox$150 Myr) $\beta$ Pictoris and AB Doradus moving groups (ABDMG) and the TW Hya, Tu...
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Boolean dimension and tree-width
The dimension is a key measure of complexity of partially ordered sets. Small dimension allows succinct encoding. Indeed if $P$ has dimension $d$, then to know whether $x \leq y$ in $P$ it is enough to check whether $x\leq y$ in each of the $d$ linear extensions of a witnessing realizer. Focusing on the encoding aspe...
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Drawing Planar Graphs with Few Geometric Primitives
We define the \emph{visual complexity} of a plane graph drawing to be the number of basic geometric objects needed to represent all its edges. In particular, one object may represent multiple edges (e.g., one needs only one line segment to draw a path with an arbitrary number of edges). Let $n$ denote the number of v...
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On the nature of the candidate T-Tauri star V501 Aurigae
We report new multi-colour photometry and high-resolution spectroscopic observations of the long-period variable V501 Aur, previously considered to be a weak-lined T-Tauri star belonging to the Taurus-Auriga star-forming region. The spectroscopic observations reveal that V501 Aur is a single-lined spectroscopic binar...
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3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks
The success of various applications including robotics, digital content creation, and visualization demand a structured and abstract representation of the 3D world from limited sensor data. Inspired by the nature of human perception of 3D shapes as a collection of simple parts, we explore such an abstract shape repre...
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Counting the number of distinct distances of elements in valued field extensions
The defect of valued field extensions is a major obstacle in open problems in resolution of singularities and in the model theory of valued fields, whenever positive characteristic is involved. We continue the detailed study of defect extensions through the tool of distances, which measure how well an element in an i...
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On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
Neural networks are known to be vulnerable to adversarial examples. In this note, we evaluate the two white-box defenses that appeared at CVPR 2018 and find they are ineffective: when applying existing techniques, we can reduce the accuracy of the defended models to 0%.
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