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Labeled Memory Networks for Online Model Adaptation
Augmenting a neural network with memory that can grow without growing the number of trained parameters is a recent powerful concept with many exciting applications. We propose a design of memory augmented neural networks (MANNs) called Labeled Memory Networks (LMNs) suited for tasks requiring online adaptation in cla...
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Perturbative approach to weakly driven many-particle systems in the presence of approximate conservation laws
We develop a Liouville perturbation theory for weakly driven and weakly open quantum systems in situations when the unperturbed system has a number of conservations laws. If the perturbation violates the conservation laws, it drives the system to a new steady state which can be approximately but efficiently described...
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Smart Mining for Deep Metric Learning
To solve deep metric learning problems and producing feature embeddings, current methodologies will commonly use a triplet model to minimise the relative distance between samples from the same class and maximise the relative distance between samples from different classes. Though successful, the training convergence ...
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Quantum phase transitions of a generalized compass chain with staggered Dzyaloshinskii-Moriya interaction
We consider a class of one-dimensional compass models with staggered Dzyaloshinskii-Moriya exchange interactions in an external transverse magnetic field. Based on the exact solution derived from Jordan-Wigner approach, we study the excitation gap, energy spectra, spin correlations and critical properties at phase tr...
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A blowup algebra of hyperplane arrangements
It is shown that the Orlik-Terao algebra is graded isomorphic to the special fiber of the ideal $I$ generated by the $(n-1)$-fold products of the members of a central arrangement of size $n$. This momentum is carried over to the Rees algebra (blowup) of $I$ and it is shown that this algebra is of fiber-type and Cohen...
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Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach
We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems. Classification networks are only responsive to small and sparse discriminative regions from the object of interest, which deviates from the ...
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Streaming Binary Sketching based on Subspace Tracking and Diagonal Uniformization
In this paper, we address the problem of learning compact similarity-preserving embeddings for massive high-dimensional streams of data in order to perform efficient similarity search. We present a new online method for computing binary compressed representations -sketches- of high-dimensional real feature vectors. G...
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Improving hot-spot pressure for ignition in high-adiabat Inertial Confinement Fusion implosion
A novel capsule target design to improve the hot-spot pressure in the high-adiabat implosion for inertial confinement fusion is proposed, where a layer of comparatively high-density material is used as a pusher between the fuel and the ablator. This design is based on our theoretical finding of the stagnation scaling...
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Cell-to-cell variation sets a tissue-rheology-dependent bound on collective gradient sensing
When a single cell senses a chemical gradient and chemotaxes, stochastic receptor-ligand binding can be a fundamental limit to the cell's accuracy. For clusters of cells responding to gradients, however, there is a critical difference: even genetically identical cells have differing responses to chemical signals. Wit...
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Languages of Play: Towards semantic foundations for game interfaces
Formal models of games help us account for and predict behavior, leading to more robust and innovative designs. While the games research community has proposed many formalisms for both the "game half" (game models, game description languages) and the "human half" (player modeling) of a game experience, little attenti...
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Hybrid Normed Ideal Perturbations of n-tuples of Operators I
In hybrid normed ideal perturbations of $n$-tuples of operators, the normed ideal is allowed to vary with the component operators. We begin extending to this setting the machinery we developed for normed ideal perturbations based on the modulus of quasicentral approximation and an adaptation of our non-commutative ge...
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Global behaviour of radially symmetric solutions stable at infinity for gradient systems
This paper is concerned with radially symmetric solutions of systems of the form \[ u_t = -\nabla V(u) + \Delta_x u \] where space variable $x$ and and state-parameter $u$ are multidimensional, and the potential $V$ is coercive at infinity. For such systems, under generic assumptions on the potential, the asymptotic ...
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On the Total Forcing Number of a Graph
Let $G$ be a simple and finite graph without isolated vertices. In this paper we study forcing sets (zero forcing sets) which induce a subgraph of $G$ without isolated vertices. Such a set is called a total forcing set, introduced and first studied by Davila \cite{Davila}. The minimum cardinality of a total forcing s...
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Brief Notes on Hard Takeoff, Value Alignment, and Coherent Extrapolated Volition
I make some basic observations about hard takeoff, value alignment, and coherent extrapolated volition, concepts which have been central in analyses of superintelligent AI systems.
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Convolutional Neural Networks In Classifying Cancer Through DNA Methylation
DNA Methylation has been the most extensively studied epigenetic mark. Usually a change in the genotype, DNA sequence, leads to a change in the phenotype, observable characteristics of the individual. But DNA methylation, which happens in the context of CpG (cytosine and guanine bases linked by phosphate backbone) di...
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Persistent Monitoring of Dynamically Changing Environments Using an Unmanned Vehicle
We consider the problem of planning a closed walk $\mathcal W$ for a UAV to persistently monitor a finite number of stationary targets with equal priorities and dynamically changing properties. A UAV must physically visit the targets in order to monitor them and collect information therein. The frequency of monitorin...
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Almost sharp nonlinear scattering in one-dimensional Born-Infeld equations arising in nonlinear Electrodynamics
We study decay of small solutions of the Born-Infeld equation in 1+1 dimensions, a quasilinear scalar field equation modeling nonlinear electromagnetism, as well as branes in String theory and minimal surfaces in Minkowski space-times. From the work of Whitham, it is well-known that there is no decay because of arbit...
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Life efficiency does not always increase with the dissipation rate
There does not exist a general positive correlation between important life-supporting properties and the entropy production rate. The simple reason is that nondissipative and time-symmetric kinetic aspects are also relevant for establishing optimal functioning. In fact those aspects are even crucial in the nonlinear ...
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Molecular simulations of entangled defect structures around nanoparticles in nematic liquid crystals
We investigate the defect structures forming around two nanoparticles in a Gay-Berne nematic liquid crystal using molecular simulations. For small separations, disclinations entangle both particles forming the figure of eight, the figure of omega and the figure of theta. These defect structures are similar in shape a...
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Quasi Maximum-Likelihood Estimation of Dynamic Panel Data Models
This paper establishes the almost sure convergence and asymptotic normality of levels and differenced quasi maximum-likelihood (QML) estimators of dynamic panel data models. The QML estimators are robust with respect to initial conditions, conditional and time-series heteroskedasticity, and misspecification of the lo...
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Disunited Nations? A Multiplex Network Approach to Detecting Preference Affinity Blocs using Texts and Votes
This paper contributes to an emerging literature that models votes and text in tandem to better understand polarization of expressed preferences. It introduces a new approach to estimate preference polarization in multidimensional settings, such as international relations, based on developments in the natural languag...
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Magnetic phase diagram of the iron pnictides in the presence of spin-orbit coupling: Frustration between $C_2$ and $C_4$ magnetic phases
We investigate the impact of spin anisotropic interactions, promoted by spin-orbit coupling, on the magnetic phase diagram of the iron-based superconductors. Three distinct magnetic phases with Bragg peaks at $(\pi,0)$ and $(0,\pi)$ are possible in these systems: one $C_2$ (i.e. orthorhombic) symmetric stripe magneti...
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Algorithms and Bounds for Very Strong Rainbow Coloring
A well-studied coloring problem is to assign colors to the edges of a graph $G$ so that, for every pair of vertices, all edges of at least one shortest path between them receive different colors. The minimum number of colors necessary in such a coloring is the strong rainbow connection number ($\src(G)$) of the graph...
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Quantile function expansion using regularly varying functions
We present a simple result that allows us to evaluate the asymptotic order of the remainder of a partial asymptotic expansion of the quantile function $h(u)$ as $u\to 0^+$ or $1^-$. This is focussed on important univariate distributions when $h(\cdot)$ has no simple closed form, with a view to assessing asymptotic ra...
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Identification of Key Proteins Involved in Axon Guidance Related Disorders: A Systems Biology Approach
Axon guidance is a crucial process for growth of the central and peripheral nervous systems. In this study, 3 axon guidance related disorders, namely- Duane Retraction Syndrome (DRS) , Horizontal Gaze Palsy with Progressive Scoliosis (HGPPS) and Congenital fibrosis of the extraocular muscles type 3 (CFEOM3) were stud...
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Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization
Motivated by applications in Game Theory, Optimization, and Generative Adversarial Networks, recent work of Daskalakis et al~\cite{DISZ17} and follow-up work of Liang and Stokes~\cite{LiangS18} have established that a variant of the widely used Gradient Descent/Ascent procedure, called "Optimistic Gradient Descent/As...
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The Lifetimes of Phases in High-Mass Star-Forming Regions
High-mass stars form within star clusters from dense, molecular regions, but is the process of cluster formation slow and hydrostatic or quick and dynamic? We link the physical properties of high-mass star-forming regions with their evolutionary stage in a systematic way, using Herschel and Spitzer data. In order to ...
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Null controllability of a population dynamics with interior degeneracy
In this paper, we deal with the null controllability of a population dynamics model with an interior degenerate diffusion. To this end, we proved first a new Carleman estimate for the full adjoint system and afterwards we deduce a suitable observability inequality which will be needed to establish the existence of a ...
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ICLR Reproducibility Challenge Report (Padam : Closing The Generalization Gap Of Adaptive Gradient Methods in Training Deep Neural Networks)
This work is a part of ICLR Reproducibility Challenge 2019, we try to reproduce the results in the conference submission PADAM: Closing The Generalization Gap of Adaptive Gradient Methods In Training Deep Neural Networks. Adaptive gradient methods proposed in past demonstrate a degraded generalization performance tha...
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Robust Bayes-Like Estimation: Rho-Bayes estimation
We consider the problem of estimating the joint distribution $P$ of $n$ independent random variables within the Bayes paradigm from a non-asymptotic point of view. Assuming that $P$ admits some density $s$ with respect to a given reference measure, we consider a density model $\overline S$ for $s$ that we endow with ...
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Nonlinear demixed component analysis for neural population data as a low-rank kernel regression problem
Here I introduce an extension to demixed principal component analysis (dPCA), a linear dimensionality reduction technique for analyzing the activity of neural populations, to the case of nonlinear dimensions. This is accomplished using kernel methods, resulting in kernel demixed principal component analysis (kdPCA). ...
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Stability of semi-wavefronts for delayed reaction-diffusion equations
This paper deals with the asymptotic behavior of solutions to the delayed monostable equation: $(*)$ $u_{t}(t,x) = u_{xx}(t,x) - u(t,x) + g(u(t-h,x)),$ $x \in \mathbb{R},\ t >0,$ where $h>0$ and the reaction term $g: \mathbb{R}_+ \to \mathbb{R}_+$ has exactly two fixed points (zero and $\kappa >0$). Under certain con...
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An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning
We propose an end-to-end approach to the natural language object retrieval task, which localizes an object within an image according to a natural language description, i.e., referring expression. Previous works divide this problem into two independent stages: first, compute region proposals from the image without the...
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Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction
With access to large datasets, deep neural networks (DNN) have achieved human-level accuracy in image and speech recognition tasks. However, in chemistry, data is inherently small and fragmented. In this work, we develop an approach of using rule-based knowledge for training ChemNet, a transferable and generalizable ...
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Intelligent Sensor Based Bayesian Neural Network for Combined Parameters and States Estimation of a Brushed DC Motor
The objective of this paper is to develop an Artificial Neural Network (ANN) model to estimate simultaneously, parameters and state of a brushed DC machine. The proposed ANN estimator is novel in the sense that his estimates simultaneously temperature, speed and rotor resistance based only on the measurement of the v...
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The infinite Fibonacci groups and relative asphericity
We prove that the generalised Fibonacci group F(r,n) is infinite for (r,n) in {(7 + 5k,5), (8 + 5k,5)} where k is greater than or equal to 0. This together with previously known results yields a complete classification of the finite F(r,n), a problem that has its origins in a question by J H Conway in 1965. The metho...
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Representations of Polynomial Rota-Baxter Algebras
A Rota--Baxter operator is an algebraic abstraction of integration, which is the typical example of a weight zero Rota-Baxter operator. We show that studying the modules over the polynomial Rota--Baxter algebra $(k[x],P)$ is equivalent to studying the modules over the Jordan plane, and we generalize the direct decomp...
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The extended ROSAT-ESO Flux-Limited X-ray Galaxy Cluster Survey (REFLEX II) VII The Mass Function of Galaxy Clusters
The mass function of galaxy clusters is a sensitive tracer of the gravitational evolution of the cosmic large-scale structure and serves as an important census of the fraction of matter bound in large structures. We obtain the mass function by fitting the observed cluster X-ray luminosity distribution from the REFLEX...
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An Optimized Pattern Recognition Algorithm for Anomaly Detection in IoT Environment
With the advent of large-scale heterogeneous search engines comes the problem of unified search control resulting in mismatches that could have otherwise avoided. A mechanism is needed to determine exact patterns in web mining and ubiquitous device searching. In this paper we demonstrate the use of an optimized strin...
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Uniform asymptotics as a stationary point approaches an endpoint
We obtain the rigorous uniform asymptotics of a particular integral where a stationary point is close to an endpoint. There exists a general method introduced by Bleistein for obtaining uniform asymptotics in this situation. However, this method does not provide rigorous estimates for the error. Indeed, the method of...
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An SDP-Based Algorithm for Linear-Sized Spectral Sparsification
For any undirected and weighted graph $G=(V,E,w)$ with $n$ vertices and $m$ edges, we call a sparse subgraph $H$ of $G$, with proper reweighting of the edges, a $(1+\varepsilon)$-spectral sparsifier if \[ (1-\varepsilon)x^{\intercal}L_Gx\leq x^{\intercal} L_{H} x\leq (1+\varepsilon) x^{\intercal} L_Gx \] holds for an...
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Self-Adjusting Threshold Mechanism for Pixel Detectors
Readout chips of hybrid pixel detectors use a low power amplifier and threshold discrimination to process charge deposited in semiconductor sensors. Due to transistor mismatch each pixel circuit needs to be calibrated individually to achieve response uniformity. Traditionally this is addressed by programmable thresho...
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Rotational inertia interface in a dynamic lattice of flexural beams
The paper presents a novel analysis of a transmission problem for a network of flexural beams incorporating conventional Euler-Bernoulli beams as well as Rayleigh beams with the enhanced rotational inertia. Although, in the low-frequency regime, these beams have a similar dynamic response, we have demonstrated novel ...
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Low-frequency wide band-gap elastic/acoustic meta-materials using the K-damping concept
The terms "acoustic/elastic meta-materials" describe a class of periodic structures with unit cells exhibiting local resonance. This localized resonant structure has been shown to result in negative effective stiffness and/or mass at frequency ranges close to these local resonances. As a result, these structures pres...
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Inertia-Constrained Pixel-by-Pixel Nonnegative Matrix Factorisation: a Hyperspectral Unmixing Method Dealing with Intra-class Variability
Blind source separation is a common processing tool to analyse the constitution of pixels of hyperspectral images. Such methods usually suppose that pure pixel spectra (endmembers) are the same in all the image for each class of materials. In the framework of remote sensing, such an assumption is no more valid in the...
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Warped Product Pointwise Semi-slant Submanifolds of Sasakian Manifolds
Recently, B.-Y. Chen and O. J. Garay studied pointwise slant submanifolds of almost Hermitian manifolds. By using this notion, we investigate pointwise semi-slant submanifolds and their warped products in Sasakian manifolds. We give non-trivial examples of such submanifolds and obtain several fundamental results, inc...
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Bayesian Semi-supervised Learning with Graph Gaussian Processes
We propose a data-efficient Gaussian process-based Bayesian approach to the semi-supervised learning problem on graphs. The proposed model shows extremely competitive performance when compared to the state-of-the-art graph neural networks on semi-supervised learning benchmark experiments, and outperforms the neural n...
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Knowledge Engineering for Hybrid Deductive Databases
Modern knowledge base systems frequently need to combine a collection of databases in different formats: e.g., relational databases, XML databases, rule bases, ontologies, etc. In the deductive database system DDBASE, we can manage these different formats of knowledge and reason about them. Even the file systems on d...
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Satisfiability Bounds for ω-regular Properties in Interval-valued Markov Chains
We derive an algorithm to compute satisfiability bounds for arbitrary {\omega}-regular properties in an Interval-valued Markov Chain (IMC) interpreted in the adversarial sense. IMCs generalize regular Markov Chains by assigning a range of possible values to the transition probabilities between states. In particular, ...
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On the relaxed mean-field stochastic control problem
This paper is concerned with optimal control problems for systems governed by mean-field stochastic differential equation, in which the control enters both the drift and the diffusion coefficient. We prove that the relaxed state process, associated with measure valued controls, is governed by an orthogonal martingale...
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A New Point-set Registration Algorithm for Fingerprint Matching
A novel minutia-based fingerprint matching algorithm is proposed that employs iterative global alignment on two minutia sets. The matcher considers all possible minutia pairings and iteratively aligns the two sets until the number of minutia pairs does not exceed the maximum number of allowable one-to-one pairings. T...
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A Faster Solution to Smale's 17th Problem I: Real Binomial Systems
Suppose $F:=(f_1,\ldots,f_n)$ is a system of random $n$-variate polynomials with $f_i$ having degree $\leq\!d_i$ and the coefficient of $x^{a_1}_1\cdots x^{a_n}_n$ in $f_i$ being an independent complex Gaussian of mean $0$ and variance $\frac{d_i!}{a_1!\cdots a_n!\left(d_i-\sum^n_{j=1}a_j \right)!}$. Recent progress ...
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Making compression algorithms for Unicode text
The majority of online content is written in languages other than English, and is most commonly encoded in UTF-8, the world's dominant Unicode character encoding. Traditional compression algorithms typically operate on individual bytes. While this approach works well for the single-byte ASCII encoding, it works poorl...
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Adaptive Exact Learning of Decision Trees from Membership Queries
In this paper we study the adaptive learnability of decision trees of depth at most $d$ from membership queries. This has many applications in automated scientific discovery such as drugs development and software update problem. Feldman solves the problem in a randomized polynomial time algorithm that asks $\tilde O(...
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Image denoising by median filter in wavelet domain
The details of an image with noise may be restored by removing noise through a suitable image de-noising method. In this research, a new method of image de-noising based on using median filter (MF) in the wavelet domain is proposed and tested. Various types of wavelet transform filters are used in conjunction with me...
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Restoration of Images with Wavefront Aberrations
This contribution deals with image restoration in optical systems with coherent illumination, which is an important topic in astronomy, coherent microscopy and radar imaging. Such optical systems suffer from wavefront distortions, which are caused by imperfect imaging components and conditions. Known image restoratio...
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Controlling the shape of membrane protein polyhedra
Membrane proteins and lipids can self-assemble into membrane protein polyhedral nanoparticles (MPPNs). MPPNs have a closed spherical surface and a polyhedral protein arrangement, and may offer a new route for structure determination of membrane proteins and targeted drug delivery. We develop here a general analytic m...
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Realizing uniformly recurrent subgroups
We show that every uniformly recurrent subgroup of a locally compact group is the family of stabilizers of a minimal action on a compact space. More generally, every closed invariant subset of the Chabauty space is the family of stabilizers of an action on a compact space on which the stabilizer map is continuous eve...
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A New Approximation Guarantee for Monotone Submodular Function Maximization via Discrete Convexity
In monotone submodular function maximization, approximation guarantees based on the curvature of the objective function have been extensively studied in the literature. However, the notion of curvature is often pessimistic, and we rarely obtain improved approximation guarantees, even for very simple objective functio...
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Electrode Reactions in Slowly Relaxing Media
Standard models of reaction kinetics in condensed materials rely on the Boltzmann-Gibbs distribution for the population of reactants at the top of the free energy barrier separating them from the products. While energy dissipation and quantum effects at the barrier top can potentially affect the transmission coeffici...
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End-to-end 3D face reconstruction with deep neural networks
Monocular 3D facial shape reconstruction from a single 2D facial image has been an active research area due to its wide applications. Inspired by the success of deep neural networks (DNN), we propose a DNN-based approach for End-to-End 3D FAce Reconstruction (UH-E2FAR) from a single 2D image. Different from recent wo...
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Entanglement of photons in their dual wave-particle nature
Wave-particle duality is the most fundamental description of the nature of a quantum object which behaves like a classical particle or wave depending on the measurement apparatus. On the other hand, entanglement represents nonclassical correlations of composite quantum systems, being also a key resource in quantum in...
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On Tensor Train Rank Minimization: Statistical Efficiency and Scalable Algorithm
Tensor train (TT) decomposition provides a space-efficient representation for higher-order tensors. Despite its advantage, we face two crucial limitations when we apply the TT decomposition to machine learning problems: the lack of statistical theory and of scalable algorithms. In this paper, we address the limitatio...
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Threshold fluctuations in a superconducting current-carrying bridge
We calculate the energy of threshold fluctuation $\delta F_{thr}$ which triggers the transition of superconducting current-carrying bridge to resistive state. We show that the dependence $\delta F_{thr}(I)\propto I_{dep}\hbar(1-I/I_{dep})^{5/4}/e$, found by Langer and Ambegaokar for a long bridge with length $L \gg \...
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Transient phenomena in a three-layer waveguide and the analytical structure of the dispersion diagram
Excitation of waves in a three-layer acoustic wavegide is studied. The wave field is presented as a sum of integrals. The summation is held over all waveguide modes. The integration is performed over the temporal frequency axis. The dispersion diagram of the waveguide is analytically continued, and the integral is tr...
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Introducing symplectic billiards
In this article we introduce a simple dynamical system called symplectic billiards. As opposed to usual/Birkhoff billiards, where length is the generating function, for symplectic billiards symplectic area is the generating function. We explore basic properties and exhibit several similarities, but also differences o...
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Banchoff's sphere and branched covers over the trefoil
A filling Dehn surface in a $3$-manifold $M$ is a generically immersed surface in $M$ that induces a cellular decomposition of $M$. Given a tame link $L$ in $M$ there is a filling Dehn sphere of $M$ that "trivializes" (\emph{diametrically splits}) it. This allows to construct filling Dehn surfaces in the coverings of...
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The Impact of Social Curiosity on Information Spreading on Networks
Most information spreading models consider that all individuals are identical psychologically. They ignore, for instance, the curiosity level of people, which may indicate that they can be influenced to seek for information given their interest. For example, the game Pokémon GO spread rapidly because of the aroused c...
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Decomposition of mean-field Gibbs distributions into product measures
We show that under a low complexity condition on the gradient of a Hamiltonian, Gibbs distributions on the Boolean hypercube are approximate mixtures of product measures whose probability vectors are critical points of an associated mean-field functional. This extends a previous work by the first author. As an applic...
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Analytic Discs and Uniform Algebras on Real-Analytic Varieties
Under very general conditions it is shown that if $A$ is a uniform algebra generated by real-analytic functions, then either $A$ consists of all continuous functions or else there exists a disc on which every function in $A$ is holomorphic. This strengthens several earlier results concerning uniform algebras generate...
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Novel solid state vacuum quartz encapsulated growth of p-Terphenyl: the parent High Tc Oraganic Superconductor (HTOS)
We report an easy and versatile route for the synthesis of the parent phase of newest superconducting wonder material i.e. p-Terphenyl. Doped p-terphenyl has recently shown superconductivity with transition temperature as high as 120K. For crystal growth, the commercially available p-Terphenyl powder is pelletized, e...
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Twistors from Killing Spinors alias Radiation from Pair Annihilation I: Theoretical Considerations
This paper is intended to be a further step through our Killing spinor programme started with Class. Quantum Grav. \textbf{32}, 175007 (2015), and we will advance our programme in accordance with the road map recently given in arXiv:1611.04424v2. In the latter reference many open problems were declared, one of which ...
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Table Space Designs For Implicit and Explicit Concurrent Tabled Evaluation
One of the main advantages of Prolog is its potential for the implicit exploitation of parallelism and, as a high-level language, Prolog is also often used as a means to explicitly control concurrent tasks. Tabling is a powerful implementation technique that overcomes some limitations of traditional Prolog systems in...
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Evidence for triplet superconductivity near an antiferromagnetic instability in CrAs
Superconductivity was recently observed in CrAs as the helimagnetic order is suppressed by applying pressure, suggesting possible unconventional superconductivity. To reveal the nature of the superconducting order parameter of CrAs, here we report the angular dependence of the upper critical field under pressure. Upo...
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Singlet ground state in the spin-$1/2$ weakly coupled dimer compound NH$_4$[(V$_2$O$_3$)$_2$(4,4$^\prime$-$bpy$)$_2$(H$_2$PO$_4$)(PO$_4$)$_2$]$\cdot$0.5H$_2$O
We present the synthesis and a detailed investigation of structural and magnetic properties of polycrystalline NH$_4$[(V$_2$O$_3$)$_2$(4,4$^\prime$-$bpy$)$_2$(H$_2$PO$_4$)(PO$_4$)$_2$]$\cdot$0.5H$_2$O by means of x-ray diffraction, magnetic susceptibility, electron spin resonance, and $^{31}$P nuclear magnetic resona...
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Deep learning bank distress from news and numerical financial data
In this paper we focus our attention on the exploitation of the information contained in financial news to enhance the performance of a classifier of bank distress. Such information should be analyzed and inserted into the predictive model in the most efficient way and this task deals with all the issues related to t...
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Theoretical studies of superconductivity in doped BaCoSO
We investigate superconductivity that may exist in the doped BaCoSO, a multi-orbital Mott insulator with a strong antiferromagnetic ground state. The superconductivity is studied in both t-J type and Hubbard type multi-orbital models by mean field approach and random phase approximation (RPA) analysis. Even if there ...
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On low for speed oracles
Relativizing computations of Turing machines to an oracle is a central concept in the theory of computation, both in complexity theory and in computability theory(!). Inspired by lowness notions from computability theory, Allender introduced the concept of "low for speed" oracles. An oracle A is low for speed if rela...
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$\mbox{Rb}_{2}\mbox{Ti}_2\mbox{O}_{5-δ}$: A superionic conductor with colossal dielectric constant
Electrical conductivity and high dielectric constant are in principle self-excluding, which makes the terms insulator and dielectric usually synonymous. This is certainly true when the electrical carriers are electrons, but not necessarily in a material where ions are extremely mobile, electronic conduction is neglig...
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LinNet: Probabilistic Lineup Evaluation Through Network Embedding
Which of your team's possible lineups has the best chances against each of your opponents possible lineups? In order to answer this question we develop LinNet. LinNet exploits the dynamics of a directed network that captures the performance of lineups at their matchups. The nodes of this network represent the differe...
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Observational Equivalence in System Estimation: Contractions in Complex Networks
Observability of complex systems/networks is the focus of this paper, which is shown to be closely related to the concept of contraction. Indeed, for observable network tracking it is necessary/sufficient to have one node in each contraction measured. Therefore, nodes in a contraction are equivalent to recover for lo...
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Incremental Adversarial Domain Adaptation for Continually Changing Environments
Continuous appearance shifts such as changes in weather and lighting conditions can impact the performance of deployed machine learning models. While unsupervised domain adaptation aims to address this challenge, current approaches do not utilise the continuity of the occurring shifts. In particular, many robotics ap...
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SAND: An automated VLBI imaging and analysing pipeline - I. Stripping component trajectories
We present our implementation of an automated VLBI data reduction pipeline dedicated to interferometric data imaging and analysis. The pipeline can handle massive VLBI data efficiently which makes it an appropriate tool to investigate multi-epoch multiband VLBI data. Compared to traditional manual data reduction, our...
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Quench-induced entanglement and relaxation dynamics in Luttinger liquids
We investigate the time evolution towards the asymptotic steady state of a one dimensional interacting system after a quantum quench. We show that at finite time the latter induces entanglement between right- and left- moving density excitations, encoded in their cross-correlators, which vanishes in the long-time lim...
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Coded Caching Schemes with Low Rate and Subpacketizations
Coded caching scheme, which is an effective technique to increase the transmission efficiency during peak traffic times, has recently become quite popular among the coding community. Generally rate can be measured to the transmission in the peak traffic times, i.e., this efficiency increases with the decreasing of ra...
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Multitask diffusion adaptation over networks with common latent representations
Online learning with streaming data in a distributed and collaborative manner can be useful in a wide range of applications. This topic has been receiving considerable attention in recent years with emphasis on both single-task and multitask scenarios. In single-task adaptation, agents cooperate to track an objective...
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Strong perpendicular magnetic anisotropy energy density at Fe alloy/HfO2 interfaces
We report on the perpendicular magnetic anisotropy (PMA) behavior of heavy metal (HM)/ Fe alloy/MgO thin film heterostructures after an ultrathin HfO2 passivation layer is inserted between the Fe alloy and the MgO. This is accomplished by depositing one to two atomic layers of Hf onto the Fe alloy before the subseque...
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Covering Groups of Nonconnected Topological Groups and 2-Groups
We investigate the universal cover of a topological group that is not necessarily connected. Its existence as a topological group is governed by a Taylor cocycle, an obstruction in 3-cohomology. Alternatively, it always exists as a topological 2-group. The splitness of this 2-group is also governed by an obstruction ...
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Polarization properties of turbulent synchrotron bubbles: an approach based on Chandrasekhar-Kendall functions
Synchrotron emitting bubbles arise when the outflow from a compact relativistic engine, either a Black Hole or a Neutron Star, impacts on the environment. The emission properties of synchrotron radiation are widely used to infer the dynamical properties of these bubbles, and from them the injection conditions of the ...
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Efimov Effect in the Dirac Semi-metals
Efimov effect refers to quantum states with discrete scaling symmetry and a universal scaling factor, and has attracted considerable interests from nuclear to atomic physics communities. In a Dirac semi-metal, when an electron interacts with a static impurity though a Coulomb interaction, the same scaling of the kine...
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Logic Lectures: Gödel's Basic Logic Course at Notre Dame
An edited version is given of the text of Gödel's unpublished manuscript of the notes for a course in basic logic he delivered at the University of Notre Dame in 1939. Gödel's notes deal with what is today considered as important logical problems par excellence, completeness, decidability, independence of axioms, and...
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Field dependent neutron diffraction study in Ni50Mn38Sb12 Heusler alloy
In this paper, we present temperature and field dependent neutron diffraction (ND) study to unravel the structural and the magnetic properties in Ni50Mn38Sb12 Heusler system. This alloy shows martensitic transition from high temperature austenite cubic phase to low temperature martensite orthorhombic phase on cooling...
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Optimistic lower bounds for convex regularized least-squares
Minimax lower bounds are pessimistic in nature: for any given estimator, minimax lower bounds yield the existence of a worst-case target vector $\beta^*_{worst}$ for which the prediction error of the given estimator is bounded from below. However, minimax lower bounds shed no light on the prediction error of the give...
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Continual Lifelong Learning with Neural Networks: A Review
Humans and animals have the ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. This ability, referred to as lifelong learning, is mediated by a rich set of neurocognitive mechanisms that together contribute to the development and specialization of our sensorimotor ...
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Potential kernel, hitting probabilities and distributional asymptotics
Z^d-extensions of probability-preserving dynamical systems are themselves dynamical systems preserving an infinite measure, and generalize random walks. Using the method of moments, we prove a generalized central limit theorem for additive functionals of the extension of integral zero, under spectral assumptions. As ...
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On the economics of electrical storage for variable renewable energy sources
The use of renewable energy sources is a major strategy to mitigate climate change. Yet Sinn (2017) argues that excessive electrical storage requirements limit the further expansion of variable wind and solar energy. We question, and alter, strong implicit assumptions of Sinn's approach and find that storage needs ar...
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Deep Learning in Customer Churn Prediction: Unsupervised Feature Learning on Abstract Company Independent Feature Vectors
As companies increase their efforts in retaining customers, being able to predict accurately ahead of time, whether a customer will churn in the foreseeable future is an extremely powerful tool for any marketing team. The paper describes in depth the application of Deep Learning in the problem of churn prediction. Us...
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Predicting and Discovering True Muonium
The recent observation of discrepancies in the muonic sector motivates searches for the yet undiscovered atom true muonium $(\mu^+\mu^-)$. To leverage potential experimental signals, precise theoretical calculations are required. I will present the on-going work to compute higher-order corrections to the hyperfine sp...
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Prediction of half-metallic properties in TlCrS2 and TlCrSe2 based on density functional theory
Half-metallic properties of TlCrS2, TlCrSe2 and hypothetical TlCrSSe have been investigated by first-principles all-electron full-potential linearized augmented plane wave plus local orbital (FP-LAPW+lo) method based on density functional theory (DFT). The results of calculations show that TlCrS2 and TlCrSSe are half...
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Giant interfacial perpendicular magnetic anisotropy in Fe/CuIn$_{1-x}$Ga$_x$Se$_2$ beyond Fe/MgO
We study interfacial magnetocrystalline anisotropies in various Fe/semiconductor heterostructures by means of first-principles calculations. We find that many of those systems show perpendicular magnetic anisotropy (PMA) with a positive value of the interfacial anisotropy constant $K_{\rm i}$. In particular, the Fe/C...
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