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Chaotic behavior in Casimir oscillators: A case study for phase change materials
Casimir forces between material surfaces at close proximity of less than 200 nm can lead to increased chaotic behavior of actuating devices depending on the strength of the Casimir interaction. We investigate these phenomena for phase change materials in torsional oscillators, where the amorphous to crystalline phase...
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Confluence in Probabilistic Rewriting
Driven by the interest of reasoning about probabilistic programming languages, we set out to study a notion of unicity of normal forms for them. To provide a tractable proof method for it, we define a property of distribution confluence which is shown to imply the desired uniqueness (even for infinite sequences of re...
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Structure preserving schemes for mean-field equations of collective behavior
In this paper we consider the development of numerical schemes for mean-field equations describing the collective behavior of a large group of interacting agents. The schemes are based on a generalization of the classical Chang-Cooper approach and are capable to preserve the main structural properties of the systems,...
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Localization optoacoustic tomography
Localization-based imaging has revolutionized fluorescence optical microscopy and has also enabled unprecedented ultrasound images of microvascular structures in deep tissues. Herein, we introduce a new concept of localization optoacoustic tomography (LOAT) that employs rapid sequential acquisition of three-dimension...
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Reduced-basis approach to many-body localization
Within the standard model of many-body localization, i.e., the disordered chain of spinless fermions, we investigate how the interaction affects the many-body states in the basis of noninteracting localized Anderson states. From this starting point we follow the approach that uses a reduced basis of many-body states....
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Electron-correlation study of Y III-Tc VII ions using a relativistic coupled-cluster theory
Spectroscopic properties, useful for plasma diagnostics and astrophysics, of a few rubidium-like ions are studied here. We choose one of the simplest, but correlationally challenging series where $d-$ and $f-$ orbitals are present in the core and/or valence shells with $4d$ $^2D_{3/2}$ as the ground state. We study d...
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Align and Copy: UZH at SIGMORPHON 2017 Shared Task for Morphological Reinflection
This paper presents the submissions by the University of Zurich to the SIGMORPHON 2017 shared task on morphological reinflection. The task is to predict the inflected form given a lemma and a set of morpho-syntactic features. We focus on neural network approaches that can tackle the task in a limited-resource setting...
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Krylov methods for low-rank commuting generalized Sylvester equations
We consider generalizations of the Sylvester matrix equation, consisting of the sum of a Sylvester operator and a linear operator $\Pi$ with a particular structure. More precisely, the commutator of the matrix coefficients of the operator $\Pi$ and the Sylvester operator coefficients are assumed to be matrices with l...
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Atomic-scale origin of dynamic viscoelastic response and creep in disordered solids
Viscoelasticity has been described since the time of Maxwell as an interpolation of purely viscous and purely elastic response, but its microscopic atomic-level mechanism in solids has remained elusive. We studied three model disordered solids: a random lattice, the bond-depleted fcc lattice, and the fcc lattice with...
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On-sky closed loop correction of atmospheric dispersion for high-contrast coronagraphy and astrometry
Adaptive optic (AO) systems delivering high levels of wavefront correction are now common at observatories. One of the main limitations to image quality after wavefront correction comes from atmospheric refraction. An Atmospheric dispersion compensator (ADC) is employed to correct for atmospheric refraction. The corr...
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Experimental observations and modelling of intrinsic rotation reversals in tokamaks
The progress made in understanding spontaneous toroidal rotation reversals in tokamaks is reviewed and current ideas to solve this ten-year-old puzzle are explored. The paper includes a summarial synthesis of the experimental observations in AUG, C-Mod, KSTAR, MAST and TCV tokamaks, reasons why turbulent momentum tra...
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Where, When, and How mmWave is Used in 5G and Beyon
Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but instead an integration of networks for vertical markets with diverse applications, answers...
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A simple script language for choreography of multiple, synchronizing non-anthropomorphic robots
The scripting language described in this document is (in the first place) intended to be used on robots developed by Anja M{\o}lle Lindelof and Henning Christiansen as part of a research project about robots performing on stage. The target robots are expected to appear as familiar domestic objects that take their own...
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Stability results for abstract evolution equations with intermittent time-delay feedback
We consider abstract evolution equations with on-off time delay feedback. Without the time delay term, the model is described by an exponentially stable semigroup. We show that, under appropriate conditions involving the delay term, the system remains asymptotically stable. Under additional assumptions exponential st...
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Solar wind turbulent cascade from MHD to sub-ion scales: large-size 3D hybrid particle-in-cell simulations
Spectral properties of the turbulent cascade from fluid to kinetic scales in collisionless plasmas are investigated by means of large-size three-dimensional (3D) hybrid (fluid electrons, kinetic protons) particle-in-cell simulations. Initially isotropic Alfvènic fluctuations rapidly develop a strongly anisotropic tur...
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Blind source separation of tensor-valued time series
The blind source separation model for multivariate time series generally assumes that the observed series is a linear transformation of an unobserved series with temporally uncorrelated or independent components. Given the observations, the objective is to find a linear transformation that recovers the latent series....
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Mixed Cages
We introduce the notion of a $[z, r; g]$-mixed cage. A $[z, r; g]$-mixed cage is a mixed graph $G$, $z$-regular by arcs, $r$-regular by edges, with girth $g$ and minimum order. In this paper we prove the existence of $[z, r ;g]$-mixed cages and exhibit families of mixed cages for some specific values. We also give lo...
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Single-beam dielectric-microsphere trapping with optical heterodyne detection
A technique to levitate and measure the three-dimensional position of micrometer-sized dielectric spheres with heterodyne detection is presented. The two radial degrees of freedom are measured by interfering light transmitted through the microsphere with a reference wavefront, while the axial degree of freedom is mea...
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An Empirical Analysis of Traceability in the Monero Blockchain
Monero is a privacy-centric cryptocurrency that allows users to obscure their transactions by including chaff coins, called "mixins," along with the actual coins they spend. In this paper, we empirically evaluate two weaknesses in Monero's mixin sampling strategy. First, about 62% of transaction inputs with one or mo...
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Automatic Face Image Quality Prediction
Face image quality can be defined as a measure of the utility of a face image to automatic face recognition. In this work, we propose (and compare) two methods for automatic face image quality based on target face quality values from (i) human assessments of face image quality (matcher-independent), and (ii) quality ...
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Stochastic Block Models are a Discrete Surface Tension
Networks, which represent agents and interactions between them, arise in myriad applications throughout the sciences, engineering, and even the humanities. To understand large-scale structure in a network, a common task is to cluster a network's nodes into sets called "communities" such that there are dense connectio...
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Robust d-wave pairing symmetry in multi-orbital cobalt high temperature superconductors
The pairing symmetry of the newly proposed cobalt high temperature (high-$T_c$) superconductors formed by vertex shared cation-anion tetrahedral complexes is studied by the methods of mean field, random phase approximation (RPA) and functional renormalization group (FRG) analysis. The results of all these methods sho...
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Thermodynamic properties of Ba$_2$CoSi$_2$O$_6$Cl$_2$ in strong magnetic field: Realization of flat-band physics in a highly frustrated quantum magnet
The search for flat-band solid-state realizations is a crucial issue to verify or to challenge theoretical predictions for quantum many-body flat-band systems. For frustrated quantum magnets flat bands lead to various unconventional properties related to the existence of localized many-magnon states. The recently syn...
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Fisher Information and Natural Gradient Learning of Random Deep Networks
A deep neural network is a hierarchical nonlinear model transforming input signals to output signals. Its input-output relation is considered to be stochastic, being described for a given input by a parameterized conditional probability distribution of outputs. The space of parameters consisting of weights and biases...
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Dynamic of plumes and scaling during the melting of a Phase Change Material heated from below
We identify and describe the main dynamic regimes occurring during the melting of the PCM n-octadecane in horizontal layers of several sizes heated from below. This configuration allows to cover a wide range of effective Rayleigh numbers on the liquid PCM phase, up to $\sim 10^9$, without changing any external parame...
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Parallel mean curvature surfaces in four-dimensional homogeneous spaces
We survey different classification results for surfaces with parallel mean curvature immersed into some Riemannian homogeneous four-manifolds, including real and complex space forms, and product spaces. We provide a common framework for this problem, with special attention to the existence of holomorphic quadratic di...
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Recent implementations, applications, and extensions of the Locally Optimal Block Preconditioned Conjugate Gradient method (LOBPCG)
Since introduction [A. Knyazev, Toward the optimal preconditioned eigensolver: Locally optimal block preconditioned conjugate gradient method, SISC (2001) DOI:10.1137/S1064827500366124] and efficient parallel implementation [A. Knyazev et al., Block locally optimal preconditioned eigenvalue xolvers (BLOPEX) in HYPRE ...
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An evaluation of cosmological models from expansion and growth of structure measurements
We compare a large suite of theoretical cosmological models to observational data from the cosmic microwave background, baryon acoustic oscillation measurements of expansion, Type Ia SNe measurements of expansion, redshift space distortion measurements of the growth of structure, and the local Hubble constant. Our th...
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The variety of $2$-dimensional algebras over an algebraically closed field
The work is devoted to the variety of $2$-dimensional algebras over an algebraically closed field. Firstly, we classify such algebras modulo isomorphism. Then we describe the degenerations and the closures of principal algebra series in the variety under consideration. Finally, we apply our results to obtain analogou...
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A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM
We present a Bayesian object observation model for complete probabilistic semantic SLAM. Recent studies on object detection and feature extraction have become important for scene understanding and 3D mapping. However, 3D shape of the object is too complex to formulate the probabilistic observation model; therefore, p...
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Generation of optical frequency combs via four-wave mixing processes for low- and medium-resolution astronomy
We investigate the generation of optical frequency combs through a cascade of four-wave mixing processes in nonlinear fibres with optimised parameters. The initial optical field consists of two continuous-wave lasers with frequency separation larger than 40 GHz (312.7 pm at 1531 nm). It propagates through three nonli...
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Cross-referencing Social Media and Public Surveillance Camera Data for Disaster Response
Physical media (like surveillance cameras) and social media (like Instagram and Twitter) may both be useful in attaining on-the-ground information during an emergency or disaster situation. However, the intersection and reliability of both surveillance cameras and social media during a natural disaster are not fully ...
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Nonlinear Dynamics of a Viscous Bubbly Fluid
A physical model of a three-dimensional flow of a viscous bubbly fluid in an intermediate regime between bubble formation and breakage is presented. The model is based on mechanics and thermodynamics of a single bubble coupled to the dynamics of a viscous fluid as a whole, and takes into account multiple physical eff...
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ConvNet-Based Localization of Anatomical Structures in 3D Medical Images
Localization of anatomical structures is a prerequisite for many tasks in medical image analysis. We propose a method for automatic localization of one or more anatomical structures in 3D medical images through detection of their presence in 2D image slices using a convolutional neural network (ConvNet). A single Con...
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Gradient estimates for heat kernels and harmonic functions
Let $(X,d,\mu)$ be a doubling metric measure space endowed with a Dirichlet form $\E$ deriving from a "carré du champ". Assume that $(X,d,\mu,\E)$ supports a scale-invariant $L^2$-Poincaré inequality. In this article, we study the following properties of harmonic functions, heat kernels and Riesz transforms for $p\in...
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The Deep Underground Neutrino Experiment -- DUNE: the precision era of neutrino physics
The last decade was remarkable for neutrino physics. In particular, the phenomenon of neutrino flavor oscillations has been firmly established by a series of independent measurements. All parameters of the neutrino mixing are now known and we have elements to plan a judicious exploration of new scenarios that are ope...
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Variations of $q$-Garnier system
We study several variants of q-Garnier system corresponding to various directions of discrete time evolutions. We also investigate a relation between the $q$-Garnier system and Suzuki's higher order $q$-Painlev/'e system by using a duality of the $q$-KP system.
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Quantum Quench dynamics in Non-local Luttinger Model: Rigorous Results
We investigate, in the Luttinger model with fixed box potential, the time evolution of an inhomogeneous state prepared as a localized fermion added to the noninteracting ground state. We proved that, if the state is evolved with the interacting Hamiltonian, the averaged density has two peaks moving in opposite direct...
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Dynamics of Relaxed Inflation
The cosmological relaxation of the electroweak scale has been proposed as a mechanism to address the hierarchy problem of the Standard Model. A field, the relaxion, rolls down its potential and, in doing so, scans the squared mass parameter of the Higgs, relaxing it to a parametrically small value. In this work, we p...
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Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling
In solving hard computational problems, semidefinite program (SDP) relaxations often play an important role because they come with a guarantee of optimality. Here, we focus on a popular semidefinite relaxation of K-means clustering which yields the same solution as the non-convex original formulation for well segrega...
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Dispersive optical detection of magnetic Feshbach resonances in ultracold gases
Magnetically tunable Feshbach resonances in ultracold atomic systems are chiefly identified and characterized through time consuming atom loss spectroscopy. We describe an off-resonant dispersive optical probing technique to rapidly locate Feshbach resonances and demonstrate the method by locating four resonances of ...
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Unveiling Bias Compensation in Turbo-Based Algorithms for (Discrete) Compressed Sensing
In Compressed Sensing, a real-valued sparse vector has to be recovered from an underdetermined system of linear equations. In many applications, however, the elements of the sparse vector are drawn from a finite set. Adapted algorithms incorporating this additional knowledge are required for the discrete-valued setup...
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Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
Momentum methods such as Polyak's heavy ball (HB) method, Nesterov's accelerated gradient (AG) as well as accelerated projected gradient (APG) method have been commonly used in machine learning practice, but their performance is quite sensitive to noise in the gradients. We study these methods under a first-order sto...
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Compressed sensing with sparse corruptions: Fault-tolerant sparse collocation approximations
The recovery of approximately sparse or compressible coefficients in a Polynomial Chaos Expansion is a common goal in modern parametric uncertainty quantification (UQ). However, relatively little effort in UQ has been directed toward theoretical and computational strategies for addressing the sparse corruptions probl...
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Learning to Remember Rare Events
Despite recent advances, memory-augmented deep neural networks are still limited when it comes to life-long and one-shot learning, especially in remembering rare events. We present a large-scale life-long memory module for use in deep learning. The module exploits fast nearest-neighbor algorithms for efficiency and t...
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Stacking-dependent electronic structure of trilayer graphene resolved by nanospot angle-resolved photoemission spectroscopy
The crystallographic stacking order in multilayer graphene plays an important role in determining its electronic structure. In trilayer graphene, rhombohedral stacking (ABC) is particularly intriguing, exhibiting a flat band with an electric-field tunable band gap. Such electronic structure is distinct from simple he...
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Interaction energy between vortices of vector fields on Riemannian surfaces
We study a variational Ginzburg-Landau type model depending on a small parameter $\epsilon>0$ for (tangent) vector fields on a $2$-dimensional Riemannian surface. As $\epsilon\to 0$, the vector fields tend to be of unit length and will have singular points of a (non-zero) index, called vortices. Our main result deter...
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Multimodal Nonlinear Microscope based on a Compact Fiber-format Laser Source
We present a multimodal non-linear optical (NLO) laser-scanning microscope, based on a compact fiber-format excitation laser and integrating coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS) and two-photon-excitation fluorescence (TPEF) on a single platform. We demonstrate its capabiliti...
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The Diffuse Light of the Universe - On the microwave background before and after its discovery: open questions
In 1965, the discovery of a new type of uniform radiation, located between radiowaves and infrared light, was accidental. Known today as Cosmic Microwave background (CMB), this diffuse radiation is commonly interpreted as a fossil light released in an early hot and dense universe and constitutes today the main 'pilar...
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Classification of $5$-Dimensional Complex Nilpotent Leibniz Algebras
Leibniz algebras are certain generalization of Lie algebras. In this paper we give the classification of $5-$dimensional complex non-Lie nilpotent Leibniz algebras. We use the canonical forms for the congruence classes of matrices of bilinear forms to classify the case $\dim(A^2)=3$ and $\dim(Leib(A))=1$ which can be...
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Haptics of Screwing and Unscrewing for its Application in Smart Factories for Disassembly
Reconstruction of skilled humans sensation and control system often leads to a development of robust control for the robots. We are developing an unscrewing robot for the automated disassembly which requires a comprehensive control system, but unscrewing experiments with robots are often limited to several conditions...
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$G$-invariant Szegö kernel asymptotics and CR reduction
Let $(X, T^{1,0}X)$ be a compact connected orientable CR manifold of dimension $2n+1$ with non-degenerate Levi curvature. Assume that $X$ admits a connected compact Lie group action $G$. Under certain natural assumptions about the group action $G$, we show that the $G$-invariant Szegö kernel for $(0,q)$ forms is a co...
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Self-similar resistive circuits as fractal-like structures
In the present work we explore resistive circuits where the individual resistors are arranged in fractal-like patterns. These circuits have some of the characteristics typically found in geometric fractals, namely self-similarity and scale invariance. Considering resistive circuits as graphs, we propose a definition ...
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DynaPhoPy: A code for extracting phonon quasiparticles from molecular dynamics simulations
We have developed a computational code, DynaPhoPy, that allow us to extract the microscopic anharmonic phonon properties from molecular dynamics (MD) simulations using the normal-mode-decomposition technique as presented by Sun et al. [T. Sun, D. Zhang, R. Wentzcovitch, 2014]. Using this code we calculated the quasip...
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Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models
The change detection problem is to determine if the Markov network structures of two Markov random fields differ from one another given two sets of samples drawn from the respective underlying distributions. We study the trade-off between the sample sizes and the reliability of change detection, measured as a minimax...
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How Usable are Rust Cryptography APIs?
Context: Poor usability of cryptographic APIs is a severe source of vulnerabilities. Aim: We wanted to find out what kind of cryptographic libraries are present in Rust and how usable they are. Method: We explored Rust's cryptographic libraries through a systematic search, conducted an exploratory study on the major ...
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Augmenting End-to-End Dialog Systems with Commonsense Knowledge
Building dialog agents that can converse naturally with humans is a challenging yet intriguing problem of artificial intelligence. In open-domain human-computer conversation, where the conversational agent is expected to respond to human responses in an interesting and engaging way, commonsense knowledge has to be in...
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A framework for Multi-A(rmed)/B(andit) testing with online FDR control
We propose an alternative framework to existing setups for controlling false alarms when multiple A/B tests are run over time. This setup arises in many practical applications, e.g. when pharmaceutical companies test new treatment options against control pills for different diseases, or when internet companies test t...
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Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization
This paper presents a statistical method of single-channel speech enhancement that uses a variational autoencoder (VAE) as a prior distribution on clean speech. A standard approach to speech enhancement is to train a deep neural network (DNN) to take noisy speech as input and output clean speech. Although this superv...
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BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning
Understanding the global optimality in deep learning (DL) has been attracting more and more attention recently. Conventional DL solvers, however, have not been developed intentionally to seek for such global optimality. In this paper we propose a novel approximation algorithm, BPGrad, towards optimizing deep models g...
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Lagrangian Flow Network approach to an open flow model
Concepts and tools from network theory, the so-called Lagrangian Flow Network framework, have been successfully used to obtain a coarse-grained description of transport by closed fluid flows. Here we explore the application of this methodology to open chaotic flows, and check it with numerical results for a model ope...
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Some new gradient estimates for two nonlinear parabolic equations under Ricci flow
In this paper, by maximum principle and cutoff function, we investigate gradient estimates for positive solutions to two nonlinear parabolic equations under Ricci flow. The related Harnack inequalities are deduced. An result about positive solutions on closed manifolds under Ricci flow is abtained. As applications, g...
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On the pointwise iteration-complexity of a dynamic regularized ADMM with over-relaxation stepsize
In this paper, we extend the improved pointwise iteration-complexity result of a dynamic regularized alternating direction method of multipliers (ADMM) for a new stepsize domain. In this complexity analysis, the stepsize parameter can even be chosen in the interval $(0,2)$ instead of interval $(0,(1+\sqrt{5})/2)$. As...
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DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders
This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencoder (CDAE) for generating an invariant, compact representation of in situ hybridization (ISH) images. While most existing methods for bio-i...
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Nonlocal heat equations in the Heisenberg group
We study the following nonlocal diffusion equation in the Heisenberg group $\mathbb{H}_n$, \[ u_t(z,s,t)=J\ast u(z,s,t)-u(z,s,t), \] where $\ast$ denote convolution product and $J$ satisfies appropriated hypothesis. For the Cauchy problem we obtain that the asymptotic behavior of the solutions is the same form that t...
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Motion Planning Networks
Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics applications such as self-driving cars. Existing motion planning methods such as RRT*, A*, and D*, become ineffective as their computational complexity increases exponentially with the dimensionality of the motion planning pr...
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Query Expansion Techniques for Information Retrieval: a Survey
With the ever increasing size of web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge. To overcome this, query expansion (QE) plays a crucial role in improving the Internet searches, where the user's initial query is reformulated to a new query by addin...
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Method for Aspect-Based Sentiment Annotation Using Rhetorical Analysis
This paper fills a gap in aspect-based sentiment analysis and aims to present a new method for preparing and analysing texts concerning opinion and generating user-friendly descriptive reports in natural language. We present a comprehensive set of techniques derived from Rhetorical Structure Theory and sentiment anal...
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Commutativity of integral quasi-arithmetic means on measure spaces
Let $(X, \mathscr{L}, \lambda)$ and $(Y, \mathscr{M}, \mu)$ be finite measure spaces for which there exist $A \in \mathscr{L}$ and $B \in \mathscr{M}$ with $0 < \lambda(A) < \lambda(X)$ and $0 < \mu(B) < \mu(Y)$, and let $I\subseteq \mathbf{R}$ be a non-empty interval. We prove that, if $f$ and $g$ are continuous bij...
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Moderate Deviation for Random Elliptic PDEs with Small Noise
Partial differential equations with random inputs have become popular models to characterize physical systems with uncertainty coming from, e.g., imprecise measurement and intrinsic randomness. In this paper, we perform asymptotic rare event analysis for such elliptic PDEs with random inputs. In particular, we consid...
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Music Transformer
Music relies heavily on repetition to build structure and meaning. Self-reference occurs on multiple timescales, from motifs to phrases to reusing of entire sections of music, such as in pieces with ABA structure. The Transformer (Vaswani et al., 2017), a sequence model based on self-attention, has achieved compellin...
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Residual-Based Detections and Unified Architecture for Massive MIMO Uplink
Massive multiple-input multiple-output (M-MIMO) technique brings better energy efficiency and coverage but higher computational complexity than small-scale MIMO. For linear detections such as minimum mean square error (MMSE), prohibitive complexity lies in solving large-scale linear equations. For a better trade-off ...
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Sparsity constrained split feasibility for dose-volume constraints in inverse planning of intensity-modulated photon or proton therapy
A split feasibility formulation for the inverse problem of intensity-modulated radiation therapy (IMRT) treatment planning with dose-volume constraints (DVCs) included in the planning algorithm is presented. It involves a new type of sparsity constraint that enables the inclusion of a percentage-violation constraint ...
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On 2-Verma modules for quantum $\mathfrak{sl}_2$
In this paper we study the superalgebra $A_n$, introduced by the authors in previous work on categorification of Verma modules for quantum $\mathfrak{sl}_2$. The superalgebra $A_n$ is akin to the nilHecke algebra, and shares similar properties. In particular, we prove a uniqueness result about 2-Verma modules on $\Bb...
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On the Number of Single-Peaked Narcissistic or Single-Crossing Narcissistic Preference Profiles
We investigate preference profiles for a set $\mathcal{V}$ of voters, where each voter $i$ has a preference order $\succ_i$ on a finite set $A$ of alternatives (that is, a linear order on $A$) such that for each two alternatives $a,b\in A$, voter $i$ prefers $a$ to $b$ if $a\succ_i b$. Such a profile is narcissistic ...
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Planet formation and disk-planet interactions
This review is based on lectures given at the 45th Saas-Fee Advanced Course 'From Protoplanetary Disks to Planet Formation' held in March 2015 in Les Diablerets, Switzerland. Starting with an overview of the main characterictics of the Solar System and extrasolar planets, we describe the planet formation process in t...
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Cherednik algebras and Calogero-Moser cells
Using the representation theory of Cherednik algebras at $t=0$ and a Galois covering of the Calogero-Moser space, we define the notions of left, right and two-sided Calogero-Moser cells for any finite complex reflection group. To each Caloger-Moser two-sided cell is associated a Calogero-Moser family, while to each C...
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Khovanov complexes of rational tangles
We show that the Khovanov complex of a rational tangle has a very simple representative whose backbone of non-zero morphisms forms a zig-zag. Furthermore, this minimal complex can be computed quickly by an inductive algorithm. (For example, we calculate $Kh(8_2)$ by hand.) We find that the bigradings of the subobject...
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Asymmetric Connectedness of Fears in the U.S. Financial Sector
We study how shocks to the forward-looking expectations of investors buying call and put options transmit across the financial system. We introduce a new contagion measure, called asymmetric fear connectedness (AFC), which captures the information related to "fear" on the two sides of the options market and can be us...
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Neural Network Based Speaker Classification and Verification Systems with Enhanced Features
This work presents a novel framework based on feed-forward neural network for text-independent speaker classification and verification, two related systems of speaker recognition. With optimized features and model training, it achieves 100% classification rate in classification and less than 6% Equal Error Rate (ERR)...
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Slimness of graphs
Slimness of a graph measures the local deviation of its metric from a tree metric. In a graph $G=(V,E)$, a geodesic triangle $\bigtriangleup(x,y,z)$ with $x, y, z\in V$ is the union $P(x,y) \cup P(x,z) \cup P(y,z)$ of three shortest paths connecting these vertices. A geodesic triangle $\bigtriangleup(x,y,z)$ is calle...
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SirenAttack: Generating Adversarial Audio for End-to-End Acoustic Systems
Despite their immense popularity, deep learning-based acoustic systems are inherently vulnerable to adversarial attacks, wherein maliciously crafted audios trigger target systems to misbehave. In this paper, we present SirenAttack, a new class of attacks to generate adversarial audios. Compared with existing attacks,...
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k-server via multiscale entropic regularization
We present an $O((\log k)^2)$-competitive randomized algorithm for the $k$-server problem on hierarchically separated trees (HSTs). This is the first $o(k)$-competitive randomized algorithm for which the competitive ratio is independent of the size of the underlying HST. Our algorithm is designed in the framework of ...
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Some Large Sample Results for the Method of Regularized Estimators
We present a general framework for studying regularized estimators; i.e., estimation problems wherein "plug-in" type estimators are either ill-defined or ill-behaved. We derive primitive conditions that imply consistency and asymptotic linear representation for regularized estimators, allowing for slower than $\sqrt{...
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Coregionalised Locomotion Envelopes - A Qualitative Approach
'Sharing of statistical strength' is a phrase often employed in machine learning and signal processing. In sensor networks, for example, missing signals from certain sensors may be predicted by exploiting their correlation with observed signals acquired from other sensors. For humans, our hands move synchronously wit...
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Optimal Invariant Tests in an Instrumental Variables Regression With Heteroskedastic and Autocorrelated Errors
This paper uses model symmetries in the instrumental variable (IV) regression to derive an invariant test for the causal structural parameter. Contrary to popular belief, we show there exist model symmetries when equation errors are heteroskedastic and autocorrelated (HAC). Our theory is consistent with existing resu...
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Longitudinal electric field: from Maxwell equation to non-locality in time and space
In this paper we use the classical electrodynamics to show that the Lorenz gauge can be incompatible with some particular solutions of the d Alembert equations for electromagnetic potentials. In its turn, the d Alembert equations for the elec- tromagnetic potentials is the result of application of the Lorenz gauge to...
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Estimating linear functionals of a sparse family of Poisson means
Assume that we observe a sample of size n composed of p-dimensional signals, each signal having independent entries drawn from a scaled Poisson distribution with an unknown intensity. We are interested in estimating the sum of the n unknown intensity vectors, under the assumption that most of them coincide with a giv...
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Fabrication of porous microrings via laser printing and ion-beam post-etching
Pulsed-laser dry printing of noble-metal microrings with a tunable internal porous structure, which can be revealed via an ion-beam etching post-procedure, was demonstrated. Abundance and average size of the pores inside the microrings were shown to be tuned in a wide range by varying incident pulse energy and a nitr...
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Performance Measurements of Supercomputing and Cloud Storage Solutions
Increasing amounts of data from varied sources, particularly in the fields of machine learning and graph analytics, are causing storage requirements to grow rapidly. A variety of technologies exist for storing and sharing these data, ranging from parallel file systems used by supercomputers to distributed block stora...
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Multi-Objective Event-triggered Consensus of Linear Multi-agent Systems
This paper proposes a distributed consensus algorithm for linear event-based heterogeneous multi-agent systems (MAS). The proposed scheme is event-triggered in the sense that an agent selectively transmits its information within its local neighbourhood based on a directed network topology under the fulfillment of cer...
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Private and Secure Coordination of Match-Making for Heavy-Duty Vehicle Platooning
A secure and private framework for inter-agent communication and coordination is developed. This allows an agent, in our case a fleet owner, to ask questions or submit queries in an encrypted fashion using semi-homomorphic encryption. The submitted query can be about the interest of the other fleet owners for using a...
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Kernel Robust Bias-Aware Prediction under Covariate Shift
Under covariate shift, training (source) data and testing (target) data differ in input space distribution, but share the same conditional label distribution. This poses a challenging machine learning task. Robust Bias-Aware (RBA) prediction provides the conditional label distribution that is robust to the worstcase ...
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Degeneration in VAE: in the Light of Fisher Information Loss
While enormous progress has been made to Variational Autoencoder (VAE) in recent years, similar to other deep networks, VAE with deep networks suffers from the problem of degeneration, which seriously weakens the correlation between the input and the corresponding latent codes, deviating from the goal of the represen...
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Room-temperature spin transport in n-Ge probed by four-terminal nonlocal measurements
We demonsrtate electrical spin injection and detection in $n$-type Ge ($n$-Ge) at room temperature using four-terminal nonlocal spin-valve and Hanle-effect measurements in lateral spin-valve (LSV) devices with Heusler-alloy Schottky tunnel contacts. The spin diffusion length ($\lambda$$_{\rm Ge}$) of the Ge layer use...
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Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning
We present an algorithm for rapidly learning controllers for robotics systems. The algorithm follows the model-based reinforcement learning paradigm, and improves upon existing algorithms; namely Probabilistic learning in Control (PILCO) and a sample-based version of PILCO with neural network dynamics (Deep-PILCO). W...
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Stealthy Deception Attacks Against SCADA Systems
SCADA protocols for Industrial Control Systems (ICS) are vulnerable to network attacks such as session hijacking. Hence, research focuses on network anomaly detection based on meta--data (message sizes, timing, command sequence), or on the state values of the physical process. In this work we present a class of seman...
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Beta-rhythm oscillations and synchronization transition in network models of Izhikevich neurons: effect of topology and synaptic type
Despite their significant functional roles, beta-band oscillations are least understood. Synchronization in neuronal networks have attracted much attention in recent years with the main focus on transition type. Whether one obtains explosive transition or a continuous transition is an important feature of the neurona...
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Renyi Differential Privacy
We propose a natural relaxation of differential privacy based on the Renyi divergence. Closely related notions have appeared in several recent papers that analyzed composition of differentially private mechanisms. We argue that the useful analytical tool can be used as a privacy definition, compactly and accurately r...
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Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal Structure
In this paper, we propose a quality enhancement network for Versatile Video Coding (VVC) compressed videos by jointly exploiting spatial details and temporal structure (SDTS). The network consists of a temporal structure prediction subnet and a spatial detail enhancement subnet. The former subnet is used to estimate ...
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