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Conformal growth rates and spectral geometry on distributional limits of graphs
For a unimodular random graph $(G,\rho)$, we consider deformations of its intrinsic path metric by a (random) weighting of its vertices. This leads to the notion of the {\em conformal growth exponent of $(G,\rho)$}, which is the best asymptotic degree of volume growth of balls that can be achieved by such a reweighti...
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Self-Supervised Vision-Based Detection of the Active Speaker as a Prerequisite for Socially-Aware Language Acquisition
This paper presents a self-supervised method for detecting the active speaker in a multi-person spoken interaction scenario. We argue that this capability is a fundamental prerequisite for any artificial cognitive system attempting to acquire language in social settings. Our methods are able to detect an arbitrary nu...
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Monocular Imaging-based Autonomous Tracking for Low-cost Quad-rotor Design - TraQuad
TraQuad is an autonomous tracking quadcopter capable of tracking any moving (or static) object like cars, humans, other drones or any other object on-the-go. This article describes the applications and advantages of TraQuad and the reduction in cost (to about 250$) that has been achieved so far using the hardware and...
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Persistence Diagrams with Linear Machine Learning Models
Persistence diagrams have been widely recognized as a compact descriptor for characterizing multiscale topological features in data. When many datasets are available, statistical features embedded in those persistence diagrams can be extracted by applying machine learnings. In particular, the ability for explicitly a...
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Characterizing the number of coloured $m$-ary partitions modulo $m$, with and without gaps
In a pair of recent papers, Andrews, Fraenkel and Sellers provide a complete characterization for the number of $m$-ary partitions modulo $m$, with and without gaps. In this paper we extend these results to the case of coloured $m$-ary partitions, with and without gaps. Our method of proof is different, giving explic...
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Towards Approximate Mobile Computing
Mobile computing is one of the main drivers of innovation, yet the future growth of mobile computing capabilities remains critically threatened by hardware constraints, such as the already extremely dense transistor packing and limited battery capacity. The breakdown of Dennard scaling and stagnating energy storage i...
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Room-temperature high detectivity mid-infrared photodetectors based on black arsenic phosphorus
The mid-infrared (MIR) spectral range, pertaining to important applications such as molecular 'fingerprint' imaging, remote sensing, free space telecommunication and optical radar, is of particular scientific interest and technological importance. However, state-of-the-art materials for MIR detection are limited by i...
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Topology determines force distributions in one-dimensional random spring networks
Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessi...
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On a local invariant of elliptic curves with a p-isogeny
An elliptic curve $E$ defined over a $p$-adic field $K$ with a $p$-isogeny $\phi:E\rightarrow E^\prime$ comes equipped with an invariant $\alpha_{\phi/K}$ that measures the valuation of the leading term of the formal group homomorphism $\Phi:\hat E \rightarrow \hat E^\prime$. We prove that if $K/\mathbb{Q}_p$ is unra...
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IIFA: Modular Inter-app Intent Information Flow Analysis of Android Applications
Android apps cooperate through message passing via intents. However, when apps do not have identical sets of privileges inter-app communication (IAC) can accidentally or maliciously be misused, e.g., to leak sensitive information contrary to users expectations. Recent research considered static program analysis to de...
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Glass+Skin: An Empirical Evaluation of the Added Value of Finger Identification to Basic Single-Touch Interaction on Touch Screens
The usability of small devices such as smartphones or interactive watches is often hampered by the limited size of command vocabularies. This paper is an attempt at better understanding how finger identification may help users invoke commands on touch screens, even without recourse to multi-touch input. We describe h...
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The Morphospace of Consciousness
We construct a complexity-based morphospace to study systems-level properties of conscious & intelligent systems. The axes of this space label 3 complexity types: autonomous, cognitive & social. Given recent proposals to synthesize consciousness, a generic complexity-based conceptualization provides a useful framewor...
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Transverse Magnetic Susceptibility of a Frustrated Spin-$\frac{1}{2}$ $J_{1}$--$J_{2}$--$J_{1}^{\perp}$ Heisenberg Antiferromagnet on a Bilayer Honeycomb Lattice
We use the coupled cluster method (CCM) to study a frustrated spin-$\frac{1}{2}$ $J_{1}$--$J_{2}$--$J_{1}^{\perp}$ Heisenberg antiferromagnet on a bilayer honeycomb lattice with $AA$ stacking. Both nearest-neighbor (NN) and frustrating next-nearest-neighbor antiferromagnetic (AFM) exchange interactions are present in...
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Minimum polyhedron with $n$ vertices
We study a polyhedron with $n$ vertices of fixed volume having minimum surface area. Completing the proof of Toth, we show that all faces of a minimum polyhedron are triangles, and further prove that a minimum polyhedron does not allow deformation of a single vertex. We also present possible minimum shapes for $n\le ...
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Theory of interacting fermions in shaken square optical lattice
We develop a theory of weakly interacting fermionic atoms in shaken optical lattices based on the orbital mixing in the presence of time-periodic modulations. Specifically, we focus on fermionic atoms in circularly shaken square lattice with near resonance frequencies, i.e., tuned close to the energy separation betwe...
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Simple to Complex Cross-modal Learning to Rank
The heterogeneity-gap between different modalities brings a significant challenge to multimedia information retrieval. Some studies formalize the cross-modal retrieval tasks as a ranking problem and learn a shared multi-modal embedding space to measure the cross-modality similarity. However, previous methods often es...
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Iteration-complexity analysis of a generalized alternating direction method of multipliers
This paper analyzes the iteration-complexity of a generalized alternating direction method of multipliers (G-ADMM) for solving linearly constrained convex problems. This ADMM variant, which was first proposed by Bertsekas and Eckstein, introduces a relaxation parameter $\alpha \in (0,2)$ into the second ADMM subprobl...
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A Game Theoretic Macroscopic Model of Bypassing at Traffic Diverges with Applications to Mixed Autonomy Networks
Vehicle bypassing is known to negatively affect delays at traffic diverges. However, due to the complexities of this phenomenon, accurate and yet simple models of such lane change maneuvers are hard to develop. In this work, we present a macroscopic model for predicting the number of vehicles that bypass at a traffic...
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Non-resonant secular dynamics of trans-Neptunian objects perturbed by a distant super-Earth
We use a secular model to describe the non-resonant dynamics of trans-Neptunian objects in the presence of an external ten-earth-mass perturber. The secular dynamics is analogous to an "eccentric Kozai mechanism" but with both an inner component (the four giant planets) and an outer one (the eccentric distant perturb...
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Stability Analysis for Switched Systems with Sequence-based Average Dwell Time
This note investigates the stability of both linear and nonlinear switched systems with average dwell time. Two new analysis methods are proposed. Different from existing approaches, the proposed methods take into account the sequence in which the subsystems are switched. Depending on the predecessor or successor sub...
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Interpreting and using CPDAGs with background knowledge
We develop terminology and methods for working with maximally oriented partially directed acyclic graphs (maximal PDAGs). Maximal PDAGs arise from imposing restrictions on a Markov equivalence class of directed acyclic graphs, or equivalently on its graphical representation as a completed partially directed acyclic g...
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A cable-driven parallel manipulator with force sensing capabilities for high-accuracy tissue endomicroscopy
This paper introduces a new surgical end-effector probe, which allows to accurately apply a contact force on a tissue, while at the same time allowing for high resolution and highly repeatable probe movement. These are achieved by implementing a cable-driven parallel manipulator arrangement, which is deployed at the ...
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Overfitting Mechanism and Avoidance in Deep Neural Networks
Assisted by the availability of data and high performance computing, deep learning techniques have achieved breakthroughs and surpassed human performance empirically in difficult tasks, including object recognition, speech recognition, and natural language processing. As they are being used in critical applications, ...
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What deep learning can tell us about higher cognitive functions like mindreading?
Can deep learning (DL) guide our understanding of computations happening in biological brain? We will first briefly consider how DL has contributed to the research on visual object recognition. In the main part we will assess whether DL could also help us to clarify the computations underlying higher cognitive functi...
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Concentration of quantum states from quantum functional and transportation cost inequalities
Quantum functional inequalities (e.g. the logarithmic Sobolev- and Poincaré inequalities) have found widespread application in the study of the behavior of primitive quantum Markov semigroups. The classical counterparts of these inequalities are related to each other via a so-called transportation cost inequality of ...
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Stochastic Training of Neural Networks via Successive Convex Approximations
This paper proposes a new family of algorithms for training neural networks (NNs). These are based on recent developments in the field of non-convex optimization, going under the general name of successive convex approximation (SCA) techniques. The basic idea is to iteratively replace the original (non-convex, highly...
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Best arm identification in multi-armed bandits with delayed feedback
We propose a generalization of the best arm identification problem in stochastic multi-armed bandits (MAB) to the setting where every pull of an arm is associated with delayed feedback. The delay in feedback increases the effective sample complexity of standard algorithms, but can be offset if we have access to parti...
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General $(α, β)$ metrics with relatively isotroic mean Landsberg curvature
In this paper, we study a new class of Finsler metrics, F=\alpha\phi(b^2,s), s:=\beta/\alpha, defined by a Riemannian metric \alpha and 1-form \beta. It is called general (\alpha, \beta) metric. In this paper, we assume \phi be coefficient by s and \beta be closed and conformal. We find a nessecary and sufficient con...
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Structured Optimal Transport
Optimal Transport has recently gained interest in machine learning for applications ranging from domain adaptation, sentence similarities to deep learning. Yet, its ability to capture frequently occurring structure beyond the "ground metric" is limited. In this work, we develop a nonlinear generalization of (discrete...
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Very metal-poor stars observed by the RAVE survey
We present a novel analysis of the metal-poor star sample in the complete Radial Velocity Experiment (RAVE) Data Release 5 catalog with the goal of identifying and characterizing all very metal-poor stars observed by the survey. Using a three-stage method, we first identified the candidate stars using only their spec...
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Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting
Recently, the intervention calculus when the DAG is absent (IDA) method was developed to estimate lower bounds of causal effects from observational high-dimensional data. Originally it was introduced to assess the effect of baseline biomarkers which do not vary over time. However, in many clinical settings, measureme...
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A Note on Cyclotomic Integers
In this note, we present a new proof that the cyclotomic integers constitute the full ring of integers in the cyclotomic field.
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Stochastic homogenization for functionals with anisotropic rescaling and non-coercive Hamilton-Jacobi equations
We study the stochastic homogenization for a Cauchy problem for a first-order Hamilton-Jacobi equation whose operator is not coercive w.r.t. the gradient variable. We look at Hamiltonians like $H(x,\sigma(x)p,\omega)$ where $\sigma(x)$ is a matrix associated to a Carnot group. The rescaling considered is consistent w...
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Automatic Software Repair: a Bibliography
This article presents a survey on automatic software repair. Automatic software repair consists of automatically finding a solution to software bugs without human intervention. This article considers all kinds of repairs. First, it discusses behavioral repair where test suites, contracts, models, and crashing inputs ...
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The design and the performance of stratospheric mission in the search for the Schumann resonances
The technical details of a balloon stratospheric mission that is aimed at measuring the Schumann resonances are described. The gondola is designed specifically for the measuring of faint effects of ELF (Extremely Low Frequency electromagnetic waves) phenomena. The prototype met the design requirements. The ELF measur...
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A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle
Self-driving technology is advancing rapidly --- albeit with significant challenges and limitations. This progress is largely due to recent developments in deep learning algorithms. To date, however, there has been no systematic comparison of how different deep learning architectures perform at such tasks, or an atte...
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On the Theory of Light Propagation in Crystalline Dielectrics
A synoptic view on the long-established theory of light propagation in crystalline dielectrics is presented, providing a new exact solution for the microscopic local electromagnetic field thus disclosing the role of the divergence-free (transversal) and curl-free (longitudinal) parts of the electromagnetic field insi...
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Microfluidic control of nucleation and growth of calcite
The nucleation and growth of calcite is an important research in scientific and industrial field. Both the macroscopic and microscopic observation of calcite growth have been reported. Now, with the development of microfluidic device, we could focus the nucleation and growth of one single calcite. By changing the flo...
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Using low-frequency pulsar observations to study the 3-D structure of the Galactic magnetic field
The Galactic magnetic field (GMF) plays a role in many astrophysical processes and is a significant foreground to cosmological signals, such as the Epoch of Reionization (EoR), but is not yet well understood. Dispersion and Faraday rotation measurements (DMs and RMs, respectively) towards a large number of pulsars pr...
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Simple mechanical cues could explain adipose tissue morphology
The mechanisms by which organs acquire their functional structure and realize its maintenance (or homeostasis) over time are still largely unknown. In this paper, we investigate this question on adipose tissue. Adipose tissue can represent 20 to 50% of the body weight. Its investigation is key to overcome a large arr...
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Comments on the National Toxicology Program Report on Cancer, Rats and Cell Phone Radiation
With the National Toxicology Program issuing its final report on cancer, rats and cell phone radiation, one can draw the following conclusions from their data. There is a roughly linear relationship between gliomas (brain cancers) and schwannomas (cancers of the nerve sheaths around the heart) with increased absorpti...
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Estimates for the coefficients of differential dimension polynomials
We answer the following long-standing question of Kolchin: given a system of algebraic-differential equations $\Sigma(x_1,\dots,x_n)=0$ in $m$ derivatives over a differential field of characteristic zero, is there a computable bound, that only depends on the order of the system (and on the fixed data $m$ and $n$), fo...
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Giant perpendicular exchange bias with antiferromagnetic MnN
We investigated an out-of-plane exchange bias system that is based on the antiferromagnet MnN. Polycrystalline, highly textured film stacks of Ta / MnN / CoFeB / MgO / Ta were grown on SiO$_x$ by (reactive) magnetron sputtering and studied by x-ray diffraction and Kerr magnetometry. Nontrivial modifications of the ex...
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A Fuzzy Community-Based Recommender System Using PageRank
Recommendation systems are widely used by different user service providers specially those who have interactions with the large community of users. This paper introduces a recommender system based on community detection. The recommendation is provided using the local and global similarities between users. The local i...
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Foundations of Complex Event Processing
Complex Event Processing (CEP) has emerged as the unifying field for technologies that require processing and correlating distributed data sources in real-time. CEP finds applications in diverse domains, which has resulted in a large number of proposals for expressing and processing complex events. However, existing ...
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Prior Variances and Depth Un-Biased Estimators in EEG Focal Source Imaging
In electroencephalography (EEG) source imaging, the inverse source estimates are depth biased in such a way that their maxima are often close to the sensors. This depth bias can be quantified by inspecting the statistics (mean and co-variance) of these estimates. In this paper, we find weighting factors within a Baye...
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Standard Galactic Field RR Lyrae. I. Optical to Mid-infrared Phased Photometry
We present a multi-wavelength compilation of new and previously-published photometry for 55 Galactic field RR Lyrae variables. Individual studies, spanning a time baseline of up to 30 years, are self-consistently phased to produce light curves in 10 photometric bands covering the wavelength range from 0.4 to 4.5 micr...
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An Updated Literature Review of Distance Correlation and its Applications to Time Series
The concept of distance covariance/correlation was introduced recently to characterize dependence among vectors of random variables. We review some statistical aspects of distance covariance/correlation function and we demonstrate its applicability to time series analysis. We will see that the auto-distance covarianc...
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A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns
This letter presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view in a panoramic RGB-D camera system. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a 360$^\circ$ field of view usi...
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Particular type of gap in the spectrum of multiband superconductors
We show, that in contrast to the free electron model (standard BCS model), a particular gap in the spectrum of multiband superconductors opens at some distance from the Fermi energy, if conduction band is composed of hybridized atomic orbitals of different symmetries. This gap has composite superconducting-hybridizat...
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Reliable Decision Support using Counterfactual Models
Decision-makers are faced with the challenge of estimating what is likely to happen when they take an action. For instance, if I choose not to treat this patient, are they likely to die? Practitioners commonly use supervised learning algorithms to fit predictive models that help decision-makers reason about likely fu...
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Robust temporal difference learning for critical domains
We present a new Q-function operator for temporal difference (TD) learning methods that explicitly encodes robustness against significant rare events (SRE) in critical domains. The operator, which we call the $\kappa$-operator, allows to learn a safe policy in a model-based fashion without actually observing the SRE....
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Structure of the Entanglement Entropy of (3+1)D Gapped Phases of Matter
We study the entanglement entropy of gapped phases of matter in three spatial dimensions. We focus in particular on size-independent contributions to the entropy across entanglement surfaces of arbitrary topologies. We show that for low energy fixed-point theories, the constant part of the entanglement entropy across...
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Dynamics and asymptotic profiles of endemic equilibrium for two frequency-dependent SIS epidemic models with cross-diffusion
This paper is concerned with two frequency-dependent SIS epidemic reaction-diffusion models in heterogeneous environment, with a cross-diffusion term modeling the effect that susceptible individuals tend to move away from higher concentration of infected individuals. It is first shown that the corresponding Neumann i...
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Stable Clustering Ansatz, Consistency Relations and Gravity Dual of Large-Scale Structure
Gravitational clustering in the nonlinear regime remains poorly understood. Gravity dual of gravitational clustering has recently been proposed as a means to study the nonlinear regime. The stable clustering ansatz remains a key ingredient to our understanding of gravitational clustering in the highly nonlinear regim...
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Heavy-Tailed Analogues of the Covariance Matrix for ICA
Independent Component Analysis (ICA) is the problem of learning a square matrix $A$, given samples of $X=AS$, where $S$ is a random vector with independent coordinates. Most existing algorithms are provably efficient only when each $S_i$ has finite and moderately valued fourth moment. However, there are practical app...
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Breaking through the bandwidth barrier in distributed fiber vibration sensing by sub-Nyquist randomized sampling
The round trip time of the light pulse limits the maximum detectable frequency response range of vibration in phase-sensitive optical time domain reflectometry ({\phi}-OTDR). We propose a method to break the frequency response range restriction of {\phi}-OTDR system by modulating the light pulse interval randomly whi...
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The Continuity of the Gauge Fixing Condition $n\cdot\partial n\cdot A=0$ for $SU(2)$ Gauge Theory
The continuity of the gauge fixing condition $n\cdot\partial n\cdot A=0$ for $SU(2)$ gauge theory on the manifold $R\bigotimes S^{1}\bigotimes S^{1}\bigotimes S^{1}$ is studied here, where $n^{\mu}$ stands for directional vector along $x_{i}$-axis($i=1,2,3$). It is proved that the gauge fixing condition is continuous...
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Estimating functions for jump-diffusions
Asymptotic theory for approximate martingale estimating functions is generalised to diffusions with finite-activity jumps, when the sampling frequency and terminal sampling time go to infinity. Rate optimality and efficiency are of particular concern. Under mild assumptions, it is shown that estimators of drift, diff...
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Automatic Skin Lesion Analysis using Large-scale Dermoscopy Images and Deep Residual Networks
Malignant melanoma has one of the most rapidly increasing incidences in the world and has a considerable mortality rate. Early diagnosis is particularly important since melanoma can be cured with prompt excision. Dermoscopy images play an important role in the non-invasive early detection of melanoma [1]. However, me...
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Quadrature-based features for kernel approximation
We consider the problem of improving kernel approximation via randomized feature maps. These maps arise as Monte Carlo approximation to integral representations of kernel functions and scale up kernel methods for larger datasets. Based on an efficient numerical integration technique, we propose a unifying approach th...
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The impossibility of "fairness": a generalized impossibility result for decisions
Various measures can be used to estimate bias or unfairness in a predictor. Previous work has already established that some of these measures are incompatible with each other. Here we show that, when groups differ in prevalence of the predicted event, several intuitive, reasonable measures of fairness (probability of...
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Measuring Quantum Entropy
The entropy of a quantum system is a measure of its randomness, and has applications in measuring quantum entanglement. We study the problem of measuring the von Neumann entropy, $S(\rho)$, and Rényi entropy, $S_\alpha(\rho)$ of an unknown mixed quantum state $\rho$ in $d$ dimensions, given access to independent copi...
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Elliptic Transverse Circulation Equations for Balanced Models in a Generalized Vertical Coordinate
When studying tropical cyclones using the $f$-plane, axisymmetric, gradient balanced model, there arises a second-order elliptic equation for the transverse circulation. Similarly, when studying zonally symmetric meridional circulations near the equator (the tropical Hadley cells) or the katabatically forced meridion...
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The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods
We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016 edition with the aim of providing a common framework for evaluating and comparing different state-of-the-art voice conversion (VC) systems. The objective of the challenge was to perform speaker conversion (i.e. transform the vocal ide...
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Levels of distribution for sieve problems in prehomogeneous vector spaces
In a companion paper, we developed an efficient algebraic method for computing the Fourier transforms of certain functions defined on prehomogeneous vector spaces over finite fields, and we carried out these computations in a variety of cases. Here we develop a method, based on Fourier analysis and algebraic geometry...
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Imagination-Augmented Agents for Deep Reinforcement Learning
We introduce Imagination-Augmented Agents (I2As), a novel architecture for deep reinforcement learning combining model-free and model-based aspects. In contrast to most existing model-based reinforcement learning and planning methods, which prescribe how a model should be used to arrive at a policy, I2As learn to int...
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Cluster-glass phase in pyrochlore XY antiferromagnets with quenched disorder
We study the impact of quenched disorder (random exchange couplings or site dilution) on easy-plane pyrochlore antiferromagnets. In the clean system, order-by-disorder selects a magnetically ordered state from a classically degenerate manifold. In the presence of randomness, however, different orders can be chosen lo...
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Non-line-of-sight tracking of people at long range
A remote-sensing system that can determine the position of hidden objects has applications in many critical real-life scenarios, such as search and rescue missions and safe autonomous driving. Previous work has shown the ability to range and image objects hidden from the direct line of sight, employing advanced optic...
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DeSIGN: Design Inspiration from Generative Networks
Can an algorithm create original and compelling fashion designs to serve as an inspirational assistant? To help answer this question, we design and investigate different image generation models associated with different loss functions to boost creativity in fashion generation. The dimensions of our explorations inclu...
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Challenges of facet analysis and concept placement in universal classifications: the example of architecture in UDC
The paper discusses the challenges of faceted vocabulary organization in universal classifications which treat the universe of knowledge as a coherent whole and in which the concepts and subjects in different disciplines are shared, related and combined. The authors illustrate the challenges of the facet analytical a...
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Coalescent-based species tree estimation: a stochastic Farris transform
The reconstruction of a species phylogeny from genomic data faces two significant hurdles: 1) the trees describing the evolution of each individual gene--i.e., the gene trees--may differ from the species phylogeny and 2) the molecular sequences corresponding to each gene often provide limited information about the ge...
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Variance-Reduced Stochastic Learning by Networked Agents under Random Reshuffling
A new amortized variance-reduced gradient (AVRG) algorithm was developed in \cite{ying2017convergence}, which has constant storage requirement in comparison to SAGA and balanced gradient computations in comparison to SVRG. One key advantage of the AVRG strategy is its amenability to decentralized implementations. In ...
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Blind Community Detection from Low-rank Excitations of a Graph Filter
This paper considers a novel framework to detect communities in a graph from the observation of signals at its nodes. We model the observed signals as noisy outputs of an unknown network process -- represented as a graph filter -- that is excited by a set of low-rank inputs. Rather than learning the precise parameter...
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Realistic theory of electronic correlations in nanoscopic systems
Nanostructures with open shell transition metal or molecular constituents host often strong electronic correlations and are highly sensitive to atomistic material details. This tutorial review discusses method developments and applications of theoretical approaches for the realistic description of the electronic and ...
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The Multiplier Problem of the Calculus of Variations for Scalar Ordinary Differential Equations
In the inverse problem of the calculus of variations one is asked to find a Lagrangian and a multiplier so that a given differential equation, after multiplying with the multiplier, becomes the Euler--Lagrange equation for the Lagrangian. An answer to this problem for the case of a scalar ordinary differential equati...
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Representation categories of Mackey Lie algebras as universal monoidal categories
Let $\mathbb{K}$ be an algebraically closed field of characteristic $0$. We study a monoidal category $\mathbb{T}_\alpha$ which is universal among all symmetric $\mathbb{K}$-linear monoidal categories generated by two objects $A$ and $B$ such that $A$ has a, possibly transfinite, filtration. We construct $\mathbb{T}_...
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Dielectric media considered as vacuum with sources
Conventional textbook treatments on electromagnetic wave propagation consider the induced charge and current densities as "bound", and therefore absorb them into a refractive index. In principle it must also be possible to treat the medium as vacuum, but with explicit charge and current densities. This gives a more d...
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Game-Theoretic Design of Secure and Resilient Distributed Support Vector Machines with Adversaries
With a large number of sensors and control units in networked systems, distributed support vector machines (DSVMs) play a fundamental role in scalable and efficient multi-sensor classification and prediction tasks. However, DSVMs are vulnerable to adversaries who can modify and generate data to deceive the system to ...
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Rank conditional coverage and confidence intervals in high dimensional problems
Confidence interval procedures used in low dimensional settings are often inappropriate for high dimensional applications. When a large number of parameters are estimated, marginal confidence intervals associated with the most significant estimates have very low coverage rates: They are too small and centered at bias...
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Phase-Encoded Hyperpolarized Nanodiamond for Magnetic Resonance Imaging
Surface-functionalized nanomaterials can act as theranostic agents that detect disease and track biological processes using hyperpolarized magnetic resonance imaging (MRI). Candidate materials are sparse however, requiring spinful nuclei with long spin-lattice relaxation (T1) and spin-dephasing times (T2), together w...
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k-Space Deep Learning for Reference-free EPI Ghost Correction
Nyquist ghost artifacts in EPI images are originated from phase mismatch between the even and odd echoes. However, conventional correction methods using reference scans often produce erroneous results especially in high-field MRI due to the non-linear and time-varying local magnetic field changes. Recently, it was sh...
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Binary Search in Graphs Revisited
In the classical binary search in a path the aim is to detect an unknown target by asking as few queries as possible, where each query reveals the direction to the target. This binary search algorithm has been recently extended by [Emamjomeh-Zadeh et al., STOC, 2016] to the problem of detecting a target in an arbitra...
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Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
The ADAM optimizer is exceedingly popular in the deep learning community. Often it works very well, sometimes it doesn't. Why? We interpret ADAM as a combination of two aspects: for each weight, the update direction is determined by the sign of stochastic gradients, whereas the update magnitude is determined by an es...
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Econometric Modeling of Regional Electricity Spot Prices in the Australian Market
Wholesale electricity markets are increasingly integrated via high voltage interconnectors, and inter-regional trade in electricity is growing. To model this, we consider a spatial equilibrium model of price formation, where constraints on inter-regional flows result in three distinct equilibria in prices. We use thi...
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Accurate Effective Medium Theory for the Analysis of Spoof Localized Surface Plasmons in Textured Metallic Cylinders
It has been recently demonstrated that textured closed surfaces which are made out of perfect electric conductors (PECs) can mimic highly localized surface plasmons (LSPs). Here, we propose an effective medium which can accurately model LSP resonances in a two-dimensional periodically decorated PEC cylinder. The accu...
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Joint Regression and Ranking for Image Enhancement
Research on automated image enhancement has gained momentum in recent years, partially due to the need for easy-to-use tools for enhancing pictures captured by ubiquitous cameras on mobile devices. Many of the existing leading methods employ machine-learning-based techniques, by which some enhancement parameters for ...
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From arteries to boreholes: Transient response of a poroelastic cylinder to fluid injection
The radially outward flow of fluid through a porous medium occurs in many practical problems, from transport across vascular walls to the pressurisation of boreholes in the subsurface. When the driving pressure is non-negligible relative to the stiffness of the solid structure, the poromechanical coupling between the...
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Social Clustering in Epidemic Spread on Coevolving Networks
Even though transitivity is a central structural feature of social networks, its influence on epidemic spread on coevolving networks has remained relatively unexplored. Here we introduce and study an adaptive SIS epidemic model wherein the infection and network coevolve with non-trivial probability to close triangles...
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A Mathematical Aspect of Hohenberg-Kohn Theorem
The Hohenberg-Kohn theorem plays a fundamental role in density functional theory, which has become a basic tool for the study of electronic structure of matter. In this article, we study the Hohenberg-Kohn theorem for a class of external potentials based on a unique continuation principle.
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Autocomplete 3D Sculpting
Digital sculpting is a popular means to create 3D models but remains a challenging task for many users. This can be alleviated by recent advances in data-driven and procedural modeling, albeit bounded by the underlying data and procedures. We propose a 3D sculpting system that assists users in freely creating models ...
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KeyXtract Twitter Model - An Essential Keywords Extraction Model for Twitter Designed using NLP Tools
Since a tweet is limited to 140 characters, it is ambiguous and difficult for traditional Natural Language Processing (NLP) tools to analyse. This research presents KeyXtract which enhances the machine learning based Stanford CoreNLP Part-of-Speech (POS) tagger with the Twitter model to extract essential keywords fro...
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A Generalized Zero-Forcing Precoder with Successive Dirty-Paper Coding in MISO Broadcast Channels
In this paper, we consider precoder designs for multiuser multiple-input-single-output (MISO) broadcasting channels. Instead of using a traditional linear zero-forcing (ZF) precoder, we propose a generalized ZF (GZF) precoder in conjunction with successive dirty-paper coding (DPC) for data-transmissions, namely, the ...
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Generating Connected Random Graphs
Sampling random graphs is essential in many applications, and often algorithms use Markov chain Monte Carlo methods to sample uniformly from the space of graphs. However, often there is a need to sample graphs with some property that we are unable, or it is too inefficient, to sample using standard approaches. In thi...
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Machine Learning Predicts Laboratory Earthquakes
Forecasting fault failure is a fundamental but elusive goal in earthquake science. Here we show that by listening to the acoustic signal emitted by a laboratory fault, machine learning can predict the time remaining before it fails with great accuracy. These predictions are based solely on the instantaneous physical ...
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New results of the search for hidden photons by means of a multicathode counter
New upper limit on a mixing parameter for hidden photons with a mass from 5 eV till 10 keV has been obtained from the results of measurements during 78 days in two configurations R1 and R2 of a multicathode counter. For a region of a maximal sensitivity from 10 eV till 30 eV the upper limit obtained is less than 4 x ...
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Higher dimensional Steinhaus and Slater problems via homogeneous dynamics
The three gap theorem, also known as the Steinhaus conjecture or three distance theorem, states that the gaps in the fractional parts of $\alpha,2\alpha,\ldots, N\alpha$ take at most three distinct values. Motivated by a question of Erdős, Geelen and Simpson, we explore a higher-dimensional variant, which asks for th...
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Bayesian Unbiasing of the Gaia Space Mission Time Series Database
21 st century astrophysicists are confronted with the herculean task of distilling the maximum scientific return from extremely expensive and complex space- or ground-based instrumental projects. This paper concentrates in the mining of the time series catalog produced by the European Space Agency Gaia mission, launc...
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On the connectivity of the hyperbolicity region of irreducible polynomials
We give an elementary proof for the fact that an irreducible hyperbolic polynomial has only one pair of hyperbolicity cones.
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Matrix Completion via Factorizing Polynomials
Predicting unobserved entries of a partially observed matrix has found wide applicability in several areas, such as recommender systems, computational biology, and computer vision. Many scalable methods with rigorous theoretical guarantees have been developed for algorithms where the matrix is factored into low-rank ...
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