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Propagation of self-localised Q-ball solitons in the $^3$He universe
In relativistic quantum field theories, compact objects of interacting bosons can become stable owing to conservation of an additive quantum number $Q$. Discovering such $Q$-balls propagating in the Universe would confirm supersymmetric extensions of the standard model and may shed light on the mysteries of dark matt...
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Improving the staggered grid Lagrangian hydrodynamics for modeling multi-material flows
In this work, we make two improvements on the staggered grid hydrodynamics (SGH) Lagrangian scheme for modeling 2-dimensional compressible multi-material flows on triangular mesh. The first improvement is the construction of a dynamic local remeshing scheme for preventing mesh distortion. The remeshing scheme is simi...
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Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins
Vehicle climate control systems aim to keep passengers thermally comfortable. However, current systems control temperature rather than thermal comfort and tend to be energy hungry, which is of particular concern when considering electric vehicles. This paper poses energy-efficient vehicle comfort control as a Markov ...
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A functional model for the Fourier--Plancherel operator truncated on the positive half-axis
The truncated Fourier operator $\mathscr{F}_{\mathbb{R^{+}}}$, $$ (\mathscr{F}_{\mathbb{R^{+}}}x)(t)=\frac{1}{\sqrt{2\pi}} \int\limits_{\mathbb{R^{+}}}x(\xi)e^{it\xi}\,d\xi\,,\ \ \ t\in{}{\mathbb{R^{+}}}, $$ is studied. The operator $\mathscr{F}_{\mathbb{R^{+}}}$ is considered as an operator acting in the space $L^2(...
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Mapping $n$ grid points onto a square forces an arbitrarily large Lipschitz constant
We prove that the regular $n\times n$ square grid of points in the integer lattice $\mathbb{Z}^{2}$ cannot be recovered from an arbitrary $n^{2}$-element subset of $\mathbb{Z}^{2}$ via a mapping with prescribed Lipschitz constant (independent of $n$). This answers negatively a question of Feige from 2002. Our resolut...
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An FPT algorithm for planar multicuts with sources and sinks on the outer face
Given a list of k source-sink pairs in an edge-weighted graph G, the minimum multicut problem consists in selecting a set of edges of minimum total weight in G, such that removing these edges leaves no path from each source to its corresponding sink. To the best of our knowledge, no non-trivial FPT result for special...
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Calibration with Bias-Corrected Temperature Scaling Improves Domain Adaptation Under Label Shift in Modern Neural Networks
Label shift refers to the phenomenon where the marginal probability p(y) of observing a particular class changes between the training and test distributions while the conditional probability p(x|y) stays fixed. This is relevant in settings such as medical diagnosis, where a classifier trained to predict disease based...
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Propagation Networks for Model-Based Control Under Partial Observation
There has been an increasing interest in learning dynamics simulators for model-based control. Compared with off-the-shelf physics engines, a learnable simulator can quickly adapt to unseen objects, scenes, and tasks. However, existing models like interaction networks only work for fully observable systems; they also...
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High-redshift galaxies and black holes in the eyes of JWST: a population synthesis model from infrared to X-rays
The first billion years of the Universe is a pivotal time: stars, black holes (BHs) and galaxies form and assemble, sowing the seeds of galaxies as we know them today. Detecting, identifying and understand- ing the first galaxies and BHs is one of the current observational and theoretical challenges in galaxy formati...
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Soft Label Memorization-Generalization for Natural Language Inference
Often when multiple labels are obtained for a training example it is assumed that there is an element of noise that must be accounted for. It has been shown that this disagreement can be considered signal instead of noise. In this work we investigate using soft labels for training data to improve generalization in ma...
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Floquet Topological Magnons
We introduce the concept of Floquet topological magnons --- a mechanism by which a synthetic tunable Dzyaloshinskii-Moriya interaction (DMI) can be generated in quantum magnets using circularly polarized electric (laser) field. The resulting effect is that Dirac magnons and nodal magnons in two-dimensional (2D) and t...
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Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
Inspired by recent interests of developing machine learning and data mining algorithms on hypergraphs, we investigate in this paper the semi-supervised learning algorithm of propagating "soft labels" (e.g. probability distributions, class membership scores) over hypergraphs, by means of optimal transportation. Borrow...
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Psychological and Personality Profiles of Political Extremists
Global recruitment into radical Islamic movements has spurred renewed interest in the appeal of political extremism. Is the appeal a rational response to material conditions or is it the expression of psychological and personality disorders associated with aggressive behavior, intolerance, conspiratorial imagination,...
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Techniques for Interpretable Machine Learning
Interpretable machine learning tackles the important problem that humans cannot understand the behaviors of complex machine learning models and how these models arrive at a particular decision. Although many approaches have been proposed, a comprehensive understanding of the achievements and challenges is still lacki...
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New Models and Methods for Formation and Analysis of Social Networks
This doctoral work focuses on three main problems related to social networks: (1) Orchestrating Network Formation: We consider the problem of orchestrating formation of a social network having a certain given topology that may be desirable for the intended usecases. Assuming the social network nodes to be strategic i...
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Identifying networks with common organizational principles
Many complex systems can be represented as networks, and the problem of network comparison is becoming increasingly relevant. There are many techniques for network comparison, from simply comparing network summary statistics to sophisticated but computationally costly alignment-based approaches. Yet it remains challe...
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Image-based Proof of Work Algorithm for the Incentivization of Blockchain Archival of Interesting Images
A new variation of blockchain proof of work algorithm is proposed to incentivize the timely execution of image processing algorithms. A sample image processing algorithm is proposed to determine interesting images using analysis of the entropy of pixel subsets within images. The efficacy of the image processing algor...
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Multi-Lane Perception Using Feature Fusion Based on GraphSLAM
An extensive, precise and robust recognition and modeling of the environment is a key factor for next generations of Advanced Driver Assistance Systems and development of autonomous vehicles. In this paper, a real-time approach for the perception of multiple lanes on highways is proposed. Lane markings detected by ca...
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Stability analysis and stabilization of LPV systems with jumps and (piecewise) differentiable parameters using continuous and sampled-data controllers
Linear Parameter-Varying (LPV) systems with jumps and piecewise differentiable parameters is a class of hybrid LPV systems for which no tailored stability analysis and stabilization conditions have been obtained so far. We fill this gap here by proposing an approach relying on the reformulation of the considered LPV ...
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Identity Testing and Interpolation from High Powers of Polynomials of Large Degree over Finite Fields
We consider the problem of identity testing and recovering (that is, interpolating) of a "hidden" monic polynomials $f$, given an oracle access to $f(x)^e$ for $x\in\mathbb F_q$, where $\mathbb F_q$ is the finite field of $q$ elements and an extension fields access is not permitted. The naive interpolation algorithm ...
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A bird's eye view on the flat and conic band world of the honeycomb and Kagome lattices: Towards an understanding of 2D Metal-Organic Frameworks electronic structure
We present a thorough tight-binding analysis of the band structure of a wide variety of lattices belonging to the class of honeycomb and Kagome systems including several mixed forms combining both lattices. The band structure of these systems are made of a combination of dispersive and flat bands. The dispersive band...
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Replacement AutoEncoder: A Privacy-Preserving Algorithm for Sensory Data Analysis
An increasing number of sensors on mobile, Internet of things (IoT), and wearable devices generate time-series measurements of physical activities. Though access to the sensory data is critical to the success of many beneficial applications such as health monitoring or activity recognition, a wide range of potentiall...
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Application of the Mixed Time-averaging Semiclassical Initial Value Representation method to Complex Molecular Spectra
The recently introduced mixed time-averaging semiclassical initial value representation molecular dynamics method for spectroscopic calculations [M. Buchholz, F. Grossmann, and M. Ceotto, J. Chem. Phys. 144, 094102 (2016)] is applied to systems with up to 61 dimensions, ruled by a condensed phase Caldeira-Leggett mod...
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Bounds on layer potentials with rough inputs for higher order elliptic equations
In this paper we establish square-function estimates on the double and single layer potentials with rough inputs for divergence form elliptic operators, of arbitrary even order 2m, with variable t-independent coefficients in the upper half-space.
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From support $τ$-tilting posets to algebras
The aim of this paper is to study a poset isomorphism between two support $\tau$-tilting posets. We take several algebraic information from combinatorial properties of support $\tau$-tilting posets. As an application, we treat a certain class of basic algebras which contains preprojective algebras of type $A$, Nakaya...
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Measuring the reionization 21 cm fluctuations using clustering wedges
One of the main challenges in probing the reionization epoch using the redshifted 21 cm line is that the magnitude of the signal is several orders smaller than the astrophysical foregrounds. One of the methods to deal with the problem is to avoid a wedge-shaped region in the Fourier $k_{\perp} - k_{\parallel}$ space ...
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Sensing-Constrained LQG Control
Linear-Quadratic-Gaussian (LQG) control is concerned with the design of an optimal controller and estimator for linear Gaussian systems with imperfect state information. Standard LQG assumes the set of sensor measurements, to be fed to the estimator, to be given. However, in many problems, arising in networked system...
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Deep Residual Learning for Instrument Segmentation in Robotic Surgery
Detection, tracking, and pose estimation of surgical instruments are crucial tasks for computer assistance during minimally invasive robotic surgery. In the majority of cases, the first step is the automatic segmentation of surgical tools. Prior work has focused on binary segmentation, where the objective is to label...
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Computing Constrained Approximate Equilibria in Polymatrix Games
This paper is about computing constrained approximate Nash equilibria in polymatrix games, which are succinctly represented many-player games defined by an interaction graph between the players. In a recent breakthrough, Rubinstein showed that there exists a small constant $\epsilon$, such that it is PPAD-complete to...
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Evolution in Groups: A deeper look at synaptic cluster driven evolution of deep neural networks
A promising paradigm for achieving highly efficient deep neural networks is the idea of evolutionary deep intelligence, which mimics biological evolution processes to progressively synthesize more efficient networks. A crucial design factor in evolutionary deep intelligence is the genetic encoding scheme used to simu...
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Polynomial Time and Sample Complexity for Non-Gaussian Component Analysis: Spectral Methods
The problem of Non-Gaussian Component Analysis (NGCA) is about finding a maximal low-dimensional subspace $E$ in $\mathbb{R}^n$ so that data points projected onto $E$ follow a non-gaussian distribution. Although this is an appropriate model for some real world data analysis problems, there has been little progress on...
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ARABIS: an Asynchronous Acoustic Indoor Positioning System for Mobile Devices
Acoustic ranging based indoor positioning solutions have the advantage of higher ranging accuracy and better compatibility with commercial-off-the-self consumer devices. However, similar to other time-domain based approaches using Time-of-Arrival and Time-Difference-of-Arrival, they suffer from performance degradatio...
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Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
Semi-supervised learning (SSL) provides a powerful framework for leveraging unlabeled data when labels are limited or expensive to obtain. SSL algorithms based on deep neural networks have recently proven successful on standard benchmark tasks. However, we argue that these benchmarks fail to address many issues that ...
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Recovering piecewise constant refractive indices by a single far-field pattern
We are concerned with the inverse scattering problem of recovering an inhomogeneous medium by the associated acoustic wave measurement. We prove that under certain assumptions, a single far-field pattern determines the values of a perturbation to the refractive index on the corners of its support. These assumptions a...
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On Bezout Inequalities for non-homogeneous Polynomial Ideals
We introduce a "workable" notion of degree for non-homogeneous polynomial ideals and formulate and prove ideal theoretic Bézout Inequalities for the sum of two ideals in terms of this notion of degree and the degree of generators. We compute probabilistically the degree of an equidimensional ideal.
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Joint Mixability of Elliptical Distributions and Related Families
In this paper, we further develop the theory of complete mixability and joint mixability for some distribution families. We generalize a result of Rüschendorf and Uckelmann (2002) related to complete mixability of continuous distribution function having a symmetric and unimodal density. Two different proofs to a resu...
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Secure uniform random number extraction via incoherent strategies
To guarantee the security of uniform random numbers generated by a quantum random number generator, we study secure extraction of uniform random numbers when the environment of a given quantum state is controlled by the third party, the eavesdropper. Here we restrict our operations to incoherent strategies that are c...
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Mobile Encryption Gateway (MEG) for Email Encryption
Email cryptography applications often suffer from major problems that prevent their widespread implementation. MEG, or the Mobile Encryption Gateway aims to fix the issues associated with email encryption by ensuring that encryption is easy to perform while still maintaining data security. MEG performs automatic decr...
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Nematic Skyrmions in Odd-Parity Superconductors
We study topological excitations in two-component nematic superconductors, with a particular focus on Cu$_x$Bi$_2$Se$_3$ as a candidate material. We find that the lowest-energy topological excitations are coreless vortices: a bound state of two spatially separated half-quantum vortices. These objects are nematic Skyr...
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Concentration and consistency results for canonical and curved exponential-family models of random graphs
Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional structure facilitates statistical inference. A simple example of a random graph with additional structure is a random graph with neighborh...
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Bayesian Network Learning via Topological Order
We propose a mixed integer programming (MIP) model and iterative algorithms based on topological orders to solve optimization problems with acyclic constraints on a directed graph. The proposed MIP model has a significantly lower number of constraints compared to popular MIP models based on cycle elimination constrai...
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The nature of the giant exomoon candidate Kepler-1625 b-i
The recent announcement of a Neptune-sized exomoon candidate around the transiting Jupiter-sized object Kepler-1625 b could indicate the presence of a hitherto unknown kind of gas giant moons, if confirmed. Three transits have been observed, allowing radius estimates of both objects. Here we investigate possible mass...
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Generative Adversarial Privacy
We present a data-driven framework called generative adversarial privacy (GAP). Inspired by recent advancements in generative adversarial networks (GANs), GAP allows the data holder to learn the privatization mechanism directly from the data. Under GAP, finding the optimal privacy mechanism is formulated as a constra...
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Hierarchical Modeling of Seed Variety Yields and Decision Making for Future Planting Plans
Eradicating hunger and malnutrition is a key development goal of the 21st century. We address the problem of optimally identifying seed varieties to reliably increase crop yield within a risk-sensitive decision-making framework. Specifically, we introduce a novel hierarchical machine learning mechanism for predicting...
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A Clinical and Finite Elements Study of Stress Urinary Incontinence in Women Using Fluid-Structure Interactions
Stress Urinary Incontinence (SUI) or urine leakage from urethra occurs due to an increase in abdominal pressure resulting from stress like a cough or jumping height. SUI is more frequent among post-menopausal women. In the absence of bladder contraction, vesical pressure exceeds from urethral pressure leading to urin...
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The n-term Approximation of Periodic Generalized Lévy Processes
In this paper, we study the compressibility of random processes and fields, called generalized Lévy processes, that are solutions of stochastic differential equations driven by $d$-dimensional periodic Lévy white noises. Our results are based on the estimation of the Besov regularity of Lévy white noises and generali...
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Sliced rotated sphere packing designs
Space-filling designs are popular choices for computer experiments. A sliced design is a design that can be partitioned into several subdesigns. We propose a new type of sliced space-filling design called sliced rotated sphere packing designs. Their full designs and subdesigns are rotated sphere packing designs. They...
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On the Convergence of Weighted AdaGrad with Momentum for Training Deep Neural Networks
Adaptive stochastic gradient descent methods, such as AdaGrad, RMSProp, Adam, AMSGrad, etc., have been demonstrated efficacious in solving non-convex stochastic optimization, such as training deep neural networks. However, their convergence rates have not been touched under the non-convex stochastic circumstance exce...
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Cyclic Dominance in the Spatial Coevolutionary Optional Prisoner's Dilemma Game
This paper studies scenarios of cyclic dominance in a coevolutionary spatial model in which game strategies and links between agents adaptively evolve over time. The Optional Prisoner's Dilemma (OPD) game is employed. The OPD is an extended version of the traditional Prisoner's Dilemma where players have a third opti...
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Analysis of universal adversarial perturbations
Deep networks have recently been shown to be vulnerable to universal perturbations: there exist very small image-agnostic perturbations that cause most natural images to be misclassified by such classifiers. In this paper, we propose the first quantitative analysis of the robustness of classifiers to universal pertur...
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Unsupervised and Semi-supervised Anomaly Detection with LSTM Neural Networks
We investigate anomaly detection in an unsupervised framework and introduce Long Short Term Memory (LSTM) neural network based algorithms. In particular, given variable length data sequences, we first pass these sequences through our LSTM based structure and obtain fixed length sequences. We then find a decision func...
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Wearable Health Monitoring Using Capacitive Voltage-Mode Human Body Communication
Rapid miniaturization and cost reduction of computing, along with the availability of wearable and implantable physiological sensors have led to the growth of human Body Area Network (BAN) formed by a network of such sensors and computing devices. One promising application of such a network is wearable health monitor...
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Electromagnetically Induced Transparency (EIT) and Autler-Townes (AT) splitting in the Presence of Band-Limited White Gaussian Noise
We investigate the effect of band-limited white Gaussian noise (BLWGN) on electromagnetically induced transparency (EIT) and Autler-Townes (AT) splitting, when performing atom-based continuous-wave (CW) radio-frequency (RF) electric (E) field strength measurements with Rydberg atoms in an atomic vapor. This EIT/AT-ba...
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SINR Outage Evaluation in Cellular Networks: Saddle Point Approximation (SPA) Using Normal Inverse Gaussian (NIG) Distribution
Signal-to-noise-plus-interference ratio (SINR) outage probability is among one of the key performance metrics of a wireless cellular network. In this paper, we propose a semi-analytical method based on saddle point approximation (SPA) technique to calculate the SINR outage of a wireless system whose SINR can be model...
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Smart grid modeling and simulation - Comparing GridLAB-D and RAPSim via two Case studies
One of the most important tools for the development of the smart grid is simulation. Therefore, analyzing, designing, modeling, and simulating the smart grid will allow to explore future scenarios and support decision making for the grid's development. In this paper, we compare two open source simulation tools for th...
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A Large-Scale CNN Ensemble for Medication Safety Analysis
Revealing Adverse Drug Reactions (ADR) is an essential part of post-marketing drug surveillance, and data from health-related forums and medical communities can be of a great significance for estimating such effects. In this paper, we propose an end-to-end CNN-based method for predicting drug safety on user comments ...
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Solutions to twisted word equations and equations in virtually free groups
It is well-known that the problem to solve equations in virtually free groups can be reduced to the problem to solve twisted word equations with regular constraints over free monoids with involution. In a first part of the paper we prove that the set of all solutions of such a twisted word equation is an EDT0L langua...
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DeepTransport: Learning Spatial-Temporal Dependency for Traffic Condition Forecasting
Predicting traffic conditions has been recently explored as a way to relieve traffic congestion. Several pioneering approaches have been proposed based on traffic observations of the target location as well as its adjacent regions, but they obtain somewhat limited accuracy due to lack of mining road topology. To addr...
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On Statistical Optimality of Variational Bayes
The article addresses a long-standing open problem on the justification of using variational Bayes methods for parameter estimation. We provide general conditions for obtaining optimal risk bounds for point estimates acquired from mean-field variational Bayesian inference. The conditions pertain to the existence of c...
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The Teichmüller Stack
This paper is a comprehensive introduction to the results of [7]. It grew as an expanded version of a talk given at INdAM Meeting Complex and Symplectic Geometry, held at Cortona in June 12-18, 2016. It deals with the construction of the Teichmüller space of a smooth compact manifold M (that is the space of isomorphi...
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On the Impact of Micro-Packages: An Empirical Study of the npm JavaScript Ecosystem
The rise of user-contributed Open Source Software (OSS) ecosystems demonstrate their prevalence in the software engineering discipline. Libraries work together by depending on each other across the ecosystem. From these ecosystems emerges a minimized library called a micro-package. Micro- packages become problematic ...
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Location and Orientation Optimisation for Spatially Stretched Tripole Arrays Based on Compressive Sensing
The design of sparse spatially stretched tripole arrays is an important but also challenging task and this paper proposes for the very first time efficient solutions to this problem. Unlike for the design of traditional sparse antenna arrays, the developed approaches optimise both the dipole locations and orientation...
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Hausdorff dimension of limsup sets of random rectangles in products of regular spaces
The almost sure Hausdorff dimension of the limsup set of randomly distributed rectangles in a product of Ahlfors regular metric spaces is computed in terms of the singular value function of the rectangles.
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Thermal Characterization of Microscale Heat Convection under Rare Gas Condition by a Modified Hot Wire Method
As power electronics shrinks down to sub-micron scale, the thermal transport from a solid surface to environment becomes significant. Under circumstances when the device works in rare gas environment, the scale for thermal transport is comparable to the mean free path of molecules, and is difficult to characterize. I...
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A summation formula for triples of quadratic spaces
Let $V_1,V_2,V_3$ be a triple of even dimensional vector spaces over a number field $F$ equipped with nondegenerate quadratic forms $\mathcal{Q}_1,\mathcal{Q}_2,\mathcal{Q}_3$, respectively. Let \begin{align*} Y \subset \prod_{i=1}V_i \end{align*} be the closed subscheme consisting of $(v_1,v_2,v_3)$ on which $\mathc...
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Designing Strassen's algorithm
In 1969, Strassen shocked the world by showing that two n x n matrices could be multiplied in time asymptotically less than $O(n^3)$. While the recursive construction in his algorithm is very clear, the key gain was made by showing that 2 x 2 matrix multiplication could be performed with only 7 multiplications instea...
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A Software-equivalent SNN Hardware using RRAM-array for Asynchronous Real-time Learning
Spiking Neural Network (SNN) naturally inspires hardware implementation as it is based on biology. For learning, spike time dependent plasticity (STDP) may be implemented using an energy efficient waveform superposition on memristor based synapse. However, system level implementation has three challenges. First, a cl...
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Max flow vitality in general and $st$-planar graphs
The \emph{vitality} of an arc/node of a graph with respect to the maximum flow between two fixed nodes $s$ and $t$ is defined as the reduction of the maximum flow caused by the removal of that arc/node. In this paper we address the issue of determining the vitality of arcs and/or nodes for the maximum flow problem. W...
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Between Homomorphic Signal Processing and Deep Neural Networks: Constructing Deep Algorithms for Polyphonic Music Transcription
This paper presents a new approach in understanding how deep neural networks (DNNs) work by applying homomorphic signal processing techniques. Focusing on the task of multi-pitch estimation (MPE), this paper demonstrates the equivalence relation between a generalized cepstrum and a DNN in terms of their structures an...
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Negative membrane capacitance of outer hair cells: electromechanical coupling near resonance
The ability of the mammalian ear in processing high frequency sounds, up to $\sim$100 kHz, is based on the capability of outer hair cells (OHCs) responding to stimulation at high frequencies. These cells show a unique motility in their cell body coupled with charge movement. With this motile element, voltage changes ...
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Resonant inelastic x-ray scattering operators for $t_{2g}$ orbital systems
We derive general expressions for resonant inelastic x-ray scattering (RIXS) operators for $t_{2g}$ orbital systems, which exhibit a rich array of unconventional magnetism arising from unquenched orbital moments. Within the fast collision approximation, which is valid especially for 4$d$ and 5$d$ transition metal com...
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Hamiltonian Path in Split Graphs- a Dichotomy
In this paper, we investigate Hamiltonian path problem in the context of split graphs, and produce a dichotomy result on the complexity of the problem. Our main result is a deep investigation of the structure of $K_{1,4}$-free split graphs in the context of Hamiltonian path problem, and as a consequence, we obtain a ...
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Design Patterns for Fusion-Based Object Retrieval
We address the task of ranking objects (such as people, blogs, or verticals) that, unlike documents, do not have direct term-based representations. To be able to match them against keyword queries, evidence needs to be amassed from documents that are associated with the given object. We present two design patterns, i...
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Early Routability Assessment in VLSI Floorplans: A Generalized Routing Model
Multiple design iterations are inevitable in nanometer Integrated Circuit (IC) design flow until desired printability and performance metrics are achieved. This starts with placement optimization aimed at improving routability, wirelength, congestion and timing in the design. Contrarily, no such practice exists on a ...
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Inverse Ising problem in continuous time: A latent variable approach
We consider the inverse Ising problem, i.e. the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form, which allows for simple iterative inference algorithms wi...
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Analysis of the flux growth rate in emerging active regions on the Sun
We studied the emergence process of 42 active region (ARs) by analyzing the time derivative, R(t), of the total unsigned flux. Line-of-sight magnetograms acquired by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) were used. A continuous piecewise linear fitting to the R(t)-pro...
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Porosity and Differentiability of Lipschitz Maps from Stratified Groups to Banach Homogeneous Groups
Let $f$ be a Lipschitz map from a subset $A$ of a stratified group to a Banach homogeneous group. We show that directional derivatives of $f$ act as homogeneous homomorphisms at density points of $A$ outside a $\sigma$-porous set. At density points of $A$ we establish a pointwise characterization of differentiability...
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A Structured Learning Approach with Neural Conditional Random Fields for Sleep Staging
Sleep plays a vital role in human health, both mental and physical. Sleep disorders like sleep apnea are increasing in prevalence, with the rapid increase in factors like obesity. Sleep apnea is most commonly treated with Continuous Positive Air Pressure (CPAP) therapy. Presently, however, there is no mechanism to mo...
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Dominant dimension and tilting modules
We study which algebras have tilting modules that are both generated and cogenerated by projective-injective modules. Crawley-Boevey and Sauter have shown that Auslander algebras have such tilting modules; and for algebras of global dimension $2$, Auslander algebras are classified by the existence of such tilting mod...
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Fast and Accurate 3D Medical Image Segmentation with Data-swapping Method
Deep neural network models used for medical image segmentation are large because they are trained with high-resolution three-dimensional (3D) images. Graphics processing units (GPUs) are widely used to accelerate the trainings. However, the memory on a GPU is not large enough to train the models. A popular approach t...
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Direct Optical Visualization of Water Transport across Polymer Nano-films
Gaining a detailed understanding of water transport behavior through ultra-thin polymer membranes is increasingly becoming necessary due to the recent interest in exploring applications such as water desalination using nanoporous membranes. Current techniques only measure bulk water transport rates and do not offer d...
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Hyperbolicity cones and imaginary projections
Recently, the authors and de Wolff introduced the imaginary projection of a polynomial $f\in\mathbb{C}[\mathbf{z}]$ as the projection of the variety of $f$ onto its imaginary part, $\mathcal{I}(f) \ = \ \{\text{Im}(\mathbf{z}) \, : \, \mathbf{z} \in \mathcal{V}(f) \}$. Since a polynomial $f$ is stable if and only if ...
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Fairness-aware Classification: Criterion, Convexity, and Bounds
Fairness-aware classification is receiving increasing attention in the machine learning fields. Recently research proposes to formulate the fairness-aware classification as constrained optimization problems. However, several limitations exist in previous works due to the lack of a theoretical framework for guiding th...
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Optimal Rates for Community Estimation in the Weighted Stochastic Block Model
Community identification in a network is an important problem in fields such as social science, neuroscience, and genetics. Over the past decade, stochastic block models (SBMs) have emerged as a popular statistical framework for this problem. However, SBMs have an important limitation in that they are suited only for...
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On Sound Relative Error Bounds for Floating-Point Arithmetic
State-of-the-art static analysis tools for verifying finite-precision code compute worst-case absolute error bounds on numerical errors. These are, however, often not a good estimate of accuracy as they do not take into account the magnitude of the computed values. Relative errors, which compute errors relative to th...
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Light yield determination in large sodium iodide detectors applied in the search for dark matter
Application of NaI(Tl) detectors in the search for galactic dark matter particles through their elastic scattering off the target nuclei is well motivated because of the long standing DAMA/LIBRA highly significant positive result on annual modulation, still requiring confirmation. For such a goal, it is mandatory to ...
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A Systematic Approach to Numerical Dispersion in Maxwell Solvers
The finite-difference time-domain (FDTD) method is a well established method for solving the time evolution of Maxwell's equations. Unfortunately the scheme introduces numerical dispersion and therefore phase and group velocities which deviate from the correct values. The solution to Maxwell's equations in more than ...
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On Synchronous, Asynchronous, and Randomized Best-Response schemes for computing equilibria in Stochastic Nash games
This work considers a stochastic Nash game in which each player solves a parameterized stochastic optimization problem. In deterministic regimes, best-response schemes have been shown to be convergent under a suitable spectral property associated with the proximal best-response map. However, a direct application of t...
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On the insertion of n-powers
In algebraic terms, the insertion of $n$-powers in words may be modelled at the language level by considering the pseudovariety of ordered monoids defined by the inequality $1\le x^n$. We compare this pseudovariety with several other natural pseudovarieties of ordered monoids and of monoids associated with the Burnsi...
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The TUS detector of extreme energy cosmic rays on board the Lomonosov satellite
The origin and nature of extreme energy cosmic rays (EECRs), which have energies above the 50 EeV, the Greisen-Zatsepin-Kuzmin (GZK) energy limit, is one of the most interesting and complicated problems in modern cosmic-ray physics. Existing ground-based detectors have helped to obtain remarkable results in studying ...
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New ellipsometric approach for determining small light ellipticities
We propose a precise ellipsometric method for the investigation of coherent light with a small ellipticity. The main feature of this method is the use of compensators with phase delays providing the maximum accuracy of measurements for the selected range of ellipticities and taking into account the interference of mu...
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Maximizing the Mutual Information of Multi-Antenna Links Under an Interfered Receiver Power Constraint
Single-user multiple-input / multiple-output (SU-MIMO) communication systems have been successfully used over the years and have provided a significant increase on a wireless link's capacity by enabling the transmission of multiple data streams. Assuming channel knowledge at the transmitter, the maximization of the m...
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Multistationarity and Bistability for Fewnomial Chemical Reaction Networks
Bistability and multistationarity are properties of reaction networks linked to switch-like responses and connected to cell memory and cell decision making. Determining whether and when a network exhibits bistability is a hard and open mathematical problem. One successful strategy consists of analyzing small networks...
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Erratum: Link prediction in drug-target interactions network using similarity indices
Background: In silico drug-target interaction (DTI) prediction plays an integral role in drug repositioning: the discovery of new uses for existing drugs. One popular method of drug repositioning is network-based DTI prediction, which uses complex network theory to predict DTIs from a drug-target network. Currently, ...
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Variable Selection for Highly Correlated Predictors
Penalty-based variable selection methods are powerful in selecting relevant covariates and estimating coefficients simultaneously. However, variable selection could fail to be consistent when covariates are highly correlated. The partial correlation approach has been adopted to solve the problem with correlated covar...
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Scraping and Preprocessing Commercial Auction Data for Fraud Classification
In the last three decades, we have seen a significant increase in trading goods and services through online auctions. However, this business created an attractive environment for malicious moneymakers who can commit different types of fraud activities, such as Shill Bidding (SB). The latter is predominant across many...
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Batch Size Influence on Performance of Graphic and Tensor Processing Units during Training and Inference Phases
The impact of the maximally possible batch size (for the better runtime) on performance of graphic processing units (GPU) and tensor processing units (TPU) during training and inference phases is investigated. The numerous runs of the selected deep neural network (DNN) were performed on the standard MNIST and Fashion...
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Minimax Euclidean Separation Rates for Testing Convex Hypotheses in $\mathbb{R}^d$
We consider composite-composite testing problems for the expectation in the Gaussian sequence model where the null hypothesis corresponds to a convex subset $\mathcal{C}$ of $\mathbb{R}^d$. We adopt a minimax point of view and our primary objective is to describe the smallest Euclidean distance between the null and a...
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Simple Policy Evaluation for Data-Rich Iterative Tasks
A data-based policy for iterative control task is presented. The proposed strategy is model-free and can be applied whenever safe input and state trajectories of a system performing an iterative task are available. These trajectories, together with a user-defined cost function, are exploited to construct a piecewise ...
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Proper quadrics in the Euclidean $n$-space
In this paper we investigate the metric properties of quadrics and cones of the $n$-dimensional Euclidean space. As applications of our formulas we give a more detailed description of the construction of Chasles and the wire model of Staude, respectively.
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