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201
Jastrow form of the Ground State Wave Functions for Fractional Quantum Hall States
The topological morphology--order of zeros at the positions of electrons with respect to a specific electron--of Laughlin state at filling fractions $1/m$ ($m$ odd) is homogeneous as every electron feels zeros of order $m$ at the positions of other electrons. Although fairly accurate ground state wave functions for m...
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202
On a common refinement of Stark units and Gross-Stark units
The purpose of this paper is to formulate and study a common refinement of a version of Stark's conjecture and its $p$-adic analogue, in terms of Fontaine's $p$-adic period ring and $p$-adic Hodge theory. We construct period-ring-valued functions under a generalization of Yoshida's conjecture on the transcendental pa...
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203
An Integrated Decision and Control Theoretic Solution to Multi-Agent Co-Operative Search Problems
This paper considers the problem of autonomous multi-agent cooperative target search in an unknown environment using a decentralized framework under a no-communication scenario. The targets are considered as static targets and the agents are considered to be homogeneous. The no-communication scenario translates as th...
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204
Chain effects of clean water: The Mills-Reincke phenomenon in early twentieth-century Japan
This study explores the validity of chain effects of clean water, which are known as the "Mills-Reincke phenomenon," in early twentieth-century Japan. Recent studies have reported that water purifications systems are responsible for huge contributions to human capital. Although a few studies have investigated the sho...
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205
Learning Transferable Architectures for Scalable Image Recognition
Developing neural network image classification models often requires significant architecture engineering. In this paper, we study a method to learn the model architectures directly on the dataset of interest. As this approach is expensive when the dataset is large, we propose to search for an architectural building ...
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206
Fast Multi-frame Stereo Scene Flow with Motion Segmentation
We propose a new multi-frame method for efficiently computing scene flow (dense depth and optical flow) and camera ego-motion for a dynamic scene observed from a moving stereo camera rig. Our technique also segments out moving objects from the rigid scene. In our method, we first estimate the disparity map and the 6-...
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207
Pointed $p^2q$-dimensional Hopf algebras in positive characteristic
Let $\K$ be an algebraically closed field of positive characteristic $p$. We mainly classify pointed Hopf algebras over $\K$ of dimension $p^2q$, $pq^2$ and $pqr$ where $p,q,r$ are distinct prime numbers. We obtain a complete classification of such Hopf algebras except two subcases when they are not generated by the ...
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208
Weak Form of Stokes-Dirac Structures and Geometric Discretization of Port-Hamiltonian Systems
We present the mixed Galerkin discretization of distributed parameter port-Hamiltonian systems. On the prototypical example of hyperbolic systems of two conservation laws in arbitrary spatial dimension, we derive the main contributions: (i) A weak formulation of the underlying geometric (Stokes-Dirac) structure with ...
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209
Clamped seismic metamaterials: Ultra-low broad frequency stop-bands
The regularity of earthquakes, their destructive power, and the nuisance of ground vibration in urban environments, all motivate designs of defence structures to lessen the impact of seismic and ground vibration waves on buildings. Low frequency waves, in the range $1$ to $10$ Hz for earthquakes and up to a few tens ...
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210
Difference analogue of second main theorems for meromorphic mapping into algebraic variety
In this paper, we prove some difference analogue of second main theorems of meromorphic mapping from Cm into an algebraic variety V intersecting a finite set of fixed hypersurfaces in subgeneral position. As an application, we prove a result on algebraically degenerate of holomorphic curves intersecting hypersurfaces...
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211
An Effective Way to Improve YouTube-8M Classification Accuracy in Google Cloud Platform
Large-scale datasets have played a significant role in progress of neural network and deep learning areas. YouTube-8M is such a benchmark dataset for general multi-label video classification. It was created from over 7 million YouTube videos (450,000 hours of video) and includes video labels from a vocabulary of 4716...
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212
Experimental Design of a Prescribed Burn Instrumentation
Observational data collected during experiments, such as the planned Fire and Smoke Model Evaluation Experiment (FASMEE), are critical for progressing and transitioning coupled fire-atmosphere models like WRF-SFIRE and WRF-SFIRE-CHEM into operational use. Historical meteorological data, representing typical weather c...
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213
Seifert surgery on knots via Reidemeister torsion and Casson-Walker-Lescop invariant III
For a knot $K$ in a homology $3$-sphere $\Sigma$, let $M$ be the result of $2/q$-surgery on $K$, and let $X$ be the universal abelian covering of $M$. Our first theorem is that if the first homology of $X$ is finite cyclic and $M$ is a Seifert fibered space with $N\ge 3$ singular fibers, then $N\ge 4$ if and only if ...
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214
Sparse mean localization by information theory
Sparse feature selection is necessary when we fit statistical models, we have access to a large group of features, don't know which are relevant, but assume that most are not. Alternatively, when the number of features is larger than the available data the model becomes over parametrized and the sparse feature select...
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215
Joint Power and Admission Control based on Channel Distribution Information: A Novel Two-Timescale Approach
In this letter, we consider the joint power and admission control (JPAC) problem by assuming that only the channel distribution information (CDI) is available. Under this assumption, we formulate a new chance (probabilistic) constrained JPAC problem, where the signal to interference plus noise ratio (SINR) outage pro...
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216
A Closer Look at the Alpha Persei Coronal Conundrum
A ROSAT survey of the Alpha Per open cluster in 1993 detected its brightest star, mid-F supergiant Alpha Persei: the X-ray luminosity and spectral hardness were similar to coronally active late-type dwarf members. Later, in 2010, a Hubble Cosmic Origins Spectrograph SNAPshot of Alpha Persei found far-ultraviolet coro...
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217
The challenge of realistic music generation: modelling raw audio at scale
Realistic music generation is a challenging task. When building generative models of music that are learnt from data, typically high-level representations such as scores or MIDI are used that abstract away the idiosyncrasies of a particular performance. But these nuances are very important for our perception of music...
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218
Interpretations of family size distributions: The Datura example
Young asteroid families are unique sources of information about fragmentation physics and the structure of their parent bodies, since their physical properties have not changed much since their birth. Families have different properties such as age, size, taxonomy, collision severity and others, and understanding the ...
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219
Intersections of $ω$ classes in $\overline{\mathcal{M}}_{g,n}$
We provide a graph formula which describes an arbitrary monomial in {\omega} classes (also referred to as stable {\psi} classes) in terms of a simple family of dual graphs (pinwheel graphs) with edges decorated by rational functions in {\psi} classes. We deduce some numerical consequences and in particular a combinat...
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220
GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging
Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure...
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221
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Generative Adversarial Networks (GANs) excel at creating realistic images with complex models for which maximum likelihood is infeasible. However, the convergence of GAN training has still not been proved. We propose a two time-scale update rule (TTUR) for training GANs with stochastic gradient descent on arbitrary G...
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222
SPIRou Input Catalog: Activity, Rotation and Magnetic Field of Cool Dwarfs
Based on optical high-resolution spectra obtained with CFHT/ESPaDOnS, we present new measurements of activity and magnetic field proxies of 442 low-mass K5-M7 dwarfs. The objects were analysed as potential targets to search for planetary-mass companions with the new spectropolarimeter and high-precision velocimeter, ...
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223
Objective Procedure for Reconstructing Couplings in Complex Systems
Inferring directional connectivity from point process data of multiple elements is desired in various scientific fields such as neuroscience, geography, economics, etc. Here, we propose an inference procedure for this goal based on the kinetic Ising model. The procedure is composed of two steps: (1) determination of ...
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224
Iteratively-Reweighted Least-Squares Fitting of Support Vector Machines: A Majorization--Minimization Algorithm Approach
Support vector machines (SVMs) are an important tool in modern data analysis. Traditionally, support vector machines have been fitted via quadratic programming, either using purpose-built or off-the-shelf algorithms. We present an alternative approach to SVM fitting via the majorization--minimization (MM) paradigm. A...
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225
Time-Series Adaptive Estimation of Vaccination Uptake Using Web Search Queries
Estimating vaccination uptake is an integral part of ensuring public health. It was recently shown that vaccination uptake can be estimated automatically from web data, instead of slowly collected clinical records or population surveys. All prior work in this area assumes that features of vaccination uptake collected...
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226
Over Recurrence for Mixing Transformations
We show that every invertible strong mixing transformation on a Lebesgue space has strictly over-recurrent sets. Also, we give an explicit procedure for constructing strong mixing transformations with no under-recurrent sets. This answers both parts of a question of V. Bergelson. We define $\epsilon$-over-recurrence ...
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227
Joint Atlas-Mapping of Multiple Histological Series combined with Multimodal MRI of Whole Marmoset Brains
Development of a mesoscale neural circuitry map of the common marmoset is an essential task due to the ideal characteristics of the marmoset as a model organism for neuroscience research. To facilitate this development there is a need for new computational tools to cross-register multi-modal data sets containing MRI ...
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228
A Practical Approach for Successive Omniscience
The system that we study in this paper contains a set of users that observe a discrete memoryless multiple source and communicate via noise-free channels with the aim of attaining omniscience, the state that all users recover the entire multiple source. We adopt the concept of successive omniscience (SO), i.e., letti...
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229
Scholars on Twitter: who and how many are they?
In this paper we present a novel methodology for identifying scholars with a Twitter account. By combining bibliometric data from Web of Science and Twitter users identified by Altmetric.com we have obtained the largest set of individual scholars matched with Twitter users made so far. Our methodology consists of a c...
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230
General notions of regression depth function
As a measure for the centrality of a point in a set of multivariate data, statistical depth functions play important roles in multivariate analysis, because one may conveniently construct descriptive as well as inferential procedures relying on them. Many depth notions have been proposed in the literature to fit to d...
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231
Photonic topological pumping through the edges of a dynamical four-dimensional quantum Hall system
When a two-dimensional electron gas is exposed to a perpendicular magnetic field and an in-plane electric field, its conductance becomes quantized in the transverse in-plane direction: this is known as the quantum Hall (QH) effect. This effect is a result of the nontrivial topology of the system's electronic band str...
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232
On Scalable Inference with Stochastic Gradient Descent
In many applications involving large dataset or online updating, stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates and has gained increasing popularity due to its numerical convenience and memory efficiency. While the asymptotic properties of SGD-based estimators have been estab...
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233
The g-Good-Neighbor Conditional Diagnosability of Locally Twisted Cubes
In the work of Peng et al. in 2012, a new measure was proposed for fault diagnosis of systems: namely, g-good-neighbor conditional diagnosability, which requires that any fault-free vertex has at least g fault-free neighbors in the system. In this paper, we establish the g-good-neighbor conditional diagnosability of ...
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234
Coherence for lenses and open games
Categories of polymorphic lenses in computer science, and of open games in compositional game theory, have a curious structure that is reminiscent of compact closed categories, but differs in some crucial ways. Specifically they have a family of morphisms that behave like the counits of a compact closed category, but...
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235
Streaming Algorithm for Euler Characteristic Curves of Multidimensional Images
We present an efficient algorithm to compute Euler characteristic curves of gray scale images of arbitrary dimension. In various applications the Euler characteristic curve is used as a descriptor of an image. Our algorithm is the first streaming algorithm for Euler characteristic curves. The usage of streaming remov...
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236
An automata group of intermediate growth and exponential activity
We give a new example of an automata group of intermediate growth. It is generated by an automaton with 4 states on an alphabet with 8 letters. This automata group has exponential activity and its limit space is not simply connected.
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237
Tuning across the BCS-BEC crossover in the multiband superconductor Fe$_{1+y}$Se$_x$Te$_{1-x}$ : An angle-resolved photoemission study
The crossover from Bardeen-Cooper-Schrieffer (BCS) superconductivity to Bose-Einstein condensation (BEC) is difficult to realize in quantum materials because, unlike in ultracold atoms, one cannot tune the pairing interaction. We realize the BCS-BEC crossover in a nearly compensated semimetal Fe$_{1+y}$Se$_x$Te$_{1-x...
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238
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Model compression is essential for serving large deep neural nets on devices with limited resources or applications that require real-time responses. As a case study, a state-of-the-art neural language model usually consists of one or more recurrent layers sandwiched between an embedding layer used for representing i...
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239
Morphological characterization of Ge ion implanted SiO2 matrix using multifractal technique
200 nm thick SiO2 layers grown on Si substrates and Ge ions of 150 keV energy were implanted into SiO2 matrix with Different fluences. The implanted samples were annealed at 950 C for 30 minutes in Ar ambience. Topographical studies of implanted as well as annealed samples were captured by the atomic force microscopy...
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240
Preliminary corrosion studies of IN-RAFM steel with stagnant Lead Lithium at 550 C
Corrosion of Indian RAFMS (reduced activation ferritic martensitic steel) material with liquid metal, Lead Lithium ( Pb-Li) has been studied under static condition, maintaining Pb-Li at 550 C for different time durations, 2500, 5000 and 9000 hours. Corrosion rate was calculated from weight loss measurements. Microstr...
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241
Magnetocapillary self-assemblies: locomotion and micromanipulation along a liquid interface
This paper presents an overview and discussion of magnetocapillary self-assemblies. New results are presented, in particular concerning the possible development of future applications. These self-organizing structures possess the notable ability to move along an interface when powered by an oscillatory, uniform magne...
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242
On asymptotically minimax nonparametric detection of signal in Gaussian white noise
For the problem of nonparametric detection of signal in Gaussian white noise we point out strong asymptotically minimax tests. The sets of alternatives are a ball in Besov space $B^r_{2\infty}$ with "small" balls in $L_2$ removed.
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243
Bayesian Metabolic Flux Analysis reveals intracellular flux couplings
Metabolic flux balance analyses are a standard tool in analysing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place unrealistic assumptions on fluxes due to the convenience of formulating the problem as a linear pr...
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244
Robust Estimation of Change-Point Location
We introduce a robust estimator of the location parameter for the change-point in the mean based on the Wilcoxon statistic and establish its consistency for $L_1$ near epoch dependent processes. It is shown that the consistency rate depends on the magnitude of change. A simulation study is performed to evaluate finit...
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245
Growing length scale accompanying the vitrification: A perspective based on non-singular density fluctuations
In glass forming liquids close to the glass transition point, even a very slight increase in the macroscopic density results in a dramatic slowing down of the macroscopic relaxation. Concomitantly, the local density itself fluctuates in space. Therefore, one can imagine that even very small local density variations c...
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246
Many-Objective Pareto Local Search
We propose a new Pareto Local Search Algorithm for the many-objective combinatorial optimization. Pareto Local Search proved to be a very effective tool in the case of the bi-objective combinatorial optimization and it was used in a number of the state-of-the-art algorithms for problems of this kind. On the other han...
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247
From Natural to Artificial Camouflage: Components and Systems
We identify the components of bio-inspired artificial camouflage systems including actuation, sensing, and distributed computation. After summarizing recent results in understanding the physiology and system-level performance of a variety of biological systems, we describe computational algorithms that can generate s...
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248
Bayesian nonparametric inference for the M/G/1 queueing systems based on the marked departure process
In the present work we study Bayesian nonparametric inference for the continuous-time M/G/1 queueing system. In the focus of the study is the unobservable service time distribution. We assume that the only available data of the system are the marked departure process of customers with the marks being the queue length...
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249
On some polynomials and series of Bloch-Polya Type
We will show that $(1-q)(1-q^2)\dots (1-q^m)$ is a polynomial in $q$ with coefficients from $\{-1,0,1\}$ iff $m=1,\ 2,\ 3,$ or $5$ and explore some interesting consequences of this result. We find explicit formulas for the $q$-series coefficients of $(1-q^2)(1-q^3)(1-q^4)(1-q^5)\dots$ and $(1-q^3)(1-q^4)(1-q^5)(1-q^6...
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250
Improvement in the UAV position estimation with low-cost GPS, INS and vision-based system: Application to a quadrotor UAV
In this paper, we develop a position estimation system for Unmanned Aerial Vehicles formed by hardware and software. It is based on low-cost devices: GPS, commercial autopilot sensors and dense optical flow algorithm implemented in an onboard microcomputer. Comparative tests were conducted using our approach and the ...
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251
Structured low rank decomposition of multivariate Hankel matrices
We study the decomposition of a multivariate Hankel matrix H\_$\sigma$ as a sum of Hankel matrices of small rank in correlation with the decomposition of its symbol $\sigma$ as a sum of polynomial-exponential series. We present a new algorithm to compute the low rank decomposition of the Hankel operator and the decom...
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252
Linear time-periodic dynamical systems: An H2 analysis and a model reduction framework
Linear time-periodic (LTP) dynamical systems frequently appear in the modeling of phenomena related to fluid dynamics, electronic circuits, and structural mechanics via linearization centered around known periodic orbits of nonlinear models. Such LTP systems can reach orders that make repeated simulation or other nec...
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253
Software metadata: How much is enough?
Broad efforts are underway to capture metadata about research software and retain it across services; notable in this regard is the CodeMeta project. What metadata are important to have about (research) software? What metadata are useful for searching for codes? What would you like to learn about astronomy software? ...
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254
A Categorical Approach for Recognizing Emotional Effects of Music
Recently, digital music libraries have been developed and can be plainly accessed. Latest research showed that current organization and retrieval of music tracks based on album information are inefficient. Moreover, they demonstrated that people use emotion tags for music tracks in order to search and retrieve them. ...
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255
Utilizing artificial neural networks to predict demand for weather-sensitive products at retail stores
One key requirement for effective supply chain management is the quality of its inventory management. Various inventory management methods are typically employed for different types of products based on their demand patterns, product attributes, and supply network. In this paper, our goal is to develop robust demand ...
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256
Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry
We propose a deformable generator model to disentangle the appearance and geometric information from images into two independent latent vectors. The appearance generator produces the appearance information, including color, illumination, identity or category, of an image. The geometric generator produces displacement...
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257
Gaussian Kernel in Quantum Paradigm
The Gaussian kernel is a very popular kernel function used in many machine-learning algorithms, especially in support vector machines (SVM). For nonlinear training instances in machine learning, it often outperforms polynomial kernels in model accuracy. We use Gaussian kernel profoundly in formulating nonlinear class...
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258
Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems
Security, privacy, and fairness have become critical in the era of data science and machine learning. More and more we see that achieving universally secure, private, and fair systems is practically impossible. We have seen for example how generative adversarial networks can be used to learn about the expected privat...
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259
Performance of Energy Harvesting Receivers with Power Optimization
The difficulty of modeling energy consumption in communication systems leads to challenges in energy harvesting (EH) systems, in which nodes scavenge energy from their environment. An EH receiver must harvest enough energy for demodulating and decoding. The energy required depends upon factors, like code rate and sig...
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260
On Convergence Rate of a Continuous-Time Distributed Self-Appraisal Model with Time-Varying Relative Interaction Matrices
This paper studies a recently proposed continuous-time distributed self-appraisal model with time-varying interactions among a network of $n$ individuals which are characterized by a sequence of time-varying relative interaction matrices. The model describes the evolution of the social-confidence levels of the indivi...
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261
Closing the loop on multisensory interactions: A neural architecture for multisensory causal inference and recalibration
When the brain receives input from multiple sensory systems, it is faced with the question of whether it is appropriate to process the inputs in combination, as if they originated from the same event, or separately, as if they originated from distinct events. Furthermore, it must also have a mechanism through which i...
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262
Block CUR: Decomposing Matrices using Groups of Columns
A common problem in large-scale data analysis is to approximate a matrix using a combination of specifically sampled rows and columns, known as CUR decomposition. Unfortunately, in many real-world environments, the ability to sample specific individual rows or columns of the matrix is limited by either system constra...
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263
Synchronous Observation on the Spontaneous Transformation of Liquid Metal under Free Falling Microgravity Situation
The unusually high surface tension of room temperature liquid metal is molding it as unique material for diverse newly emerging areas. However, unlike its practices on earth, such metal fluid would display very different behaviors when working in space where gravity disappears and surface property dominates the major...
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264
Continuously tempered Hamiltonian Monte Carlo
Hamiltonian Monte Carlo (HMC) is a powerful Markov chain Monte Carlo (MCMC) method for performing approximate inference in complex probabilistic models of continuous variables. In common with many MCMC methods, however, the standard HMC approach performs poorly in distributions with multiple isolated modes. We presen...
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265
Automated Synthesis of Safe Digital Controllers for Sampled-Data Stochastic Nonlinear Systems
We present a new method for the automated synthesis of digital controllers with formal safety guarantees for systems with nonlinear dynamics, noisy output measurements, and stochastic disturbances. Our method derives digital controllers such that the corresponding closed-loop system, modeled as a sampled-data stochas...
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266
Magnus integrators on multicore CPUs and GPUs
In the present paper we consider numerical methods to solve the discrete Schrödinger equation with a time dependent Hamiltonian (motivated by problems encountered in the study of spin systems). We will consider both short-range interactions, which lead to evolution equations involving sparse matrices, and long-range ...
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267
High Dimensional Estimation and Multi-Factor Models
This paper re-investigates the estimation of multiple factor models relaxing the convention that the number of factors is small and using a new approach for identifying factors. We first obtain the collection of all possible factors and then provide a simultaneous test, security by security, of which factors are sign...
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268
Scaling Law for Three-body Collisions in Identical Fermions with $p$-wave Interactions
We experimentally confirmed the threshold behavior and scattering length scaling law of the three-body loss coefficients in an ultracold spin-polarized gas of $^6$Li atoms near a $p$-wave Feshbach resonance. We measured the three-body loss coefficients as functions of temperature and scattering volume, and found that...
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269
An Expanded Local Variance Gamma model
The paper proposes an expanded version of the Local Variance Gamma model of Carr and Nadtochiy by adding drift to the governing underlying process. Still in this new model it is possible to derive an ordinary differential equation for the option price which plays a role of Dupire's equation for the standard local vol...
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270
An attentive neural architecture for joint segmentation and parsing and its application to real estate ads
In processing human produced text using natural language processing (NLP) techniques, two fundamental subtasks that arise are (i) segmentation of the plain text into meaningful subunits (e.g., entities), and (ii) dependency parsing, to establish relations between subunits. In this paper, we develop a relatively simpl...
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271
Multilevel maximum likelihood estimation with application to covariance matrices
The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of covariance models to the sample, which is important in data assimilation. The hierarch...
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272
Auto-Meta: Automated Gradient Based Meta Learner Search
Fully automating machine learning pipelines is one of the key challenges of current artificial intelligence research, since practical machine learning often requires costly and time-consuming human-powered processes such as model design, algorithm development, and hyperparameter tuning. In this paper, we verify that ...
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273
Convergence of the Forward-Backward Algorithm: Beyond the Worst Case with the Help of Geometry
We provide a comprehensive study of the convergence of forward-backward algorithm under suitable geometric conditions leading to fast rates. We present several new results and collect in a unified view a variety of results scattered in the literature, often providing simplified proofs. Novel contributions include the...
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274
Calibration-Free Relaxation-Based Multi-Color Magnetic Particle Imaging
Magnetic Particle Imaging (MPI) is a novel imaging modality with important applications such as angiography, stem cell tracking, and cancer imaging. Recently, there have been efforts to increase the functionality of MPI via multi-color imaging methods that can distinguish the responses of different nanoparticles, or ...
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275
Neural Machine Translation
Draft of textbook chapter on neural machine translation. a comprehensive treatment of the topic, ranging from introduction to neural networks, computation graphs, description of the currently dominant attentional sequence-to-sequence model, recent refinements, alternative architectures and challenges. Written as chap...
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276
On algebraically integrable domains in Euclidean spaces
Let $D$ be a bounded domain $D$ in $\mathbb R^n $ with infinitely smooth boundary and $n$ is odd. We prove that if the volume cut off from the domain by a hyperplane is an algebraic function of the hyperplane, free of real singular points, then the domain is an ellipsoid. This partially answers a question of V.I. Arn...
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277
Vocabulary-informed Extreme Value Learning
The novel unseen classes can be formulated as the extreme values of known classes. This inspired the recent works on open-set recognition \cite{Scheirer_2013_TPAMI,Scheirer_2014_TPAMIb,EVM}, which however can have no way of naming the novel unseen classes. To solve this problem, we propose the Extreme Value Learning ...
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278
Cross-layer optimized routing with low duty cycle TDMA across multiple wireless body area networks
In this paper, we study the performance of two cross-layer optimized dynamic routing techniques for radio interference mitigation across multiple coexisting wireless body area networks (BANs), based on real-life measurements. At the network layer, the best route is selected according to channel state information from...
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279
A Team-Formation Algorithm for Faultline Minimization
In recent years, the proliferation of online resumes and the need to evaluate large populations of candidates for on-site and virtual teams have led to a growing interest in automated team-formation. Given a large pool of candidates, the general problem requires the selection of a team of experts to complete a given ...
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280
A Survey of Model Compression and Acceleration for Deep Neural Networks
Deep convolutional neural networks (CNNs) have recently achieved great success in many visual recognition tasks. However, existing deep neural network models are computationally expensive and memory intensive, hindering their deployment in devices with low memory resources or in applications with strict latency requi...
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281
Non-Parametric Calibration of Probabilistic Regression
The task of calibration is to retrospectively adjust the outputs from a machine learning model to provide better probability estimates on the target variable. While calibration has been investigated thoroughly in classification, it has not yet been well-established for regression tasks. This paper considers the probl...
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282
Cyclotron resonant scattering feature simulations. II. Description of the CRSF simulation process
Cyclotron resonant scattering features (CRSFs) are formed by scattering of X-ray photons off quantized plasma electrons in the strong magnetic field (of the order 10^12 G) close to the surface of an accreting X-ray pulsar. The line profiles of CRSFs cannot be described by an analytic expression. Numerical methods suc...
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283
New quantum mds constacylıc codes
This paper is devoted to the study of the construction of new quantum MDS codes. Based on constacyclic codes over Fq2 , we derive four new families of quantum MDS codes, one of which is an explicit generalization of the construction given in Theorem 7 in [22]. We also extend the result of Theorem 3:3 given in [17].
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284
Infinitary first-order categorical logic
We present a unified categorical treatment of completeness theorems for several classical and intuitionistic infinitary logics with a proposed axiomatization. This provides new completeness theorems and subsumes previous ones by Gödel, Kripke, Beth, Karp, Joyal, Makkai and Fourman/Grayson. As an application we prove,...
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285
Stochastic Gradient Monomial Gamma Sampler
Recent advances in stochastic gradient techniques have made it possible to estimate posterior distributions from large datasets via Markov Chain Monte Carlo (MCMC). However, when the target posterior is multimodal, mixing performance is often poor. This results in inadequate exploration of the posterior distribution....
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286
Gini estimation under infinite variance
We study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index $\alpha\in(1,2)$). We show that, in such a case, the Gini coefficient cannot be reliably estimat...
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287
Training Neural Networks Using Features Replay
Training a neural network using backpropagation algorithm requires passing error gradients sequentially through the network. The backward locking prevents us from updating network layers in parallel and fully leveraging the computing resources. Recently, there are several works trying to decouple and parallelize the ...
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288
The anti-spherical category
We study a diagrammatic categorification (the "anti-spherical category") of the anti-spherical module for any Coxeter group. We deduce that Deodhar's (sign) parabolic Kazhdan-Lusztig polynomials have non-negative coefficients, and that a monotonicity conjecture of Brenti's holds. The main technical observation is a l...
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289
Trajectories and orbital angular momentum of necklace beams in nonlinear colloidal suspensions
Recently, we have predicted that the modulation instability of optical vortex solitons propagating in nonlinear colloidal suspensions with exponential saturable nonlinearity leads to formation of necklace beams (NBs) [S.~Z.~Silahli, W.~Walasik and N.~M.~Litchinitser, Opt.~Lett., \textbf{40}, 5714 (2015)]. Here, we in...
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290
Unified Treatment of Spin Torques using a Coupled Magnetisation Dynamics and Three-Dimensional Spin Current Solver
A three-dimensional spin current solver based on a generalised spin drift-diffusion description, including the spin Hall effect, is integrated with a magnetisation dynamics solver. The resulting model is shown to simultaneously reproduce the spin-orbit torques generated using the spin Hall effect, spin pumping torque...
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291
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization
This paper aims to explore models based on the extreme gradient boosting (XGBoost) approach for business risk classification. Feature selection (FS) algorithms and hyper-parameter optimizations are simultaneously considered during model training. The five most commonly used FS methods including weight by Gini, weight...
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292
Rheology of High-Capillary Number Flow in Porous Media
Immiscible fluids flowing at high capillary numbers in porous media may be characterized by an effective viscosity. We demonstrate that the effective viscosity is well described by the Lichtenecker-Rother equation. The exponent $\alpha$ in this equation takes either the value 1 or 0.6 in two- and 0.5 in three-dimensi...
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293
Quantum Charge Pumps with Topological Phases in Creutz Ladder
Quantum charge pumping phenomenon connects band topology through the dynamics of a one-dimensional quantum system. In terms of a microscopic model, the Su-Schrieffer-Heeger/Rice-Mele quantum pump continues to serve as a fruitful starting point for many considerations of topological physics. Here we present a generali...
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294
On Deep Neural Networks for Detecting Heart Disease
Heart disease is the leading cause of death, and experts estimate that approximately half of all heart attacks and strokes occur in people who have not been flagged as "at risk." Thus, there is an urgent need to improve the accuracy of heart disease diagnosis. To this end, we investigate the potential of using data a...
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295
Exponential Stability Analysis via Integral Quadratic Constraints
The theory of integral quadratic constraints (IQCs) allows verification of stability and gain-bound properties of systems containing nonlinear or uncertain elements. Gain bounds often imply exponential stability, but it can be challenging to compute useful numerical bounds on the exponential decay rate. This work pre...
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296
Fermi acceleration of electrons inside foreshock transient cores
Foreshock transients upstream of Earth's bow shock have been recently observed to accelerate electrons to many times their thermal energy. How such acceleration occurs is unknown, however. Using THEMIS case studies, we examine a subset of acceleration events (31 of 247 events) in foreshock transients with cores that ...
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297
Quantum Speed Limit is Not Quantum
The quantum speed limit (QSL), or the energy-time uncertainty relation, describes the fundamental maximum rate for quantum time evolution and has been regarded as being unique in quantum mechanics. In this study, we obtain a classical speed limit corresponding to the QSL using the Hilbert space for the classical Liou...
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298
Adaptive Diffusion Processes of Time-Varying Local Information on Networks
This paper mainly discusses the diffusion on complex networks with time-varying couplings. We propose a model to describe the adaptive diffusion process of local topological and dynamical information, and find that the Barabasi-Albert scale-free network (BA network) is beneficial to the diffusion and leads nodes to a...
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299
ACVAE-VC: Non-parallel many-to-many voice conversion with auxiliary classifier variational autoencoder
This paper proposes a non-parallel many-to-many voice conversion (VC) method using a variant of the conditional variational autoencoder (VAE) called an auxiliary classifier VAE (ACVAE). The proposed method has three key features. First, it adopts fully convolutional architectures to construct the encoder and decoder ...
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300
Spectral analysis of jet turbulence
Informed by LES data and resolvent analysis of the mean flow, we examine the structure of turbulence in jets in the subsonic, transonic, and supersonic regimes. Spectral (frequency-space) proper orthogonal decomposition is used to extract energy spectra and decompose the flow into energy-ranked coherent structures. T...
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