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title stringlengths 7 239	abstract stringlengths 7 2.76k	cs int64 0 1	phy int64 0 1	math int64 0 1	stat int64 0 1
Infinite symmetric ergodic index and related examples in infinite measure	We define an infinite measure-preserving transformation to have infinite symmetric ergodic index if all finite Cartesian products of the transformation and its inverse are ergodic, and show that infinite symmetric ergodic index does not imply that all products of powers are conservative, so does not imply power weak ...	0	0	1	0
Exploiting gradients and Hessians in Bayesian optimization and Bayesian quadrature	An exciting branch of machine learning research focuses on methods for learning, optimizing, and integrating unknown functions that are difficult or costly to evaluate. A popular Bayesian approach to this problem uses a Gaussian process (GP) to construct a posterior distribution over the function of interest given a ...	0	0	0	1
Permanency of the age-structured population model on several temporally variable patches	We consider a system of nonlinear partial differential equations that describes an age-structured population inhabiting several temporally varying patches. We prove existence and uniqueness of solution and analyze its large-time behavior in cases when the environment is constant and when it changes periodically. A pi...	0	1	1	0
Rapid laser-induced photochemical conversion of sol-gel precursors to In2O3 layers and their application in thin-film transistors	We report the development of indium oxide (In2O3) transistors via a single step laser-induced photochemical conversion process of a sol-gel metal oxide precursor. Through careful optimization of the laser annealing conditions we demonstrated successful conversion of the precursor to In2O3 and its subsequent implement...	0	1	0	0
Testing for Change in Stochastic Volatility with Long Range Dependence	In this paper, change-point problems for long memory stochastic volatility models are considered. A general testing problem which includes various alternative hypotheses is discussed. Under the hypothesis of stationarity the limiting behavior of CUSUM- and Wilcoxon-type test statistics is derived. In this context, a ...	0	0	1	1
Kinematics effects of atmospheric friction in spacecraft flybys	Gravity assist manoeuvres are one of the most succesful techniques in astrodynamics. In these trajectories the spacecraft comes very close to the surface of the Earth, or other Solar system planets or moons, and, as a consequence, it experiences the effect of atmospheric friction by the outer layers of the Earth's at...	0	1	0	0
Interval vs. Point Temporal Logic Model Checking: an Expressiveness Comparison	In the last years, model checking with interval temporal logics is emerging as a viable alternative to model checking with standard point-based temporal logics, such as LTL, CTL, CTL*, and the like. The behavior of the system is modeled by means of (finite) Kripke structures, as usual. However, while temporal logics ...	1	0	0	0
Calculations for electron-impact ionization of magnesium and calcium atoms in the method of interacting configurations in the complex number representation	Next investigations in our program of transition from the He atom to the complex atoms description have been presented. The method of interacting configurations in the complex number representation is under consideration. The spectroscopic characteristics of the Mg and Ca atoms in the problem of the electron-impact i...	0	1	0	0
An Information Theoretic Approach to Sample Acquisition and Perception in Planetary Robotics	An important and emerging component of planetary exploration is sample retrieval and return to Earth. Obtaining and analyzing rock samples can provide unprecedented insight into the geology, geo-history and prospects for finding past life and water. Current methods of exploration rely on mission scientists to identif...	1	1	0	0
Global solvability of the Navier-Stokes equations with a free surface in the maximal $L_p\text{-}L_q$ regularity class	We consider the motion of incompressible viscous fluids bounded above by a free surface and below by a solid surface in the $N$-dimensional Euclidean space for $N\geq 2$ when the gravity is not taken into account. The aim of this paper is to show the global solvability of the Naiver-Stokes equations with a free surfa...	0	0	1	0
The fundamental group of the complement of the singular locus of Lauricella's $F_C$	We study the fundamental group of the complement of the singular locus of Lauricella's hypergeometric function $F_C$ of $n$ variables. The singular locus consists of $n$ hyperplanes and a hypersurface of degree $2^{n-1}$ in the complex $n$-space. We derive some relations that holds for general $n\geq 3$. We give an e...	0	0	1	0
Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis	Spectral Clustering (SC) is a widely used data clustering method which first learns a low-dimensional embedding $U$ of data by computing the eigenvectors of the normalized Laplacian matrix, and then performs k-means on $U^\top$ to get the final clustering result. The Sparse Spectral Clustering (SSC) method extends SC...	1	0	0	0
Stable Geodesic Update on Hyperbolic Space and its Application to Poincare Embeddings	A hyperbolic space has been shown to be more capable of modeling complex networks than a Euclidean space. This paper proposes an explicit update rule along geodesics in a hyperbolic space. The convergence of our algorithm is theoretically guaranteed, and the convergence rate is better than the conventional Euclidean ...	0	0	0	1
A Parameterized Approach to Personalized Variable Length Summarization of Soccer Matches	We present a parameterized approach to produce personalized variable length summaries of soccer matches. Our approach is based on temporally segmenting the soccer video into 'plays', associating a user-specifiable 'utility' for each type of play and using 'bin-packing' to select a subset of the plays that add up to t...	1	0	0	0
Towards Robust Neural Networks via Random Self-ensemble	Recent studies have revealed the vulnerability of deep neural networks: A small adversarial perturbation that is imperceptible to human can easily make a well-trained deep neural network misclassify. This makes it unsafe to apply neural networks in security-critical applications. In this paper, we propose a new defen...	1	0	0	1
Prospects for detection of intermediate-mass black holes in globular clusters using integrated-light spectroscopy	The detection of intermediate mass black holes (IMBHs) in Galactic globular clusters (GCs) has so far been controversial. In order to characterize the effectiveness of integrated-light spectroscopy through integral field units, we analyze realistic mock data generated from state-of-the-art Monte Carlo simulations of ...	0	1	0	0
A Multi-frequency analysis of possible Dark Matter Contributions to M31 Gamma-Ray Emissions	We examine the possibility of a dark matter (DM) contribution to the recently observed gamma-ray spectrum seen in the M31 galaxy. In particular, we apply limits on Weakly Interacting Massive Particle DM annihilation cross-sections derived from the Coma galaxy cluster and the Reticulum II dwarf galaxy to determine the...	0	1	0	0
Tensor Decompositions for Modeling Inverse Dynamics	Modeling inverse dynamics is crucial for accurate feedforward robot control. The model computes the necessary joint torques, to perform a desired movement. The highly non-linear inverse function of the dynamical system can be approximated using regression techniques. We propose as regression method a tensor decomposi...	1	0	0	1
Synthesis and Hydrogen Sorption Characteristics of Mechanically Alloyed Mg(NixMn1-x)2 Intermetallics	New ternary Mg-Ni-Mn intermetallics have been successfully synthesized by High Energy Ball Milling (HEBM) and have been studied as possible materials for efficient hydrogen storage applications. The microstructures of the as-cast and milled alloys were characterized by means of X-ray Powder Diffraction (XRD) and Scan...	0	1	0	0
Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective	Recent advances in the field of network embedding have shown the low-dimensional network representation is playing a critical role in network analysis. However, most of the existing principles of network embedding do not incorporate auxiliary information such as content and labels of nodes flexibly. In this paper, we...	1	0	0	1
Incremental Principal Component Analysis Exact implementation and continuity corrections	This paper describes some applications of an incremental implementation of the principal component analysis (PCA). The algorithm updates the transformation coefficients matrix on-line for each new sample, without the need to keep all the samples in memory. The algorithm is formally equivalent to the usual batch versi...	1	0	0	1
More investment in Research and Development for better Education in the future?	The question in this paper is whether R&D efforts affect education performance in small classes. Merging two datasets collected from the PISA studies and the World Development Indicators and using Learning Bayesian Networks, we prove the existence of a statistical causal relationship between investment in R&D of a co...	0	0	0	1
Discriminative Modeling of Social Influence for Prediction and Explanation in Event Cascades	The global dynamics of event cascades are often governed by the local dynamics of peer influence. However, detecting social influence from observational data is challenging, due to confounds like homophily and practical issues like missing data. In this work, we propose a novel discriminative method to detect influen...	1	0	0	0
Online codes for analog signals	We revisit a classical scenario in communication theory: a source is generating a waveform which we sample at regular intervals; we wish to transform the signal in such a way as to minimize distortion in its reconstruction, despite noise. The transformation must be online (also called causal), in order to enable real...	1	0	0	0
Statistical test for fractional Brownian motion based on detrending moving average algorithm	Motivated by contemporary and rich applications of anomalous diffusion processes we propose a new statistical test for fractional Brownian motion, which is one of the most popular models for anomalous diffusion systems. The test is based on detrending moving average statistic and its probability distribution. Using t...	0	0	0	1
Fast Radio Map Construction and Position Estimation via Direct Mapping for WLAN Indoor Localization System	The main limitation that constrains the fast and comprehensive application of Wireless Local Area Network (WLAN) based indoor localization systems with Received Signal Strength (RSS) positioning algorithms is the building of the fingerprinting radio map, which is time-consuming especially when the indoor environment ...	1	0	0	1
Lagrangian solutions to the Vlasov-Poisson system with a point charge	We consider the Cauchy problem for the repulsive Vlasov-Poisson system in the three dimensional space, where the initial datum is the sum of a diffuse density, assumed to be bounded and integrable, and a point charge. Under some decay assumptions for the diffuse density close to the point charge, under bounds on the ...	0	0	1	0
MITHRIL: Mining Sporadic Associations for Cache Prefetching	The growing pressure on cloud application scalability has accentuated storage performance as a critical bottle- neck. Although cache replacement algorithms have been extensively studied, cache prefetching - reducing latency by retrieving items before they are actually requested remains an underexplored area. Existing...	1	0	0	0
On 2-level polytopes arising in combinatorial settings	2-level polytopes naturally appear in several areas of pure and applied mathematics, including combinatorial optimization, polyhedral combinatorics, communication complexity, and statistics. In this paper, we present a study of some 2-level polytopes arising in combinatorial settings. Our first contribution is provin...	1	0	1	0
Learned Optimizers that Scale and Generalize	Learning to learn has emerged as an important direction for achieving artificial intelligence. Two of the primary barriers to its adoption are an inability to scale to larger problems and a limited ability to generalize to new tasks. We introduce a learned gradient descent optimizer that generalizes well to new tasks...	1	0	0	1
Toward Optimal Run Racing: Application to Deep Learning Calibration	This paper aims at one-shot learning of deep neural nets, where a highly parallel setting is considered to address the algorithm calibration problem - selecting the best neural architecture and learning hyper-parameter values depending on the dataset at hand. The notoriously expensive calibration problem is optimally...	1	0	0	0
Bernstein - von Mises theorems for statistical inverse problems I: Schrödinger equation	The inverse problem of determining the unknown potential $f>0$ in the partial differential equation $$\frac{\Delta}{2} u - fu =0 \text{ on } \mathcal O ~~\text{s.t. } u = g \text { on } \partial \mathcal O,$$ where $\mathcal O$ is a bounded $C^\infty$-domain in $\mathbb R^d$ and $g>0$ is a given function prescribing ...	0	0	1	1
Tailoring Architecture Centric Design Method with Rapid Prototyping	Many engineering processes exist in the industry, text books and international standards. However, in practice rarely any of the processes are followed consistently and literally. It is observed across industries the processes are altered based on the requirements of the projects. Two features commonly lacking from m...	1	0	0	0
Easy High-Dimensional Likelihood-Free Inference	We introduce a framework using Generative Adversarial Networks (GANs) for likelihood--free inference (LFI) and Approximate Bayesian Computation (ABC) where we replace the black-box simulator model with an approximator network and generate a rich set of summary features in a data driven fashion. On benchmark data sets...	1	0	0	1
Narrow-line Laser Cooling by Adiabatic Transfer	We propose and demonstrate a novel laser cooling mechanism applicable to particles with narrow-linewidth optical transitions. By sweeping the frequency of counter-propagating laser beams in a sawtooth manner, we cause adiabatic transfer back and forth between the ground state and a long-lived optically excited state....	0	1	0	0
Assessing the Effect of Stellar Companions from High-Resolution Imaging of Kepler Objects of Interest	We report on 176 close (<2") stellar companions detected with high-resolution imaging near 170 hosts of Kepler Objects of Interest. These Kepler targets were prioritized for imaging follow-up based on the presence of small planets, so most of the KOIs in these systems (176 out of 204) have nominal radii <6 R_E . Each...	0	1	0	0
Semi-Supervised Learning via New Deep Network Inversion	We exploit a recently derived inversion scheme for arbitrary deep neural networks to develop a new semi-supervised learning framework that applies to a wide range of systems and problems. The approach outperforms current state-of-the-art methods on MNIST reaching $99.14\%$ of test set accuracy while using $5$ labeled...	1	0	0	1
Using English as Pivot to Extract Persian-Italian Parallel Sentences from Non-Parallel Corpora	The effectiveness of a statistical machine translation system (SMT) is very dependent upon the amount of parallel corpus used in the training phase. For low-resource language pairs there are not enough parallel corpora to build an accurate SMT. In this paper, a novel approach is presented to extract bilingual Persian...	1	0	0	0
Intrinsic geometry and analysis of Finsler structures	In this short note, we prove that if $F$ is a weak upper semicontinuous admissible Finsler structure on a domain in $\mathbb{R}^n$, $n\geq 2$, then the intrinsic distance and differential structures coincide.	0	0	1	0
Combining Prediction of Human Decisions with ISMCTS in Imperfect Information Games	Monte Carlo Tree Search (MCTS) has been extended to many imperfect information games. However, due to the added complexity that uncertainty introduces, these adaptations have not reached the same level of practical success as their perfect information counterparts. In this paper we consider the development of agents ...	1	0	0	0
The KLASH Proposal	We propose a search of galactic axions with mass about 0.2 microeV using a large volume resonant cavity, about 50 m^3, cooled down to 4 K and immersed in a moderate axial magnetic field of about 0.6 T generated inside the superconducting magnet of the KLOE experiment located at the National Laboratory of Frascati of ...	0	1	0	0
Dimensionality-Driven Learning with Noisy Labels	Datasets with significant proportions of noisy (incorrect) class labels present challenges for training accurate Deep Neural Networks (DNNs). We propose a new perspective for understanding DNN generalization for such datasets, by investigating the dimensionality of the deep representation subspace of training samples...	0	0	0	1
Delving into adversarial attacks on deep policies	Adversarial examples have been shown to exist for a variety of deep learning architectures. Deep reinforcement learning has shown promising results on training agent policies directly on raw inputs such as image pixels. In this paper we present a novel study into adversarial attacks on deep reinforcement learning pol...	1	0	0	1
On two functions arising in the study of the Euler and Carmichael quotients	We investigate two arithmetic functions naturally occurring in the study of the Euler and Carmichael quotients. The functions are related to the frequency of vanishing of the Euler and Carmichael quotients. We obtain several results concerning the relations between these functions as well as their typical and extreme...	0	0	1	0
Lurking Variable Detection via Dimensional Analysis	Lurking variables represent hidden information, and preclude a full understanding of phenomena of interest. Detection is usually based on serendipity -- visual detection of unexplained, systematic variation. However, these approaches are doomed to fail if the lurking variables do not vary. In this article, we address...	0	0	0	1
System calibration method for Fourier ptychographic microscopy	Fourier ptychographic microscopy (FPM) is a recently proposed quantitative phase imaging technique with high resolution and wide field-of-view (FOV). In current FPM imaging platforms, systematic error sources come from the aberrations, LED intensity fluctuation, parameter imperfections and noise, which will severely ...	0	1	0	0
Categories for Dynamic Epistemic Logic	The primary goal of this paper is to recast the semantics of modal logic, and dynamic epistemic logic (DEL) in particular, in category-theoretic terms. We first review the category of relations and categories of Kripke frames, with particular emphasis on the duality between relations and adjoint homomorphisms. Using ...	1	0	1	0
Accurate Pouring with an Autonomous Robot Using an RGB-D Camera	Robotic assistants in a home environment are expected to perform various complex tasks for their users. One particularly challenging task is pouring drinks into cups, which for successful completion, requires the detection and tracking of the liquid level during a pour to determine when to stop. In this paper, we pre...	1	0	0	0
Restriction of Odd Degree Characters of $\mathfrak{S}_n$	Let $n$ and $k$ be natural numbers such that $2^k < n$. We study the restriction to $\mathfrak{S}_{n-2^k}$ of odd-degree irreducible characters of the symmetric group $\mathfrak{S}_n$. This analysis completes the study begun in [Ayyer A., Prasad A., Spallone S., Sem. Lothar. Combin. 75 (2015), Art. B75g, 13 pages] an...	0	0	1	0
CSGNet: Neural Shape Parser for Constructive Solid Geometry	We present a neural architecture that takes as input a 2D or 3D shape and outputs a program that generates the shape. The instructions in our program are based on constructive solid geometry principles, i.e., a set of boolean operations on shape primitives defined recursively. Bottom-up techniques for this shape pars...	1	0	0	0
Composite Weyl nodes stabilized by screw symmetry with and without time reversal	We classify the band degeneracies in 3D crystals with screw symmetry $n_m$ and broken $\mathcal P*\mathcal T$ symmetry, where $\mathcal P$ stands for spatial inversion and $\mathcal T$ for time reversal. The generic degeneracies along symmetry lines are Weyl nodes: Chiral contact points between pairs of bands. They c...	0	1	0	0
Deep Neural Networks as 0-1 Mixed Integer Linear Programs: A Feasibility Study	Deep Neural Networks (DNNs) are very popular these days, and are the subject of a very intense investigation. A DNN is made by layers of internal units (or neurons), each of which computes an affine combination of the output of the units in the previous layer, applies a nonlinear operator, and outputs the correspondi...	1	0	0	0
Directionality Fields generated by a Local Hilbert Transform	We propose a new approach based on a local Hilbert transform to design non-Hermitian potentials generating arbitrary vector fields of directionality, p(r), with desired shapes and topologies. We derive a local Hilbert transform to systematically build such potentials, by modifying background potentials (being either ...	0	1	0	0
Bulk Eigenvalue Correlation Statistics of Random Biregular Bipartite Graphs	This paper is the second chapter of three of the author's undergraduate thesis. In this paper, we consider the random matrix ensemble given by $(d_b, d_w)$-regular graphs on $M$ black vertices and $N$ white vertices, where $d_b \in [N^{\gamma}, N^{2/3 - \gamma}]$ for any $\gamma > 0$. We simultaneously prove that the...	0	0	1	1
A local weighted Axler-Zheng theorem in $\mathbb{C}^n$	The well-known Axler-Zheng theorem characterizes compactness of finite sums of finite products of Toeplitz operators on the unit disk in terms of the Berezin transform of these operators. Subsequently this theorem was generalized to other domains and appeared in different forms, including domains in $\mathbb{C}^n$ on...	0	0	1	0
Spatial modulation of Joule losses to increase the normal zone propagation velocity in (RE)BaCuO tapes	This paper presents a simple approach to increase the normal zone propagation velocity in (RE)BaCuO thin films grown on a flexible metallic substrate, also called superconducting tapes. The key idea behind this approach is to use a specific geometry of the silver thermal stabilizer that surrounds the superconducting ...	0	1	0	0
Vortex Thermometry for Turbulent Two-Dimensional Fluids	We introduce a new method of statistical analysis to characterise the dynamics of turbulent fluids in two dimensions. We establish that, in equilibrium, the vortex distributions can be uniquely connected to the temperature of the vortex gas, and apply this vortex thermometry to characterise simulations of decaying su...	0	1	0	0
The Hurwitz-type theorem for the regular Coulomb wave function via Hankel determinants	We derive a closed formula for the determinant of the Hankel matrix whose entries are given by sums of negative powers of the zeros of the regular Coulomb wave function. This new identity applied together with results of Grommer and Chebotarev allows us to prove a Hurwitz-type theorem about the zeros of the regular C...	0	0	1	0
An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients	In this technical report, we consider an approach that combines the PPO objective and K-FAC natural gradient optimization, for which we call PPOKFAC. We perform a range of empirical analysis on various aspects of the algorithm, such as sample complexity, training speed, and sensitivity to batch size and training epoc...	0	0	0	1
On the density of sets avoiding parallelohedron distance 1	The maximal density of a measurable subset of R^n avoiding Euclidean distance1 is unknown except in the trivial case of dimension 1. In this paper, we consider thecase of a distance associated to a polytope that tiles space, where it is likely that the setsavoiding distance 1 are of maximal density 2^-n, as conjectur...	0	0	1	0
Adversarial Deep Structured Nets for Mass Segmentation from Mammograms	Mass segmentation provides effective morphological features which are important for mass diagnosis. In this work, we propose a novel end-to-end network for mammographic mass segmentation which employs a fully convolutional network (FCN) to model a potential function, followed by a CRF to perform structured learning. ...	1	0	0	0
The downward directed grounds hypothesis and very large cardinals	A transitive model $M$ of ZFC is called a ground if the universe $V$ is a set forcing extension of $M$. We show that the grounds of $V$ are downward set-directed. Consequently, we establish some fundamental theorems on the forcing method and the set-theoretic geology. For instance, (1) the mantle, the intersection of...	0	0	1	0
A Distributed Control Framework of Multiple Unmanned Aerial Vehicles for Dynamic Wildfire Tracking	Wild-land fire fighting is a hazardous job. A key task for firefighters is to observe the "fire front" to chart the progress of the fire and areas that will likely spread next. Lack of information of the fire front causes many accidents. Using Unmanned Aerial Vehicles (UAVs) to cover wildfire is promising because it ...	1	0	0	0
Rayleigh-Brillouin light scattering spectroscopy of nitrous oxide (N$_2$O)	High signal-to-noise and high-resolution light scattering spectra are measured for nitrous oxide (N$_2$O) gas at an incident wavelength of 403.00 nm, at 90$^\circ$ scattering, at room temperature and at gas pressures in the range $0.5-4$ bar. The resulting Rayleigh-Brillouin light scattering spectra are compared to a...	0	1	0	0
Competition between Chaotic and Non-Chaotic Phases in a Quadratically Coupled Sachdev-Ye-Kitaev Model	The Sachdev-Ye-Kitaev (SYK) model is a concrete solvable model to study non-Fermi liquid properties, holographic duality and maximally chaotic behavior. In this work, we consider a generalization of the SYK model that contains two SYK models with different number of Majorana modes coupled by quadratic terms. This mod...	0	1	0	0
Symmetry Realization via a Dynamical Inverse Higgs Mechanism	The Ward identities associated with spontaneously broken symmetries can be saturated by Goldstone bosons. However, when space-time symmetries are broken, the number of Goldstone bosons necessary to non-linearly realize the symmetry can be less than the number of broken generators. The loss of Goldstones may be due to...	0	1	0	0
Growth of strontium ruthenate films by hybrid molecular beam epitaxy	We report on the growth of epitaxial Sr2RuO4 films using a hybrid molecular beam epitaxy approach in which a volatile precursor containing RuO4 is used to supply ruthenium and oxygen. The use of the precursor overcomes a number of issues encountered in traditional MBE that uses elemental metal sources. Phase-pure, ep...	0	1	0	0
Possible Evidence for the Stochastic Acceleration of Secondary Antiprotons by Supernova Remnants	The antiproton-to-proton ratio in the cosmic-ray spectrum is a sensitive probe of new physics. Using recent measurements of the cosmic-ray antiproton and proton fluxes in the energy range of 1-1000 GeV, we study the contribution to the $\bar{p}/p$ ratio from secondary antiprotons that are produced and subsequently ac...	0	1	0	0
The Host Galaxy and Redshift of the Repeating Fast Radio Burst FRB 121102	The precise localization of the repeating fast radio burst (FRB 121102) has provided the first unambiguous association (chance coincidence probability $p\lesssim3\times10^{-4}$) of an FRB with an optical and persistent radio counterpart. We report on optical imaging and spectroscopy of the counterpart and find that i...	0	1	0	0
Thicket Density	Thicket density is a new measure of the complexity of a set system, having the same relationship to stable formulas that VC density has to NIP formulas. It satisfies a Sauer-Shelah type dichotomy that has applications in both model theory and the theory of algorithms	0	0	1	0
Uniformizations of stable $(γ,n)$-gonal Riemann surfaces	A $(\gamma,n)$-gonal pair is a pair $(S,f)$, where $S$ is a closed Riemann surface and $f:S \to R$ is a degree $n$ holomorphic map onto a closed Riemann surface $R$ of genus $\gamma$. If the signature of $(S,f)$ is of hyperbolic type, then there is pair $(\Gamma,G)$, called an uniformization of $(S,f)$, where $G$ is ...	0	0	1	0
If you are not paying for it, you are the product: How much do advertisers pay to reach you?	Online advertising is progressively moving towards a programmatic model in which ads are matched to actual interests of individuals collected as they browse the web. Letting the huge debate around privacy aside, a very important question in this area, for which little is known, is: How much do advertisers pay to reac...	1	0	0	0
Circularly polarized vacuum field in three-dimensional chiral photonic crystals probed by quantum dot emission	The quantum nature of light-matter interactions in a circularly polarized vacuum field was probed by spontaneous emission from quantum dots in three-dimensional chiral photonic crystals. Due to the circularly polarized eigenmodes along the helical axis in the GaAs-based mirror-asymmetric structures we studied, we obs...	0	1	0	0
Critical behavior of quasi-two-dimensional semiconducting ferromagnet CrGeTe$_3$	The critical properties of the single-crystalline semiconducting ferromagnet CrGeTe$_3$ were investigated by bulk dc magnetization around the paramagnetic to ferromagnetic phase transition. Critical exponents $\beta = 0.200\pm0.003$ with critical temperature $T_c = 62.65\pm0.07$ K and $\gamma = 1.28\pm0.03$ with $T_c...	0	1	0	0
Scale-free Monte Carlo method for calculating the critical exponent $γ$ of self-avoiding walks	We implement a scale-free version of the pivot algorithm and use it to sample pairs of three-dimensional self-avoiding walks, for the purpose of efficiently calculating an observable that corresponds to the probability that pairs of self-avoiding walks remain self-avoiding when they are concatenated. We study the pro...	0	1	1	0
The quadratic M-convexity testing problem	M-convex functions, which are a generalization of valuated matroids, play a central role in discrete convex analysis. Quadratic M-convex functions constitute a basic and important subclass of M-convex functions, which has a close relationship with phylogenetics as well as valued constraint satisfaction problems. In t...	0	0	1	0
Distributed Bayesian Matrix Factorization with Limited Communication	Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challenging and requires distributing both data and computation over many wor...	1	0	0	1
Optimized Certificate Revocation List Distribution for Secure V2X Communications	The successful deployment of safe and trustworthy Connected and Autonomous Vehicles (CAVs) will highly depend on the ability to devise robust and effective security solutions to resist sophisticated cyber attacks and patch up critical vulnerabilities. Pseudonym Public Key Infrastructure (PPKI) is a promising approach...	1	0	0	0
Optical response of highly reflective film used in the water Cherenkov muon veto of the XENON1T dark matter experiment	The XENON1T experiment is the most recent stage of the XENON Dark Matter Search, aiming for the direct detection of Weakly Interacting Massive Particles (WIMPs). To reach its projected sensitivity, the background has to be reduced by two orders of magnitude compared to its predecessor XENON100. This requires a water ...	0	1	0	0
On spectral partitioning of signed graphs	We argue that the standard graph Laplacian is preferable for spectral partitioning of signed graphs compared to the signed Laplacian. Simple examples demonstrate that partitioning based on signs of components of the leading eigenvectors of the signed Laplacian may be meaningless, in contrast to partitioning based on ...	1	0	1	1
Sensor Fusion for Public Space Utilization Monitoring in a Smart City	Public space utilization is crucial for urban developers to understand how efficient a place is being occupied in order to improve existing or future infrastructures. In a smart cities approach, implementing public space monitoring with Internet-of-Things (IoT) sensors appear to be a viable solution. However, choice ...	1	0	0	1
Symplectic integrators for second-order linear non-autonomous equations	Two families of symplectic methods specially designed for second-order time-dependent linear systems are presented. Both are obtained from the Magnus expansion of the corresponding first-order equation, but otherwise they differ in significant aspects. The first family is addressed to problems with low to moderate di...	0	0	1	0
Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations	The recent breakthroughs of deep reinforcement learning (DRL) technique in Alpha Go and playing Atari have set a good example in handling large state and actions spaces of complicated control problems. The DRL technique is comprised of (i) an offline deep neural network (DNN) construction phase, which derives the cor...	1	0	0	0
Experimental observation of node-line-like surface states in LaBi	In a Dirac nodal line semimetal, the bulk conduction and valence bands touch at extended lines in the Brillouin zone. To date, most of the theoretically predicted and experimentally discovered nodal lines derive from the bulk bands of two- and three-dimensional materials. Here, based on combined angle-resolved photoe...	0	1	0	0
Manin's conjecture for a class of singular cubic hypersurfaces	Let $n$ be a positive multiple of $4$. We establish an asymptotic formula for the number of rational points of bounded height on singular cubic hypersurfaces $S_n$ defined by $$ x^3=(y_1^2 + \cdots + y_n^2)z . $$ This result is new in two aspects: first, it can be viewed as a modest start on the study of density of r...	0	0	1	0
A Flexible Approach to Automated RNN Architecture Generation	The process of designing neural architectures requires expert knowledge and extensive trial and error. While automated architecture search may simplify these requirements, the recurrent neural network (RNN) architectures generated by existing methods are limited in both flexibility and components. We propose a domain...	1	0	0	1
Convexification of Neural Graph	Traditionally, most complex intelligence architectures are extremely non-convex, which could not be well performed by convex optimization. However, this paper decomposes complex structures into three types of nodes: operators, algorithms and functions. Iteratively, propagating from node to node along edge, we prove t...	0	0	0	1
Pseudogaps in strongly interacting Fermi gases	A central challenge in modern condensed matter physics is developing the tools for understanding nontrivial yet unordered states of matter. One important idea to emerge in this context is that of a "pseudogap": the fact that under appropriate circumstances the normal state displays a suppression of the single particl...	0	1	0	0
Resolution-Exact Planner for Thick Non-Crossing 2-Link Robots	We consider the path planning problem for a 2-link robot amidst polygonal obstacles. Our robot is parametrizable by the lengths $\ell_1, \ell_2>0$ of its two links, the thickness $\tau \ge 0$ of the links, and an angle $\kappa$ that constrains the angle between the 2 links to be strictly greater than $\kappa$. The ca...	1	0	0	0
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks	Heterogeneous information networks (HINs) are ubiquitous in real-world applications. In the meantime, network embedding has emerged as a convenient tool to mine and learn from networked data. As a result, it is of interest to develop HIN embedding methods. However, the heterogeneity in HINs introduces not only rich i...	1	0	0	0
Generic Dynamical Phase Transition in One-Dimensional Bulk-Driven Lattice Gases with Exclusion	Dynamical phase transitions are crucial features of the fluctuations of statistical systems, corresponding to boundaries between qualitatively different mechanisms of maintaining unlikely values of dynamical observables over long periods of time. They manifest themselves in the form of non-analyticities in the large ...	0	1	0	0
Semianalytical calculation of the zonal-flow oscillation frequency in stellarators	Due to their capability to reduce turbulent transport in magnetized plasmas, understanding the dynamics of zonal flows is an important problem in the fusion programme. Since the pioneering work by Rosenbluth and Hinton in axisymmetric tokamaks, it is known that studying the linear and collisionless relaxation of zona...	0	1	0	0
Geometric phase of a moving dipole under a magnetic field at a distance	We predict a geometric quantum phase shift of a moving electric dipole in the presence of an external magnetic field at a distance. On the basis of the Lorentz-covariant field interaction approach, we show that a geometric phase appears under the condition that the dipole is moving in the field-free region, which is ...	0	1	0	0
A refined count of Coxeter element factorizations	For well-generated complex reflection groups, Chapuy and Stump gave a simple product for a generating function counting reflection factorizations of a Coxeter element by their length. This is refined here to record the number of reflections used from each orbit of hyperplanes. The proof is case-by-case via the classi...	0	0	1	0
Tuning the magnetism of the top-layer FeAs on BaFe$_{2}$As$_{2}$(001): First-principles study	The magnetic properties of BaFe$_{2}$As$_{2}$(001) surface have been studied by using first-principles electronic structure calculations. We find that for As-terminated surface the magnetic ground state of the top-layer FeAs is in the staggered dimer antiferromagnetic (AFM) order, while for Ba-terminated surface the ...	0	1	0	0
Cubature methods to solve BSDEs: Error expansion and complexity control	We obtain an explicit error expansion for the solution of Backward Stochastic Differential Equations (BSDEs) using the cubature on Wiener spaces method. The result is proved under a mild strengthening of the assumptions needed for the application of the cubature method. The explicit expansion can then be used to cons...	0	0	1	0
An Earth-mass Planet in a 1-AU Orbit around an Ultracool Dwarf	We combine $Spitzer$ and ground-based KMTNet microlensing observations to identify and precisely measure an Earth-mass ($1.43^{+0.45}_{-0.32} M_\oplus$) planet OGLE-2016-BLG-1195Lb at $1.16^{+0.16}_{-0.13}$ AU orbiting a $0.078^{+0.016}_{-0.012} M_\odot$ ultracool dwarf. This is the lowest-mass microlensing planet to...	0	1	0	0
Distributed Statistical Estimation and Rates of Convergence in Normal Approximation	This paper presents a class of new algorithms for distributed statistical estimation that exploit divide-and-conquer approach. We show that one of the key benefits of the divide-and-conquer strategy is robustness, an important characteristic for large distributed systems. We establish connections between performance ...	0	0	1	1
Connecting HL Tau to the Observed Exoplanet Sample	The Atacama Large Millimeter/submilimeter Array (ALMA) recently revealed a set of nearly concentric gaps in the protoplanetary disk surrounding the young star HL Tau. If these are carved by forming gas giants, this provides the first set of orbital initial conditions for planets as they emerge from their birth disks....	0	1	0	0
How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics	Endowing robots with the capability of assessing risk and making risk-aware decisions is widely considered a key step toward ensuring safety for robots operating under uncertainty. But, how should a robot quantify risk? A natural and common approach is to consider the framework whereby costs are assigned to stochasti...	1	0	0	0

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