August 2018 arXiv papers — page 14

Rudi Brits, Francois Schulz

In stark contrast to the case of finite rank operators on a Banach space, the socle of a general, complex, semisimple, and unital Banach algebra $A$ may exhibit the `pathological' property that not all traceless elements of the socle of $A$ can be expressed as the commutator of two elements belonging to the socle. The aim of this paper is to show how one

Xiangyu Liang

In this article we treat two closely related problems: 1) the upper semi continuity property for Almgren minimal sets in regions with regular boundary, which guanrantees that the uniqueness property is well defined; and 2) the Almgren (resp. topological) uniqueness property for all the 2-dimensional Almgren (resp. topological) minimal cones in $\mathbb{R}^3$

Koen Thas

In a recent paper [2], Chang et al. have proposed studying "Quantum $\mathbb{F}_{un}$": the $q \mapsto 1$ limit of Modal Quantum Theories over finite fields $\mathbb{F}_q$, motivated by the fact that such limit theories can be naturally interpreted in classical Quantum Theory. In this letter, we first make a number of rectifications of statements mad

M. Usman Maqbool Bhutta, Ming Liu

For both indoor and outdoor environments, we propose an efficient and novel method for different scales and sparse 3D point clouds registration that cannot be handled by the current popular ICP approaches. Our algorithm efficiently detects the scale difference between point clouds and uses the keyframes to estimate the relative pose for calculating the scale

Xiangyu Liang

In this article we prove the measure stability for all 2-dimensional Almgren minimal cones in $\mathbb{R}^n$, and the Almgren (resp. topological) sliding stability for the 2-dimensional Almgren (resp. topological) minimal cones in $\mathbb{R}^3$. As proved in \cite{2T}, when several 2-dimensional Almgren (resp. topological) minimal cones are measure and Almg

Felix Stahlberg, Danielle Saunders, Bill Byrne

We propose to achieve explainable neural machine translation (NMT) by changing the output representation to explain itself. We present a novel approach to NMT which generates the target sentence by monotonically walking through the source sentence. Word reordering is modeled by operations which allow setting markers in the target sentence and move a target-s

Xiangyu Liang

In this article we prove that for a large class of 2-dimensional minimal cones (including almost all 2-dimensional minimal cones that we know), the almost orthogonal union of any two of them is still a minimal cone. Comparing to existing results for minimality of almost orthogonal union of planes \cite{2p,2ptopo}, here we are dealing with unions of cones wit

Samuel N. Cohen, Timo Henckel, Gordon D. Menzies, Johannes Muhle-Karbe

We relate models based on costs of switching beliefs (e.g. due to inattention) to hypothesis tests. Specifically, for an inference problem with a penalty for mistakes and for switching the inferred value, a band of inaction is optimal. We show this band is equivalent to a confidence interval, and therefore to a two-sided hypothesis test.

Lorenzo Brasco

We generalize to the case of the $p-$Laplacian an old result by Hersch and Protter. Namely, we show that it is possible to estimate from below the first eigenvalue of the Dirichlet $p-$Laplacian of a convex set in terms of its inradius. We also prove a lower bound in terms of isoperimetric ratios and we briefly discuss the more general case of Poincaré-Sobol

Hung Dang, Dat Le Tien, Ee-Chien Chang

The cloud computing paradigm offers clients ubiquitous and on demand access to a shared pool of computing resources, enabling the clients to provision scalable services with minimal management effort. Such a pool of resources, however, is typically owned and controlled by a single service provider, making it a single-point-of-failure. This paper presents Kos

S. M. Carturan, M. Vesco, I. Bonesso, A. Quaranta

The production of flexible and robust thermal neutron detectors with improved properties as compared to the commercial ZnS:Ag based phosphors is here pursued, exploiting a siloxane binder, whose intrinsic properties as related to the chemical features of the functional groups and to the optical properties are investigated and tailored in correlation with the

Xiaohuan Wu, Wei-Ping Zhu, Min Lin, Jun Yan

Channel estimation is essential for precoding/combining in millimeter wave (mmWave) communications. However, accurate estimation is usually difficult because the receiver can only observe the low-dimensional projection of the received signals due to the hybrid architecture. We take the high speed scenario into consideration where the Doppler effect caused by

Andrei Tokovinin

Spectroscopic orbits are computed for inner pairs in 9 hierarchical multiple systems (HIP 19639, 60845, 75663, 76816, 78163, 78416, 80448, 84789, and HD 105080) and for one simple binary HIP 61840. All subsystems are double-lined, and their periods range from 2.27 to 30.4 days. Five spectroscopic binaries are twins with equal masses. Each hierarchical system

Henrik Bachmann

We present explicit formulas for Hecke eigenforms as linear combinations of q-analogues of modified double zeta values. As an application, we obtain period polynomial relations and sum formulas for these modified double zeta values. These relations have similar shapes as the period polynomial relations of Gangl, Kaneko and Zagier and the usual sum formulas f

Klaus Scherer, Alexander Noack, Jens Kleimann, Horst Fichtner

While several studies have investigated large-scale cluster winds resulting from an intra-cluster interaction of multiple stellar winds, as yet they have not provided details of the bordering flows inside a given cluster. The present work explores the principal structure of the combined flow resulting from the interaction of multiple stellar winds inside ste

T. Kubo, T. Karino, H. Kato, S. Kawata

In inertial confinement fusion, the scientific issues include the generation and transport of driver energy, the pellet design, the uniform target implosion physics, the realistic nuclear fusion reactor design, etc. In this paper, we present a pellet injection into a power reactor in heavy ion inertial fusion. We employ a magnetic correction method to reduce

Ankit Garg, Rafael Oliveira

Scaling problems have a rich and diverse history, and thereby have found numerous applications in several fields of science and engineering. For instance, the matrix scaling problem has had applications ranging from theoretical computer science to telephone forecasting, economics, statistics, optimization, among many other fields. Recently, a generalization

Adrian Diaconu, Vicenţiu Paşol

In this paper we provide an explicit construction of a $distinctive$ multiple Dirichlet series associated to products of quadratic Dirichlet L-series, which we believe should be tightly connected to a generalized metaplectic Whittaker function on the double cover of a Kac-Moody group. To do so, we first impose a set of axioms, independent of any group of fun

Loet Leydesdorff, Tobias Opthof

Following discussions in 2010 and 2011, scientometric evaluators have increasingly abandoned relative indicators in favor of comparing observed with expected citation ratios. The latter method provides parameters with error values allowing for the statistical testing of differences in citation scores. A further step would be to proceed to non-parametric stat

Mikhail Khovanov, Louis-Hadrien Robert

We introduce and study combinatorial equivariant analogues of the Kronheimer--Mrowka homology theory of planar trivalent graphs.

Qiushi Cui, Yang Weng, Chin-Woo Tan

For accommodating more electric vehicles (EVs) to battle against fossil fuel emission, the problem of charging station placement is inevitable and could be costly if done improperly. Some researches consider a general setup, using conditions such as driving ranges for planning. However, most of the EV growths in the next decades will happen in the urban area

Pratyoosh Kumar, Sumit Kumar Rano

In this article we prove the restriction theorem for Helgason-Fourier transform on homogeneous tree. Our proof is based on the duality argument and the norm estimates of Poisson transform. We also characterize all eigenfunctions of the laplacian on homogeneous tree which are Poisson transform of $L^p$ functions defined on the boundary.

Yang Gao, Christian M. Meyer, Iryna Gurevych

We propose a method to perform automatic document summarisation without using reference summaries. Instead, our method interactively learns from users' preferences. The merit of preference-based interactive summarisation is that preferences are easier for users to provide than reference summaries. Existing preference-based interactive learning methods su

Ge Gao, Eunsol Choi, Yejin Choi, Luke Zettlemoyer

We present end-to-end neural models for detecting metaphorical word use in context. We show that relatively standard BiLSTM models which operate on complete sentences work well in this setting, in comparison to previous work that used more restricted forms of linguistic context. These models establish a new state-of-the-art on existing verb metaphor detectio

Trevor Esward, Sascha Eichstädt, Ian Smith, Thomas Bruns

Recently several European National Measurement Institutes have established traceable calibration methods for dynamic mechanical quantities, e.g., dynamic force, torque and pressure. However, the use in industry and elsewhere of dynamic calibration information provided on certificates is not straightforward. Typically it is necessary to employ deconvolution t

Kapil Dev, Indrani Paul, Wei Huang, Yasuko Eckert

Heterogeneous processors with architecturally different cores (CPU and GPU) integrated on the same die lead to new challenges and opportunities for thermal and power management techniques because of shared thermal/power budgets between these cores. In this paper, we show that new parallel programming paradigms (e.g., OpenCL) for CPU-GPU processors create a t

F. Bock, D. Rautenbach

We study the possible values of the matching number among all trees with a given degree sequence as well as all bipartite graphs with a given bipartite degree sequence. For tree degree sequences, we obtain closed formulas for the possible values. For bipartite degree sequences, we show the existence of realizations with a restricted structure, which allows t

Kun Wang

Wireless receiver design is critical to the overall system performance. In this work, we apply the techniques of mixed-integer programming to formulate a unified receiver in relay networks with only partial channel information. We also relax all the constraints into real field to save computations, but at the cost of bit error performance. Moreover, a receiv

Laura Brake, Wilhelm Winter

We prove the title by constructing 2-colourable completely positive approximations for the Toeplitz algebra. Besides results about nuclear dimension and completely positive contractive order zero maps, our argument involves projectivity of the cone over a finite dimensional C*-algebra and Lin's theorem on almost normal matrices.

R. Rane, S. Chauhan, P. Bharathi, K. Nigam

The electron sheath formation in a DC magnetised plasma of modified hollow cathode source is studied. The discharge consists of two plane parallel cathodes and a small cubical anode placed off axis at the center. The argon plasma is produced and the properties of the plasma in response to the sheath formation near the anode are studied using electrical and o

Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang

In this paper, we propose to adopt the diffusion approximation tools to study the dynamics of Oja's iteration which is an online stochastic gradient descent method for the principal component analysis. Oja's iteration maintains a running estimate of the true principal component from streaming data and enjoys less temporal and spatial complexities. We

Haoyue Shi, Hao Zhou, Jiaze Chen, Lei Li

Neural networks with tree-based sentence encoders have shown better results on many downstream tasks. Most of existing tree-based encoders adopt syntactic parsing trees as the explicit structure prior. To study the effectiveness of different tree structures, we replace the parsing trees with trivial trees (i.e., binary balanced tree, left-branching tree and

Chris Junchi Li, Zhaoran Wang, Han Liu

Solving statistical learning problems often involves nonconvex optimization. Despite the empirical success of nonconvex statistical optimization methods, their global dynamics, especially convergence to the desirable local minima, remain less well understood in theory. In this paper, we propose a new analytic paradigm based on diffusion processes to characte

Chuan-Ming Song, Bo Fu, Xiang-Hai Wang, Ming-Zhe Fu

This work presents a 3-D wavelet video coding algorithm. By analyzing the contribution of each biorthogonal wavelet basis to reconstructed signal's energy, we weight each wavelet subband according to its basis energy. Based on distribution of weighted coefficients, we further discuss a 3-D wavelet tree structure named \textbf{significance probability bal

The Anh Bui, Xuan Thinh Duong

In this paper we first study the generalized weighted Hardy spaces $H^p_{L,w}(X)$ for $0<p\le 1$ associated to nonnegative self-adjoint operators $L$ satisfying Gaussian upper bounds on the space of homogeneous type $X$ in both cases of finite and infinite measure. We show that the weighted Hardy spaces defined via maximal functions and atomic decompositions

He He, Derek Chen, Anusha Balakrishnan, Percy Liang

We consider negotiation settings in which two agents use natural language to bargain on goods. Agents need to decide on both high-level strategy (e.g., proposing \$50) and the execution of that strategy (e.g., generating &#34;The bike is brand new. Selling for just \$50.&#34;). Recent work on negotiation trains neural models, but their end-to-end nature make

Wen-Chin Huang, Hsin-Te Hwang, Yu-Huai Peng, Yu Tsao

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- ever, VAE using other types of spectral featu

Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin

Network embeddings, which learn low-dimensional representations for each vertex in a large-scale network, have received considerable attention in recent years. For a wide range of applications, vertices in a network are typically accompanied by rich textual information such as user profiles, paper abstracts, etc. We propose to incorporate semantic features i

Etienne Artigau, Rebecca A. Bernstein, Timothy Brandt, Jeffrey Chilcote

Direct detection, also known as direct imaging, is a method for discovering and characterizing the atmospheres of planets at intermediate and wide separations. It is the only means of obtaining spectra of non-transiting exoplanets. Characterizing the atmospheres of planets in the <5 AU regime, where RV surveys have revealed an abundance of other worlds, requ

James M. Bardeen

The existence of trace anomalies for conformally coupled quantum fields in curved spacetimes, despite the vanishing of the trace of the conformally invariant classical stress-energy tensor, was firmly established in the 1970&#39;s, and expressions for the anomalous trace of the semi-classical quantum stress-energy tensor constructed from the curvature tensor

D. Khangulyan, V. Bosch-Ramon, Y. Uchiyama

The gamma-ray emission detected from several microquasars can be produced by relativistic electrons emitting through inverse Compton scattering. In particular, the GeV emission detected from Cygnus X-3, and its orbital phase dependence, strongly suggest that the emitting electrons are accelerated in a relativistic jet, and that the optical companion provides

Gopala Krishna Srinivasan

In this note we provide a direct approach to the most basic operator in this theory namely the exterior derivative. The crucial ingredient is a calculus lemma based on determinants. We maintain the view that in a first course at least this direct approach is preferable to the more abstract one based on characterization of the exterior derivative in terms of

Leping Li, Jun Zhang, Hardi Peter, Lakshmi Pradeep Chitta

Employing Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) multi-wavelength images, we report the coronal condensation during the magnetic reconnection (MR) between a system of open and closed coronal loops. Higher-lying magnetically open structures, observed in AIA 171 A images above the solar limb, move downward and interact with the low

C. Zhang, L. Deng, D. R. Xiong

Within the framework of non-local time-dependent stellar convection theory, we study in detail the effect of turbulent anisotropy on stellar pulsation stability. The results show that anisotropy has no substantial influence on pulsation stability of g modes and low-order (radial order $n_\mathrm{r}<5$) p modes. The effect of turbulent anisotropy increases as

L. M. Kozhevnikova

The Dirichlet problem in arbitrary domains for a wide class of anisotropic elliptic equations of the second order with variable exponent nonlinearities and the right-hand side as a measure is considered. The existence of an entropy solution in anisotropic Sobolev spaces with variable exponents is established.It is proved that the obtained entropy solution is

Lukas Berns

Since Kamiokande, the basic design of water-Cherenkov detectors has not changed: the walls of a water tank are lined with photodetectors that capture Cherenkov photons produced by relativistic particles. However, with this design the majority of photons are lost in insensitive regions between photodetectors, while at the same time most photodetectors are out

D. R. Xiong, L. Deng, C. Zhang

Starting from hydrodynamic equations, we have established a set of hydrodynamic equations for average flow and a set of dynamic equations of auto- and cross-correlations of turbulent velocity and temperature fluctuations, following the classic Reynold&#39;s treatment of turbulence. The combination of the two sets of equations leads to a complete and self-con

D. R. Xiong, L. Deng, C. Zhang, K. Wang

By using a non-local and time-dependent convection theory, we have calculated radial and low-degree non-radial oscillations for stellar evolutionary models with $M=1.4$--3.0\,$\mathrm{M}_\odot$. The results of our study predict theoretical instability strips for $δ$ Scuti and $γ$ Doradus stars, which overlap with each other. The strip of $γ$ Doradus is sligh

D. R. Xiong, L. Deng, C. Zhang

We have computed linear non-adiabatic oscillations of luminous red giants using a non-local and anisotropic time-dependent theory of convection. The results show that low-order radial modes can be self-excited. Their excitation is the result of radiation and the coupling between convection and oscillations. Turbulent pressure has important effects on the exc

Jinhui Chen, Declan Keane, Yugang Ma, Aihong Tang

We review progress in the study of antinuclei, starting from Dirac&#39;s equation and the discovery of the positron in cosmic-ray events. The development of proton accelerators led to the discovery of antiprotons, followed by the first antideuterons, demonstrating that antinucleons bind into antinuclei. With the development of heavy-ion programs at the Brook

Adane K. Geremew, Sergey Rumyantsev, Matthew A. Bloodgood, Tina T. Salguero

We describe the low-frequency current fluctuations, i.e. electronic noise, in quasi-one-dimensional ZrTe3 van der Waals nanoribbons, which have recently attracted attention owing to their extraordinary high current carrying capacity. Whereas the low-frequency noise spectral density reveals 1/f behavior near room temperature, it is dominated by the Lorentzian

Harinaivo Andriatahiny, Jean Jacques Ferdinand Randriamiarampanahy, Toussaint Joseph Rabeherimanana

The binary Reed-Muller codes can be characterized as the radical powers of a modular algebra. We use the Groebner bases to decode these codes.

Ben Andrews, Changwei Xiong

We derive estimates relating the values of a solution at any two points to the distance between the points, for quasilinear isotropic elliptic equations on compact Riemannian manifolds, depending only on dimension and a lower bound for the Ricci curvature. These estimates imply sharp gradient bounds relating the gradient of an arbitrary solution at given hei

Naoki Hamamoto, Futoshi Takahashi

In this paper, we prove Hardy-Leray and Rellich-Leray inequalities for curl-free vector fields with sharp constants. This complements the former work by Costin-Maz&#39;ya \cite{Costin-Mazya} on the sharp Hardy-Leray inequality for axisymmetric divergence-free vector fields.

Chengyuan Zhang, Yunwu Lin, Lei Zhu, Zuping Zhang

With the proliferation of online social networking services and mobile smart devices equipped with mobile communications module and position sensor module, massive amount of multimedia data has been collected, stored and shared. This trend has put forward higher request on massive multimedia data retrieval. In this paper, we investigate a novel spatial query

Dan-Bo Zhang, Shi-Liang Zhu, Z. D. Wang

Incorporating nonlinearity into quantum machine learning is essential for learning a complicated input-output mapping. We here propose quantum algorithms for nonlinear regression, where nonlinearity is introduced with feature maps when loading classical data into quantum states. Our implementation is based on a hybrid quantum computer, exploiting both discre

Xia Liao

Let $f: M \to N$ be a holomorphic map between two complex manifolds. Assume $f$ is flat and sans éclatement en codimension 0 (no blowup in codimension 0). We study the theory of Lagrangian specialisation for such $f$, and prove a González-Sprinberg type formula for the local Euler obstruction relative to $f$. With the help of this formula and MacPherson&#39;

Xiong Zhang, Jie Zhang, Congcong Yuan, Sen Liu

The accurate and automated determination of earthquake locations is still a challenging endeavor. However, such information is critical for monitoring seismic activity and assessing potential hazards in real time. Recently, a convolutional neural network was applied to detect earthquakes from single-station waveforms and approximately map events across sever

Yi Luan, Luheng He, Mari Ostendorf, Hannaneh Hajishirzi

We introduce a multi-task setup of identifying and classifying entities, relations, and coreference clusters in scientific articles. We create SciERC, a dataset that includes annotations for all three tasks and develop a unified framework called Scientific Information Extractor (SciIE) for with shared span representations. The multi-task setup reduces cascad

Salvatore Giorgi, Daniel Preotiuc-Pietro, Anneke Buffone, Daniel Rieman

Nowcasting based on social media text promises to provide unobtrusive and near real-time predictions of community-level outcomes. These outcomes are typically regarding people, but the data is often aggregated without regard to users in the Twitter populations of each community. This paper describes a simple yet effective method for building community-level

Thomas Kister, Debora Monego, Paul Mulvaney, Asaph Widmer-Cooper

Being able to predict and tune the colloidal stability of nanoparticles is essential for a wide range of applications, yet our ability to do so is currently poor due to a lack of understanding of how they interact with one another. Here, we show that the agglomeration of apolar particles is dominated by either the core or the ligand shell, depending on the p

Denis Rosset

Semidefinite relaxations are widely used to compute upper bounds on the objective of optimization problems involving noncommutative polynomials. Such optimization problems are prevalent in quantum information. We present an algorithm able to discover automatically and exploit the symmetries present in the problem formulation. We also provide an open source s

Alan Hammond

For $d \geq 2$ and $n \in \mathbb{N}$, let $\mathsf{W}_n$ denote the uniform law on self-avoiding walks of length $n$ beginning at the origin in the nearest-neighbour integer lattice $\mathbb{Z}^d$, and write $Γ$ for a $\mathsf{W}_n$-distributed walk. We show that the closing probability $\mathsf{W}_n \big( \vert\vert Γ_n \vert\vert = 1 \big)$ that $Γ$&#39;s

Ben Wormleighton

The Hilbert series of a polarised algebraic variety $(X,D)$ is a powerful invariant that, while it captures some features of the geometry of $(X,D)$ precisely, often cannot recover much information about its singular locus. This work explores the extent to which the Hilbert series of an orbifold del Pezzo surface fails to pin down its singular locus, which p

Minghua Chen, Sven-Erik Ekström, Stefano Serra-Capizzano

The nonlocal problems have been used to model very different applied scientific phenomena, which involve the fractional Laplacian when one looks at the Lévy processes and stochastic interfaces. This paper deals with the nonlocal problems on a bounded domain, where the stiffness matrices of the resulting systems are Toeplitz-plus-tridiagonal and far from bein

S. Greenfield, Y. Shi, J. K. Eastman, A. R. R. Carvalho

Measurement choices in weakly-measured open quantum systems can affect quantum trajectory chaos. We consider this scenario semi-classically and show that measurement acts as nonlinear generalized fluctuation and dissipation forces. These can alter effective dissipation in the quantum spread variables and hence change the dynamics, such that measurement choic

Martín Rinemberg, Francisco J. Soulignac

We prove that, in games in which all the guards move at the same turn, the eternal domination and the clique-connected cover numbers coincide for interval graphs. A linear algorithm for the eternal dominating set problem is obtained as a by-product.

Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer

Source code is rarely written in isolation. It depends significantly on the programmatic context, such as the class that the code would reside in. To study this phenomenon, we introduce the task of generating class member functions given English documentation and the programmatic context provided by the rest of the class. This task is challenging because the

Venkat R. Dasari, Mee Seong Im, Billy Geerhart

There is a subset of computational problems that are computable in polynomial time for which an existing algorithm may not complete due to a lack of high performance technology on a mission field. We define a subclass of deterministic polynomial time complexity class called mission class, as many polynomial problems are not computable in mission time. By foc

Anatolii Puhalskii

We establish some properties of substochastic matrices that we haven&#39;t been able to find in the literature

Shuo Yang, Samuel F. Potter, Maria K. Cameron

Nongradient SDEs with small white noise often arise when modeling biological and ecological time-irreversible processes. If the governing SDE were gradient, the maximum likelihood transition paths, transition rates, expected exit times, and the invariant probability distribution would be given in terms of its potential function. The quasipotential plays a si

John Maidens, Axel Barrau, Silvere Bonnabel, Murat Arcak

We present a method of exploiting symmetries of discrete-time optimal control problems to reduce the dimensionality of dynamic programming iterations. The results are derived for systems with continuous state variables, and can be applied to systems with continuous or discrete symmetry groups. We prove that symmetries of the state update equation and stage c

Douglas Arnold, Guy David, Marcel Filoche, David Jerison

The approximation of the eigenvalues and eigenfunctions of an elliptic operator is a key computational task in many areas of applied mathematics and computational physics. An important case, especially in quantum physics, is the computation of the spectrum of a Schrödinger operator with a disordered potential. Unlike plane waves or Bloch waves that arise as

Pouya Badri, Mahdi Sojoodi

Stability and stabilization analysis of fractional-order linear time-invariant (FO-LTI) systems with different derivative orders is studied in this paper. First, by using an appropriate linear matrix function, a single-order equivalent system for the given different-order system is introduced by which a new stability condition is obtained that is easier to c

Amir Ali Ahmadi, Anirudha Majumdar

In recent years, optimization theory has been greatly impacted by the advent of sum of squares (SOS) optimization. The reliance of this technique on large-scale semidefinite programs however, has limited the scale of problems to which it can be applied. In this paper, we introduce DSOS and SDSOS optimization as linear programming and second-order cone progra

Wen Yuan, Winfried Sickel, Dachun Yang

Some Besov-type spaces $B^{s,τ}_{p,q}(\mathbb{R}^n)$ can be characterized in terms of the behavior of the Fourier--Haar coefficients. In this article, the authors discuss some necessary restrictions for the parameters $s$, $τ$, $p$, $q$ and $n$ of this characterization. Therefore, the authors measure the regularity of the characteristic function $\mathcal X$

Yilin Yang, Liang Huang, Mingbo Ma

Beam search is widely used in neural machine translation, and usually improves translation quality compared to greedy search. It has been widely observed that, however, beam sizes larger than 5 hurt translation quality. We explain why this happens, and propose several methods to address this problem. Furthermore, we discuss the optimal stopping criteria for

C. M. Swank, E. K. Webb, X. Liu, B. W. Filippone

Critical dressing, the simultaneous dressing of two spin species to the same effective Larmor frequency, is a technique that can, in principle, improve the sensitivity to small frequency shifts. The benefits of spin dressing and thus critical dressing are achieved at the expense of generating a large (relative to the holding field $B_{0}$,) homogeneous oscil

Vivienne F. Baldassare, Marla Geha, Jenny Greene

We present an analysis of the nuclear variability of $\sim28,000$ nearby ($z<0.15$) galaxies with Sloan Digital Sky Survey (SDSS) spectroscopy in Stripe 82. We construct light curves using difference imaging of SDSS g-band images, which allows us to detect subtle variations in the central light output. We select variable AGN by assessing whether detected var

Wanlu Song, Tianyi Du, Haibin Liu, Martin B. Plenio

Quantum sensing exploits fundamental features of quantum mechanics and quantum control to realise sensing devices with potential applications in a broad range of scientific fields ranging from basic science to applied technology. The ultimate goal are devices that combine unprecedented sensitivity with excellent spatial resolution. Here, we propose a new pla

Thomas G. Beatty, Mark S. Marley, B. Scott Gaudi, Knicole D. Colon

We observed two full orbital phase curves of the transiting brown dwarf KELT-1b, at 3.6um and 4.5um, using the Spitzer Space Telescope. Combined with previous eclipse data from Beatty et al. (2014), we strongly detect KELT-1b&#39;s phase variation as a single sinusoid in both bands, with amplitudes of $964\pm36$ ppm at 3.6um and $979\pm54$ ppm at 4.5um, and

Nicholas R. Waytowich, Vinicius G. Goecks, Vernon J. Lawhern

We discuss different types of human-robot interaction paradigms in the context of training end-to-end reinforcement learning algorithms. We provide a taxonomy to categorize the types of human interaction and present our Cycle-of-Learning framework for autonomous systems that combines different human-interaction modalities with reinforcement learning. Two key

Yu Luo, Jianbo Ye, Reginald B. Adams,, Jia Li

Humans are arguably innately prepared to comprehend others&#39; emotional expressions from subtle body movements. If robots or computers can be empowered with this capability, a number of robotic applications become possible. Automatically recognizing human bodily expression in unconstrained situations, however, is daunting given the incomplete understanding

Chunlei Zhang, Huan Gao, Yongqiang Wang

This paper considers the problem of privacy-preservation in decentralized optimization, in which $N$ agents cooperatively minimize a global objective function that is the sum of $N$ local objective functions. We assume that each local objective function is private and only known to an individual agent. To cooperatively solve the problem, most existing decent

Nikole M. Nielsen, Glenn G. Kacprzak, Stephanie K. Pointon, Christopher W. Churchill

By comparing MgII absorption in the circumgalactic medium (CGM) of group environments to isolated galaxies, we investigated the impact of environment on the CGM. A MgII absorber is associated with a group if there are two or more galaxies at the absorption redshift within a projected distance of D=200 kpc from a background quasar and a line-of-sight velocity

Luan Tran, Xiaoming Liu

As a classic statistical model of 3D facial shape and albedo, 3D Morphable Model (3DMM) is widely used in facial analysis, e.g., model fitting, image synthesis. Conventional 3DMM is learned from a set of 3D face scans with associated well-controlled 2D face images, and represented by two sets of PCA basis functions. Due to the type and amount of training dat

Panagiotis Linardos, Eva Mohedano, Monica Cherto, Cathal Gurrin

This work adapts a deep neural model for image saliency prediction to the temporal domain of egocentric video. We compute the saliency map for each video frame, firstly with an off-the-shelf model trained from static images, secondly by adding a a convolutional or conv-LSTM layers trained with a dataset for video saliency prediction. We study each configurat

Camille Chapdelaine

In many inverse problems such as 3D X-ray Computed Tomography (CT), the estimation of an unknown quantity, such as a volume or an image, can be greatly enhanced, compared to maximum-likelihood techniques, by incorporating a prior model on the quantity to reconstruct. A complex prior can be designed for multi-channel estimation such as reconstruction and segm

Nick S. Blunt, Eric Neuscamman

We perform excited-state variational Monte Carlo and diffusion Monte Carlo calculations using a simple and efficient wave function ansatz. This ansatz follows the recent variation-after-response formalism, accurately approximating a configuration interaction singles wave function as a sum of only two non-orthogonal Slater determinants, and further including

Heng Guo, Mark Jerrum

We give a fully polynomial-time randomised approximation scheme (FPRAS) for the number of bases in a bicircular matroids. This is a natural class of matroids for which counting bases exactly is #P-hard and yet approximate counting can be done efficiently.

Ahmed Matar, Jan Nekovar

Let $E$ be an elliptic curve defined over ${\bf Q}$ and $K$ an imaginary quadratic field satisfying the Heegner hypothesis. A classical result of Kolyvagin states that, under suitable assumptions, if the basic Heegner point $y_K \in E(K)$ is not divisible by an odd prime $p$, then the groups $E(K)/{\bf Z} y_K$ and $\sha(E/K)$ are finite and their orders are

Alexander Cerjan, Sheng Huang, Kevin P. Chen, Yidong Chong

Weyl points are isolated degeneracies in reciprocal space that are monopoles of the Berry curvature. This topological charge makes them inherently robust to Hermitian perturbations of the system. However, non-Hermitian effects, usually inaccessible in condensed matter systems, are an important feature of photonics systems, and when added to an otherwise Herm

Chris Finlay, Jeff Calder, Bilal Abbasi, Adam Oberman

In this work we study input gradient regularization of deep neural networks, and demonstrate that such regularization leads to generalization proofs and improved adversarial robustness. The proof of generalization does not overcome the curse of dimensionality, but it is independent of the number of layers in the networks. The adversarial robustness regulariz

Alexander Tsymbaliuk

We construct a family of PBWD (Poincaré-Birkhoff-Witt-Drinfeld) bases for the quantum loop algebras $U_v(L\mathfrak{sl}_n), U_{v_1,v_2}(L\mathfrak{sl}_n), U_v(L\mathfrak{sl}(m|n))$ in the new Drinfeld realizations. In the 2-parameter case, this proves Theorem 3.11 of [Hu-Rosso-Zhang] (stated in loc. cit. without a proof), while in the super case it proves a

R. Prozorov, M. Konczykowski, M. A. Tanatar, H. H. Wen

The response of superconductors to controlled introduction of point-like disorder is an important tool to probe their microscopic electronic collective behavior. In the case of iron-based superconductors (IBS), magnetic fluctuations presumably play an important role in inducing high temperature superconductivity. In some cases, these two seemingly incompatib

Victor Vaquero, Alberto Sanfeliu, Francesc Moreno-Noguer

Perception technologies in Autonomous Driving are experiencing their golden age due to the advances in Deep Learning. Yet, most of these systems rely on the semantically rich information of RGB images. Deep Learning solutions applied to the data of other sensors typically mounted on autonomous cars (e.g. lidars or radars) are not explored much. In this paper

Alexandre Afgoustidis

Attached to any reductive Lie group $G$ is a &#34;Cartan motion group&#34; $G_0$ $-$ a Lie group with the same dimension as $G$, but a simpler group structure. A natural one-to-one correspondence between the irreducible tempered representations of $G$ and the unitary irreducible representations of $G_0$, whose existence had been suggested by Mackey in the 19

Harry Crimmins, Gary Froyland

The unpredictability of chaotic nonlinear dynamics leads naturally to statistical descriptions, including probabilistic limit laws such as the central limit theorem and large deviation principle. A key tool in the Nagaev-Guivarc&#39;h spectral method for establishing statistical limit theorems is a &#34;twisted&#34; transfer operator. In the abstract setting

Souheyb Dehimi, Mohammed Hichem Mortad

In this paper, we give an example of a closed unbounded operator whose square&#39;s domain and adjoint&#39;s square domain are equal and trivial. Then, we come up with an essentially self-adjoint whose square has a trivial domain.

Steve Yadlowsky, Hongseok Namkoong, Sanjay Basu, John Duchi

For observational studies, we study the sensitivity of causal inference when treatment assignments may depend on unobserved confounders. We develop a loss minimization approach for estimating bounds on the conditional average treatment effect (CATE) when unobserved confounders have a bounded effect on the odds ratio of treatment selection. Our approach is sc