September 2018 arXiv papers — page 3

Nadeen Rishani, Hadeel Elayan, Raed Shubair, Asimina Kiourti

Continuous health monitoring using wireless body area networks (WBANs) of wearable, epidermal and implantable medical devices is envisioned as a transformative approach to healthcare. Rapid advances in biomedical sensors, low-power electronics, and wireless communications have brought this vision to the verge of reality. However, key challenges still remain

P. Gao

In this paper, the proof of the existence of a rational point on an elliptic curve is transformed into the proof of the existence of an integer solution for a Diophantine equation. By a new formula for calculating the number of elements in intersection of two finite sets, a necessary and sufficient condition for existence of a rational point on an elliptic c

Toshihide Tadenuma, Masaki Ogura, Kenji Sugimoto

In this paper, we study the problem of continuous-time state observation over lossy communication networks. We consider the situation in which the samplers for measuring the output of the plant are spatially distributed and their communication with the observer is scheduled according to a round-robin scheduling protocol. We allow the observer gains to dynami

Katherine Montenegro, Dante Minniti, Javier Alonso-García, Maren Hempel

We characterize the population of blue horizontal-branch (BHB) stars in the bulge-halo transition region of the Milky Way using the VISTA Variables in the Vía Láctea (VVV) ESO Public Survey data. The selection of BHB stars is made using the globular cluster M22 as a reference standard, and constructing color-magnitude and color-color diagrams with specific c

Xiaodong Li, Yudong Chen, Jiaming Xu

This paper surveys recent theoretical advances in convex optimization approaches for community detection. We introduce some important theoretical techniques and results for establishing the consistency of convex community detection under various statistical models. In particular, we discuss the basic techniques based on the primal and dual analysis. We also

He Yin, Andrew Packard, Murat Arcak, Pete Seiler

We present a method for synthesizing controllers to steer trajectories from an initial set to a target set on a finite time horizon. The proposed control synthesis problem is decomposed into two steps. The first step under-approximates the backward reachable set (BRS) from the target set, using level sets of storage functions. The storage function is constru

Xiaoshan Chen, Zhen-Qing Chen, Ky Tran, George Yin

This work develops asymptotic properties of a class of switching jump diffusion processes. The processes under consideration may be viewed as a number of jump diffusion processes modulated by a random switching mechanism. The underlying processes feature in the switching process depends on the jump diffusions. In this paper, conditions for recurrence and pos

Xiaoshan Chen, Zhen-Qing Chen, Ky Tran, George Yin

This work examines a class of switching jump diffusion processes. The main effort is devoted to proving the maximum principle and obtaining the Harnack inequalities. Compared with the diffusions and switching diffusions, the associated operators for switching jump diffusions are non-local, resulting in more difficulty in treating such systems. Our study is c

Konstantinos Kourliouros

In this paper we obtain exact normal forms with functional invariants for local diffeomorphisms, under the action of the symplectomorphism group in the source space. Using these normal forms we obtain exact classification results for the first occurring singularities of Hamiltonian systems with one-sided constraints, a problem posed by R. B. Melrose in his s

Octavio A. Agustín-Aquino, Guerino Mazzola

Drawing inspiration from both the classical Guerino Mazzola's symmetry-based model for first-species counterpoint (one note against one note) and Johann Joseph Fux's "Gradus ad Parnassum", we propose an extension for second-species (two notes against one note).

Cheol-Ho Hong, Blesson Varghese

Contrary to using distant and centralized cloud data center resources, employing decentralized resources at the edge of a network for processing data closer to user devices, such as smartphones and tablets, is an upcoming computing paradigm, referred to as fog/edge computing. Fog/edge resources are typically resource-constrained, heterogeneous, and dynamic c

Zichuan Liu, Guosheng Lin, Wang Ling Goh, Fayao Liu

In this work, we propose a novel hybrid method for scene text detection namely Correlation Propagation Network (CPN). It is an end-to-end trainable framework engined by advanced Convolutional Neural Networks. Our CPN predicts text objects according to both top-down observations and the bottom-up cues. Multiple candidate boxes are assembled by a spatial commu

Min Chen, Yiming Miao, Xin Jian, Xiaofei Wang

The relentless development of the Internet of Things (IoT) communication technologies and the gradual maturity of Artificial Intelligence (AI) have led to a powerful cognitive computing ability. Users can now access efficient and convenient smart services in smart-city, green-IoT and heterogeneous networks. AI has been applied in various areas, including the

Photios A. Stavrou, Jan Ostergaard, Charalambos D. Charalambous

We deal with zero-delay source coding of a vector-valued Gauss-Markov source subject to a mean-squared error (MSE) fidelity criterion characterized by the operational zero-delay vector-valued Gaussian rate distortion function (RDF). We address this problem by considering the nonanticipative RDF (NRDF) which is a lower bound to the causal optimal performance

Zhaobo Liu, Chanying Li

We attempt to answer the question what data brings adaptive diffusion algorithms converging to true parameters. The discussion begins with the diffusion recursive least squares (RLS). When unknown parameters are scalar, the necessary and sufficient condition of the convergence for the diffusion RLS is established, in terms of the strong consistency and mean-

Ki-Young Choi, Hyun Min Lee

We consider the thermal production of axino dark matter in high-scale supersymmetry where all the superpartners except the axino are heavier than the maximum and reheating temperatures. In this case, the axinos are produced dominantly in pairs from the scattering of SM particles in thermal plasma in the early Universe after inflation. We find that the therma

Qiaolin He, Ming Mei, Xiaoding Shi, Xiaoping Wang

This paper is concerned with a diffuse interface model for the gas-liquid phase transition. The model consists the compressible Navier-Stokes equations with van der Waals equation of state and a modified Allen-Cahn equation. The global existence and uniqueness of strong solution with the periodic boundary condition (or the mixed boundary condition) in one di

F. Bertrand, M. Maumy-Bertrand

We designed a completely automated Maple ($\geqslant 15$) worksheet for deriving Edgeworth and Cornish-Fisher expansions as well as the acceleration constant of the bootstrap bias-corrected and accelerated technique. It is valid for non-parametric or parametric bootstrap, of any (studentized) statistics that is -a regular enough- function of the mean of an i

John A. C. Albay, Govind Paneru, Hyuk Kyu Pak, Yonggun Jun

The ability to create and manipulate the spatio-temporal potentials is essential in the diverse fields of science and technology. Here, we introduce an optical feedback trap system based on a high precision position detection and an ultrafast feedback control of a Brownian particle in the optical tweezers to generate spatio-temporal virtual potentials of the

José R. Mohallem, Paulo F. G. Velloso, Antonio F. C. Arapiraca

A HD-like isotopic dipole moment is proposed as a sensible probe for molecular environments, in particular for electrostatic fields and polarizable (reactive) sites of molecules. Fictitious nuclear masses are chosen in order to yield a rigid dipole with appropriate magnitude. Upon subtracting the Born-Oppenheimer energy, the interaction is reduced to the Fie

Xing-Yan Chen, Zhang-qi Yin

We propose a scheme to realize universal quantum gates between nitrogen-vacancy (NV) centers in an optically trapped nanodiamond, through uniform magnetic field induced coupling between the NV centers and the torsional mode of the levitated nanodiamond. The gates are tolerant to the thermal noise of the torsional mode. By combining the scheme with dynamical

Quanyan Zhu

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision the

Quanyan Zhu, Stefan Rass, Peter Schartner

With more and more devices becoming connectable to the internet, the number of services but also a lot of threats increases dramatically. Security is often a secondary matter behind functionality and comfort, but the problem has already been recognized. Still, with many IoT devices being deployed already, security will come step-by-step and through updates,

Daniel Ferenc, Andrew Chang, Cameron Saylor, Sebastian Böser

The ABALONE Photosensor Technology (U.S. Pat. 9064678) is a modern, scalable technology specifically invented for cost effective mass production, robustness, and high performance. We present the performance of advanced fused silica ABALONE Photosensors, developed specifically for the potential extension of the Ice Cube neutrino experiment, and stress tested

Abu Hasnat Mohammad Rubaiyat, Yongming Qin, Homa Alemzadeh

Autonomous vehicles (AV) depend on the sensors like RADAR and camera for the perception of the environment, path planning, and control. With the increasing autonomy and interactions with the complex environment, there have been growing concerns regarding the safety and reliability of AVs. This paper presents a Systems-Theoretic Process Analysis (STPA) based

Marcia Fampa, Jon Lee

We study sparse generalized inverses $H$ of a rank-$r$ real matrix $A$. We give a construction for reflexive generalized inverses having at most $r^2$ nonzeros. For $r=1$ and for $r=2$ with $A$ nonnegative, we demonstrate how to minimize the (vector) 1-norm over reflexive generalized inverses. For general $r$, we efficiently find reflexive generalized invers

Kyumin Moon, Hongju Pae

The purpose of this article is to provide an overall critical appraisal of Integrated Information Theory(IIT) of consciousness. We explore how it has evolved and what problems are involved in the theory. IIT is a hypothesis that consciousness can be explained in terms of integrated information. It argues that a number of fundamental properties of experience

Christian Lessig

We present a Parseval tight wavelet frame for the representation and analysis of velocity vector fields of incompressible fluids. Our wavelets have closed form expressions in the frequency and spatial domains, are divergence free in the ideal, analytic sense, have a multi-resolution structure and fast transforms, and an intuitive correspondence to common flo

Giuseppe Belgioioso, Sergio Grammatico

We address the generalized aggregative equilibrium seeking problem for noncooperative agents playing average aggregative games with affine coupling constraints. First, we use operator theory to characterize the generalized aggregative equilibria of the game as the zeros of a monotone set-valued operator. Then, we massage the Douglas-Rachford splitting to sol

Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva

Even though machine learning has become the major scene in dialogue research community, the real breakthrough has been blocked by the scale of data available. To address this fundamental obstacle, we introduce the Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and t

Claudia Mureşan

We prove that an infinite (bounded) involution lattice and even pseudo--Kleene algebra can have any number of congruences between $2$ and its number of elements or equalling its number of subsets, regardless of whether it has as many ideals as elements or as many ideals as subsets; consequently, the same holds for antiortholattices. Under the Generalized Con

Chao Zheng, Shidong Yu, Oleg Rubel

The extended carrier lifetime in hybrid halide perovskites was attributed to a quasi-indirect band gap that arises due to Rashba splitting in both conduction and valence band edges. In this paper, we present results for an effective relativistic band structure of (CH3NH3)PbI3 with the focus on the dispersion of electronic states near the band edges of (CH3NH

Bartłomiej Bosek, Tomasz Krawczyk

An on-line chain partitioning algorithm receives the elements of a poset one at a time, and when an element is received, irrevocably assigns it to one of the chains. In this paper, we present an on-line algorithm that partitions posets of width $w$ into $w^{O(\log{\log{w}})}$ chains. This improves over previously best known algorithms using $w^{O(\log{w})}$

Michael Andreas Klatt, Günter Last, D. Yogeshwaran

We study a stable partial matching $τ$ of the (possibly randomized) $d$-dimensional lattice with a stationary determinantal point process $Ψ$ on $\mathbb{R}^d$ with intensity $α>1$. For instance, $Ψ$ might be a Poisson process. The matched points from $Ψ$ form a stationary and ergodic (under lattice shifts) point process $Ψ^τ$ with intensity $1$ that very mu

Marc Andrew Valdez, Gavriil Shchedrin, Fernando Sols, Lincoln D. Carr

We investigate the dimension of the phase space attractor of a quantum chaotic many-body ratchet in the mean-field limit. Specifically, we explore a driven Bose-Einstein condensate in three distinct dynamical regimes - Rabi oscillations, chaos, and self-trapping regime, and for each of them we calculate the correlation dimension. For the ground state of the

Ilijas Farah, Georgios Katsimpas, Andrea Vaccaro

Every $\mathrm{C}^*$-algebra, regardless of its density character, can be embedded into the Calkin algebra in a forcing extension of the universe obtained without collapsing any cardinal.

Arjun Sharma, Mohit Sharma, Nicholas Rhinehart, Kris M. Kitani

The use of imitation learning to learn a single policy for a complex task that has multiple modes or hierarchical structure can be challenging. In fact, previous work has shown that when the modes are known, learning separate policies for each mode or sub-task can greatly improve the performance of imitation learning. In this work, we discover the interactio

Frédéric Paquin-Lefebvre, Wayne Nagata, Michael J. Ward

On a two-dimensional circular domain, we analyze the formation of spatio-temporal patterns for a class of coupled bulk-surface reaction-diffusion models for which a passive diffusion process occurring in the interior bulk domain is linearly coupled to a nonlinear reaction-diffusion process on the domain boundary. For this coupled PDE system we construct a ra

Yash Sharma, Tien-Dung Le, Moustafa Alzantot

Deep neural networks (DNNs) are vulnerable to adversarial examples, perturbations carefully crafted to fool the targeted DNN, in both the non-targeted and targeted case. In the non-targeted case, the attacker simply aims to induce misclassification. In the targeted case, the attacker aims to induce classification to a specified target class. In addition, it

W. R. Johnson, J. Nilsen

Standard measures of opacity, the imaginary part of the atomic scattering factor $f_2$ and the x-ray mass attenuation coefficient $μ/ρ$, are evaluated in shock-heated boron, boron carbide and boron nitride plasmas. The Hugoniot equation, relating the temperature $T$ behind a shock wave to the compression ratio $ρ/ρ_0$ across the shock front, is used in conne

Priodyuti Pradhan, Sarika Jalan

Understanding the localization properties of eigenvectors of complex networks is important to get insight into various structural and dynamical properties of the corresponding systems. Here, we analytically develop a scheme to construct a highly localized network for a given set of networks parameters that is the number of nodes and the number of interaction

Sylvia Carlisle, C Ward Henson

We show the theory of pointed $\R$-trees with radius at most $r$ is axiomatizable in a suitable continuous signature. We identify the model companion $\rbRT_r$ of this theory and study its properties. In particular, the model companion is complete and has quantifier elimination; it is stable but not superstable. We identify its independence relation and find

Amol Sasane

The set $\mathcal{E}'(\mathbb{R})$ of all compactly distributions, with the operations of addition, convolution, multiplication by complex scalars, and with the strong dual topology is a topological algebra. In this article, it is shown that the topological stable rank of $\mathcal{E}'(\mathbb{R})$ is 2.

Giovanni Interdonato, Marcus Karlsson, Emil Björnson, Erik G. Larsson

Cell-free Massive multiple-input multiple-output (MIMO) ensures ubiquitous communication at high spectral efficiency (SE) thanks to increased macro-diversity as compared cellular communications. However, system scalability and performance are limited by fronthauling traffic and interference. Unlike conventional precoding schemes that only suppress intra-cell

Faisal Mahmood, Daniel Borders, Richard Chen, Gregory N. McKay

Nuclei segmentation is a fundamental task that is critical for various computational pathology applications including nuclei morphology analysis, cell type classification, and cancer grading. Conventional vision-based methods for nuclei segmentation struggle in challenging cases and deep learning approaches have proven to be more robust and generalizable. Ho

Aris Tritsis, Christoph Federrath, Vasiliki Pavlidou

The atomic interstellar medium (ISM) is observed to be full of linear structures that are referred to as "fibers". Fibers exhibit similar properties to linear structures found in molecular clouds known as striations. Suggestive of a similar formation mechanism, both striations and fibers appear to be ordered, quasi-periodic, and well-aligned with the

Jaitra Chattopadhyay, Bidisha Roy, Subha Sarkar, R. Thangadurai

Let $p$ be an odd prime number. In this article, we study the number of quadratic residues and non-residues modulo $p$ which are multiples of $2$ or $3$ or $4$ and lying in the interval $[1, p-1]$, by applying the Dirichlet's class number formula for the imaginary quadratic field $\mathbb{Q}(\sqrt{-p})$.

Tamir Bendory, Nicolas Boumal, William Leeb, Eitan Levin

Single-particle cryo-electron microscopy (cryo-EM) has recently joined X-ray crystallography and NMR spectroscopy as a high-resolution structural method to resolve biological macromolecules. In a cryo-EM experiment, the microscope produces images called micrographs. Projections of the molecule of interest are embedded in the micrographs at unknown locations,

Xiaoyu Zhang, Zhou Fang, Chuanhou Gao

In this paper, we propose a novel technique, referred to as the Lyapunov Function PDEs technique, to diagnose persistence of chemical reaction networks with mass-action kinetics. The technique allows that every network is attached to a Lyapuonv function PDE and a boundary condition whose solutions are expected to be Lyapunov functions for the network. By mea

Luiz M. R. Gadelha, Pedro C. de Siracusa, Artur Ziviani, Eduardo Couto Dalcin

The unprecedented size of the human population, along with its associated economic activities, have an ever increasing impact on global environments. Across the world, countries are concerned about the growing resource consumption and the capacity of ecosystems to provide them. To effectively conserve biodiversity, it is essential to make indicators and know

Lucas J. Fernández-Alcázar, Horacio M. Pastawski, Raúl A. Bustos-Marún

In recent years there has been an increasing interest in nanomachines. Among them, current-driven ones deserve special attention as quantum effects can play a significant role there. Examples of the latter are the so-called adiabatic quantum motors. In this work, we propose using Anderson's localization to induce nonequilibrium forces in adiabatic quantu

Nikhil Chavan-Dafle, Rachel Holladay, Alberto Rodriguez

In this paper, we present the mechanics and algorithms to compute the set of feasible motions of an object pushed in a plane. This set is known as the motion cone and was previously described for non-prehensile manipulation tasks in the horizontal plane. We generalize its geometric construction to a broader set of planar tasks, where external forces such as

Alberto Cobos, Daniel Seco

We study generalized inner functions on a large family of Reproducing Kernel Hilbert Spaces. We show that the only inner functions that are entire are the normalized monomials.

Susumu Hirose, Eiko Kin

The branched virtual fibering theorem by Sakuma states that every closed orientable $3$-manifold with a Heegaard surface of genus $g$ has a branched double cover which is a genus $g$ surface bundle over the circle. It is proved by Brooks that such a surface bundle can be chosen to be hyperbolic. We prove that the minimal entropy over all hyperbolic, genus $g

Weisheng Cui, Wenzheng Liu, Yongjie Gao

A special surface discharge is proposed based on the multi-anode electrode geometry. Instead of the traditional surface flashover of creepage on the insulator surface between the electrodes, a surface discharge with one of the electrodes being placed far away from the insulator is achieved in this paper. The unique electric field distribution due to the mult

Yiren Zhao, Ilia Shumailov, Robert Mullins, Ross Anderson

As deep neural networks (DNNs) become widely used, pruned and quantised models are becoming ubiquitous on edge devices; such compressed DNNs are popular for lowering computational requirements. Meanwhile, recent studies show that adversarial samples can be effective at making DNNs misclassify. We, therefore, investigate the extent to which adversarial sample

Salvador Pineda, Ricardo Fernandez-Blanco, Juan Miguel Morales

The short-term operation of a power system is usually planned by solving a day-ahead unit commitment problem. Due to historical reasons, the commitment of the power generating units is decided over a time horizon typically consisting of the 24 hourly periods of a day. In this paper, we show that, as a result of the increasing penetration of intermittent rene

Andrey Ryabichev

We extend Y.Eliashberg's $h$-principle to smooth maps of surfaces which are allowed to have cusp singularities, as well as folds. More precisely, we prove a necessary and sufficient condition for a given map of surfaces to be homotopic to one with given loci of folds and cusps. Then we use these results to obtain a necessary and sufficient condition for

CMS Collaboration

A search is conducted for new physics in final states containing a photon and missing transverse momentum in proton-proton collisions at $\sqrt{s} =$ 13 TeV, using the data collected in 2016 by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. No deviations from the predictions of the standard model are observed. The

Ting-Jui Hsu, Fengping Jin, Christian Seidel, Florian Neukart

We study the effect of the anneal path control per qubit, a new user control feature offered on the D-Wave 2000Q quantum annealer, on the performance of quantum annealing for solving optimization problems by numerically solving the time-dependent Schrödinger equation for the time-dependent Hamiltonian modeling the annealing problems. The anneal path control

V. O. Shkolnikov, Guido Burkard

In this work we present an effective Hamiltonian description of the quantum dynamics of a generalized Lambda system undergoing adiabatic evolution. We assume the system to be initialized in the dark subspace and show that its holonomic evolution can be viewed as a conventional Hamiltonian dynamics in an appropriately chosen extended Hilbert space. In contras

Armen Sedrakian

We study the axion cooling of neutron stars within the Dine-Fischler-Srednicki-Zhitnitsky (DFSZ) model, which allows for tree level coupling of electrons to the axion {and locks the Peccei-Quinn charges of fermions via an angle parameter}. This extends our previous study [Phys. Rev. D 93, 065044 (2016)] limited to hadronic models of axions. We explore the tw

Julien David, Lionel Pournin, Rado Rakotonarivo

We introduce a graph structure on Euclidean polytopes. The vertices of this graph are the $d$-dimensional polytopes contained in $\mathbb{R}^d$ and its edges connect any two polytopes that can be obtained from one another by either inserting or deleting a vertex, while keeping their vertex sets otherwise unaffected. We prove several results on the connectivi

Vindhyawasini Prasad

Light hadron spectroscopy plays an important role in understanding the decay dynamics of unconventional hadronic states, such as strangeonium and glueballs. BESIII provides an ideal avenue to search for these exotic states thanks to a huge amount of data recorded at various energy points in the tau-charm mass region including J/psi resonance. This report sum

Guanxiong Zeng, Yang Chen, Bo Cui, Shan Yu

Deep neural networks (DNNs) are powerful tools in learning sophisticated but fixed mapping rules between inputs and outputs, thereby limiting their application in more complex and dynamic situations in which the mapping rules are not kept the same but changing according to different contexts. To lift such limits, we developed a novel approach involving a lea

Ralph Strebel

In this article, I study some classes of finitely presented groups with the aim of finding out whether the maximal metabelian quotients of the members of these classes admit finite presentations. The considered classes include those of soluble groups, of one-relator or knot groups, and of Artin groups.

B. Korany, M. I. Nouh

The aim of this paper is to study the variability of the warm absorber "clouds of ionised gas within AGN", for the Seyfert 1 galaxies Arakelian 564. The X-ray spectra for four XMM-Newton observations of this object are analysed in EPIC and RGS instruments. These four observations covered a period of eleven years. There are some changes in the ionisat

Jie-Shuang Wang, Fang-Kun Peng, Kinwah Wu, Zi-Gao Dai

We investigate emission signatures of binary compact star gravitational wave sources consisting of strongly magnetized neutron stars (NSs) and/or white dwarfs (WDs) in their late-time inspiral phase. Because of electromagnetic interactions between the magnetospheres of the two compact stars, a substantial amount of energy will be extracted, and the resultant

Norbert Schorghofer

Neutral exospheres of the Moon, Mercury, and several other solar system bodies consist of particles on ballistic trajectories. Here, the vertical density profile of a surface-bounded exosphere is calculated using thermodynamic averages of an ensemble of ballistic trajectories. When the initial velocities follow the so-called "Maxwell-Boltzmann Flux"

Tao Yang, Bin Hu, Rong-Gen Cai, Bin Wang

Strong gravitational lensing by galaxies provides us with a unique opportunity to understand the nature of gravity on galactic and extra-galactic scales. In this paper, we propose a new multimessenger approach using data from both gravitational wave (GW) and the corresponding electromagnetic (EM) counterpart to infer the constraint of the modified gravity (M

Chaim Baskin, Natan Liss, Yoav Chai, Evgenii Zheltonozhskii

Convolutional Neural Networks (CNN) are very popular in many fields including computer vision, speech recognition, natural language processing, to name a few. Though deep learning leads to groundbreaking performance in these domains, the networks used are very demanding computationally and are far from real-time even on a GPU, which is not power efficient an

Eugene Goldberg

We consider the Quantifier Elimination (QE) problem for propositional CNF formulas with existential quantifiers. QE plays a key role in formal verification. Earlier, we presented an approach based on the following observation. To perform QE, one just needs to add a set of clauses depending on free variables that makes the quantified clauses (i.e. clauses wit

Jun Jin, Laura Petrich, Masood Dehghan, Zichen Zhang

We present a robot eye-hand coordination learning method that can directly learn visual task specification by watching human demonstrations. Task specification is represented as a task function, which is learned using inverse reinforcement learning(IRL) by inferring differential rewards between state changes. The learned task function is then used as continu

Tao Yang, Jemin George, Jiahu Qin, Xinlei Yi

In this paper, we study the problem of finding the least square solutions of over-determined linear algebraic equations over networks in a distributed manner. Each node has access to one of the linear equations and holds a dynamic state. We first propose a distributed least square solver over connected undirected interaction graphs and establish a necessary

Brian Hall, Todd Kemp

The free multiplicative Brownian motion $b_{t}$ is the large-$N$ limit of Brownian motion $B_t^N$ on the general linear group $\mathrm{GL}(N;\mathbb{C})$. We prove that the Brown measure for $b_{t}$---which is an analog of the empirical eigenvalue distribution for matrices---is supported on the closure of a certain domain $Σ_{t}$ in the plane. The domain $Σ_

Hongwei Lou, Jiongmin Yong

Maximization and minimization problems of the principle eigenvalue for divergence form second order elliptic operators with the Dirichlet boundary condition are considered. The principal eigen map of such elliptic operators is introduced and some basic properties of this map, including continuity, concavity, and differentiability with respect to the paramete

De-Xian Wei, Wei-Tian Deng, Xu-Guang Huang

The hot and dense matter generated in heavy-ion collisions contains intricate vortical structure in which the local fluid vorticity can be very large. Such vorticity can polarize the spin of the produced particles. We study the event-by-event generation of the so-called thermal vorticity in Au + Au collisions at energy region $\sqrt{s}=7.7-200$ GeV and calcu

Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang

Although stochastic gradient descent (SGD) is a driving force behind the recent success of deep learning, our understanding of its dynamics in a high-dimensional parameter space is limited. In recent years, some researchers have used the stochasticity of minibatch gradients, or the signal-to-noise ratio, to better characterize the learning dynamics of SGD. I

Eric Marberg

We present an expository overview of the monoidal structures in the category of linearly compact vector spaces. Bimonoids in this category are the natural duals of infinite-dimensional bialgebras. We classify the relations on words whose equivalence classes generate linearly compact bialgebras under shifted shuffling and deconcatenation. We also extend some

Tianmin Shu, Yuandong Tian

Most of the prior work on multi-agent reinforcement learning (MARL) achieves optimal collaboration by directly controlling the agents to maximize a common reward. In this paper, we aim to address this from a different angle. In particular, we consider scenarios where there are self-interested agents (i.e., worker agents) which have their own minds (preferenc

Hejia Zhang, Eric Heiden, Stefanos Nikolaidis, Joseph J. Lim

Personal robots assisting humans must perform complex manipulation tasks that are typically difficult to specify in traditional motion planning pipelines, where multiple objectives must be met and the high-level context be taken into consideration. Learning from demonstration (LfD) provides a promising way to learn these kind of complex manipulation skills e

Peter Bantay

We study the problem of orbifold deconstruction, i.e., the process of recognizing, using only readily available information, whether a given conformal model can be realized as an orbifold, and the identification of the twist group and the original conformal model.

Fuxun Yu, Chenchen Liu, Yanzhi Wang, Liang Zhao

One popular hypothesis of neural network generalization is that the flat local minima of loss surface in parameter space leads to good generalization. However, we demonstrate that loss surface in parameter space has no obvious relationship with generalization, especially under adversarial settings. Through visualizing decision surfaces in both parameter spac

Zhiming Zhou, Qingru Zhang, Guansong Lu, Hongwei Wang

Adam is shown not being able to converge to the optimal solution in certain cases. Researchers recently propose several algorithms to avoid the issue of non-convergence of Adam, but their efficiency turns out to be unsatisfactory in practice. In this paper, we provide new insight into the non-convergence issue of Adam as well as other adaptive learning rate

Minsuk Shin, Jun S Liu

Although Bayesian variable selection methods have been intensively studied, their routine use in practice has not caught up with their non-Bayesian counterparts such as Lasso, likely due to difficulties in both computations and flexibilities of prior choices. To ease these challenges, we propose the neuronized priors to unify and extend some popular shrinkag

Jacky C. K. Chow, Derek Lichti, Kathleen Ang, Gregor Kuntze

X-ray imaging is a fundamental tool of routine clinical diagnosis. Fluoroscopic imaging can further acquire X-ray images at video frame rates, thus enabling non-invasive in-vivo motion studies of joints, gastrointestinal tract, etc. For both the qualitative and quantitative analysis of static and dynamic X-ray images, the data should be free of systematic bi

Rongwei Yang

This survey aims to give a brief introduction to operator theory in the Hardy space over the bidisc $H^2(\mathbb D^2)$. As an important component of multivariable operator theory, the theory in $H^2(\mathbb D^2)$ focuses primarily on two pairs of commuting operators that are naturally associated with invariant subspaces (or submodules) in $H^2(\mathbb D^2)$.

Roman Chernov, Kostiantyn Drach, Kateryna Tatarko

We consider the class of $λ$-concave bodies in $\mathbb R^{n+1}$; that is, convex bodies with the property that each of their boundary points supports a tangent ball of radius $1/λ$ that lies locally (around the boundary point) inside the body. In this class we solve a reverse isoperimetric problem: we show that the convex hull of two balls of radius $1/λ$ (

Chris Connell, Shi Wang

We relate the Gromov norm on homology classes to the harmonic norm on the dual cohomology and obtain double sided bounds in terms of the volume and other geometric quantities of the underlying manifold. Along the way, we provide comparisons to other related norms and quantities as well.

Jesse Farebrother, Marlos C. Machado, Michael Bowling

Deep reinforcement learning algorithms have shown an impressive ability to learn complex control policies in high-dimensional tasks. However, despite the ever-increasing performance on popular benchmarks, policies learned by deep reinforcement learning algorithms can struggle to generalize when evaluated in remarkably similar environments. In this paper we p

Yongqiang Cai, Qianxiao Li, Zuowei Shen

Despite its empirical success and recent theoretical progress, there generally lacks a quantitative analysis of the effect of batch normalization (BN) on the convergence and stability of gradient descent. In this paper, we provide such an analysis on the simple problem of ordinary least squares (OLS). Since precise dynamical properties of gradient descent (G

Garritt L. Page, Fernando A. Quintana, Gary L. Rosner

Combination chemotherapy treatment regimens created for patients diagnosed with childhood acute lymphoblastic leukemia have had great success in improving cure rates. Unfortunately, patients prescribed these types of treatment regimens have displayed susceptibility to the onset of osteonecrosis. Some have suggested that this is due to pharmacokinetic interac

Jialin Liu, Wotao Yin, Wuchen Li, Yat Tin Chow

We propose a fast algorithm for the calculation of the Wasserstein-1 distance, which is a particular type of optimal transport distance with homogeneous of degree one transport cost. Our algorithm is built on multilevel primal-dual algorithms. Several numerical examples and a complexity analysis are provided to demonstrate its computational speed. On some co

Evgeny Andriyash, Arash Vahdat, Bill Macready

In many applications we seek to maximize an expectation with respect to a distribution over discrete variables. Estimating gradients of such objectives with respect to the distribution parameters is a challenging problem. We analyze existing solutions including finite-difference (FD) estimators and continuous relaxation (CR) estimators in terms of bias and v

Kunkun Pang, Mingzhi Dong, Yang Wu, Timothy M. Hospedales

Active learning aims to reduce annotation cost by predicting which samples are useful for a human teacher to label. However it has become clear there is no best active learning algorithm. Inspired by various philosophies about what constitutes a good criteria, different algorithms perform well on different datasets. This has motivated research into ensembles

Owen J. Brison, Jason A. C. Gallas

Equivalence between algebraic equations of motion may be detected by using a $p$-adic method, methods using factorization and linear algebra, or by systematic computer search of suitable Tschirnhausen transformations. Here, we show standard {\sl polynomial interpolation} to be a competitive alternative method for detecting orbital equivalences and field isom

Supratim Mitra, Satakshi Gupta, Aneesh M. Joseph, Umesh Kumar Dwivedi

An attempt has been made to synthesize (Ca0.4Sr0.6)Bi4Ti4O15(CSBT) thin film using pulsed laser deposition (PLD) and successfully optimized the deposition conditions. A good quality film with the desired phase is obtained at a substrate temperature of 650 oC based on phase, composition and morphology studies. Highly c-axis oriented films with average thickne

Guihao Jia, Yu Xu, Xiao Kong, Cuixian Guo

Using the linear local induction approximation, we investigated the self-induced motion of a vortex line that corresponds to the motion of a particle in quantum mechanics. Concerning Kelvin waves, the effective Schrödinger equation, physical quantities operators, and the corresponding path-integral formula are obtained. The vortex line-particle mapping may h

Adrian Wills, Carl Jidling, Thomas Schon

During recent years there has been an increased interest in stochastic adaptations of limited memory quasi-Newton methods, which compared to pure gradient-based routines can improve the convergence by incorporating second order information. In this work we propose a direct least-squares approach conceptually similar to the limited memory quasi-Newton methods

Xin Zhong

We consider the singularity formation of strong solutions to the two-dimensional full compressible Navier-Stokes equations with zero heat conduction in a bounded domain. It is shown that for the initial density allowing vacuum, the strong solution exists globally if the density and the pressure are bounded from above. Critical Sobolev inequalities of logarit