February 2019 arXiv papers — page 14

Haofei Xu, Jianmin Zheng, Jianfei Cai, Juyong Zhang

While learning based depth estimation from images/videos has achieved substantial progress, there still exist intrinsic limitations. Supervised methods are limited by a small amount of ground truth or labeled data and unsupervised methods for monocular videos are mostly based on the static scene assumption, not performing well on real world scenarios with th

Itay Griniasty, Hillel Aharoni, Efi Efrati

Thin nematic elastomers, composite hydrogels and plant tissues are among many systems that display uniform anisotropic deformation upon external actuation. In these materials, the spatial orientation variation of a local director field induces intricate global shape changes. Despite extensive recent efforts, to date, there is no general solution to the inver

Shadman Sakib, Md. Abu Bakr Siddique

Tissue classification is one of the significant tasks in the field of biomedical image analysis. Magnetic Resonance Imaging (MRI) is of great importance in tissue classification especially in the areas of brain tissue classification which is able to recognize anatomical areas of interest such as surgical planning, monitoring therapy, clinical drug trials, im

Lavinia Corina Ciungu

In this paper we define two types of implicative derivations on pseudo-BCI algebras, we investigate their properties and we give a characterization of regular implicative derivations of type II. We also define the notion of a $d$-invariant deductive system of a pseudo-BCI algebra $A$ proving that $d$ is a regular derivation of type II if and only if every de

Maxim Kontsevich, Vasily Pestun, Yuri Tschinkel

We introduce new invariants in equivariant birational geometry and study their relation to modular symbols and cohomology of arithmetic groups.

Md Moniruzzaman, S. M. Shamsul Islam, Paul Lavery, Mohammed Bennamoun

Monitoring underwater habitats is a vital part of observing the condition of the environment. The detection and mapping of underwater vegetation, especially seagrass has drawn the attention of the research community as early as the nineteen eighties. Initially, this monitoring relied on in situ observation by experts. Later, advances in remote-sensing techno

Oliver Janzer

A tensor defined over a finite field $\mathbb{F}$ has low analytic rank if the distribution of its values differs significantly from the uniform distribution. An order $d$ tensor has partition rank 1 if it can be written as a product of two tensors of order less than $d$, and it has partition rank at most $k$ if it can be written as a sum of $k$ tensors of p

S. Kimura, Y. Nakajima, Z. Mita, R. Jha

The carrier dynamics and electronic structures of type-II Weyl semimetal candidates MoTe$_2$ and WTe$_2$ have been investigated by using temperature-dependent optical conductivity [$σ(ω)$] spectra. Two kinds of Drude peaks (narrow and broad) have been separately observed. The width of the broad Drude peak increases with elevating temperature above the Debye

Zi-Hang Jiang, Qianyi Wu, Keyu Chen, Juyong Zhang

In this paper, we present a novel strategy to design disentangled 3D face shape representation. Specifically, a given 3D face shape is decomposed into identity part and expression part, which are both encoded and decoded in a nonlinear way. To solve this problem, we propose an attribute decomposition framework for 3D face mesh. To better represent face shape

Mohammad Ali Ahmadpoor, Marzieh Shams Yousefi

In this paper, we follow two main goals. In the first attempt, we give some functorial properties of the $p$-analog of the Fourier-Stieltjes algebras in which we generalize some previously existed definitions and theorems in Arsac and Cowling's works, to utilize them to prove $p$-complete boundedness of some well-known maps on these algebras. In the seco

Sajjad Taravati, George V. Eleftheriades

This paper studies the theory and applications of the diffraction of electromagnetic waves by space-time periodic (STP) diffraction gratings. We show that, in contrast with conventional spatially periodic grating, a STP diffraction grating produces spatial diffraction orders, each of which is formed by an infinite set of temporal diffraction orders. Such spa

Shadman Sakib, Md. Abu Bakr Siddique

This paper proposes the implementation of a circuit based simulation for a Solar Photovoltaic (PV) cell in order to get the maximum power output. The model is established based on the mathematical model of the PV module. As the PV cell is used to determine the physical and electrical behavior of the cell corresponding to environmental factors such as tempera

Antreas Antoniou, Amos Storkey

The field of few-shot learning has been laboriously explored in the supervised setting, where per-class labels are available. On the other hand, the unsupervised few-shot learning setting, where no labels of any kind are required, has seen little investigation. We propose a method, named Assume, Augment and Learn or AAL, for generating few-shot tasks using u

Richard Howl, Ivette Fuentes

We consider an interferometer that contains active elements, such as a parametric amplifier, with general two-mode Gaussian unitary channels rather than the usually considered phase-shift channel. We concentrate on a scheme based on the recently proposed pumped-up SU(1,1) active interferometer where all input particles participate in the parameter estimation

S. L. A. de Queiroz, R. B. Stinchcombe

We present a numerical study of a two-lane version of the stochastic non-equilibrium model known as the totally asymmetric simple exclusion process. For such a system with open boundaries, and suitably chosen values of externally-imposed particle injection ($α$) and ejection ($β$) rates, spontaneous symmetry breaking can occur. We investigate the statistics

Maurice Laveaux, Jan Friso Groote, Tim A. C. Willemse

The notion of refinement plays an important role in software engineering. It is the basis of a stepwise development methodology in which the correctness of a system can be established by proving, or computing, that a system refines its specification. Wang et al. describe algorithms based on antichains for efficiently deciding trace refinement, stable failure

Atefeh Rezaei, Paeiz Azmi, Nader Mokari, Mohammad Reza Javan

In this paper, we consider a hybrid scheme of coordinated multi-point (CoMP) technology in MISO heterogeneous communication networks based on power domain non-orthogonal multiple access (PD-NOMA). We propose a novel method based on matching game with externalities to realize the hybrid scheme where the number of the cooperative nodes are variable. Moreover,

Nanyu Li, Cuiyin Liu

The optimization inspired network can bridge convex optimization and neural networks in Compressive Sensing (CS) reconstruction of natural image, like ISTA-Net+, which mapping optimization algorithm: iterative shrinkage-thresholding algorithm (ISTA) into network. However, measurement matrix and input initialization are still hand-crafted, and multi-channel f

Ralph Kritzinger, Markus Passenbrunner

The irregularities of a distribution of $N$ points in the unit interval are often measured with various notions of discrepancy. The discrepancy function can be defined with respect to intervals of the form $[0,t)\subset [0,1)$ or arbitrary subintervals of the unit interval. In the former case, it is a well known fact in discrepancy theory that the $N$-elemen

Goran Malic, Sibylle Schroll

In this paper, we associate a finite dimensional algebra, called a Brauer graph algebra, to every clean dessin d'enfant by constructing a quiver based on the monodromy of the dessin. We show that Galois conjugate dessins d'enfants give rise to derived equivalent Brauer graph algebras and that the stable Auslander-Reiten quiver and the dimension of th

Laura Jakobsson

Cellular resolutions is a well studied topic on the level of single resolutions and certain specific families of cellular resolutions. One question coming out of the work on families is to understand the structure of cellular resolutions more generally. We give a starting point to understanding higher level structures by defining the category of cellular res

Bastian Wandt, Bodo Rosenhahn

This paper addresses the problem of 3D human pose estimation from single images. While for a long time human skeletons were parameterized and fitted to the observation by satisfying a reprojection error, nowadays researchers directly use neural networks to infer the 3D pose from the observations. However, most of these approaches ignore the fact that a repro

Jianlin Li, Pengfei Yang, Jiangchao Liu, Liqian Chen

Deep neural networks (DNNs) have been shown lack of robustness for the vulnerability of their classification to small perturbations on the inputs. This has led to safety concerns of applying DNNs to safety-critical domains. Several verification approaches have been developed to automatically prove or disprove safety properties of DNNs. However, these approac

Maohui Lyu, Weng Cho Chew, Lijun Jiang, Maojun Li

It is known that both linear and nonlinear optical phenomena can be produced when the plasmon in metallic nanostructures are excited by the external electromagnetic waves. In this work, a coupled system of Maxwell equations and a gas dynamic model including a quantum pressure term is employed to simulate the plasmon dynamics of free electron fluid in differe

T. Weber, R. Georgii, P. Böni

Due to the instrument's non-trivial resolution function, measurements on triple-axis spectrometers require extra care from the experimenter in order to obtain optimal results and to avoid unwanted spurious artefacts. We present a free and open-source software system that aims to ease many of the tasks encountered during the planning phase, in the executi

Martin Barisits, Thomas Beermann, Frank Berghaus, Brian Bockelman

Rucio is an open-source software framework that provides scientific collaborations with the functionality to organize, manage, and access their data at scale. The data can be distributed across heterogeneous data centers at widely distributed locations. Rucio was originally developed to meet the requirements of the high-energy physics experiment ATLAS, and n

Changhee Han, Kohei Murao, Tomoyuki Noguchi, Yusuke Kawata

Accurate Computer-Assisted Diagnosis, associated with proper data wrangling, can alleviate the risk of overlooking the diagnosis in a clinical environment. Towards this, as a Data Augmentation (DA) technique, Generative Adversarial Networks (GANs) can synthesize additional training data to handle the small/fragmented medical imaging datasets collected from v

L. Bugnet, R. A. García, S. Mathur, G. R. Davies

The NASA's Transiting Exoplanet Survey Satellite (TESS) is about to provide full-frame images of almost the entire sky. The amount of stellar data to be analysed represents hundreds of millions stars, which is several orders of magnitude above the amount of stars observed by CoRoT, Kepler, or K2 missions. We aim at automatically classifying the newly obs

Xinlong Wang, Shu Liu, Xiaoyong Shen, Chunhua Shen

A 3D point cloud describes the real scene precisely and intuitively.To date how to segment diversified elements in such an informative 3D scene is rarely discussed. In this paper, we first introduce a simple and flexible framework to segment instances and semantics in point clouds simultaneously. Then, we propose two approaches which make the two tasks take

D. L. Shepelyansky

It is proposed to modify the Cirac-Zoller proposal of quantum computer with cold ions in a global oscillator trap potential by adding a periodic potential with an incommensurate average ratio of number of ions to number of periods being order of unity. With the increase of the periodic potential amplitude the system enters in the Aubry pinned phase character

Antonio González-Arroyo, Issaku Kanamori, Ken-Ichi Ishikawa, Kanata Miyahana

We present the results of an exploratory study of the numerical stochastic perturbation theory (NSPT) applied to the four dimensional twisted Eguchi-Kawai (TEK) model. We employ a Kramers type algorithm based on the Generalized Hybrid Molecular Dynamics (GHMD) algorithm. We have computed the perturbative expansion of square Wilson loops up to $O(g^8)$. The r

Bongjune Kim, Ko-Tang Chen, Chia-Yu Hsu, Shih-Si Hsiao

The effect of electromagnetically induced transparency (EIT) combined with Rydberg-state atoms provides high optical nonlinearity to efficiently mediate the photon-photon interaction. However, the decay rate of Rydberg coherence, i.e., the decoherence rate, plays an important role in optical nonlinear efficiency, and can be largely influenced by laser freque

Laura Giordano, Alberto Policriti

We explore the relationships between Description Logics and Set Theory. The study is carried on using, on the set-theoretic side, a very rudimentary axiomatic set theory Omega, consisting of only four axioms characterizing binary union, set difference, inclusion, and the power-set. An extension of ALC, ALC^Omega, is then defined in which concepts are natural

José Ángel Peláez, Jouni Rättyä

The question of when the Bergman projection $P_ω$ induced by a radial weight $ω$ on the unit disc is a bounded operator from one space into another is of primordial importance in the theory of Bergman spaces. The long-standing problem of describing the radial weights $ω$ such that $P_ω$ is bounded on the Lebesgue space $L^p_ω$ had been known to experts since

Homayun Afrabandpey, Tomi Peltola, Samuel Kaski

Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work focuses on directly eliciting informative prior distributions for parameters. This either requires considerable statistical expertise or is laborious, as the emphasis has been on ac

Alexander Holm Kiilerich, Klaus Mølmer

We present a formalism that accounts for the evolution of quantum states of travelling light pulses incident on and emanating from a local quantum scatterer such as an atom or a cavity. We assume non-dispersive asymptotic propagation of the pulses and Markovian coupling of the stationary system to input and output fields. This permits derivation of a cascade

Alexander Kuznetsov, Alexander Perry

We show that over an algebraically closed field of characteristic not equal to 2, homological projective duality for smooth quadric hypersurfaces and for double covers of projective spaces branched over smooth quadric hypersurfaces is a combination of two operations: one interchanges a quadric hypersurface with its classical projective dual and the other int

Luka Milićević

Let $G_1, \dots, G_k$ be vector spaces over a finite field $\mathbb{F} = \mathbb{F}_q$ with a non-trivial additive character $χ$. The analytic rank of a multilinear form $α\colon G_1 \times \dots \times G_k \to \mathbb{F}$ is defined as $\operatorname{arank}(α) = -\log_q \mathbb{E}_{x_1 \in G_1, \dots, x_k\in G_k} χ\big(α(x_1,\dots, x_k)\big)$. The partition

Youngji Kim, Ayoung Kim

We proposed an end-to-end deep learning-based simultaneous localization and mapping (SLAM) system following conventional visual odometry (VO) pipelines. The proposed method completes the SLAM framework by including tracking, mapping, and sequential optimization networks while training them in an unsupervised manner. Together with the camera pose and depth ma

Alexander Kuznetsov, Alexander Perry

We introduce the notion of a categorical cone, which provides a categorification of the classical cone over a projective variety, and use our work on categorical joins to describe its behavior under homological projective duality. In particular, our construction provides well-behaved categorical resolutions of singular quadrics, which we use to obtain an exp

Luis A. Anchordoqui, Carlos Garcia Canal, Jorge F. Soriano

IceCube has observed 80 astrophysical neutrino candidates in the energy range 0.02 < E_ν/PeV < 2. Deep inelastic scattering of these neutrinos with nucleons on Antarctic ice sheet probe center-of-mass energies $\sqrt{s} \sim$ 1 TeV. By comparing the rates for two classes of observable events, any departure from the benchmark (perturbative QCD) neutrino-nucle

Seongyeon Kim, Ihyeok Seo, Jihyeon Seok

We obtain Strichartz inequalities for the wave equation with potentials which behave like the inverse square potential $|x|^{-2}$ but might be not a radially symmetric function.

Heming Zhang, Shalini Ghosh, Larry Heck, Stephen Walsh

The key challenge of generative Visual Dialogue (VD) systems is to respond to human queries with informative answers in natural and contiguous conversation flow. Traditional Maximum Likelihood Estimation (MLE)-based methods only learn from positive responses but ignore the negative responses, and consequently tend to yield safe or generic responses. To addre

Ziyao Li, Liang Zhang, Guojie Song

Graph Convolutional Networks (GCNs) have proved to be a most powerful architecture in aggregating local neighborhood information for individual graph nodes. Low-rank proximities and node features are successfully leveraged in existing GCNs, however, attributes that graph links may carry are commonly ignored, as almost all of these models simplify graph links

Yong Zhao, Yao Wu, Zhenhua Chai, Baochang Shi

A block triple-relaxation-time (B-TriRT) lattice Boltzmann model for general nonlinear anisotropic convection-diffusion equations (NACDEs) is proposed, and the Chapman-Enskog analysis shows that the present B-TriRT model can recover the NACDEs correctly. There are some striking features of the present B-TriRT model: firstly, the relaxation matrix of B-TriRT

Francis Comets, Mikhail V. Menshikov, Andrew R. Wade

Fix integers $d \geq 2$ and $k\geq d-1$. Consider a random walk $X_0, X_1, \ldots$ in $\mathbb{R}^d$ in which, given $X_0, X_1, \ldots, X_n$ ($n \geq k$), the next step $X_{n+1}$ is uniformly distributed on the unit ball centred at $X_n$, but conditioned that the line segment from $X_n$ to $X_{n+1}$ intersects the convex hull of $\{0, X_{n-k}, \ldots, X_n\}$

S. U. Piatrusha, E. S. Tikhonov, Z. D. Kvon, N. N. Mikhailov

Recent topological band theory distinguishes electronic band insulators with respect to various symmetries and topological invariants, most commonly, the time reversal symmetry and the $\rm Z_2$ invariant. The interface of two topologically distinct insulators hosts a unique class of electronic states -- the helical states, which shortcut the gapped bulk and

Yeong Deok Han, Taeseung Choi, Sam Young Cho

We have studied the phase singularity of the relativistic vortex beams for the two sets of relativistic operators. One includes the new spin and orbital angular momentum (OAM) operators, which is derived from the parity-extended Poincaré group, and the other is composed of the (usual) Dirac spin and OAM operators. The first set predicts the same singular cir

Daohai Li, Alexander J. Mustill, Melvyn B. Davies

Stars formed in clusters can encounter other stars at close distances. In typical open clusters in the Solar neighbourhood containing hundreds or thousands of member stars, ten to twenty per cent of Solar-mass member stars are expected to encounter another star at distances closer than 100 au. These close encounters strongly perturb the planetary systems, di

Alex Krolewski, Shirley Ho, Yen-Chi Chen, P. F. Chan

Halos and galaxies acquire their angular momentum during the collapse of surrounding large-scale structure. This process imprints alignments between galaxy spins and nearby filaments and sheets. Low mass halos grow by accretion onto filaments, aligning their spins with the filaments, whereas high mass halos grow by mergers along filaments, generating spins p

P. Wittenburg, H. Pergl Sustkova, A. Montesanti, S. M. Bloemers

There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of workshops t

Zhenyu Zhang, Gan Gu, Xiaoma Wang, Yun-He Li

The tomographic Alcock-Paczynski (AP) method can result in tight cosmological constraints by using small and intermediate clustering scales of the large scale structure (LSS) of the galaxy distribution. By focusing on the redshift dependence, the AP distortion can be distinguished from the distortions produced by the redshift space distortions (RSD). In this

Anqi Huang, Álvaro Navarrete, Shi-Hai Sun, Poompong Chaiwongkhot

Quantum key distribution (QKD) based on the laws of quantum physics allows the secure distribution of secret keys over an insecure channel. Unfortunately, imperfect implementations of QKD compromise its information-theoretical security. Measurement-device-independent quantum key distribution (MDI-QKD) is a promising approach to remove all side channels from

Ernest K. Ryu, Robert Hannah, Wotao Yin

Many iterative methods in applied mathematics can be thought of as fixed-point iterations, and such algorithms are usually analyzed analytically, with inequalities. In this paper, we present a geometric approach to analyzing contractive and nonexpansive fixed point iterations with a new tool called the scaled relative graph (SRG). The SRG provides a correspo

Pan Li, Niao He, Olgica Milenkovic

We introduce a new convex optimization problem, termed quadratic decomposable submodular function minimization (QDSFM), which allows to model a number of learning tasks on graphs and hypergraphs. The problem exhibits close ties to decomposable submodular function minimization (DSFM), yet is much more challenging to solve. We approach the problem via a new du

Mohammed Lemou, Ana Maria Luz, Florian Méhats

In this work we prove the nonlinear instability of inhomogeneous steady states solutions to the Hamiltonian Mean Field (HMF) model. We first study the linear instability of this model under a simple criterion by adapting the techniques developed in [19]. In a second part, we extend to the inhomogeneous case some techniques developed in [14, 17, 18] and prove

Robert Goldblatt

Structures based on polarities have been used to provide relational semantics for propositional logics that are modelled algebraically by non-distributive lattices with additional operators. This article develops a first order notion of morphism between polarity-based structures that generalises the theory of bounded morphisms for Boolean modal logics. It de

Tanweer Alam

Blockchain (BC) in the Internet of Things (IoT) is a novel technology that acts with decentralized, distributed, public and real-time ledger to store transactions among IoT nodes. A blockchain is a series of blocks, each block is linked to its previous blocks. Every block has the cryptographic hash code, previous block hash, and its data. The transactions in

Zehao Yu, Jia Zheng, Dongze Lian, Zihan Zhou

Single-image piece-wise planar 3D reconstruction aims to simultaneously segment plane instances and recover 3D plane parameters from an image. Most recent approaches leverage convolutional neural networks (CNNs) and achieve promising results. However, these methods are limited to detecting a fixed number of planes with certain learned order. To tackle this p

Jonathan Walg, Anatoly Rodnianski, Itzhak Orion

Radioactive sources presented annual periodical half-life changes in several accurate measurements, although customary practice claims that radioactive decay should be a physical constant for each radionuclide. Besides that, the Purdue measurements of Mn-54 decay-rates indicated response to solar X-ray flare events in 2006. The Mn-54 source emits neutrino fr

Dmytro Oliinychenko, Volker Koch

We present a sampling method for the transition from relativistic hydrodynamics to particle transport, commonly referred to as particlization, which preserves the local event-by-event conservation of energy, momentum, baryon number, strangeness, and electric charge. The proposed method is essential for studying fluctuations and correlations by means of stoch

I. K. Hong, C. S. Kim

By using complex quaternion, which is the system of quaternion representation extended to complex numbers, we show that the laws of electromagnetism can be expressed much more simply and concisely. We also derive the quaternion representation of rotations and boosts from the spinor representation of Lorentz group. It is suggested that the imaginary &#39;i&#3

Zhouping Xin, Qian Yuan, Yuan Yuan

This paper studies the asymptotic stability of shock profiles and rarefaction waves under space-periodic perturbations for one-dimensional convex scalar viscous conservation laws. For the shock profile, we show that the solution approaches the background shock profile with a constant shift in the $ L^\infty(\mathbb{R}) $ norm at exponential rates. The new ph

Andreas Finke

The applicability of a linearized perturbed FLRW metric to the late, lumpy universe has been subject to debate. We consider in an elementary way the Newtonian limit of the Einstein equations with this ansatz for the case of structure formation in late-time cosmology, on small and large scales, and argue that linearizing the Einstein tensor produces only a sm

Liu Hong, Hong Qian, Lowell F. Thompson

Radon-Nikodym (RN) derivative between two measures arises naturally in the affine structure of the space of probability measures with densities. Entropy, free energy, relative entropy, and entropy production as mathematical concepts associated with RN derivatives are introduced. We identify a simple equation that connects two measures with densities as a pos

E. M. Tursunov, Daniel Baye, S. A. Turakulov

At the long-wavelength approximation, electric dipole transitions are forbidden between isospin-zero states. In an $α+n+p$ model with $T = 1$ contributions, the $α(d,γ)^6$Li astrophysical $S$-factor is in agreement with the experimental data of the LUNA collaboration, without adjustable parameter. The exact-masses prescription used to avoid the disappearance

Beni Yoshida

Recently we pointed out that the black hole interior operators can be reconstructed by using the Hayden-Preskill recovery protocols. Building on this observation, we propose a resolution of the firewall problem by presenting a state-independent reconstruction of interior operators. Our construction avoids the non-locality problem which plagued the &#34;$A=R_

Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang

While Bayesian neural networks (BNNs) have drawn increasing attention, their posterior inference remains challenging, due to the high-dimensional and over-parameterized nature. To address this issue, several highly flexible and scalable variational inference procedures based on the idea of particle optimization have been proposed. These methods directly opti

Manjun Ma, Peng Xia, Qifeng Zhang, Matti Vuorinen

We investigate the structure and stability of the steady states for a bacterial colony model with density-suppressed motility. We treat the growth rate of bacteria as a bifurcation parameter to explore the local and global structure of the steady states. Relying on asymptotic analysis and the theory of Fredholm solvability, we derive the second-order approxi

Arindam Banerjee, Dipankar Ghosh, S. Selvaraja

Let $ X $ be an $ m \times n $ matrix of distinct indeterminates over a field $ K $, where $ m \le n $. Set the polynomial ring $ K[X] := K[X_{ij} : 1 \le i \le m, 1 \le j \le n] $. Let $ 1 \le k < l \le n $ be such that $ l - k + 1 \ge m $. Consider the submatrix $ Y_{kl} $ of consecutive columns of $ X $ from $ k $th column to $ l $th column. Let $ J_{kl}

Zi Cai, Yizhen huang, W. Vincent Liu

Spontaneous symmetry breaking is responsible for rich quantum phenomena from crystalline structures to superconductivity. This concept was boldly extended to the breaking of time translation, opening an avenue to finding exotic phases of quantum matter with collective time modulation and correlation. Here we report that a thermally open quantum ensemble mani

Inon Peled, Kelvin Lee, Yu Jiang, Justin Dauwels

This study develops an online predictive optimization framework for dynamically operating a transit service in an area of crowd movements. The proposed framework integrates demand prediction and supply optimization to periodically redesign the service routes based on recently observed demand. To predict demand for the service, we use Quantile Regression to e

Tanweer Alam

The smart devices are extremely useful devices that are making our lives easier than before. A smart device is facilitated us to establish a connection with another smart device in a wireless network with a decentralized approach. The mobile ad hoc network (MANET) is a novel methodology that discovers neighborhood devices and establishes connection among the

S. Cobzaş

We prove versions of Ekeland, Takahashi and Caristi principles in sequentially right $K$-complete quasi-pseudometric spaces (meaning asymmetric pseudometric spaces), the equivalence between these principles, as well as their equivalence to the completeness of the underlying quasi-pseudometric space. The key tools are Picard sequences for some special set-val

Jeremy Morton, Freddie D Witherden, Mykel J Kochenderfer

Koopman theory asserts that a nonlinear dynamical system can be mapped to a linear system, where the Koopman operator advances observations of the state forward in time. However, the observable functions that map states to observations are generally unknown. We introduce the Deep Variational Koopman (DVK) model, a method for inferring distributions over obse

Nicolau Saldanha, Boris Shapiro, Michael Shapiro

In this paper we settle a special case of the Grassmann convexity conjecture formulated earlier by B.and M.Shapiro. We present a conjectural formula for the maximal total number of real zeros of the consecutive Wronskians of an arbitrary fundamental solution to a disconjugate linear ordinary differential equation with real time. We show that this formula giv

Jingrun Chen, Cheng Wang, Changjian Xie

The numerical approximation for the Landau-Lifshitz equation, the dynamics of magnetization in a ferromagnetic material, is taken into consideration. This highly nonlinear equation, with a non-convex constraint, has several equivalent forms, and involves solving an auxiliary problem in the infinite domain. All these features have posed interesting challenges

Peiliang Li, Xiaozhi Chen, Shaojie Shen

We propose a 3D object detection method for autonomous driving by fully exploiting the sparse and dense, semantic and geometry information in stereo imagery. Our method, called Stereo R-CNN, extends Faster R-CNN for stereo inputs to simultaneously detect and associate object in left and right images. We add extra branches after stereo Region Proposal Network

Estia J. Eichten, Chris Quigg

The $B_c ^+$ family of $(c\bar{b})$ mesons with beauty and charm is of special interest among heavy quarkonium systems. The $B_c ^+$ mesons are intermediate between $(c\bar{c})$ and $(b\bar{b})$ states both in mass and size, so many features of the $(c\bar{b})$ spectrum can be inferred from what we know of the charmonium and bottomonium systems. The unequal

Yi-Zhi Huang

We introduce and study twist vertex operators for a (lower-bounded generalized) twisted modules for a grading-restricted vertex (super)algebra. We prove duality, weak associativity, a Jacobi identity, a generalized commutator formula, generalized weak commutativity, and convergence and commutativity for products of more than two operators involving twist ver

Alexandru Chirvasitu, Debashish Goswami

We prove the existence of a quantum isometry groups for new classes of metric spaces: (i) geodesic metrics for compact connected Riemannian manifolds (possibly with boundary) and (ii) metric spaces admitting a uniformly distributed probability measure. In the former case it also follows from recent results of the second author that the quantum isometry group

Tyler W. Hughes, R. Joel England, Shanhui Fan

Dielectric laser acceleration (DLA) represents a promising approach to building miniature particle accelerators on a chip. However, similar to conventional RF accelerators, an automatic and reconfigurable control mechanism is needed to scale DLA technology towards high energy gains and practical applications. We present a system providing control of the lase

Jinhan Kim, Gabin An, Robert Feldt, Shin Yoo

Mutation analysis can effectively capture the dependency between source code and test results. This has been exploited by Mutation Based Fault Localisation (MBFL) techniques. However, MBFL techniques suffer from the need to expend the high cost of mutation analysis after the observation of failures, which may present a challenge for its practical adoption. W

O. I. Chashchina, A. Sen, Z. K. Silagadze

Several quantum gravity and string theory thought experiments indicate that the Heisenberg uncertainty relations get modified at the Planck scale so that a minimal length do arises. This modification may imply a modification of the canonical commutation relations and hence quantum mechanics at the Planck scale. The corresponding modification of classical mec

Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli

Reward functions are easy to misspecify; although designers can make corrections after observing mistakes, an agent pursuing a misspecified reward function can irreversibly change the state of its environment. If that change precludes optimization of the correctly specified reward function, then correction is futile. For example, a robotic factory assistant

Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne

We present a novel technique for tailoring Bayesian quadrature (BQ) to model selection. The state-of-the-art for comparing the evidence of multiple models relies on Monte Carlo methods, which converge slowly and are unreliable for computationally expensive models. Previous research has shown that BQ offers sample efficiency superior to Monte Carlo in computi

Fereshteh Jafariakinabad, Sansiri Tarnpradab, Kien A. Hua

Writing style is a combination of consistent decisions at different levels of language production including lexical, syntactic, and structural associated to a specific author (or author groups). While lexical-based models have been widely explored in style-based text classification, relying on content makes the model less scalable when dealing with heterogen

Sindri Magnússon, Hossein Shokri-Ghadikolaei, Na Li

In distributed optimization and machine learning, multiple nodes coordinate to solve large problems. To do this, the nodes need to compress important algorithm information to bits so that it can be communicated over a digital channel. The communication time of these algorithms follows a complex interplay between a) the algorithm&#39;s convergence properties,

Khalil Mrini, Claudiu Musat, Michael Baeriswyl, Martin Jaggi

We propose a method to create document representations that reflect their internal structure. We modify Tree-LSTMs to hierarchically merge basic elements such as words and sentences into blocks of increasing complexity. Our Structure Tree-LSTM implements a hierarchical attention mechanism over individual components and combinations thereof. We thus emphasize

Wenbo Sun

We formulate the generalized Sarnak&#39;s Möbius disjointness conjecture for an arbitrary number field $K$, and prove a quantitative disjointness result between polynomial nilsequences $(Φ(g(n)Γ))_{n\in\mathbb{Z}^{D}}$ and aperiodic multiplicative functions on $\mathcal{O}_{K}$, the ring of integers of $K$. Here $D=[K\colon\mathbb{Q}]$, $X=G/Γ$ is a nilmanif

Caleb I. Cañas, Gudmundur Stefansson, Andrew J. Monson, Johanna K. Teske

We report the detection of a hot Jupiter ($M_{p}=1.75_{-0.17}^{+0.14}\ M_{J}$, $R_{p}=1.38\pm0.04\ R_{J}$) orbiting a middle-aged star ($\log g=4.152^{+0.030}_{-0.043}$) in the Transiting Exoplanet Survey Satellite (TESS) southern continuous viewing zone ($β=-79.59^{\circ}$). We confirm the planetary nature of the candidate TOI-150.01 using radial velocity o

Qunliang Xing, Zhenyu Guan, Mai Xu, Ren Yang

The past few years have witnessed great success in applying deep learning to enhance the quality of compressed image/video. The existing approaches mainly focus on enhancing the quality of a single frame, not considering the similarity between consecutive frames. Since heavy fluctuation exists across compressed video frames as investigated in this paper, fra

Doried Ghader, Antoine Khater

Antiferromagnetic two-dimensional (2D) materials are currently under intensive theoretical and experimental investigations in view of their potential applications in antiferromagnet-based magnonic and spintronic devices. Recent experimental studies revealed the importance of magnetic anisotropy and Dzyaloshinskii-Moriya interactions (DMI) on the ordered grou

Gecia Bravo-Hermsdorff, Lee M. Gunderson

How might one &#34;reduce&#34; a graph? That is, generate a smaller graph that preserves the global structure at the expense of discarding local details? There has been extensive work on both graph sparsification (removing edges) and graph coarsening (merging nodes, often by edge contraction); however, these operations are currently treated separately. Inter

Pedro Savarese, Michael Maire

We introduce a parameter sharing scheme, in which different layers of a convolutional neural network (CNN) are defined by a learned linear combination of parameter tensors from a global bank of templates. Restricting the number of templates yields a flexible hybridization of traditional CNNs and recurrent networks. Compared to traditional CNNs, we demonstrat

Ryoma Sato, Makoto Yamada, Hisashi Kashima

Hard instances, which require a long time for a specific algorithm to solve, help (1) analyze the algorithm for accelerating it and (2) build a good benchmark for evaluating the performance of algorithms. There exist several efforts for automatic generation of hard instances. For example, evolutionary algorithms have been utilized to generate hard instances.

Bas Peters, Felix J. Herrmann

We propose algorithms and software for computing projections onto the intersection of multiple convex and non-convex constraint sets. The software package, called SetIntersectionProjection, is intended for the regularization of inverse problems in physical parameter estimation and image processing. The primary design criterion is working with multiple sets,

Ankit Raj, Yuqi Li, Yoram Bresler

A Generative Adversarial Network (GAN) with generator $G$ trained to model the prior of images has been shown to perform better than sparsity-based regularizers in ill-posed inverse problems. Here, we propose a new method of deploying a GAN-based prior to solve linear inverse problems using projected gradient descent (PGD). Our method learns a network-based

Phoebe Mulcaire, Jungo Kasai, Noah A. Smith

We introduce Rosita, a method to produce multilingual contextual word representations by training a single language model on text from multiple languages. Our method combines the advantages of contextual word representations with those of multilingual representation learning. We produce language models from dissimilar language pairs (English/Arabic and Engli

Yue Yu, Behçet Açıkmeşe

Bregman parallel direction method of multipliers (BPDMM) efficiently solves distributed optimization over a network, which arises in a wide spectrum of collaborative multi-agent learning applications. In this paper, we generalize BPDMM to stochastic BPDMM, where each iteration only solves local optimization on a randomly selected subset of nodes rather than