September 2018 arXiv papers — page 2

S. Ulrych

The Laplace equation in the two-dimensional Euclidean plane is considered in the context of the inverse stereographic projection. The Lie algebra of the conformal group as the symmetry group of the Laplace equation can be represented solely in terms of the solutions and derivatives of the solutions of the Laplace equation. It is then possible to put contents

Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti, Tsang Ing Ren

Dynamic ensemble selection systems work by estimating the level of competence of each classifier from a pool of classifiers. Only the most competent ones are selected to classify a given test sample. This is achieved by defining a criterion to measure the level of competence of a base classifier, such as, its accuracy in local regions of the feature space ar

Olga G. Novozhenova

We give a brief outline of biography, review 3 of his works on the use of confluent hypergeometric function for description asymmetric relaxation spectrum and provide an overview of the Soviet works of the past (20th) that are in tune with this topic.

Fakrul Islam Tushar

Skin lesion segmentation is one of the first steps towards automatic Computer-Aided Diagnosis of skin cancer. Vast variety in the appearance of the skin lesion makes this task very challenging. The contribution of this paper is to apply a power foreground extraction technique called GrabCut for automatic skin lesion segmentation with minimal human interactio

Akihisa Koga, Hiroyuki Tomishige, Joji Nasu

We study ground state properties in the bilayer Kitaev model by means of the dimer expansion. The existence of parity symmetries in the system reduces the computational cost significantly. This allows us to expand the ground state energy and interlayer spin-spin correlation up to 30th order in the interdimer Kitaev coupling. The numerical calculations clarif

Patrick E. Lancaster, Joshua R. Smith, Siddhartha S. Srinivasa

We describe a single fingertip-mounted sensing system for robot manipulation that provides proximity (pre-touch), contact detection (touch), and force sensing (post-touch). The sensor system consists of optical time-of-flight range measurement modules covered in a clear elastomer. Because the elastomer is clear, the sensor can detect and range nearby objects

Maja Krivokuća, Maxim Koroteev, Philip A. Chou

Compression of point clouds has so far been confined to coding the positions of a discrete set of points in space and the attributes of those discrete points. We introduce an alternative approach based on volumetric functions, which are functions defined not just on a finite set of points, but throughout space. As in regression analysis, volumetric functions

Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn

Reinforcement learning and planning methods require an objective or reward function that encodes the desired behavior. Yet, in practice, there is a wide range of scenarios where an objective is difficult to provide programmatically, such as tasks with visual observations involving unknown object positions or deformable objects. In these cases, prior methods

Cristian E. Rusu, Cameron A. Lemon

Data mining through large, multi-band ground-based surveys and the recent availability of source catalogues from the {\it Gaia} space mission has led to a surge in the number of known gravitationally lensed quasars, including some unusual systems. One of these newly discovered systems is GraL~J181730853+272940139. This system was reported in Delchambre et al

Timothy Burton Warrington

Ciliopathies are a class of human diseases marked by dysfunction of the cellular organelle, cilia. While many of the molecular components that make up cilia have been identified and studied, comparatively little is understood about the transcriptional regulation of genes encoding these components. The conserved transcription factor Regulatory Factor X (RFX)/

Elena G. Ferreiro

Quarkonium has long been proposed as one of the golden probes to identify the phase transition from confined hadronic matter to the deconfined quark-gluon plasma in heavy-ion collisions. Since then, we have achieved a better understanding, not only about the propagation of quarkonium in-medium, but also about its production. Recent theoretical developments i

Riddhish Bhalodia, Anupama Goparaju, Tim Sodergren, Alan Morris

Left atrium shape has been shown to be an independent predictor of recurrence after atrial fibrillation (AF) ablation. Shape-based representation is imperative to such an estimation process, where correspondence-based representation offers the most flexibility and ease-of-computation for population-level shape statistics. Nonetheless, population-level shape

Tao Wang, Toma Toncian, Mingsheng Wei, Alexey Arefiev

A solid density target irradiated by a high-intensity laser pulse can become relativistically transparent, which then allows it to sustain an extremely strong laser-driven longitudinal electron current. The current generates a filament with a slowly-varying MT-level azimuthal magnetic field that has been shown to prompt efficient emission of multi-MeV photon

C. D. Pemmaraju

An atomic-orbital basis set framework is presented for carrying out velocity- gauge real-time time-dependent density functional theory (TDDFT) simulations in periodic systems employing range-separated hybrid functionals. Linear optical response obtained from real-time propagation of the time-dependent Kohn-Sham equations including nonlocal exchange is consid

Yujie Xing, Raquel Fernández

Stylistic variation is critical to render the utterances generated by conversational agents natural and engaging. In this paper, we focus on sequence-to-sequence models for open-domain dialogue response generation and propose a new method to evaluate the extent to which such models are able to generate responses that reflect different personality traits.

Daniel McDuff, Roger Cheng, Ashish Kapoor

Machine learned models exhibit bias, often because the datasets used to train them are biased. This presents a serious problem for the deployment of such technology, as the resulting models might perform poorly on populations that are minorities within the training set and ultimately present higher risks to them. We propose to use high-fidelity computer simu

Fabian Steiner, Gerhard Kramer

Protograph-based, off-the-shelf low-density parity-check (LDPC) codes are optimized for higher-order modulation and quantized sum-product decoders. As an example, for the recently proposed LDPC code from the upcoming IEEE 802.3ca standard for passive optical networks (PONs), an optimized mapping of the bit channels originating from bit-metric decoding to the

Michalis K. Titsias, Sotirios Nikoloutsopoulos

We propose a probabilistic framework to directly insert prior knowledge in reinforcement learning (RL) algorithms by defining the behaviour policy as a Bayesian posterior distribution. Such a posterior combines task specific information with prior knowledge, thus allowing to achieve transfer learning across tasks. The resulting method is flexible and it can

Dimbinaina Ralaivaosaona, Matas Šileikis, Stephan Wagner

An additive functional of a rooted tree is a functional that can be calculated recursively as the sum of the values of the functional over the branches, plus a certain toll function. Janson recently proved a central limit theorem for additive functionals of conditioned Galton-Watson trees under the assumption that the toll function is local, i.e. only depend

Rodrigo Pérez-Dattari, Carlos Celemin, Javier Ruiz-del-Solar, Jens Kober

Deep Reinforcement Learning (DRL) has become a powerful strategy to solve complex decision making problems based on Deep Neural Networks (DNNs). However, it is highly data demanding, so unfeasible in physical systems for most applications. In this work, we approach an alternative Interactive Machine Learning (IML) strategy for training DNN policies based on

Y. A. Ageeva, O. A. Evseev, O. I. Melichev, V. A. Rubakov

We consider Genesis in the Horndeski theory as an alternative to or completion of the inflationary scenario. One of the options free of instabilities at all cosmological epochs is the one in which the early Genesis is naively plagued with strong coupling. We address this issue to see whether classical field theory description of the background evolution at t

Panagiotis Papadopoulos, Panagiotis Ilia, Michalis Polychronakis, Evangelos P. Markatos

The proliferation of web applications has essentially transformed modern browsers into small but powerful operating systems. Upon visiting a website, user devices run implicitly trusted script code, the execution of which is confined within the browser to prevent any interference with the user's system. Recent JavaScript APIs, however, provide advanced c

Longsheng Jiang, Yue Wang

Regret theory is a theory that describes human decision-making under risk. The key of obtaining a quantitative model of regret theory is to measure the preference in humans' mind when they choose among a set of options. Unlike physical quantities, measuring psychological preference is not procedure invariant, i.e. the readings alter when the methods chan

Priyanka Mandikal, Navaneet K L, R. Venkatesh Babu

We propose a mechanism to reconstruct part annotated 3D point clouds of objects given just a single input image. We demonstrate that jointly training for both reconstruction and segmentation leads to improved performance in both the tasks, when compared to training for each task individually. The key idea is to propagate information from each task so as to a

Gang Liu

This paper is the continuation of the previous two papers with the same title.

Martin Farach-Colton, Meng Li, Meng-Tsung Tsai

Many classical algorithms are known for computing the convex hull of a set of $n$ point in $\mathbb{R}^2$ using $O(n)$ space. For large point sets, whose size exceeds the size of the working space, these algorithms cannot be directly used. The current best streaming algorithm for computing the convex hull is computationally expensive, because it needs to sol

Boyang Zhao, Jayakanth Ravichandran

Neuro-inspired computing architectures are one of the leading candidates to solve complex, large-scale associative learning problems. The two key building blocks for neuromorphic computing are the synapse and the neuron, which form the distributed computing and memory units. Solid state implementations of these units remain an active area of research. Specif

Vladimir Lifschitz, Patrick Lühne, Torsten Schaub

In a recent paper by Harrison et al., the concept of program completion is extended to a large class of programs in the input language of the ASP grounder gringo. We would like to automate the process of generating and simplifying completion formulas for programs in that language, because examining the output produced by this kind of software may help progra

Victor V. Zubkov

An equation describing the irreversible evolution of the local density of a continuous medium without involving any statistical hypotheses and assumptions is derived. The derivation is based on the smoothing of the microscopic dynamic characteristics of a many-body system, taking into account the retardation of the interactions between them. The resulting eq

Ruslan Ishkuvatov

The notion of generic reducibility was introduced by A.Rybalov in his CiE 2018 paper: a set A is generically reducible to set B if there exists a total computable function f that m-reduces A to B such that the f-preimage of every set that has density 0 has density 0. It may be considered as the ``generic version'' of the notion of m-reducibility. In

Dawsen Hwang, Patrick Jaillet, Vahideh Manshadi

For online resource allocation problems, we propose a new demand arrival model where the sequence of arrivals contains both an adversarial component and a stochastic one. Our model requires no demand forecasting; however, due to the presence of the stochastic component, we can partially predict future demand as the sequence of arrivals unfolds. Under the pro

K. M. Taddei, L. Sanjeewa, J. W. Kolis, A. S. Sefat

The recent discoveries of proximate quantum spin-liquid compounds and their potential application in quantum computing informs the search for new candidate materials for quantum spin-ice and spin-liquid physics. While the majority of such work has centered on members of the pyrochlore family due to their inherently frustrated linked tetrahedral structure, th

Qinglin Zhang, Chris Benton, Daniela Inclezan

This paper presents a practical application of Answer Set Programming to the understanding of narratives about restaurants. While this task was investigated in depth by Erik Mueller, exceptional scenarios remained a serious challenge for his script-based story comprehension system. We present a methodology that remedies this issue by modeling characters in a

Glenn Barnich, Fabrizio Del Monte

Lectures held at the 22nd "Saalburg" Summer School (2016)

Elena Mirela Babalic, Calin Iuliu Lazaroiu

We outline the geometric formulation of cosmological flows for FLRW models with scalar matter as well as certain aspects which arise in their study with methods originating from the geometric theory of dynamical systems. We briefly summarize certain results of numerical analysis which we carried out when the scalar manifold of the model is a hyperbolic surfa

Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato

While deep neural networks are a highly successful model class, their large memory footprint puts considerable strain on energy consumption, communication bandwidth, and storage requirements. Consequently, model size reduction has become an utmost goal in deep learning. A typical approach is to train a set of deterministic weights, while applying certain tec

Andres Romero-Wolf, P. W. Gorham, J. Nam, S. Hoover

These proceedings address a recent publication by the ANITA collaboration of four upward- pointing cosmic-ray-like events observed in the first flight of ANITA. Three of these events were consistent with stratospheric cosmic-ray air showers where the axis of propagation does not inter- sect the surface of the Earth. The fourth event was consistent with a pri

Mark Bugden, Claudio Paganini

We study the $Λ\to 0$ behaviour of Schwarzschild-de Sitter spacetime and show, according to Geroch's notion of spacetime limits, that it converges to the Schwarzschild spacetime. We use an embedding into $AdS_3$ to illustrate and quantify this limiting behaviour. We use these quantitative observations to establish a hierarchy of validity between the Eins

Sergey Georgievich Merzlyakov, Sergey Victorovich Popenov

The study is made of the problem of multiple interpolation on an infinite nodes set by the sums of absolutely convergent series of exponentials whose exponents are from a given set. For entire function conditions on nodes and exponents are obtained that give solubility of the problem. A new approach is demonstrated that enable us, for the case of holomorphic

Gauree Shanker, Ruchi Kaushik Sharma

The classification of Finsler spaces of constant curvature is an interesting and important topic of research in differential geometry. In this paper we obtain necessary and sufficient conditions for generalized Kropina space to be of constant flag curvature.

Saeed Najafi, Colin Cherry, Grzegorz Kondrak

Neural approaches to sequence labeling often use a Conditional Random Field (CRF) to model their output dependencies, while Recurrent Neural Networks (RNN) are used for the same purpose in other tasks. We set out to establish RNNs as an attractive alternative to CRFs for sequence labeling. To do so, we address one of the RNN's most prominent shortcomings

Alakabha Datta

An important prediction of the standard model is the universality of the gauge interactions of the three generation of charged leptons. Violation of this universality would be a clean evidence of new physics (NP) beyond the standard model. In recent times anomalies in measurements of certain $B$ decays indicate violation of lepton universality (LUV). I will

A. S. Ioselevich, N. S. Peshcherenko

Quasi-one-dimensional systems demonstrate Van Hove singularities in the density of states $ν_F$ and the resistivity $ρ$, occurring when the Fermi level $E$ crosses a bottom $E_N$ of some subband of transverse quantization. We demonstrate that the character of smearing of the singularities crucially depends on the concentration of impurities. There is a cross

Xinbo Geng, Swati Gupta, Le Xie

Increasing penetration of highly variable components such as solar generation and electric vehicle charging loads pose significant challenges to keeping three-phase loads balanced in modern distribution systems. Failure to maintain balance across three phases would lead to asset deterioration and increasing delivery losses. Motivated by the real-world needs

Jens O. Andersen, Prabal Adhikari, Patrick Kneschke

We use the Polyakov-loop extended two-flavor quark-meson model as a low-energy effective model for QCD to study 1) the possibility of inhomogeneous chiral condensates and its competition with a homogeneous pion condensate in the $μ$--$μ_I$ plane at $T=0$ and 2) the phase diagram in the $μ_I$--$T$ plane. In the $μ$--$μ_I$ plane, we find that an inhomogeneous

Yuri Imamura

The present paper establishes a discrete version of the result obtained by P. Carr and S. Nadtochiy (2011) for 1-dimensional diffusion processes. Our result is for Markov chains on $\mathbf{Z}^d$.

Rutvika Manohar, Takashi Hikihara

This paper discusses a dispersed generation system of multiple DC/DC converters with DC power sources connected in a ring formulation. Here is presented the analysis of the system based on the stored energy and passivity characteristics of the system. Passivity Based Control (PBC), with its energy-modifying and damping-injection technique, is applied to a ri

Norbert Bogya, Gábor P. Nagy

The aim of this paper is twofold: First we classify all abstract light dual multinets of order $6$ which have a unique line of length at least two. Then we classify the weak projective embeddings of these objects in projective planes over fields of characteristic zero. For the latter we present a computational algebraic method for the study of weak projectiv

Minas Benyamin, Jeff Calder, Ganesh Sundaramoorthi, Anthony Yezzi

We further develop a new framework, called PDE Acceleration, by applying it to calculus of variations problems defined for general functions on $\mathbb{R}^n$, obtaining efficient numerical algorithms to solve the resulting class of optimization problems based on simple discretizations of their corresponding accelerated PDE's. While the resulting family

Georgia Benkart, Persi Diaconis, Martin W. Liebeck, Pham Huu Tiep

We analyze families of Markov chains that arise from decomposing tensor products of irreducible representations. This illuminates the Burnside-Brauer Theorem for building irreducible representations, the McKay Correspondence, and Pitman's 2M-X Theorem. The chains are explicitly diagonalizable, and we use the eigenvalues/eigenvectors to give sharp rates o

Shi-Yang Shen, Ming-Wei Dai, Xue-Tao Zheng, Qi-Yao Sun

We use single homodyne detector to accomplish Continuous-Variable quantum key distribution(CV QKD) in a laboratory and urban environment free-space channel. This is based on Gaussian modulation with coherent-states in the polarization degree of freedom. We achieved a QKD distance at 460m, at the repetition rate of 10 kHz. We give the security of this protoco

Elena Ancona, Roman Ya. Kezerashvili, Gregory L. Matloff

We discuss a possibility to survey many Kuiper Belt Objects (KBO) with a single launch using a few smallscale spacecraft, each equipped with solar sails, which could be unfurled from a single interplanetary bus at the perihelion of that craft's solar orbit. Each small-scale spacecraft would carry a scientific payload and would be directed to intersect on

Kevin Conley, Neha Nayyar, Tuomas P. Rossi, Mikael Kuisma

We study the plasmonic properties of arrays of atomic chains which comprise noble (Cu, Ag, and Au) and transition (Pd, Pt) metal atoms using time-dependent density-functional theory. We show that the response to the electromagnetic radiation is related to both physics, the geometry-dependent confinement of sp-valence electrons, and chemistry, the energy posi

Ido Zachevsky, Yehoshua Y. Zeevi

The Fourier magnitude has been studied extensively, but less effort has been devoted to the Fourier phase, despite its well-established importance in image representation. Global phase was shown to be more important for image representation than the magnitude, whereas local phase, exhibited in Gabor filters, has been used for analysis purposes in detecting i

Laurent Gizon, Damien Fournier, Dan Yang, Aaron C. Birch

Helioseismic holography is an imaging technique used to study heterogeneities and flows in the solar interior from observations of solar oscillations at the surface. Holograms contain noise due to the stochastic nature of solar oscillations. We provide a theoretical framework for modeling signal and noise in Porter-Bojarski helioseismic holography. The wave

Raphael Hiesgen, Dominik Charousset, Thomas C. Schmidt

The message-driven nature of actors lays a foundation for developing scalable and distributed software. While the actor itself has been thoroughly modeled, the message passing layer lacks a common definition. Properties and guarantees of message exchange often shift with implementations and contexts. This adds complexity to the development process, limits po

Martin Friesen, Peng Jin, Barbara Rüdiger

Let X be a multi-type continuous-state branching process with immigration (CBI process) on state space $\mathbb{R}^d$. Denote by $g_t$, $t \geq 0$, the law of $X_{t}$. We provide sufficient conditions under which $g_t$ has, for each $t > 0$, a density with respect to the Lebesgue measure. Such density has, by construction, some anisotropic Besov regularity.

Aditya A. Shastri, Kapil Ahuja, Milind B. Ratnaparkhe, Aditya Shah

We develop a Vector Quantized Spectral Clustering (VQSC) algorithm that is a combination of Spectral Clustering (SC) and Vector Quantization (VQ) sampling for grouping Soybean genomes. The inspiration here is to use SC for its accuracy and VQ to make the algorithm computationally cheap (the complexity of SC is cubic in-terms of the input size). Although the

Roman Khudorozhkov, Dmitry Podvyaznikov

In this work we apply variations of ResNet architecture to the task of atrial fibrillation classification. Variations differ in number of filter after first convolution, ResNet block layout, number of filters in block convolutions and number of ResNet blocks between downsampling operations. We have found a range of model size in which models with quite diffe

Jesse Johnson

In order to choose a neural network architecture that will be effective for a particular modeling problem, one must understand the limitations imposed by each of the potential options. These limitations are typically described in terms of information theoretic bounds, or by comparing the relative complexity needed to approximate example functions between dif

Ágnes Cseh, Attila Juhos

We study the classical, two-sided stable marriage problem under pairwise preferences. In the most general setting, agents are allowed to express their preferences as comparisons of any two of their edges and they also have the right to declare a draw or even withdraw from such a comparison. This freedom is then gradually restricted as we specify six stages o

Gino Biondini, Sitai Li, Dionyssios Mantzavinos

Interactions between solitons and the coherent oscillation structures generated by localized disturbances via modulational instability are studied within the framework of the focusing nonlinear Schrodinger equation. Two main interaction regimes are identified based on the relative value of the velocity of the incident soliton compared to the amplitude of the

Lei Zhou, Bin Wu, Jinming Du, Long Wang

Evolutionary game dynamics in structured populations are strongly affected by updating rules. Previous studies usually focus on imitation-based rules, which rely on payoff information of social peers. Recent behavioral experiments suggest that whether individuals use such social information for strategy updating may be crucial to the outcomes of social inter

Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen

It is challenging for stochastic optimizations to handle large-scale sensitive data safely. Recently, Duchi et al. proposed private sampling strategy to solve privacy leakage in stochastic optimizations. However, this strategy leads to robustness degeneration, since this strategy is equal to the noise injection on each gradient, which adversely affects updat

Lena Maerten, Andre Bojahr, Matthias Reinhardt, Akitoshi Koreeda

We determine the temperature dependent damping rate of longitudinal acoustic phonons in SrTiO3 using frequency domain Brillouin scattering and time domain Brillouin scattering. We investigate samples with (La,Sr)MnO3 and SrRuO3 capping layers, which result in compressive or tensile strain at the layer - substrate interface, respectively. The different strain

C. Y. Guo, C. H. Wan, X. Wang, C. Fang

As an alternative angular momentum carrier, magnons or spin waves can be utilized to encode information and breed magnon-based circuits with ultralow power consumption and non-Boolean data processing capability. In order to construct such a circuit, it is indispensable to design some electronic components with both long magnon decay and coherence length and

Ryoutaro Watanabe

Recent theoretical developments on $R_D$ and $R_{D^*}$ -- discrepancies between experimental data and the Standard Model predictions have been reported (B anomaly) -- are reviewed. New Physics explanations for the B anomaly and other relevant observables to obtain additional bounds on New Physics are also summarized. This is the proceedings for the talk at C

Marcello De Bernardi, MHR Khouzani, Pasquale Malacaria

Pseudo-random number generators (PRNG) are a fundamental element of many security algorithms. We introduce a novel approach to their implementation, by proposing the use of generative adversarial networks (GAN) to train a neural network to behave as a PRNG. Furthermore, we showcase a number of interesting modifications to the standard GAN architecture. The m

Huan Yu, Quansen Jiu

In this paper, we consider the following singular integral \begin{equation*} T_jf(x)=K_j*f(x), K_j(x)=\frac{x_j}{|x|^{n+1-β}}, \end{equation*} where $x\in R^n, 0\le β<n, j=1,2,\cdots, n$. When $β=0$, it corresponds to the Riesz transform. We will make an estimate the $L^q (1<q<\infty)$ norm of $T_jf$, which holds uniformly for $0\leβ<\frac{n(q-1)}{q}$. In pa

Israa Abdulqasim Mohammed Ali, Chorng-Yuan Hwang, Zamri Zainal Abidin, Adele Laurie Plunkett

We investigated the central mass distribution of the luminous infrared galaxy NGC 3256 at a distance of 35 Mpc by using CO(1-0) observations of the Atacama Large Millimeter and sub-millimeter Array (ALMA) and near-IR data of the Two Micron Sky Survey (2MASS). We found that there is a huge amount of invisible dynamical mass ($4.84 \times 10^{10} M_{\odot}$) i

V. Beylin, M. Bezuglov, V. Kuksa, E. Tretyakov

High-energy cosmic ray electrons interaction with Dark Matter particles are considered. In particular, a weakening of energy spectrum of cosmic electrons is predicted resulting from inelastic electron scattering on hyper-pions in the hypercolor extension of the Standard Model. Corresponding cross section and angular distributions of secondary neutrino are ca

Akito Suzuki

Quantum walks have attracted attention as a promising platform realizing topological phenomena and many physicists have introduced various types of indices to characterize topologically protected bound states that are robust against perturbations. In this paper, we introduce an index from a supersymmetric point of view. This allows us to define indices for a

F. Y. Gao, J. Y. Li, Y. Q. Xue

We compile multi-wavelength data from ultraviolet to infrared (IR) bands as well as redshift and source-type information for a large sample of 178,341 sources in the Hawaii-Hubble Deep Field-North field. A total of 145,635 sources among the full sample are classified/treated as galaxies and have redshift information available. We derive physical properties f

Longji Bing, Yong Shi, Yanmei Chen, Sebastián F. Sánchez

Negative feedback from accretion onto super-massive black holes (SMBHs), that is to remove gas and suppress star formation in galaxies, has been widely suggested. However, for Seyfert galaxies which harbor less active, moderately accreting SMBHs in the local universe, the feedback capability of their black hole activity is elusive. We present spatially-resol

Dawood Al Chanti, Alice Caplier

Facial expression is the most natural means for human beings to communicate their emotions. Most facial expression analysis studies consider the case of acted expressions. Spontaneous facial expression recognition is significantly more challenging since each person has a different way to react to a given emotion. We consider the problem of recognizing sponta

Gino Brunner, Manuel Fritsche, Oliver Richter, Roger Wattenhofer

Learning in sparse reward settings remains a challenge in Reinforcement Learning, which is often addressed by using intrinsic rewards. One promising strategy is inspired by human curiosity, requiring the agent to learn to predict the future. In this paper a curiosity-driven agent is extended to use these predictions directly for training. To achieve this, th

Dawood Al Chanti, Alice Caplier

Bag-of-Visual-Words (BoVW) approach has been widely used in the recent years for image classification purposes. However, the limitations regarding optimal feature selection, clustering technique, the lack of spatial organization of the data and the weighting of visual words are crucial. These factors affect the stability of the model and reduce performance.

Lorenzo Ruffoni, Francesca Tripaldi

Extending an example by Colding and Minicozzi, we construct a sequence of properly embedded minimal disks $Σ_i$ in an infinite Euclidean cylinder around the $x_3$-axis with curvature blow-up at a single point. The sequence converges to a non smooth and non proper minimal lamination in the cylinder. Moreover, we show that the disks $Σ_i$ are not properly embe

Joni Salminen, Bernard J. Jansen

The landscape of analytics is changing rapidly. Much of online user analytics, however, is based on collection of various user analytics numbers. Understanding these numbers, and then relating them to higher numerical analysis for the evaluation of key performance indicators (KPIs) can be quite challenging, especially with large volumes of data. There is a p

Christian R. G. Dreher, Nicklas Kulp, Christian Mandery, Mirko Wächter

There have been many proposals for algorithms segmenting human whole-body motion in the literature. However, the wide range of use cases, datasets, and quality measures that were used for the evaluation render the comparison of algorithms challenging. In this paper, we introduce a framework that puts motion segmentation algorithms on a unified testing ground

Takayuki Okuno, Masao Fukushima

In this paper, we propose two algorithms for nonlinear semi-infinite semi-definite programs with infinitely many convex inequality constraints, called SISDP for short. A straightforward approach to the SISDP is to use classical methods for semi-infinite programs such as discretization and exchange methods and solve a sequence of (nonlinear) semi-definite pro

Tingxiang Fan, Xinjing Cheng, Jia Pan, Pinxin Long

We aim to enable a mobile robot to navigate through environments with dense crowds, e.g., shopping malls, canteens, train stations, or airport terminals. In these challenging environments, existing approaches suffer from two common problems: the robot may get frozen and cannot make any progress toward its goal, or it may get lost due to severe occlusions ins

Irene Dutta

The Compact Muon Solenoid (CMS) detector at the CERN Large Hadron Collider (LHC) is undergoing an extensive Phase II upgrade program to prepare for the challenging conditions of the High-Luminosity LHC (HL-LHC). A new timing layer is designed to measure minimum ionizing particles (MIPs) with a time resolution of 30 ps and a hermetic coverage up to a pseudo-r

Kazım Rıfat Özyılmaz, Mehmet Doğan, Arda Yurdakul

Today, Internet of Things (IoT) devices are the powerhouse of data generation with their ever-increasing numbers and widespread penetration. Similarly, artificial intelligence (AI) and machine learning (ML) solutions are getting integrated to all kinds of services, making products significantly more &#34;smarter&#34;. The centerpiece of these technologies is

Lianhua Zhu, Peng Wang, Songze Chen, Zhaoli Guo

This paper presents a Graphics Processing Units (GPUs) acceleration method of an iterative scheme for gas-kinetic model equations. Unlike the previous GPU parallelization of explicit kinetic schemes, this work features a fast converging iterative scheme. The memory reduction techniques in this method enable full three-dimensional (3D) solution of kinetic mod

Xiaoxiao Yin, Daqi Zheng, Zhengdong Lu, Ruifang Liu

We propose Neural Entity Reasoner (NE-Reasoner), a framework to introduce global consistency of recognized entities into Neural Reasoner over Named Entity Recognition (NER) task. Given an input sentence, the NE-Reasoner layer can infer over multiple entities to increase the global consistency of output labels, which then be transfered into entities for the i

Richard Berkovits

Entanglement, which quantifies non-local correlations in quantum mechanics, is the fascinating concept behind much of aspiration towards quantum technologies. Nevertheless, directly measuring the entanglement of a many-particle system is very challenging. Here we show that via supervised machine learning using a convolutional neural network, we can infer the

Shida Wang

Hom gives an example of a knot with vanishing Upsilon invariant but nonzero epsilon invariant. We build more such knots that are linearly independent in the smooth concordance group.

Hui Yang, Jin Yang, Xibiao Ren, Haiyuan Chen

Two-dimensional hexagonal boron nitride (h-BN) single crystals with various shapes have been synthesized by chemical vapor deposition over the past several years. Here we report the formation of three-leaf dart (3LD)-shaped single crystals of h-BN on Cu foil by atmospheric-pressure chemical vapor deposition. The leaves of the 3LD-shaped h-BN are as long as 1

Edward Shuryak, Alexander V Turbiner

Based on Generalized Bloch equation the trans-series expansion for the phase (exponent) of the ground state density for double-well potential is constructed. It is shown that the leading and next-to-leading semiclassical terms are still defined by the flucton trajectory (its classical action) and quadratic fluctuations (the determinant), respectively, while

Shaohan Huang, Yu Wu, Furu Wei, Ming Zhou

In this paper, we introduce a novel natural language generation task, termed as text morphing, which targets at generating the intermediate sentences that are fluency and smooth with the two input sentences. We propose the Morphing Networks consisting of the editing vector generation networks and the sentence editing networks which are trained jointly. Speci

X. H. Liu, W. Liu, Z. M. Dai, S. K. Li

We report a direct observation of magnetic domain evolution near the Verwey transition (TV) in Fe3O4 films. We found the stripe domains in the Fe3O4/Mg2TiO4 film while the irregular domains in the Fe3O4/MgO film and the similar characters of magnetic domains in the vicinity of TV for both samples: the bigger domain size and the higher contrast of the phase s

Zhenchao Wang, Yunzhao Wu, Xiaomeng Zhang, Yu Lu

The mineralogy of mare basalts reflects the chemical composition of the magma source, as well as the physical and chemical environment of the rock&#39;s formation. It is significant for understanding the thermal evolution of the Moon. In this study, the spatial distribution of the mineralogy of the lunar northern nearside basalts was mapped using the Moon Mi

Kfir Sulimany, Ohad Lib, Gilad Masri, Avi Klein

We study experimentally and theoretically the interactions among ultrashort optical pulses in the soliton rain multiple-pulse dynamics of a fiber laser. The laser is mode-locked by a graphene saturable absorber fabricated using the mechanical transfer technique. Dissipative optical solitons aggregate into pulse bunches that exhibit complex behavior, which in

Hajime Kawahara, Takami Kuroda, Tomoya Takiwaki, Kazuhiro Hayama

Recent core-collapse supernova (CCSN) simulations have predicted several distinct features in gravitational-wave (GW) spectrograms, including a ramp-up signature due to the g-mode oscillation of the proto-neutron star (PNS) and an excess in the low-frequency domain (100-300 Hz) potentially induced by the standing accretion shock instability (SASI). These pre

Albert Gatt, Nicolás Marín, Gustavo Rivas-Gervilla, Daniel Sánchez

In this paper we study empirically the validity of measures of referential success for referring expressions involving gradual properties. More specifically, we study the ability of several measures of referential success to predict the success of a user in choosing the right object, given a referring expression. Experimental results indicate that certain fu

Vasco Lopes, Luís A. Alexandre

Blockchain technology is growing everyday at a fast-passed rhythm and it&#39;s possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there isn&#39;t yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many different methods and platforms that

Shuntaro Yamagishi

Let $F \in \mathbb{R}[x_1, \ldots, x_n]$ be a homogeneous form of degree $d > 1$ satisfying $(n - \dim V_{F}^*) > 4$, where $V_F^*$ is the singular locus of $V(F) = \{ \mathbf{z} \in {\mathbb{C}}^n: F(\mathbf{z}) = 0 \}$. Suppose there exists $\mathbf{x}_0 \in (0,1)^n \cap (V(F) \backslash V_F^*)$. Let $\mathbf{t} = (t_1, \ldots, t_n) \in \mathbb{R}^n$. Then

Amirhossein Dadashzadeh, Alireza Tavakoli Targhi

Accurate and reliable image segmentation is an essential part of biomedical image analysis. In this paper, we consider the problem of biomedical image segmentation using deep convolutional neural networks. We propose a new end-to-end network architecture that effectively integrates local and global contextual patterns of histologic primitives to obtain a mor

Wahyudi, Masayu Leylia Khodra, Ary Setijadi Prihatmanto, Carmadi Machbub

We propose the use of Graph-Pattern Association Rules (GPARs) on the Yago knowledge base. Extending association rules for itemsets, GPARS can help to discover regularities between entities in knowledge bases. A rule-generated graph pattern (RGGP) algorithm was used for extracting rules from the Yago knowledge base and a graph-pattern association rules algori