January 2019 arXiv papers — page 38

Sara Mandelli, Vincenzo Lipari, Paolo Bestagini, Stefano Tubaro

Seismic data processing algorithms greatly benefit from regularly sampled and reliable data. Therefore, interpolation and denoising play a fundamental role as one of the starting steps of most seismic processing workflows. We exploit convolutional neural networks for the joint tasks of interpolation and random noise attenuation of 2D common shot gathers. Ins

Alexander Lindenberger, Paul F. X. Müller, Michael Schmuckenschläger

In this paper we determine the value of the best constants in the 2-uniform PL-convexity estimates of $\mathbb C$. This solves a problem posed by W. J. Davis, D. J. H. Garling and N. Tomczak-Jaegermann.

Hanwen Huang, Qinglong Yang

Margin-based classifiers have been popular in both machine learning and statistics for classification problems. Since a large number of classifiers are available, one natural question is which type of classifiers should be used given a particular classification task. We answer this question by investigating the asymptotic performance of a family of large-mar

Xin Wu, Danfeng Hong, Jiaojiao Tian, Jocelyn Chanussot

With the rapid development of spaceborne imaging techniques, object detection in optical remote sensing imagery has drawn much attention in recent decades. While many advanced works have been developed with powerful learning algorithms, the incomplete feature representation still cannot meet the demand for effectively and efficiently handling image deformati

Chao Gan, Jing Yang, Ruida Zhou, Cong Shen

In this paper, we investigate the impact of diverse user preference on learning under the stochastic multi-armed bandit (MAB) framework. We aim to show that when the user preferences are sufficiently diverse and each arm can be optimal for certain users, the O(log T) regret incurred by exploring the sub-optimal arms under the standard stochastic MAB setting

Lucas Giroto de Oliveira, Mateus de L. Filomeno, Luiz Fernando Colla, H. Vincent Poor

This work discusses the suitability of typical power line communication (PLC) pulses for fault sensing in power lines via pulse-compression time-domain reflectometry (TDR). For this purpose, we first carefully outline a TDR system operating over a power distribution network, discussing its limitations and ultimately resorting to the pulse compression procedu

Vittorio Lippi, Giacomo Ceccarelli

This paper describes some applications of an incremental implementation of the principal component analysis (PCA). The algorithm updates the transformation coefficients matrix on-line for each new sample, without the need to keep all the samples in memory. The algorithm is formally equivalent to the usual batch version, in the sense that given a sample set t

Silvana Bazzoni, Giovanna Le Gros

Given a $1$-tilting cotorsion pair over a commutative ring, we characterise the rings over which the $1$-tilting class is an enveloping class. To do so, we consider the faithful finitely generated Gabriel topology $\mathcal{G}$ associated to the $1$-tilting class $\mathcal{T}$ over a commutative ring as illustrated by Hrbek. We prove that a $1$-tilting class

Dimitra Liotsiou, Bence Kollanyi, Philip N. Howard

In recent years, the phenomenon of online misinformation and junk news circulating on social media has come to constitute an important and widespread problem affecting public life online across the globe, particularly around important political events such as elections. At the same time, there have been calls for more transparency around misinformation on so

Tunahan Demirci, Maximilian Kruss, Jens Teiser, Tabea Bogdan

In parabolic flight experiments we studied the wind induced erosion of granular beds composed of spherical glass beads at low gravity and low ambient pressure. Varying g-levels were set by centrifugal forces. Expanding existing parameter sets to a pressure range between $p=300-1200\,$Pa and to g-levels of $g=1.1-2.2\,\rm m\,s^{-2}$ erosion thresholds are sti

Semyon Abramyan, Taras Panov

We study the question of realisability of iterated higher Whitehead products with a given form of nested brackets by simplicial complexes, using the notion of the moment-angle complex $Z_K$. Namely, we say that a simplicial complex $K$ realises an iterated higher Whitehead product $w$ if $w$ is a nontrivial element of $\pi_*(Z_K)$. The combinatorial approach

Jan Kristof Behrens, Ralph Lange, Masoumeh Mansouri

Modern lightweight dual-arm robots bring the physical capabilities to quickly take over tasks at typical industrial workplaces designed for workers. In times of mass-customization, low setup times including the instructing/specifying of new tasks are crucial to stay competitive. We propose a constraint programming approach to simultaneous task allocation and

Yaping Sun, Zhiyong Chen, Meixia Tao, Hui Liu

In this paper, we present a novel mobile edge computing (MEC) model where the MEC server has the input and output data of all computation tasks and communicates with multiple caching-and-computing-enabled mobile devices via a shared wireless link. Each task request can be served from local output caching, local computing with input caching, local computing o

Hong-Yue Zou, Wen-Feng Zhou, Xi Chen, Yun Bao

The logarithmic law of mean temperature profile has been observed in different regions in Rayleigh-B\'enard turbulence. However, how thermal plumes correlate to the log law of temperature and how the velocity profile changes with pressure gradient are not fully understood. Here, we performed three-dimensional simulations of Rayleigh-B\'enard turbulence in a

Zhi-zhong Xing, Di Zhang

In the canonical seesaw mechanism we require the relevant neutrino mass terms to be invariant under the $S^{}_3$ charge-conjugation transformations of left- and right-handed neutrino fields. Then both the Dirac mass matrix $M^{}_{\rm D}$ and the right-handed neutrino mass matrix $M^{}_{\rm R}$ are well constrained, so is the effective light Majorana neutrino

Philipp Grohs, Sarah Koppensteiner, Martin Rathmair

The problem of phase retrieval, i.e., the problem of recovering a function from the magnitudes of its Fourier transform, naturally arises in various fields of physics, such as astronomy, radar, speech recognition, quantum mechanics and, perhaps most prominently, diffraction imaging. The mathematical study of phase retrieval problems possesses a long history

Oscar J. Romero, Ankit Dangi, Sushma A. Akoju

Current approaches for service composition (assemblies of atomic services) require developers to use: (a) domain-specific semantics to formalize services that restrict the vocabulary for their descriptions, and (b) translation mechanisms for service retrieval to convert unstructured user requests to strongly-typed semantic representations. In our work, we ar

Alessandro Muscoloni, Carlo Vittorio Cannistraci

Network navigability is a key feature of complex networked systems. For a network embedded in a geometrical space, maximization of greedy routing (GR) measures based on the node geometrical coordinates can ensure efficient greedy navigability. In PNAS, Seguin et al. (PNAS 2018, vol. 115, no. 24) define a measure for quantifying the efficiency of brain networ

Yunduan Cui, Shigeki Osaki, Takamitsu Matsubara

In this research we focus on developing a reinforcement learning system for a challenging task: autonomous control of a real-sized boat, with difficulties arising from large uncertainties in the challenging ocean environment and the extremely high cost of exploring and sampling with a real boat. To this end, we explore a novel Gaussian processes (GP) based r

Kazuya Shinjo, Shigetoshi Sota, Seiji Yunoki, Takami Tohyama

Photoinduced nonequilibrium states can provide new insight into dynamical properties of strongly correlated electron systems. One of the typical and extensively studied systems is the half-filled one-dimensional extended Hubbard model (1DEHM). Here, we propose that the supervised machine learning (ML) can provide useful information for characterizing photoex

L. C. Gallo, A. G. Gonzalez, S. G. H. Waddell, H. J. S. Ehler

A triggered 140 ks XMM-Newton observation of the narrow-line Seyfert 1 (NLS1) Mrk 335 in December 2015 caught the active galaxy at its lowest X-ray flux since 2007. The NLS1 is relatively quiescent for the first ~120 ks of the observation before it flares in brightness by a factor of about five in the last 20 ks. Although only part of the flare is captured b

Weijun Zhu, Mingliang Xu, Jianwei Wang

In this paper, we study how to predict the results of LTL model checking using some machine learning algorithms. Some Kripke structures and LTL formulas and their model checking results are made up data set. The approaches based on the Random Forest (RF), K-Nearest Neighbors (KNN), Decision tree (DT), and Logistic Regression (LR) are used to training and pre

I. V. Tokatly, B. Bujnowski, F. S. Bergeret

We demonstrate that the interplay of Zeeman and spin-orbit coupling fields in a 1D wire leads to an equilibrium spin current that manifests itself in a spin accumulation at the wire ends with a polarization perpendicular to both fields. This is a universal property that occurs in the normal and superconducting state independently of the degree of disorder. W

Haiyun Peng, Yukun Ma, Soujanya Poria, Yang Li

The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Particularly, we propose two effective features to encode phonetic information. Next, we d

Yujendra Mitikiri, Kamran Mohseni

This paper presents solutions to the following two common quaternion attitude estimation problems: (i) estimation of attitude using measurement of two reference vectors, and (ii) estimation of attitude using rate measurement and measurement of a single reference vector. Both these problems yield to a direct geometric analysis and solution. The former problem

Wencong Jiang, Lina Chen, Kaiyuan Zhou, Liyuan Li

Spintronic nanodevices have ultrafast nonlinear dynamic and recurrence behaviors on a nanosecond scale that promises to enable spintronic reservoir computing (RC) system. Here two physical RC systems based on a single magnetic skyrmion memristor (MSM) and 24 spin-torque nano-oscillators (STNOs) were proposed and modeled to process image classification task a

Christian Otto, Sebastian Holzki, Ralph Ewerth

Successful multimodal search and retrieval requires the automatic understanding of semantic cross-modal relations, which, however, is still an open research problem. Previous work has suggested the metrics cross-modal mutual information and semantic correlation to model and predict cross-modal semantic relations of image and text. In this paper, we present a

Kyriaki Kalimeri, Mariano G. Beiro, Andrea Bonanomi, Alessandro Rosina

Social media in scientific research offer a unique digital observatory of human behaviours and hence great opportunities to conduct research at large scale answering complex sociodemographic questions. We focus on the identification and assessment of biases in social media administered surveys. This study aims to shed light on population, self-selection and

Simon Baker

In this paper we develop a new approach for studying overlapping iterated function systems. This approach is inspired by a famous result due to Khintchine from Diophantine approximation. This result shows that for a family of limsup sets, their Lebesgue measure is determined by the convergence or divergence of naturally occurring volume sums. For many parame

Jan Hamhalter, Ondřej F. K. Kalenda, Antonio M. Peralta, Hermann Pfitzner

We prove, among other results, that three standard measures of weak non-compactness coincide in preduals of JBW$^*$-triples. This result is new even for preduals of von Neumann algebras. We further provide a characterization of JBW$^*$-triples with strongly WCG predual and describe the order of seminorms defining the strong$^*$ topology. As a byproduct we im

Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier

We report on an empirical study of the main strategies for quantile regression in the context of stochastic computer experiments. To ensure adequate diversity, six metamodels are presented, divided into three categories based on order statistics, functional approaches, and those of Bayesian inspiration. The metamodels are tested on several problems character

Meena Pargaei, B. V. Rathish Kumar

In this study, we consider a system of degenerate reaction-diffusion equations, which govern the electric activity in the heart with a diffusion term modeling the potential in the surrounding tissue and the nonlinear ionic model proposed by Morris $\&$ Lecar. The global existence of a solution is established based on regularization argument using Fedo-Galerk

Patrick Spettel, Hans-Georg Beyer

Theoretical analyses of evolution strategies are indispensable for gaining a deep understanding of their inner workings. For constrained problems, rather simple problems are of interest in the current research. This work presents a theoretical analysis of a multi-recombinative evolution strategy with cumulative step size adaptation applied to a conically con

Yu. D. Fomin, V. V. Brazhkin

Investigation of melting line of graphite and liquid carbon has long history. However, up to now there are still numerous controversies in the field, for instance, the melting temperatures obtained in different experiments are in very bad agrement. In the present paper we compare several models of carbon widely used in computational studies and the results o

Sushil Bhunia

Let G be a group. Two elements x and y in G are said to be in the same z-class if their centralizers in G are conjugate within G. In this paper, we prove that the number of z-classes in the group of upper triangular matrices is infinite provided that the field is infinite and size of the matrices is at least 6, and finite otherwise.

Ryoma Sato, Makoto Yamada, Hisashi Kashima

The recent advancements in graph neural networks (GNNs) have led to state-of-the-art performances in various applications, including chemo-informatics, question-answering systems, and recommender systems. However, scaling up these methods to huge graphs, such as social networks and Web graphs, remains a challenge. In particular, the existing methods for acce

Mohd Zeeshan Ansari, Lubna Khan

A word having multiple senses in a text introduces the lexical semantic task to find out which particular sense is appropriate for the given context. One such task is Word sense disambiguation which refers to the identification of the most appropriate meaning of the polysemous word in a given context using computational algorithms. The language processing re

Radhakrishnan Balu, Ajinkya Borle

We report a scalable hybrid quantum-classical machine learning framework to build Bayesian networks (BN) that captures the conditional dependence and causal relationships of random variables. The generation of a BN consists of finding a directed acyclic graph (DAG) and the associated joint probability distribution of the nodes consistent with a given dataset

Giuliano Basso

The linear projection constant $\Pi(E)$ of a finite-dimensional real Banach space $E$ is the smallest number $C\in [0,+\infty)$ such that $E$ is a $C$-absolute retract in the category of real Banach spaces with bounded linear maps. We denote by $\Pi_n$ the maximal linear projection constant amongst $n$-dimensional Banach spaces. In this article, we prove tha

Lijun Sun, Chao Lyu, Yuhui Shi

The pursuit domain, or predator-prey problem is a standard testbed for the study of coordination techniques. In spite that its problem setup is apparently simple, it is challenging for the research of the emerged swarm intelligence. This paper presents a particle swarm optimization (PSO) based cooperative coevolutionary algorithm for the (predator) robots, c

Boris Blok, Konrad Tywoniuk

We calculate higher-order corrections to the quenching factor of heavy-quark jets due to hard, in-medium splittings in the framework of the BDMPS-Z formalism. These corrections turn out to be sensitive to a single mass-scale $m_\ast = (\hat q L)^{1/2}$, where $\hat q$ is the medium transport coefficient and $L$ the path length, and allow to draw a distinctio

H. D. Cornean, V. Moldoveanu, C. -A. Pillet

We consider a small interacting sample coupled to several non-interacting leads. Initially, the system is at thermal equilibrium. At some instant $t_0$ the system is set into the so called partition-free transport scenario by turning on a bias on the leads. Using the theory of Volterra operators we rigorously formulate a Dyson equation for the retarded Green

Erhard Aichinger

Recently, M. Kompatscher proved that for each finite supernilpotent algebra $\mathbf{A}$ in a congruence modular variety, there is a polynomial time algorithm to solve polynomial equations over this algebra. Let $\mu$ be the maximal arity of the fundamental operations of $\mathbf{A}$, and let \[ d := |A|^{\log_2 (\mu) + \log_2 (|A|) + 1}.\] Applying a method

Shirli Di-Castro Shashua, Shie Mannor

Policy evaluation is a key process in reinforcement learning. It assesses a given policy using estimation of the corresponding value function. When using a parameterized function to approximate the value, it is common to optimize the set of parameters by minimizing the sum of squared Bellman Temporal Differences errors. However, this approach ignores certain

Kai Olav Ellefsen, Charles Patrick Martin, Jim Torresen

Gaining a better understanding of how and what machine learning systems learn is important to increase confidence in their decisions and catalyze further research. In this paper, we analyze the predictions made by a specific type of recurrent neural network, mixture density RNNs (MD-RNNs). These networks learn to model predictions as a combination of multipl

Bo Liu, Wenhao Chi, Xinran Li, Peng Li

Lung cancer is the commonest cause of cancer deaths worldwide, and its mortality can be reduced significantly by performing early diagnosis and screening. Since the 1960s, driven by the pressing needs to accurately and effectively interpret the massive volume of chest images generated daily, computer-assisted diagnosis of pulmonary nodule has opened up new o

Lefteris Kirousis, John Livieratos

The acyclic chromatic index of a graph $G$ is the least number of colors needed to properly color its edges so that none of its cycles is bichromatic. In this work, we show that $2\Delta-1$ colors are sufficient to produce such a coloring, where $\Delta$ is the maximum degree of the graph. In contrast with most extant randomized algorithmic approaches to the

Marat Gafurov, Andrey Galukhin, Yuri Osin, Fadis Murzakhanov

Porous silica materials offer wide range of possibilities for enhancement of the productivity of oil reservoirs. However the mechanism of adsorption of polar components of crude oil on silica surface is poorly understood that hinders technological improvement of supports and oil extraction. We have synthesized opal films with the silica microspheres size of

Biao Ma, Julia Sauter

We revisit faithfully balanced modules. These are faithful modules having the double centralizer property. For finite-dimensional algebras our main tool is the category ${\rm cogen}^1(M)$ of modules with a copresentation by summands of finite sums of $M$ on which ${\rm Hom}(-,M)$ is exact. For a faithfully balanced module $M$ the functor ${\rm Hom}(-,M)$ is

Cyril Simon Wedlund, E. Behar, E. Kallio, H. Nilsson

Solar wind charge-changing reactions are of paramount importance to the physico-chemistry of the atmosphere of a comet because they mass-load the solar wind through an effective conversion of fast, light solar wind ions into slow, heavy cometary ions. The ESA/Rosetta mission to comet 67P/Churyumov-Gerasimenko (67P) provided a unique opportunity to study char

V. P. Kostylyov, A. V. Sachenko, V. M. Vlasiuk, I. O. Sokolovskyi

Presented in this work are the results of our study of the photoelectric properties of perovskite $CH_3NH_3PbI_{2.98}Cl_{0.02}$ films deposited on a glass substrate using the spin-coating method. The unit cell parameters of the perovskite are determined using x-ray diffractometry. It is shown that the film morphology represents a net of non-oriented needle-l

Manolis C. Tsakiris, Liangzu Peng

A recent line of research termed unlabeled sensing and shuffled linear regression has been exploring under great generality the recovery of signals from subsampled and permuted measurements; a challenging problem in diverse fields of data science and machine learning. In this paper we introduce an abstraction of this problem which we call homomorphic sensing

Ke-Wei Huang, Mengke Qiao, Xuanqi Liu, Siyuan Liu

This paper proposes a new deep-learning method to construct test statistics by computer vision and metrics learning. The application highlighted in this paper is applying computer vision on Q-Q plot to construct a new test statistic for normality test. To the best of our knowledge, there is no similar application documented in the literature. Traditionally,

Daniel Weller, James P. Shaffer, Tilman Pfau, Robert Löw

We investigate the phenomenon of bistability in a thermal gas of cesium atoms excited to Rydberg states. We present both measurements and a numerical model of the phenomena based on collisions. By directly measuring the plasma frequency, we show that the origin of the bistable behavior lies in the creation of a plasma formed by ionized Rydberg atoms. Recombi

Wei Li, Chengwei Pan, Rong Zhang, Jiaping Ren

Simulation systems have become an essential component in the development and validation of autonomous driving technologies. The prevailing state-of-the-art approach for simulation is to use game engines or high-fidelity computer graphics (CG) models to create driving scenarios. However, creating CG models and vehicle movements (e.g., the assets for simulatio

Matthieu Alfaro, Mario Veruete

We analyze a replicator-mutator model arising in the context of directed evolution [23], where the selection term is modulated over time by the mean-fitness. We combine a Cumulant Generating Function approach [13] and a spatio-temporal rescaling related to the Avron-Herbst formula [1] to give of a complete picture of the Cauchy problem. Besides its well-pose

Seungsang Oh

The exact enumeration of pure dimer coverings on the square lattice was obtained by Kasteleyn, Temperley and Fisher in 1961. In this paper, we consider the monomer-dimer covering problem (allowing multiple monomers) which is an outstanding unsolved problem in lattice statistics. We have developed the state matrix recursion method that allows us to compute th

Tianyu Du, Shouling Ji, Jinfeng Li, Qinchen Gu

Despite their immense popularity, deep learning-based acoustic systems are inherently vulnerable to adversarial attacks, wherein maliciously crafted audios trigger target systems to misbehave. In this paper, we present SirenAttack, a new class of attacks to generate adversarial audios. Compared with existing attacks, SirenAttack highlights with a set of sign

Piotr Bartman, Krzysztof Bartosz, Michał Jureczka, Paweł Szafraniec

In this work, we analyze a non-clamped dynamic viscoelastic contact problem involving thermal effect. The friction law is described by a non-monotone relation between the tangential stress and the tangential velocity. This leads to a system of second-order inclusion for displacement and a parabolic equation for temperature. We provide a fully discrete approx

Kari Astala, Martí Prats, Eero Saksman

We study quasiconformal mappings in planar domains $\Omega$ and their regularity properties described in terms of Sobolev, Bessel potential or Triebel-Lizorkin scales. This leads to optimal conditions, in terms of the geometry of the boundary $\partial \Omega$ and of the smoothness of the Beltrami coefficient, that guarantee the global regularity of the mapp

Wadim Zudilin

We discuss $q$-analogues of the classical congruence $\binom{ap}{bp}\equiv\binom{a}{b}\pmod{p^3}$, valid for primes $p>3$, as well as its generalisations. In particular, we prove related congruences for ($q$-analogues of) integral factorial ratios.

Ather Gattami, Qinbo Bai, Vaneet Agarwal

In this paper, we consider the problem of optimization and learning for constrained and multi-objective Markov decision processes, for both discounted rewards and expected average rewards. We formulate the problems as zero-sum games where one player (the agent) solves a Markov decision problem and its opponent solves a bandit optimization problem, which we h

Kathleen D. Barnetson, Andrea C. Burgess, Jessica Enright, Jared Howell

Suppose we have a network that is represented by a graph $G$. Potentially a fire (or other type of contagion) might erupt at some vertex of $G$. We are able to respond to this outbreak by establishing a firebreak at $k$ other vertices of $G$, so that the fire cannot pass through these fortified vertices. The question that now arises is which $k$ vertices wil

Christoph Reisinger, Yufei Zhang

This paper proposes penalty schemes for a class of weakly coupled systems of Hamilton-Jacobi-Bellman quasi-variational inequalities (HJBQVIs) arising from stochastic hybrid control problems of regime-switching models with both continuous and impulse controls. We show that the solutions of the penalized equations converge monotonically to those of the HJBQVIs

V. N. Gorbachev, L. A. Denisov, E. M. Kaynarova, I. K. Metelev

Digital array orthogonal transformations that can be presented as a decomposition over basis items or basis images are considered. The orthogonal transform provides digital data scattering, a process of pixel energy redistributing, that is illustrated with the help of basis images. Data scattering plays important role for applications as image coding and wat

Ather Gattami

In this paper, we consider reinforcement learning of Markov Decision Processes (MDP) with peak constraints, where an agent chooses a policy to optimize an objective and at the same time satisfy additional constraints. The agent has to take actions based on the observed states, reward outputs, and constraint-outputs, without any knowledge about the dynamics,

Byeongkeun Kang, Subarna Tripathi, Truong Q. Nguyen

In this paper, we present a generative adversarial network framework that generates compressed images instead of synthesizing raw RGB images and compressing them separately. In the real world, most images and videos are stored and transferred in a compressed format to save storage capacity and data transfer bandwidth. However, since typical generative advers

Krzysztof Bartosz, Leszek Gasiński, Zhenhai Liu, Paweł Szafraniec

We study an abstract second order inclusion involving two nonlinear single-valued operators and a nonlinear multivalued term. Our goal is to establish the existence of solutions to the problem by applying numerical scheme based on time discretization. We show that the sequence of approximate solution converges weakly to a solution of the exact problem. We ap

Pengcheng Ai, Dong Wang, Guangming Huang, Ni Fang

Timing systems based on Analog-to-Digital Converters are widely used in the design of previous high energy physics detectors. In this paper, we propose a new method based on deep learning to extract the time information from a finite set of ADC samples. Firstly, a quantitative analysis of the traditional curve fitting method regarding three kinds of variatio

Alekha C. Nayak

In Very Special Relativity (VSR), the neutrino mass term is coupled with the VSR preferred axis, and hence Lorentz violating in nature. Beyond standard model physics predicts neutrino magnetic moment which is linearly proportional to the mass eigenstates of the neutrinos. We report an additive kinematic phase in the neutrino flavor oscillation due to the neu

Fuminori Tatsuoka, Tomohiro Sogabe, Yuto Miyatake, Shao-Liang Zhang

We consider the computation of the matrix logarithm by using numerical quadrature. The efficiency of numerical quadrature depends on the integrand and the choice of quadrature formula. The Gauss--Legendre quadrature has been conventionally employed; however, the convergence could be slow for ill-conditioned matrices. This effect may stem from the rapid chang

Michael Zopf, Robert Keil, Yan Chen, Jingzhong Yang

Transferring entangled states between photon pairs is essential for quantum communication technologies. Semiconductor quantum dots are the most promising candidate for generating polarization-entangled photons deterministically. Recent improvements in photonic quality and brightness now make them suited for complex quantum optical purposes in practical devic

Luca Amendola, Yves Dirian, Henrik Nersisyan, Sohyun Park

We study the cosmology of a specific class of nonlocal model of modified gravity, the so-called Deser-Woodard (DW) model, modifying the Einstein-Hilbert action by a term $\sim R f(\Box^{-1}R)$, where $f$ is a free function. Choosing $f$ so as to reproduce the $\Lambda{\rm CDM}$ cosmological background expansion history within the nonlocal model, we implement

Jonas Arista, Neil O'Connell

It is well known that there are close connections between non-intersecting processes in one dimension and random matrices, based on the reflection principle. There is a generalisation of the reflection principle for more general (e.g. planar) processes, due to S. Fomin, in which the non-intersection condition is replaced by a condition involving loop-erased

Eli Bagno, Riccardo Biagioli, David Garber

Using Reiner's definition of Stirling numbers of the second kind in types $B$ and $D$, we generalize two well-known identities concerning the classical Stirling numbers of the second kind. The first identity relates them with Eulerian numbers and the second identity interprets them as entries in a transition matrix between the elements of two standard bases

Sergey I. Nikolenko, Elena Tutubalina, Valentin Malykh, Ilya Shenbin

We propose a novel end-to-end Aspect-based Rating Prediction model (AspeRa) that estimates user rating based on review texts for the items and at the same time discovers coherent aspects of reviews that can be used to explain predictions or profile users. The AspeRa model uses max-margin losses for joint item and user embedding learning and a dual-headed arc

Byeongkeun Kang, Truong Q. Nguyen

In this work, we present a random forest framework that learns the weights, shapes, and sparsities of feature representations for real-time semantic segmentation. Typical filters (kernels) have predetermined shapes and sparsities and learn only weights. A few feature extraction methods fix weights and learn only shapes and sparsities. These predetermined con

Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li

Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems. In this paper, we consider knowledge graphs as the source of side information. We propose MKR, a Multi-task fe

Shaohui Lin, Rongrong Ji, Yuchao Li, Cheng Deng

The success of convolutional neural networks (CNNs) in computer vision applications has been accompanied by a significant increase of computation and memory costs, which prohibits its usage on resource-limited environments such as mobile or embedded devices. To this end, the research of CNN compression has recently become emerging. In this paper, we propose

F. F. Karpeshin, M. B. Trzhaskovskaya

Some aspects of description of the Bohr-Weisskopf effect in hyperfine splitting of the H- and Li-like ions of 209Bi are considered by application of the surface and volume models of the nuclear currents. Extension of these models, used in internal conversion theory, to description of the HFS allows one to successfully describe the effect, without resorting t

Albert Atserias, Anuj Dawar, Joanna Ochremiak

We consider families of symmetric linear programs (LPs) that decide a property of graphs (or other relational structures) in the sense that, for each size of graph, there is an LP defining a polyhedral lift that separates the integer points corresponding to graphs with the property from those corresponding to graphs without the property. We show that this is

Alberto Sonnino, Michał Król, Argyrios G. Tasiopoulos, Ioannis Psaras

Recent developments in blockchains and edge computing allows to deploy decentralized shared economy with utility tokens, where altcoins secure and reward useful work. However, the majority of the systems being developed, does not provide mechanisms to pair workers and clients, or rely on manual and insecure resolution. AStERISK bridges this gap allowing to p

Hari Hara Suthan Chittoor, Bhavana M, Prasad Krishnan

Coded Caching is a promising solution to reduce the peak traffic in broadcast networks by prefetching the popular content close to end users and using coded transmissions. One of the chief issues of most coded caching schemes in literature is the issue of large $\textit{subpacketization}$, i.e., they require each file to be divided into a large number of sub

Yuhui Chen, Wei Luo, Xiaoping Zhai

In this paper, we mainly investigate the Cauchy problem for the Phan-Thein-Tanner (PTT) model. The PPT model can be viewed as a Navier-Stokes equations couple with a nonlinear transport system. This model is derived from network theory for the polymeric fluid. We study about the global well posedness of the PTT model in critical Besov spaces. When the initia

Ilianna Kollia, Andreas-Georgios Stafylopatis, Stefanos Kollias

This paper presents a new method for medical diagnosis of neurodegenerative diseases, such as Parkinson's, by extracting and using latent information from trained Deep convolutional, or convolutional-recurrent Neural Networks (DNNs). In particular, our approach adopts a combination of transfer learning, k-means clustering and k-Nearest Neighbour classificati

Yochai Blau, Tomer Michaeli

Lossy compression algorithms are typically designed and analyzed through the lens of Shannon's rate-distortion theory, where the goal is to achieve the lowest possible distortion (e.g., low MSE or high SSIM) at any given bit rate. However, in recent years, it has become increasingly accepted that "low distortion" is not a synonym for "high perceptual quality

Pierre Hyvernat

This paper introduces an ML / Haskell like programming language with nested inductive and coinductive algebraic datatypes called \chariot. Functions are defined by arbitrary recursive definitions and can thus lead to non-termination and other ``bad'' behavior. \chariot comes with a totality checker that tags possibly ill-behaved definitions. Such a totality

Federico Andreatta, Habib Rostami, Antonija Grubišić Čabo, Marco Bianchi

Using time- and angle-resolved photoemission spectroscopy, we study the response of metallic single layer TaS$_2$ in the 1H structural modification to the generation of excited carriers by a femtosecond laser pulse. A complex interplay of band structure modifications and electronic temperature increase is observed and analyzed by direct fits of model spectra

Samy Skander Bahoura

We give blow-up behavior for solutions to an elliptic system with Dirichlet condition, and, weight and boundary singularity. Also, we have a compactness result for this elliptic system with regular H{\"o}lderian weight and boundary singularity and Lipschitz condition.

Nobutaka Boumuki

In this paper we consider the complex vector spaces of holomorphic cross-sections of homogeneous holomorphic vector bundles over elliptic adjoint orbits, and provide a sufficient condition for the vector spaces to be finite dimensional in view of root systems.

Ruth E. Baker, Gergely Röst

The delayed logistic equation (also known as Hutchinson's equation or Wright's equation) was originally introduced to explain oscillatory phenomena in ecological dynamics. While it motivated the development of a large number of mathematical tools in the study of nonlinear delay differential equations, it also received criticism from modellers because of the

Luis Ortiz-Gutiérrez, Raul Teixeira, Aurélien Eloy, Dilleys Ferreira da Silva

In this paper, we measure the spectrum of light scattered by a cold atomic cloud driven by a strong laser beam. The experimental technique is based on heterodyne spectroscopy coupled to single-photon detectors and intensity correlations. At resonance, we observe the Mollow triplet. This spectrum is quantitatively compared to the theoretical one, emphasizing

S. Plumari, G. Coci, S. K. Das, V. Minissale

We study the propagation of heavy quarks (HQs) in the quark-gluon plasma (QGP) by means of a relativistic Boltzmann transport (RBT) approach. The non-perturbative interaction between heavy quarks and light quarks is described by means of a quasi-particle approach able to describe simultaneously the experimental data for the nuclear suppression factor $R_{\rm

I. Pillitteri, S. Sciortino, F. Reale, G. Micela

[Abridged] We investigated the X-ray characteristics of the Class I YSO Elias 29 with joint XMM-Newton and NuSTAR observations of 300 ks and 450 ks, respectively. These are the first observations of a very young (<1 Myr) stellar object in a band encompassing simultaneously both soft and hard X-rays. In addition to the hot Fe complex at 6.7 keV, we observed f

Nikos Fotiou, George C. Polyzos

With the Internet of Things (IoT), Things are expected to live in different "domains" and "contexts" during their lifetime. Information generated by and associated with Things should be manageable by multiple, diverse stakeholders accordingly. Moreover, the scope of the information related to Things can range from private and confidential to public and audit

Rahul Tallamraju, Eric Price, Roman Ludwig, Kamalakar Karlapalem

Autonomous motion capture (mocap) systems for outdoor scenarios involving flying or mobile cameras rely on i) a robotic front-end to track and follow a human subject in real-time while he/she performs physical activities, and ii) an algorithmic back-end that estimates full body human pose and shape from the saved videos. In this paper we present a novel fron

Sebastian East, Mark Cannon

In this paper we present a convex formulation of the Model Predictive Control (MPC) optimisation for energy management in hybrid electric vehicles, and an Alternating Direction Method of Multipliers (ADMM) algorithm for its solution. We develop a new proof of convexity for the problem that allows the nonlinear dynamics to be modelled as a linear system, then

S. Thanos, A. K. Theophilou, M. Tassi

It was realized from the early days of Chemical Physics (Rev. Mod. Phys. 35, 496 (1963)) that the energy $E_{HF}$ of the Slater determinant (SlDet) $|\Phi _{HF}\rangle$, obtained by the single particle Hartree-Fock (HF) equation, does not coincide with the minimum energy of the functional $\langle\Phi|H|\Phi \rangle$ where $|\Phi \rangle$ is a SlDet and $H$

Lei Ding, Pascal Manuel, Sebastian Bachus, Franziska Grußler

We present the structural characterization and low-temperature magnetism of the triangular-lattice delafossite NaYbO$_2$. Synchrotron x-ray diffraction and neutron scattering exclude both structural disorder and crystal-electric-field randomness, whereas heat-capacity measurements and muon spectroscopy reveal the absence of magnetic order and persistent spin

Uriel Feige

Alice and Bob take turns (with Alice playing first) in declaring numbers from the set $[1,2N]$. If a player declares a number that was previously declared, that player looses and the other player wins. If all numbers are declared without repetition, the outcome is a tie. If both players have unbounded memory and play optimally, then the game will be tied. Ga