July 2019 arXiv papers — page 39

Li He, Long Xia, Wei Zeng, Zhi-Ming Ma

It is well known that the historical logs are used for evaluating and learning policies in interactive systems, e.g. recommendation, search, and online advertising. Since direct online policy learning usually harms user experiences, it is more crucial to apply off-policy learning in real-world applications instead. Though there have been some existing works,

Stefan Hackstein, Marcus Brüggen, Franco Vazza, Bryan Gaensler

We investigate the possibility of measuring intergalactic magnetic fields using the dispersion measures and rotation measures of fast radio bursts. With Bayesian methods, we produce probability density functions for values of these measures. We distinguish between contributions from the intergalactic medium, the host galaxy and the local environment of the p

William Rushworth

A cobordism between links in thickened surfaces consists of a surface $ S $ and a $3$-manifold $M $, with $ S $ properly embedded in $ M \times I $. We show that there exist links in thickened surfaces such that if $(S,M) $ is a cobordism between them in which $ S $ is simple, then $ M $ must be complex. That is, there are cases in which low complexity of th

Ran Xin, Soummya Kar, Usman A. Khan

Decentralized solutions to finite-sum minimization are of significant importance in many signal processing, control, and machine learning applications. In such settings, the data is distributed over a network of arbitrarily-connected nodes and raw data sharing is prohibitive often due to communication or privacy constraints. In this article, we review decent

Xin Sun, Hongwei Xv, Junyu Dong, Qiong Li

Learning to recognize novel visual categories from a few examples is a challenging task for machines in real-world industrial applications. In contrast, humans have the ability to discriminate even similar objects with little supervision. This paper attempts to address the few shot fine-grained image classification problem. We propose a feature fusion model

Haoran Zhao, Xin Sun, Junyu Dong, Changrui Chen

High storage and computational costs obstruct deep neural networks to be deployed on resource-constrained devices. Knowledge distillation aims to train a compact student network by transferring knowledge from a larger pre-trained teacher model. However, most existing methods on knowledge distillation ignore the valuable information among training process ass

Wei Liu, Pingping Zhang, Yinjie Lei, Xiaolin Huang

Image smoothing is a fundamental procedure in applications of both computer vision and graphics. The required smoothing properties can be different or even contradictive among different tasks. Nevertheless, the inherent smoothing nature of one smoothing operator is usually fixed and thus cannot meet the various requirements of different applications. In this

Jeffrey C. Lagarias, D. Harry Richman

This paper completes the classification of the set $S$ of all real parameter pairs $(\alpha,\beta)$ such that the dilated floor functions $f_\alpha(x) = \lfloor{\alpha x}\rfloor$, $f_\beta(x) = \lfloor{\beta x}\rfloor$ have a nonnegative commutator, i.e. $ [ f_{\alpha}, f_{\beta}](x) = \lfloor{\alpha \lfloor{\beta x}\rfloor}\rfloor - \lfloor{\beta \lfloor{\a

Jing Jin, Junhui Hou, Jie Chen, Sam Kwong

This paper explores the problem of reconstructing high-resolution light field (LF) images from hybrid lenses, including a high-resolution camera surrounded by multiple low-resolution cameras. To tackle this challenge, we propose a novel end-to-end learning-based approach, which can comprehensively utilize the specific characteristics of the input from two co

Payam Sabbaghi, Linshuang Long, Xiaoyan Ying, Lee Lambert

In this Letter we experimentally demonstrate that the radiative heat transfer between metallic planar surfaces exceeds the blackbody limit by employing the near-field and thin-film effects. Nanosized polystyrene particles were used to create a nanometer gap between aluminum thin-films of different thicknesses coated on 5x5 mm2 diced silicon chips while the g

Konstantinos Pantazis, Daniel L. Sussman, Youngser Park, Zhirui Li

We consider the problem of detecting a noisy induced multiplex template network in a larger multiplex background network. Our approach, which extends the framework of Sussman et al. (2019) to the multiplex setting, leverages a multiplex analogue of the classical graph matching problem to use the template as a matched filter for efficiently searching the back

Akrati Saxena, Pratishtha Saxena, Harita Reddy, Ralucca Gera

Do studies show that physical and online students' social networks support education? Analyzing interactions between students in schools and universities can provide a wealth of information. Studies on students' social networks can help us understand their behavioral dynamics, the correlation between their friendships and academic performance, commun

Xavier Porte, Louis Andreoli, Maxime Jacquot, Laurent Larger

The implementation of artificial neural networks in hardware substrates is a major interdisciplinary enterprise. Well suited candidates for physical implementations must combine nonlinear neurons with dedicated and efficient hardware solutions for both connectivity and training. Reservoir computing addresses the problems related with the network connectivity

Leo Cazenille

Quality-Diversity (QD) algorithms are a recent type of optimisation methods that search for a collection of both diverse and high performing solutions. They can be used to effectively explore a target problem according to features defined by the user. However, the field of QD still does not possess extensive methodologies and reference benchmarks to compare

Jesus L. Lobo, Javier Del Ser, Albert Bifet, Nikola Kasabov

Applications that generate huge amounts of data in the form of fast streams are becoming increasingly prevalent, being therefore necessary to learn in an online manner. These conditions usually impose memory and processing time restrictions, and they often turn into evolving environments where a change may affect the input data distribution. Such a change ca

Jesus L. Lobo, Izaskun Oregi, Albert Bifet, Javier Del Ser

Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. One of the most promising techniques in stream learning is the Spiking Neural Network, and some of them use an interesting population encoding scheme to transform the incoming stimuli into spikes. This study sheds lights on the key issu

Soumen Kanrar

The literature survey typically predicated sharp growth for IP-based video traffic i.e., 30% or more annually. For the Internet TV in mobile networks, video traffic growth rate is expected to rise 80% or more. These high growth rates of video traffic will account for a large portion of the bandwidth. The performance of video-on-demand system during real-time

Chenwei Zhang

Nowadays, with the booming development of the Internet, people benefit from its convenience due to its open and sharing nature. A large volume of natural language texts is being generated by users in various forms, such as search queries, documents, and social media posts. As the unstructured text corpus is usually noisy and messy, it becomes imperative to c

Boyuan Pan, Yazheng Yang, Hao Li, Zhou Zhao

Machine Comprehension (MC) is one of the core problems in natural language processing, requiring both understanding of the natural language and knowledge about the world. Rapid progress has been made since the release of several benchmark datasets, and recently the state-of-the-art models even surpass human performance on the well-known SQuAD evaluation. In

Sören Schlichting, Dominik Smith, Lorenz von Smekal

We calculate spectral functions of the relativistic $O(4)$ model from real-time lattice simulations in classical-statistical field theory. While in the low and high temperature phase of the model, the spectral functions of longitudinal $(σ)$ and transverse $(π)$ modes are well described by relativistic quasi-particle peaks, we find a highly non-trivial behav

Juan Sebastián Ardenghi

By applying Monte-Carlo method, the Moon radius is obtained by counting craters in a spherical square over the surface of it. As it is well known, approximate values for $π$ can be obtained by counting random numbers in a square and in a quarter of circle inscribed in it in Euclidean geometry. This procedure can be extend it to spherical geometry, where new

Matsuo Sato

We formulate a quantum theory of the Universe based on Bayesian probability. In this theory, the probability of the Universe is not a frequency probability, which can be obtained by observing experimental results several times, but is a Bayesian probability, which can define a probability of an event that occurs just once. As an example, by applying the quan

Mengshu Liu, Jingya Wang, Kareem Abdelfatah, Mohammed Korayem

Job recommendation is a crucial part of the online job recruitment business. To match the right person with the right job, a good representation of job postings is required. Such representations should ideally recommend jobs with fitting titles, aligned skill set, and reasonable commute. To address these aspects, we utilize three information graphs ( job-job

Vikas Kumar

Machine learning techniques for Recommendation System (RS) and Classification has become a prime focus of research to tackle the problem of information overload. RS are software tools that aim at making informed decisions about the services that a user may like. On the other hand, classification technique deals with the categorization of a data object into o

Jose Ilton de Oliveira Filho, Abderrahmen Trichili, Boon S. Ooi, Mohamed-Slim Alouini

Exploiting light beams to carry information and deliver power is mooted as a potential technology to recharge batteries of future generation Internet of things (IoT) and Internet of underwater things (IoUT) devices while providing optical connectivity. Simultaneous lightwave information and power transfer (SLIPT) has been recently proposed as an efficient wa

R. Santagata, D. Tran, B. Argence, O. Lopez

There is an increasing demand for precise molecular spectroscopy, in particular in the mid-infrared fingerprint window that hosts a considerable number of vibrational signatures, whether it be for modeling our atmosphere, interpreting astrophysical spectra or testing fundamental physics. We present a high-resolution mid-infrared spectrometer traceable to pri

J. Brian Pitts

Reflective equilibrium between physics and philosophy, and between GR and particle physics, is fruitful and rational. I consider the virtues of simplicity, conservatism, and conceptual coherence, along with perturbative expansions. There are too many theories to consider. Simplicity supplies initial guidance, after which evidence increasingly dominates. One

Sanjib Dey, Aswathy Raj, Sandeep K. Goyal

We have studied the effect of a non-Hermitian Bosonic bath on the dynamics of a two-level spin system. The non-Hermitian Hamiltonian of the bath is chosen such that it converges to the harmonic oscillator Hamiltonian when the non-Hermiticity is switched off. We calculate the dynamics of the spin system and found that the non-Hermiticity can have positive as

Alan Chern, Phuong Hoang, Madhav Sigdel, Janani Balaji

Job transitions and upskilling are common actions taken by many industry working professionals throughout their career. With the current rapidly changing job landscape where requirements are constantly changing and industry sectors are emerging, it is especially difficult to plan and navigate a predetermined career path. In this work, we implemented a system

Donato Bini, Andrea Geralico

We present the first analytical computation of the (conservative) gravitational self-force correction to the periastron advance around a spinning black hole. Our result is accurate to the second order in the rotational parameter and through the 9.5 post-Newtonian level. It has been obtained as the circular limit of the correction to the gyroscope precession

Donato Bini, Andrea Geralico

We analytically compute the gravitational self-force correction to the gyroscope precession along slightly eccentric equatorial orbits in the Kerr spacetime, generalizing previous results for the Schwarzschild spacetime. Our results are accurate through the 9.5 post-Newtonian order and to second order in both eccentricity and rotation parameter. We also prov

Donato Bini, Andrea Geralico

The Detweiler-Barack-Sago redshift function for particles moving along slightly eccentric equatorial orbits around a Kerr black hole is currently known up to the second order in eccentricity, second order in spin parameter, and the 8.5 post-Newtonian order. We improve the analytical computation of such a gauge-invariant quantity by including terms up to the

Eunice Y. S. Chan, Robert M. Corless, Laureano Gonzalez-Vega, J. Rafael Sendra

We look at Bohemians, specifically those with population $\{-1, 0, {+1}\}$ and sometimes $\{0,1,i,-1,-i\}$. More, we specialize the matrices to be upper Hessenberg Bohemian. From there, focusing on only those matrices whose characteristic polynomials have maximal height allows us to explicitly identify these polynomials and give useful bounds on their height

Diego Moussallem, Matthias Wauer, Axel-Cyrille Ngonga Ngomo

A large number of machine translation approaches have recently been developed to facilitate the fluid migration of content across languages. However, the literature suggests that many obstacles must still be dealt with to achieve better automatic translations. One of these obstacles is lexical and syntactic ambiguity. A promising way of overcoming this probl

G. Mathys, I. I. Romanyuk, S. Hubrig, D. O. Kudryavtsev

Context. One of the keys to understanding the origin of the Ap stars and their significance in the general context of stellar astrophysics is the consideration of the most extreme properties displayed by some of them. In that context, HD 965 is particularly interesting, as it combines some of the most pronounced chemical peculiarities with one of the longest

A. G. Ghazaryan, Kh. V. Sedrakian

The microscopic quantum theory of nonlinear stimulated scattering of chiral particles in doped $AB$ stacked bilayer graphene on Coulomb field of charged impurities in the presence of strong coherent electromagnetic radiation is presented. The Liouville-von Neumann equation for the density matrix is solved analytically. Here the interaction of electrons with

Apostolos I. Rikos, Christoforos N. Hadjicostis

We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the nodes, each associated with some initial value, to obtain the average (or some value close to the average) of these initial values. In this paper, we p

Francesco Malandrino, Carla-Fabiana Chiasserini, Claudio Casetti, Giada Landi

5G network nodes, fronthaul and backhaul alike, will have both forwarding and computational capabilities. This makes energy-efficient network management more challenging, as decisions such as activating or deactivating a node impact on both the ability of the network to route traffic and the amount of processing it can perform. To this end, we formulate an o

Olexandr Polishchuk

This paper provides the analysis for functional approaches of complex network systems research. In order to study the behavior of these systems the flow adjacency matrices were introduced. The concepts of strength, power, domain and diameter of influence of complex network nodes are analyzed for the purpose of determining their importance in the systems stru

Edison Marcavillaca Niño de Guzmán, Abramo Hefez

The main result in this paper is to supply a recursive formula, on the number of minimal primes, for the colength of a fractional ideal in terms of the maximal points of the value set of the ideal itself. The fractional ideals are taken in the class of complete admissible rings, a more general class of rings than those of algebroid curves. For such rings wit

Asma Ghandeharioun, Daniel McDuff, Mary Czerwinski, Kael Rowan

A natural conversational interface that allows longitudinal symptom tracking would be extremely valuable in health/wellness applications. However, the task of designing emotionally-aware agents for behavior change is still poorly understood. In this paper, we present the design and evaluation of an emotion-aware chatbot that conducts experience sampling in a

Roberto Frigerio

Let $X$ be a topological space admitting an amenable cover of multiplicity $k\in\mathbb{N}$. We show that, for every $n\geq k$ and every $α\in H_n(X;\mathbb{R})$, the image of $α$ in the $\ell^1$-homology module $H_n^{\ell^1}(X;\mathbb{R})$ vanishes. This strenghtens previous results by Gromov and Ivanov, who proved, under the same assumptions, that the $\el

Kourosh Hakhamaneshi, Nick Werblun, Pieter Abbeel, Vladimir Stojanovic

The discrepancy between post-layout and schematic simulation results continues to widen in analog design due in part to the domination of layout parasitics. This paradigm shift is forcing designers to adopt design methodologies that seamlessly integrate layout effects into the standard design flow. Hence, any simulation-based optimization framework should ta

Evgeny Postnikov, Alexander Kryukov, Stanislav Polyakov, Dmitry Zhurov

Deep learning techniques, namely convolutional neural networks (CNN), have previously been adapted to select gamma-ray events in the TAIGA experiment, having achieved a good quality of selection as compared with the conventional Hillas approach. Another important task for the TAIGA data analysis was also solved with CNN: gamma-ray energy estimation showed so

Ayush Hariharan, Ankit Gupta, Trisha Pal

As machine learning and cybersecurity continue to explode in the context of the digital ecosystem, the complexity of cybersecurity data combined with complicated and evasive machine learning algorithms leads to vast difficulties in designing an end to end system for intelligent, automatic anomaly classification. On the other hand, traditional systems use ele

Simon Langenscheidt

In this bachelor thesis, possible kinetic terms and couplings of standard fields in MacDowell-Mansouri-Stelle-West gravity are studied with some aspects of group theory in mind. Possible obstructions to these couplings are considered and used to make statements about the validity of the theory when coupled to matter. While interactions themselves turn out to

Roufaida Laidi, Djamel Djenouri, Marc Ringel

This work investigates the economic, social, and environmental impact of adopting different smart lighting architectures for home automation in two geographical and regulatory regions: Algiers, Algeria, and Stuttgart, Germany. Lighting consumes a considerable amount of energy, and devices for smart light-ing solutions are among the most purchased smart home

Jing Han, Zixing Zhang, Zhao Ren, Björn Schuller

Despite remarkable advances in emotion recognition, they are severely restrained from either the essentially limited property of the employed single modality, or the synchronous presence of all involved multiple modalities. Motivated by this, we propose a novel crossmodal emotion embedding framework called EmoBed, which aims to leverage the knowledge from ot

Aimon Rahman, Hasib Zunair, M Sohel Rahman, Jesia Quader Yuki

Malaria is a female anopheles mosquito-bite inflicted life-threatening disease which is considered endemic in many parts of the world. This article focuses on improving malaria detection from patches segmented from microscopic images of red blood cell smears by introducing a deep convolutional neural network. Compared to the traditional methods that use tedi

Qingjian Lin, Ruiqing Yin, Ming Li, Hervé Bredin

More and more neural network approaches have achieved considerable improvement upon submodules of speaker diarization system, including speaker change detection and segment-wise speaker embedding extraction. Still, in the clustering stage, traditional algorithms like probabilistic linear discriminant analysis (PLDA) are widely used for scoring the similarity

Théis Bazin, Gaëtan Hadjeres

Inpainting-based generative modeling allows for stimulating human-machine interactions by letting users perform stylistically coherent local editions to an object using a statistical model. We present NONOTO, a new interface for interactive music generation based on inpainting models. It is aimed both at researchers, by offering a simple and flexible API all

Luca Anthony Thiede, Pratik Prabhanjan Brahma

Trajectory or behavior prediction of traffic agents is an important component of autonomous driving and robot planning in general. It can be framed as a probabilistic future sequence generation problem and recent literature has studied the applicability of generative models in this context. The variety or Minimum over N (MoN) loss, which tries to minimize th

Tabea Rebafka, Etienne Roquain, Fanny Villers

In this paper, a noisy version of the stochastic block model (NSBM) is introduced and we investigate the three following statistical inferences in this model: estimation of the model parameters, clustering of the nodes and identification of the underlying graph. While the two first inferences are done by using a variational expectation-maximization (VEM) alg

Andrew Reynolds, Haniel Barbosa, Andres Nötzli, Clark Barrett

CVC4Sy is a syntax-guided synthesis (SyGuS) solver based on bounded term enumeration and, for restricted fragments, quantifier elimination. The enumerative strategies are based on encoding term enumeration as an extension of the quantifier-free theory of algebraic datatypes and on a highly optimized brute-force algorithm. The quantifier elimination strategy

Athreya Shankar, Leonardo Salvi, Maria Luisa Chiofalo, Nicola Poli

Bragg interferometers, operating using pseudospin-1/2 systems composed of two momentum states, have become a mature technology for precision measurements. State-of-the-art Bragg interferometers are rapidly surpassing technical limitations and are soon expected to operate near the projection noise limit set by uncorrelated atoms. Despite the use of large numb

William M. Briggs, Jaap Hanekamp

We investigate trend identification in the LML and MAN atmospheric ammonia data. The signals are mixed in the LML data, with just as many positive, negative, and no trends found. The start date for trend identification is crucial, with the trends claimed changing sign and significance depending on the start date. The MAN data is calibrated to the LML data. T

Bryce L. Ferguson, Philip N. Brown, Jason R. Marden

How can a system designer exploit system-level knowledge to derive incentives to optimally influence social behavior? The literature on network routing contains many results studying the application of monetary tolls to influence behavior and improve the efficiency of self-interested network traffic routing. These results typically fall into two categories:

Yanxu Su, Yang Shi, Changyin Sun

This paper analyzes the contraction of the primal-dual gradient optimization via contraction theory in the context of discrete-time updating dynamics. The contraction theory based on Riemannian manifolds is first established for convergence analysis of a convex optimization algorithm. The equality and inequality constrained optimization cases are studied, re

Yeping Hu, Liting Sun, Masayoshi Tomizuka

Accurately predicting future behaviors of surrounding vehicles is an essential capability for autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others, however, are full of uncertainties. Both rational and irrational behaviors exist, and the autonomous vehicles need to be aware of this in their prediction module. The predi

Yanxu Su, Yang Shi, Changyin Sun

This paper develops a distributed model predictive control (DMPC) strategy for a class of discrete-time linear systems with consideration of globally coupled constraints. The DMPC under study is based on the dual problem concerning all subsystems, which is solved by means of the primal-dual gradient optimization in a distributed manner using Laplacian consen

Andrea Muolo, Edit Mátyus, Markus Reiher

Various explicitly correlated Gaussian (ECG) basis sets are considered for the solution of the molecular Schrödinger equation with particular attention to the simplest polyatomic system, H$_3^+$. Shortcomings and advantages are discussed for plain ECGs, ECGs with the global vector representation, floating ECGs and their numerical projection, and ECGs with co

Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor

String similarity models are vital for record linkage, entity resolution, and search. In this work, we present STANCE --a learned model for computing the similarity of two strings. Our approach encodes the characters of each string, aligns the encodings using Sinkhorn Iteration (alignment is posed as an instance of optimal transport) and scores the alignment

Rinat Abdrashitov, Alec Jacobson, Karan Singh

Computer animation in conjunction with 3D printing has the potential to positively impact traditional stop-motion animation. As 3D printing every frame of a computer animation is prohibitively slow and expensive, 3D printed stop-motion can only be viable if animations can be faithfully reproduced using a compact library of 3D printed and efficiently assembla

Luca Planat, Ekaterina Al-Tavil, Javier Puertas Martinez, Remy Dassonneville

We report on the fabrication and characterization of 50 Ohms, flux-tunable, low-loss, SQUID-based transmission lines. The fabrication process relies on the deposition of a thin dielectric layer (few tens of nanometers) via Atomic Layer Deposition (ALD) on top of a SQUID array, the whole structure is then covered by a non-superconducting metallic top ground p

D. -C. Kim, E. Momjian, Ilsang Yoon, Minjin Kim

We report the results of an investigation to determine the nature of the offset active galactic nucleus (AGN) found in the source CXO J101527.2+625911. Hubble Space Telescope and Chandra X-ray observatory data had suggested that the offset AGN, which has an angular separation of only 0\farcs26 from the center of the host galaxy, is a recoiled Super Massive B

Saeid Tizpaz-Niari, Pavol Cerny, Sriram Sankaranarayanan, Ashutosh Trivedi

Detection and quantification of information leaks through timing side channels are important to guarantee confidentiality. Although static analysis remains the prevalent approach for detecting timing side channels, it is computationally challenging for real-world applications. In addition, the detection techniques are usually restricted to 'yes' or &

A. Kurup, J. Pasternak, R. Taylor, L. Murgatroyd

The Centre for the Clinical Application of Particles' Laser-hybrid Accelerator for Radiobiological Applications (LhARA) facility is being studied and requires simulation of novel accelerator components (such as the Gabor lens capture system), detector simulation and simulation of the ion beam interaction with cells. The first stage of LhARA will provide

Chao Zhang, Samson Lasaulce, Achal Agrawal, Raphael Visoz

One of the goals of this paper is to contribute to finding distributed power control strategies which exploit efficiently the information available about the global channel state; it may be local or noisy. A suited way of measuring the global efficiency of a distributed power control scheme is to use the long-term utility region. First, we provide the utilit

Michael Weylandt, Yu Han, Katherine B. Ensor

Financial markets for Liquified Natural Gas (LNG) are an important and rapidly-growing segment of commodities markets. Like other commodities markets, there is an inherent spatial structure to LNG markets, with different price dynamics for different points of delivery hubs. Certain hubs support highly liquid markets, allowing efficient and robust price disco

Edward Hardy, Susha Parameswaran

We present a novel source of dark energy, which is motivated by the prevalence of hidden sectors in string theory models and is consistent with all of the proposed swampland conjectures. Thermal effects hold a light hidden sector scalar at a point in field space that is not a minimum of its zero temperature potential. This leads to an effective "cosmolog

Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary, James Route

This paper presents the submissions by Team Dr.Quad to the ACL-BioNLP 2019 shared task on Textual Inference and Question Entailment in the Medical Domain. Our system is based on the prior work Liu et al. (2019) which uses a multi-task objective function for textual entailment. In this work, we explore different strategies for generalizing state-of-the-art la

Yao Qiao, Antonio Alessandro Deleo, Marco Salviato

Composite structures must endure a great variety of multi-axial stress states during their lifespan while guaranteeing their structural integrity and functional performance. Understanding the fatigue behavior of these materials, especially in the presence of notches that are ubiquitous in structural design, lies at the hearth of this study which presents a c

Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat, David R. Mortensen

This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which pred

Siddhant Sahu, Manoj Kumar Lenka, Pankaj Kumar Sa

We inspect all the deep learning based solutions and provide holistic understanding of various architectures that have evolved over the past few years to solve blind deblurring. The introductory work used deep learning to estimate some features of the blur kernel and then moved onto predicting the blur kernel entirely, which converts the problem into non-bli

Marco Giordani, Takayuki Shimizu, Andrea Zanella, Takamasa Higuchi

Recently, millimeter wave (mmWave) bands have been investigated as a means to enhance automated driving and address the challenging data rate and latency demands of emerging automotive applications. For the development of those systems to operate in bands above 6 GHz, there is a need to have accurate channel models able to predict the peculiarities of the ve

Debmalya Panigrahi, Shweta Patwa, Sudeepa Roy

We investigate the computational complexity of minimizing the source side-effect in order to remove a given number of tuples from the output of a conjunctive query. In particular, given a multi-relational database $D$, a conjunctive query $Q$, and a positive integer $k$ as input, the goal is to find a minimum subset of input tuples to remove from D that woul

Marco Giordani, Andrea Zanella, Takamasa Higuchi, Onur Altintas

The next generations of vehicles are expected to be equipped with sophisticated sensors to support advanced automotive services. The large volume of data generated by such applications will likely put a strain on the vehicular communication technologies, which may be unable to guarantee the required quality of service. In this scenario, it is fundamental to

Remigiusz Augusiak, Alexia Salavrakos, Jordi Tura, Antonio Acín

In device-independent quantum information processing Bell inequalities are not only used as detectors of nonlocality, but also as certificates of relevant quantum properties. In order for these certificates to work, one very often needs Bell inequalities that are maximally violated by specific quantum states. Recently, in [A. Salavrakos et al., Phys. Rev. Le

Sofia Ruiz-Suarez, Vianey Leos-Barajas, Ignacio Alvarez-Castro, Juan M. Morales

The study of animal movement is challenging because it is a process modulated by many factors acting at different spatial and temporal scales. Several models have been proposed which differ primarily in the temporal conceptualization, namely continuous and discrete time formulations. Naturally, animal movement occurs in continuous time but we tend to observe

Behzad Mahmoudian

In the environmental modeling field, the exploratory analysis of responses often exhibits spatial correlation as well as some non-Gaussian attributes such as skewness and/or heavy-tailedness. Consequently, we propose a general spatial model based on scale-shape mixtures of the multivariate skew-normal distribution. Intuitively, it incorporates distinct rando

Vinayak Jagadish, R. Srikanth, Francesco Petruccione

We show that the set of not-completely-positive (NCP) maps is unbounded, unless further assumptions are made. This is done by first proposing a reasonable definition of a valid NCP map, which is nontrivial because NCP maps may lack a full positivity domain. The definition is motivated by specific examples. We prove that for valid NCP maps, the eigenvalue spe

Shinichiro Shirota, Andrew O. Finley, Bruce D. Cook, Sudipto Banerjee

A key challenge in spatial statistics is the analysis for massive spatially-referenced data sets. Such analyses often proceed from Gaussian process specifications that can produce rich and robust inference, but involve dense covariance matrices that lack computationally exploitable structures. The matrix computations required for fitting such models involve

Christopher M. Pasco, Ismail El Baggari, Elisabeth Bianco, Lena F. Kourkoutis

Incorporating magnetism into two dimensional (2D) van der Waals (VdW) heterostrutures is crucial for the development of functional electronic and magnetic devices. Here we show that Nb3X8 (X = Cl, Br) is a family of 2D layered trimerized kagomé magnets that are paramagnetic at high temperatures and undergo a first order phase transition on cooling to a singl

Tai Manh Ho, Thinh Duy Tran, Ti Ti Nguyen, S. M. Ahsan Kazmi

5G wireless systems will extend mobile communication services beyond mobile telephony, mobile broadband, and massive machine-type communication into new application domains, namely the so-called vertical domains including the smart factory, smart vehicles, smart grid, smart city, etc. Supporting these vertical domains comes with demanding requirements: high-

Kathryne J. Daniel, David A. Schaffner, Fiona McCluskey, Codie Fiedler Kawaguchi

It is widely accepted that stars in a spiral disk, like the Milky Way's, can radially migrate on order a scale length over the disk's lifetime. With the exception of cold torquing, also known as "churning," processes that contribute to the radial migration of stars are necessarily associated with kinematic heating. Additionally, it is an open

Sixiong You, Ran Dai, Ping Lu

Many optimal control problems are formulated as two point boundary value problems (TPBVPs) with conditions of optimality derived from the Hamilton-Jacobi-Bellman (HJB) equations. In most cases, it is challenging to solve HJBs due to the difficulty of guessing the adjoint variables. This paper proposes two learning-based approaches to find the initial guess o

William Layton, Michael McLaughlin

The standard $1-$equation model \ of turbulence was first derived by Prandtl and has evolved to be a common method for practical flow simulations. Five fundamental laws that any URANS model should satisfy are \[ \begin{array} [c]{ccc} \textbf{1.} & \text{Time window:} & \begin{array} [c]{c} τ\downarrow 0\text{ implies }v_{\text{\small URANS}}\rightarrow u_{\

R. A. J. Eyles, P. T. O'Brien, K. Wiersema, R. L. C. Starling

We present X-ray and optical observations of the short duration gamma-ray burst GRB 071227 and its host at $z=0.381$, obtained using \textit{Swift}, Gemini South and the Very Large Telescope. We identify a short-lived and moderately bright optical transient, with flux significantly in excess of that expected from a simple extrapolation of the X-ray spectrum

M. M. Piva, W. Zhu, F. Ronning, J. D. Thompson

Here we report the structural and electronic properties of CeAu$_{2}$Bi, a new heavy-fermion compound crystallizing in a nonsymmorphic hexagonal structure ($P63/mmc$). The Ce$^{3+}$ ions form a triangular lattice which orders antiferromagnetically below $T_{N} = 3.1$~K with a magnetic hard axis along the c-axis. Under applied pressure, $T_{N}$ increases line

Dogucan Yaman, Fevziye Irem Eyiokur, Hazım Kemal Ekenel

In this paper, we present multimodal deep neural network frameworks for age and gender classification, which take input a profile face image as well as an ear image. Our main objective is to enhance the accuracy of soft biometric trait extraction from profile face images by additionally utilizing a promising biometric modality: ear appearance. For this purpo

Benjamin Heymann, Alejandro Jofré

Motivated by the problem of market power in electricity markets, we introduced in previous works a mechanism for simplified markets of two agents with linear cost. In standard procurement auctions, the market power resulting from the quadratic transmission losses allows the producers to bid above their true values, which are their production cost. The mechan

Michael Marsset, Francesca DeMeo, Adrian Sonka, Mirel Birlan

We present near-infrared spectroscopy of the sporadically active asteroid (6478) Gault collected on the 3 m NASA/Infrared Telescope Facility observatory in late 2019 March/early April. Long-exposure imaging with the 0.5 m NEEMO T05 telescope and previously published data simultaneously monitored the asteroid activity, providing context for our measurements.

Ian D. Kivlichan, Christopher E. Granade, Nathan Wiebe

Iterative phase estimation has long been used in quantum computing to estimate Hamiltonian eigenvalues. This is done by applying many repetitions of the same fundamental simulation circuit to an initial state, and using statistical inference to glean estimates of the eigenvalues from the resulting data. Here, we show a generalization of this framework where

Riccardo Arcodia, Andrea Merloni, Kirpal Nandra, Gabriele Ponti

The correlation observed between monochromatic X-ray and UV luminosities in radiatively-efficient active galactic nuclei (AGN) lacks a clear theoretical explanation despite being used for many applications. Such a correlation, with its small intrinsic scatter and its slope that is smaller than unity in log space, represents the compelling evidence that a mec

N. Miret-Roig, H. Bouy, J. Olivares, L. M. Sarro

Context. The study of star formation is extremely challenging due to the lack of complete and clean samples of young, nearby clusters, and star forming regions. The recent Gaia DR2 catalogue complemented with the deep, ground based COSMIC DANCe catalogue offers a new database of unprecedented accuracy to revisit the membership of clusters and star forming re

Massimiliano Zanin, Bahar Güntekin, Tuba Aktürk, Lütfü Hanoğlu

Characterising brain activity at rest is of paramount importance to our understanding both of general principles of brain functioning and of the way brain dynamics is affected in the presence of neurological or psychiatric pathologies. We measured the time-reversal symmetry of spontaneous electroencephalographic brain activity recorded from three groups of p

Omar Ajebbar, Elhoucien Elqorachi

The aim of the present paper is to give extensions of the cosine-sine functional equation.

Benoit Vuillemin, Lionel Delphin-Poulat, Rozenn Nicol, Laëtitia Matignon

This paper presents a new algorithm: TSRuleGrowth, looking for partially-ordered rules over a time series. This algorithm takes principles from the state of the art of rule mining and applies them to time series via a new notion of support. We apply this algorithm to real data from a connected environment, which extract user habits through different connecte

Saeed Nosratabadi, Amir Mosavi, Shahaboddin Shamshirband, Edmundas Kazimieras Zavadskas

The concept of the sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural, or other contexts, in a sustainable way. The process of sustainable business model construction forms an innovative part of a business strategy. Different industries and businesses have utilized su

Denis Tome, Patrick Peluse, Lourdes Agapito, Hernan Badino

We present a new solution to egocentric 3D body pose estimation from monocular images captured from a downward looking fish-eye camera installed on the rim of a head mounted virtual reality device. This unusual viewpoint, just 2 cm. away from the user's face, leads to images with unique visual appearance, characterized by severe self-occlusions and stron