November 2019 arXiv papers — page 2

Hiroo Azuma

In this paper, we show that there are instances where eavesdropping causes noise reduction for a quantum key distribution (QKD) protocol. To witness these phenomena, we investigate a fault-tolerant six-state QKD protocol over a collective unitary noise channel. In this protocol, legitimate users send and receive two-qubit states that belong to the noiseless

Kamran Ali, Charles E. Hughes

Representations used for Facial Expression Recognition (FER) usually contain expression information along with identity features. In this paper, we propose a novel Disentangled Expression learning-Generative Adversarial Network (DE-GAN) which combines the concept of disentangled representation learning with residue learning to explicitly disentangle facial e

Xiao Yang, Fangyun Wei, Hongyang Zhang, Jun Zhu

We consider universal adversarial patches for faces -- small visual elements whose addition to a face image reliably destroys the performance of face detectors. Unlike previous work that mostly focused on the algorithmic design of adversarial examples in terms of improving the success rate as an attacker, in this work we show an interpretation of such patche

Guohao Li, Guocheng Qian, Itzel C. Delgadillo, Matthias Müller

Architecture design has become a crucial component of successful deep learning. Recent progress in automatic neural architecture search (NAS) shows a lot of promise. However, discovered architectures often fail to generalize in the final evaluation. Architectures with a higher validation accuracy during the search phase may perform worse in the evaluation. A

Qisi Wang, M. Horio, K. von Arx, Y. Shen

We use resonant inelastic x-ray scattering to investigate charge-stripe correlations in La$_{1.675}$Eu$_{0.2}$Sr$_{0.125}$CuO$_4$. By differentiating elastic from inelastic scattering, it is demonstrated that charge-stripe correlations precede both the structural low-temperature tetragonal phase and the transport-defined pseudogap onset. The scattering peak

Ying-Zhi Zhang

We propose a magnetic confinement nuclear fusion mechanism for the evolution of a solar flare in solar atmosphere. The mechanism agree with two observed characteristics of explosive flares and coronal mass ejections (CMEs) that have proved to be very difficult to explain with previous mechanisms: the huge enrichments of $^{3}He$ and the high energy gamma ray

Sina Ebrahimi, Abulfazl Zakeri, Behzad Akbari, Nader Mokari

Network slicing is a crucial part of the 5G networks that communication service providers (CSPs) seek to deploy. By exploiting three main enabling technologies, namely, software-defined networking (SDN), network function virtualization (NFV), and network slicing, communication services can be served to the end-users in an efficient, scalable, and flexible ma

Junning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma

Autonomous driving systems have a pipeline of perception, decision, planning, and control. The decision module processes information from the perception module and directs the execution of downstream planning and control modules. On the other hand, the recent success of deep learning suggests that this pipeline could be replaced by end-to-end neural control

Ibrahim Al-Dayel, Sharief Deshmukh, Olga Belova

In this paper, we show that given a nontrivial concircular vector field $\boldsymbol{u}$ on a Riemannian manifold $(M,g)$ with potential function $f$, there exists a unique smooth function $\rho $ on $M$ that connects $\boldsymbol{u}$ to the gradient of potential function $\nabla f$, which we call the connecting function of the concircular vector field $\bol

Miaoxin Liu, Zhiqi Huang, Xiaolin Luo, Haitao Miao

The inconsistent Hubble constant values derived from cosmic microwave background (CMB) observations and from local distance-ladder measurements may suggest new physics beyond the standard $\Lambda$CDM paradigm. It has been found in earlier works that, at least phenomenologically, non-standard recombination histories can reduce the $\gtrsim 4\sigma$ Hubble te

Shi-Gui Yang, Yuan-Yuan Wang, Di Liu, Xu Jiang

In this paper, we propose \textit{ReLeTA}: Reinforcement Learning based Task Allocation for temperature minimization. We design a new reward function and use a new state model to facilitate optimization of reinforcement learning algorithm. By means of the new reward function and state model, \releta is able to effectively reduce the system peak temperature w

V. Del Duca, S. Druc, J. M. Drummond, C. Duhr

We propose an all-loop expression for scattering amplitudes in planar N=4 super Yang-Mills theory in multi-Regge kinematics valid for all multiplicities, all helicity configurations and arbitrary logarithmic accuracy. Our expression is arrived at from comparing explicit perturbative results with general expectations from the integrable structure of a closely

Christian Prehal, Stefan A. Freunberger

In a recent issue of Joule, Dongmin Im and coworkers from Samsung in South Korea describe a prototype lithium-O2 battery that reaches 700 Wh kg-1 and 600 Wh L-1 on cell level. They cut all components to the minimum to reach this value. Difficulties to fill the pores with discharge product and inhomogeneous cell utilization turn out to limit the achievable en

Mohsen Tajallifar, Sina Ebrahimi, Mohammad Reza Javan, Nader Mokari

In this paper, we propose a novel resource management scheme that jointly allocates the transmit power and computational resources in a centralized radio access network architecture. The network comprises a set of computing nodes to which the requested tasks of different users are offloaded. The optimization problem minimizes the energy consumption of task o

Anugraha Sinha, Naveen Kumar, Murukesh Mohanan, MD Muhaimin Rahman

In this work, we present a quantized deep neural network deployed on a low-power edge device, inferring learned motor-movements of a suspended robot in a defined space. This serves as the fundamental building block for the original setup, a robotic system for farms or greenhouses aimed at a wide range of agricultural tasks. Deep learning on edge devices and

Ramadan Abdul-Rashid, Basit Olakunle Alawode

In this paper, the Butterfly Optimization Algorithm (BOA) proposed by [1] is adopted to optimize the parameters of a designed Lead-Lad Controller so as to obtain a stabilized control system. Numerical analysis was carried out for BOA on the control problem and the results are compared to those obtained from the well known Genetic Algorithm (GA) and Different

Łukasz T. Stȩpień

Some exact solutions of boundary or initial conditions formulated for Bogomolny equations (derived by using the strong necessary conditions and associated with some ordinary equation and some partial differential equations), have been found. Besides, a degeneracy of the hamiltonian for the restricted baby Skyrme model has been established.

Deniz Ekiz, Yekta Said Can, Cem Ersoy

Continuous high perceived workload has a negative impact on the individual's well-being. Prior works focused on detecting the workload with medical-grade wearable systems in the restricted settings, and the effect of applying deep learning techniques for perceived workload detection in the wild settings is not investigated. We present an unobtrusive, comfort

Paulo J. Almeida, Julia Lieb

Maximum distance profile (MDP) convolutional codes have been proven to be very suitable for transmission over an erasure channel. In addition, the subclass of complete MDP convolutional codes has the ability to restart decoding after a burst of erasures. However, there is a lack of constructions of these codes over fields of small size. In this paper, we int

Isac Arnekvist, Dmytro Kalpakchi

This work is a reproducibility study of the paper of Antoniou and Storkey [2019], published at NeurIPS 2019. Our results are in parts similar to the ones reported in the original paper, supporting the central claim of the paper that the proposed novel method, called Self-Critique and Adapt (SCA), improves the performance of MAML++. The conducted additional e

Ling-Zheng Meng, Yan-Hong Qin, Li-Chen Zhao

Solitons in multi-component Bose-Einstein condensates have been paid much attention, due to the stability and wide applications of them. The exact soliton solutions are usually obtained for integrable models. In this paper, we present four families of exact spin soliton solutions for non-integrable cases in spin-1 Bose-Einstein Condensates. The whole particl

Yang Song, Qiyu Kang, Wee Peng Tay

Though deep learning has been applied successfully in many scenarios, malicious inputs with human-imperceptible perturbations can make it vulnerable in real applications. This paper proposes an error-correcting neural network (ECNN) that combines a set of binary classifiers to combat adversarial examples in the multi-class classification problem. To build an

Anton Kolonin

The motivation, concept, design and implementation of latent semantic search for search engines have limited semantic search, entity extraction and property attribution features, have insufficient accuracy and response time of latent search, may impose privacy concerns and the search results are unavailable in offline mode for robotic search operations. The

V. A. Fedorova, A. E. Rodin

The results of a search for individual fast radio bursts with the Large Phased Array of the Lebedev Physical Institute at 111 MHz during July 2012 through August 2018 are presented. The signals were distinguished by convolving the data with a template with a fixed form, followed by convolution with test dispersion measures. Areas of sky containing the galaxi

Yang Feng, Wanying Xie, Shuhao Gu, Chenze Shao

Neural machine translation models usually adopt the teacher forcing strategy for training which requires the predicted sequence matches ground truth word by word and forces the probability of each prediction to approach a 0-1 distribution. However, the strategy casts all the portion of the distribution to the ground truth word and ignores other words in the

Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma

Hand-crafting generalised decision-making rules for real-world urban autonomous driving is hard. Alternatively, learning behaviour from easy-to-collect human driving demonstrations is appealing. Prior work has studied imitation learning (IL) for autonomous driving with a number of limitations. Examples include only performing lane-following rather than follo

Anton Kolonin

The problem of reliable democratic governance is important for survival of any community, and it will be more critical over time communities with levels of social connectivity in society rapidly increasing with speeds and scales of electronic communication. In order to face such challenge, different sorts of rating and reputation systems are being developed,

P. Yu. Artemchuk, O. R. Sulymenko, S. Louis, J. Li

A method to perform spectrum analysis on low power signals between 0.1 and 10 THz is proposed. It utilizes a nanoscale antiferromagnetic tunnel junction (ATJ) that produces an oscillating tunneling anisotropic magnetoresistance, whose frequency is dependent on the magnitude of an evanescent spin current. It is first shown that the ATJ oscillation frequency c

Anna Denkowska, Stanisław Wanat

This work is an answer to the EIOPA 2017 report. It follows from the latter that in order to assess the potential systemic risk we should take into account the build-up of risk and in particular the risk that arises in time, as well as the interlinkages in the financial sector and the whole economy. Our main tools used to analyse the systemic risk dynamics i

Michel Waldschmidt

Let $s_0,s_1,\dots,s_{m-1}$ be complex numbers and $r_0,\dots,r_{m-1}$ rational integers in the range $0\le r_j\le m-1$. Our first goal is to prove that if an entire function $f$ of sufficiently small exponential type satisfies $f^{(mn+r_j)}(s_j)\in{\mathbb Z}$ for $0\le j\le m-1$ and all sufficiently large $n$, then $f$ is a polynomial. Under suitable assum

Michel Waldschmidt

Given a subset $S=\{s_0, s_1\}$ of the complex plane with two points and an infinite subset ${\mathscr S}$ of $S\times {\mathbb N}$, where ${\mathbb N}=\{0,1,2,\dots\}$ is the set of nonnegative integers, we ask for a lower bound for the order of growth of a transcendental entire function $f$ such that $f^{(n)}(s)\in{\mathbb Z}$ for all $(s,n)\in{\mathscr S}

T. A. Soldatov, A. I. Smirnov, K. Yu. Povarov, A. Paduan-Filho

We studied electron spin resonance in a quantum magnet NiCl2-4SC(NH2)2, demonstrating a field-induced quantum phase transition from a quantum-disordered phase to an antiferromagnet. We observe two branches of the antiferromagnetic resonance of the ordered phase, one of them has a gap and the other is a Goldstone mode with zero frequency at a magnetic field a

Nadia Labai, Tomer Kotek, Magdalena Ortiz, Helmut Veith

We introduce a novel automata model, called pebble-intervals automata (PIA), and study its power and closure properties. PIAs are tailored for a decidable fragment of FO that is important for reasoning about structures that use data values from infinite domains: the two-variable fragment with one total preorder and its induced successor relation, one linear

A. A. Gunya, Y. N. Istomin

Acceleration of protons in the active galactic nuclei is considered. The largest energy is achieved by protons during centrifugal acceleration in the magnetosphere of the central machine. When the proton accelerated in the magnetosphere of a black hole approaches light cylinder surface, acceleration occurs mainly in the azimuthal direction, i.e. the accelera

Darina Krylosova, Evgeny Seleznev, Nataliya Stankevich

The dynamics of a non-autonomous oscillator in which the phase and frequency of the external force depend on the dynamical variable is studied. Such a control of the phase and frequency of the external force leads to the appearance of complex chaotic dynamics in the behavior of oscillator. A hierarchy of various periodic and chaotic oscillations is observed.

Xiyuan Liu, Li Qiu

UAV collective motion has become a hot research topic in recent years. The realization of UAV collective motion, however, relied heavily on centralized control method and suffered from instability. Inspired by bird flocking theory, a control strategy for UAV collective motion with distributed measure and control methods was proposed in this study. In order t

Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang

The practical usage of reinforcement learning agents is often bottlenecked by the duration of training time. To accelerate training, practitioners often turn to distributed reinforcement learning architectures to parallelize and accelerate the training process. However, modern methods for scalable reinforcement learning (RL) often tradeoff between the throug

Ramadan Abdul-Rashid

This paper proposes a novel asynchronous consensus algorithm which is based on a continuous update rule and an energy efficient event triggered duty (wake-sleep) cycle based on a discrete Markov chain model. The system model of the proposed algorithm is formulated and analyzed. The conditions for convergence and stability of the algorithm are derived and the

Satsuki Matsuno

In a three-dimensional Riemannian manifold M that admits a unit Killing vector field $\xi$, we regard $\xi$ as a magnetic vector field. A magnetic Hopf surface is a surface obtained by Lie dragging the magnetic curve with $\xi$. Then we characterize Sasakian structure on M from magnetic Hopf surfaces. That is, we show that if an arbitrary magnetic Hopf surfa

Yanli Ai, Liming Dou, Chenwei Yang, Luming Sun

We analyze the X-ray, optical, and mid-infrared data of a "changing-look" Seyfert galaxy \sdssj15 at $z\simeq0.086$. Over a period of one decade (2009 - 2018), its broad H$\alpha$ line intensity increased by a factor of $\sim$4. Meanwhile, the X-ray emission in 2014 as observed by \chandra\ was about five times brighter than that in 2010 by {\it Suzaku}, and

Gaurav Sinha, Ayush Chauhan, Aurghya Maiti, Naman Poddar

We study the problem of separating a mixture of distributions, all of which come from interventions on a known causal bayesian network. Given oracle access to marginals of all distributions resulting from interventions on the network, and estimates of marginals from the mixture distribution, we want to recover the mixing proportions of different mixture comp

Stefan A. Freunberger

Beyond-intercalation batteries promise a step-change in energy storage compared to intercalation based lithium- and sodium-ion batteries. However, only performance metrics that include all cell components and operation parameters can tell whether a true advance over intercalation batteries has been achieved.

Jia-Hong Huang, Modar Alfadly, Bernard Ghanem, Marcel Worring

Deep neural networks have been playing an essential role in the task of Visual Question Answering (VQA). Until recently, their accuracy has been the main focus of research. Now there is a trend toward assessing the robustness of these models against adversarial attacks by evaluating the accuracy of these models under increasing levels of noisiness in the inp

Oussama Landoulsi

We consider the focusing $L^2$-supercritical Schr\"odinger equation in the exterior of a smooth, compact, strictly convex obstacle. We construct a solution behaving asymptotically as a solitary waves on $R^3$, as large time. When the velocity of the solitary wave is high, the existence of such a solution can be proved by a classical fixed point argument. To

Thi Huyen Chau Nguyen, Werner Grass, Klaus Jansen

In some important application areas of hard real-time systems, preemptive sporadic tasks with harmonic periods and constraint deadlines running upon a uni-processor platform play an important role. We propose a new algorithm for determining the exact worst-case response time for a task that has a lower computational complexity (linear in the number of tasks)

Yihang Ding, Xiaosheng Xiao, Kewei Liu, Shuzheng Fan

Dissipative nonlinear wave dynamics have been investigated extensively in mode-locked lasers with single transverse-mode, whereas there are few studies related to three-dimensional nonlinear dynamics within lasers. Recently, spatiotemporal mode-locking (STML) was proposed in lasers with small modal (i.e., transverse-mode) dispersion, which has been considere

Adel P. Kazemi, Farshad Kazemnejad

The total dominator total coloring of a graph is a total coloring of the graph such that each object of the graph is adjacent or incident to every object of some color class. The minimum namber of the color classes of a total dominator total coloring of a graph is called the total dominator total chromatic number of the graph. Here, we will find the total do

Elena B. Yarovaya, Jordan M. Stoyanov, Konstantin K. Kostyashin

We study the relationship between the well-known Carleman's condition guaranteeing that a probability distribution is uniquely determined by its moments, and a recent easily checkable condition on the rate of growth of the moments. We use asymptotic methods in theory of integrals and involve properties of the Lambert $W$-function to show that the quadratic r

Lucy Linder, Michael Jungo, Jean Hennebert, Claudiu Musat

This paper presents SwissCrawl, the largest Swiss German text corpus to date. Composed of more than half a million sentences, it was generated using a customized web scraping tool that could be applied to other low-resource languages as well. The approach demonstrates how freely available web pages can be used to construct comprehensive text corpora, which a

Pulkit S. Ghoderao, P. Ramadevi

Our familiar Newton's laws allow determination of both position and velocity of any object precisely. Early nineteenth century saw the birth of quantum mechanics where all measurements must obey Heisenberg's uncertainty principle. Basically, we cannot simultaneously measure with precision, both position and momentum of particles in the microscopic atomic wor

Boris Brimkov, Zachary Scherr

The minimum rank of a graph G is the minimum rank over all real symmetric matrices whose off-diagonal sparsity pattern is the same as that of the adjacency matrix of G. In this note we present the first exact algorithm for the minimum rank of an arbitrary graph G. In particular, we use the notion of determinantal rank to transform the minimum rank problem in

Shady Abu Hussein, Tom Tirer, Raja Giryes

The single image super-resolution task is one of the most examined inverse problems in the past decade. In the recent years, Deep Neural Networks (DNNs) have shown superior performance over alternative methods when the acquisition process uses a fixed known downsampling kernel-typically a bicubic kernel. However, several recent works have shown that in pract

Alexandra L. Gregory, Michelle L. M. Collins, Denis Erkal, Erik Tollerud

We present new chemo--kinematics of the Hercules dwarf galaxy based on Keck II-- DEIMOS spectroscopy. Our 21 confirmed members have a systemic velocity of $v_{\mathrm{Herc}}=46.4\pm1.3$ kms$^{-1}$ and a velocity dispersion $\sigma_{v,\mathrm{Herc}}=4.4^{+1.4}_{-1.2}$ kms$^{-1}$. From the strength of the Ca II triplet, we obtain a metallicity of [Fe/H]= $-2.4

Jie Qiao, Zijian Li, Boyan Xu, Ruichu Cai

The challenge of learning disentangled representation has recently attracted much attention and boils down to a competition using a new real world disentanglement dataset (Gondal et al., 2019). Various methods based on variational auto-encoder have been proposed to solve this problem, by enforcing the independence between the representation and modifying the

Muhammet Abdullah Soyturk, Konstantinos Parasyris, Behzad Salami, Osman Unsal

To improve power efficiency, researchers are experimenting with dynamically adjusting the supply voltage of systems below the nominal operating points. However, production systems are typically not allowed to function on voltage settings that is below the reliable limit. Consequently, existing software fault tolerance studies are based on fault models, which

Wei Sun, Xian-Hui Ge

We examine the complexity/volume conjecture and further investigate the possible connections between complexity and partition function. The complexity/volume 2.0 states that the complexity growth rate $\mathcal{\dot{C}}\sim PV$. In the standard statistics, there is a fundamental relation among $PV$, the grand potential $\Omega$ and the partition function $\m

Karthikeya Racharla, Vineet Kumar, Chaudhari Bhushan Jayant, Ankit Khairkar

This work aims to examine one of the cornerstone problems of Musical Instrument Retrieval (MIR), in particular, instrument classification. IRMAS (Instrument recognition in Musical Audio Signals) data set is chosen for this purpose. The data includes musical clips recorded from various sources in the last century, thus having a wide variety of audio quality.

Giuseppina di Blasio, Pier Domenico Lamberti

We study the dependence of the first eigenvalue of the Finsler $p$-Laplacian and the corresponding eigenfunctions upon perturbation of the domain and we generalize a few results known for the standard $p$-Laplacian. In particular, we prove a Frech\'{e}t differentiability result for the eigenvalues, we compute the corresponding Hadamard formulas and we prove

Nicholas R. Beaton, Leo Li, Jonathon Liu, Thomas Wong

We study a model of a semiflexible long chain polymer confined to a two-dimensional slit of width $w$, and interacting with the walls of the slit. The interactions with the walls are controlled by Boltzmann weights $a$ and $b$, and the flexibility of the polymer is controlled by another Boltzmann weight $c$. This is a simple model of the steric stabilisation

Ba Amadou Diadie

In the present work, we provide the asymptotic behavior of the residual-past entropy, of the mean residual-past lifetime distribution and of the residual-past inaccuracy measure. We are interested in these measures of uncertainty in the discrete case. Almost sure rates of convergence and asymptotic normality results are established. Our theoretical results a

Guillaume Tahar

A branched affine structure on a compact topological surface with marked points is a complex affine structure outside the marked points. We give a proof of an unpublished foundational theorem of Veech, stating that any branched affine surface can be decomposed into affine triangles and some annulus-shaped cylinders. Then, we prove that any pair of such decom

C. O. Edet, P. O. Amadi, A. N. Ikot, U. S. Okorie

Analytical solutions of the Schrodinger equation for the generalized trigonometric Poschl Teller potential by using an appropriate approximation to the centrifugal term within the framework of the Functional Analysis Approach have been considered. Using the energy equation obtained, the vibrational partition function was calculated and other relevant thermod

Bin He, Di Zhou, Jinghui Xiao, Xin jiang

Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information. However, traditional methods usually treat a triple as a training unit during the knowledge representation learning (KRL) procedure, neglecting contextualized information of the nodes in knowledge graphs (KGs). We generalize the modeling

Ishaan Lodha, Lakshana Kolur, K. Sree Hari, Honnavalli Prasad

The Internet of Things (IoT) is an exploding market as well as a important focus area for research. Security is a major issue for IoT products and solutions, with several massive problems that are still commonplace in the field. In this paper, we have successfully minimized the risk of data eavesdropping and tampering over the network by securing these commu

Biao Zhang, Peter Wonka

In this paper we propose a new framework for point cloud instance segmentation. Our framework has two steps: an embedding step and a clustering step. In the embedding step, our main contribution is to propose a probabilistic embedding space for point cloud embedding. Specifically, each point is represented as a tri-variate normal distribution. In the cluster

Huangxing Lin, Weihong Zeng, Xinghao Ding, Yue Huang

The performance of a deep neural network is highly dependent on its training, and finding better local optimal solutions is the goal of many optimization algorithms. However, existing optimization algorithms show a preference for descent paths that converge slowly and do not seek to avoid bad local optima. In this work, we propose Learning Rate Dropout (LRD)

Siddhartha Jain

Succinct representations of a graph have been objects of central study in computer science for decades. In this paper, we study the operation called \emph{Distance Preserving Graph Contractions}, which was introduced by Bernstein et al. (ITCS, 2018). This operation gives a minor as a succinct representation of a graph that preserves all the distances of the

Christian Marzahl, Marc Aubreville, Christof A. Bertram, Stefan Gerlach

Modern, state-of-the-art deep learning approaches yield human like performance in numerous object detection and classification tasks. The foundation for their success is the availability of training datasets of substantially high quantity, which are expensive to create, especially in the field of medical imaging. Recently, crowdsourcing has been applied to c

Omid Zabeti

Suppose $X$ is a locally solid vector lattice. In this paper, we introduce the notion "$AM$-property" in $X$ as an extension for $AM$-spaces in the category of all Banach lattices. With the aid of this concept, we characterize spaces in which bounded sets and order bounded sets agree. This, in turn, characterizes conditions under which each class of bounded

Wenzhe Yang

The Bombieri-Dwork conjecture predicts that the differential equations satisfied by $G$-functions come from geometry. In this paper, we will look at special $G$-functions whose differential equations have a special singularity with maximally unipotent monodromy. We will formulate a Gamma conjecture about such $G$-functions, which has close connections with t

Rahul Debnath, Indrajit Maity, Manish Jain, Arindam Ghosh

Twisted van der Waals heterostructures unravel a new platform to study strongly correlated quantum phases. The interlayer coupling in these heterostructures is sensitive to twist angles ($\theta$) and key to controllably tune several exotic properties. Here, we demonstrate a systematic evolution of the interlayer coupling strength with twist angle in bilayer

Haziq Jamil, Wicher Bergsma

This is an overview of the R package iprior, which implements a unified methodology for fitting parametric and nonparametric regression models, including additive models, multilevel models, and models with one or more functional covariates. Based on the principle of maximum entropy, an I-prior is an objective Gaussian process prior for the regression functio

Yannick Wend Kuni Zoetgnande, Geoffroy Cormier, Alain-Jérôme Fougères, Jean-Louis Dillenseger

In the context of a localization and tracking application, we developed a stereo vision system based on cheap low-resolution 80x60 pixels thermal cameras. We proposed a threefold sub-pixel stereo matching framework (called ST for Subpixel Thermal): 1) robust features extraction method based on phase congruency, 2) rough matching of these features in pixel pr

Laurent Condat, Daichi Kitahara, Andrés Contreras, Akira Hirabayashi

Convex nonsmooth optimization problems, whose solutions live in very high dimensional spaces, have become ubiquitous. To solve them, the class of first-order algorithms known as proximal splitting algorithms is particularly adequate: they consist of simple operations, handling the terms in the objective function separately. In this overview, we demystify a s

Surojit Ghosh

The additive structure of the $RO(C_{pq})$-graded Bredon cohomology $S^0$ with coefficients in the constant Mackey functor was computed in \cite{BG19}. Using that computation, the ring structure in the positive degrees has been computed here. Further, we calculate the slices of the spectrum $S^V \wedge H\uZ$ for any representation $V.$

Hirokazu Saito, Xin Zhang

This paper shows the unique solvability of elliptic problems associated with two-phase incompressible flows, which are governed by the two-phase Navier-Stokes equations, in unbounded domains such as the whole space separated by a compact interface and the whole space separated by a non-compact interface. As a by-product of the unique solvability of elliptic

Rafaela Castro, Yania M. Souto, Eduardo Ogasawara, Fabio Porto

Applying machine learning models to meteorological data brings many opportunities to the Geosciences field, such as predicting future weather conditions more accurately. In recent years, modeling meteorological data with deep neural networks has become a relevant area of investigation. These works apply either recurrent neural networks (RNN) or some hybrid a

Ran Liu, Sumudu Hasala Marakkalage, Madhushanka Padmal, Thiruketheeswaran Shaganan

Simultaneous localization and mapping (SLAM) has been extensively researched in past years particularly with regard to range-based or visual-based sensors. Instead of deploying dedicated devices that use visual features, it is more pragmatic to exploit the radio features to achieve this task, due to their ubiquitous nature and the widespread deployment of Wi

Sebastián Domínguez, Nilima Nigam

In this paper we show that Korn's inequality \cite{ref:korn1906} holds for vector fields with a zero normal or tangential trace on a subset (of positive measure) of the boundary of Lipschitz domains. We further show that the validity of this inequality depends on the geometry of this subset of the boundary. We then consider the {\it Jones eigenvalue problem}

K. Sheshadri, A. Chainani

A model of a mixture of spinless fermions and spin-zero hardcore bosons, with filling fractions $\rho_F$ and $\rho_B$, respectively, on a two-dimensional square lattice with {\em composite} hopping $t$ is presented. In this model, hopping swaps the locations of a fermion and a boson at nearest-neighbor sites. When $\rho_F+\rho_B=1$, the fermion hopping ampli

Keith Bonawitz, Fariborz Salehi, Jakub Konečný, Brendan McMahan

Federated Learning enables mobile devices to collaboratively learn a shared inference model while keeping all the training data on a user's device, decoupling the ability to do machine learning from the need to store the data in the cloud. Existing work on federated learning with limited communication demonstrates how random rotation can enable users' model

Jiacheng Zhang, Sayantan Bhattacharya, Pavlos P. Vlachos

A novel uncertainty-based pressure reconstruction method is proposed to evaluate the instantaneous pressure fields from velocity fields measured using particle image velocimetry (PIV) or particle tracking velocimetry (PTV). First, the pressure gradient fields are calculated from velocity fields, while the local and instantaneous pressure gradient uncertainty

Dominik M. Juraschek, Prineha Narang, Nicola A. Spaldin

The magneto-optical and opto-magnetic effects describe the interaction of light with a magnetic medium. The most prominent examples are the Faraday and Cotton-Mouton effects that modify the transmission of light through a medium, and the inverse Faraday and inverse Cotton-Mouton effects that produce effective magnetic fields for the spin in the material. Her

Mutasim Mim

We prove that the Wiener Index $W(G)$ of a Maximal Planar graph $G$ with $n$ vertices satisfies $W(G) \leq \Big{\lfloor} \frac{1}{18}(n^3 + 3n^2) \Big{\rfloor}$ for $3 \leq n \leq 18$.

Md. Hasibur Rahman, Chowdhury Rafeed Rahman, Ruhul Amin, Md. Habibur Rahman Sifat

Question classification (QC) is the primary step of the Question Answering (QA) system. Question Classification (QC) system classifies the questions in particular classes so that Question Answering (QA) System can provide correct answers for the questions. Our system categorizes the factoid type questions asked in natural language after extracting features o

Krzysztof Burdzy, Soumik Pal

We prove the sharp bound for the probability that two experts who have access to different information, represented by different $\sigma$-fields, will give radically different estimates of the probability of an event. This is relevant when one combines predictions from various experts in a common probability space to obtain an aggregated forecast. Our proof

Igor Lima, Josyane Pereira

Let $G$ be a group, define an equivalence relation $\sim$ as below: $$\forall \ g, h \in G, \ g \sim h \Longleftrightarrow |g| = |h|$$ the set of sizes of equivalence classes with respect to this relation is called the same-order type of $G$ and denoted by $\alpha(G)$. And $G$ is said a $\alpha_n$-group if $|\alpha(G)|=n$. Let $\pi(G)$ be the set of prime di

Jihyeon Lee, Sho Arora

Despite their importance in training artificial intelligence systems, large datasets remain challenging to acquire. For example, the ImageNet dataset required fourteen million labels of basic human knowledge, such as whether an image contains a chair. Unfortunately, this knowledge is so simple that it is tedious for human annotators but also tacit enough suc

Jie Ma, Tianyun Tang, Xingxing Yu

For integers $n\ge 0$, an iterated triangulation $Tr(n)$ is defined recursively as follows: $Tr(0)$ is the plane triangulation on three vertices and, for $n\ge 1$, $Tr(n)$ is the plane triangulation obtained from the plane triangulation $Tr(n-1)$ by, for each inner face $F$ of $Tr(n-1)$, adding inside $F$ a new vertex and three edges joining this new vertex

Dominik M. Juraschek, Tomáš Neuman, Johannes Flick, Prineha Narang

Nonlinear interactions between phonon modes govern the behavior of vibrationally highly excited solids and molecules. Here, we demonstrate theoretically that optical cavities can be used to control the redistribution of energy from a highly excited coherent infrared-active phonon state into the other vibrational degrees of freedom of the system. The hybridiz

Yongjun Li, Yue Hao, Kilean Hwang, Robert Rainer

A fast method for dynamic aperture (DA) optimization of storage rings has been developed through the use of reversal integration. While chaotic dynamical systems have exact time-reversal symmetry, numerical forward integration differs from its reversal due to scaled cumulative round-off errors. The difference, intrinsically associated with the Lyapunov expon

Sanchita Basak, Fangzhou Sun, Saptarshi Sengupta, Abhishek Dubey

Bus transit systems are the backbone of public transportation in the United States. An important indicator of the quality of service in such infrastructures is on-time performance at stops, with published transit schedules playing an integral role governing the level of success of the service. However there are relatively few optimization architectures lever

An-Dong Xiong, Xiao-Peng Jin, Wen-Kai Yu, Qing Zhao

Fraunhofer diffraction is a well-known phenomenon achieved with most wavelength even without lens. A single-shot intensity measurement of diffraction is generally considered inadequate to reconstruct the original light field, because the lost phase part is indispensable for reverse transformation. Phase retrieval is usually conducted in two means: priori kno

Matthew Shunshi Zhang, Bradly Stadie

Recent advances in the sparse neural network literature have made it possible to prune many large feed forward and convolutional networks with only a small quantity of data. Yet, these same techniques often falter when applied to the problem of recovering sparse recurrent networks. These failures are quantitative: when pruned with recent techniques, RNNs typ

D. Mandal, D. Sharma, H. Schamel

Numerical simulations recover ultra slow electron holes (EH) of electron-acoustic genre propagating stably well below the ion acoustic speed where the ion response disallows any known pure electron perturbation. The reason of stability of EH at high ion temperature ($T_{i}> T_{e}$) is traced to the loss of neutralizing cold ion response. In a background of c

Jinlong Zhang

The production of $W^\pm$ bosons in longitudinally polarized proton-proton collisions at RHIC provides a direct probe for the spin-flavor structure of the proton through the parity-violating single-spin asymmetry, $A_L$. At STAR, the leptonic decay channel $W \to e\nu$ can be effectively measured with the electromagnetic calorimeters and time projection cham

Ali Al-Aradi, Adolfo Correia, Danilo de Frietas Naiff, Gabriel Jardim

We extend the Deep Galerkin Method (DGM) introduced in Sirignano and Spiliopoulos (2018)} to solve a number of partial differential equations (PDEs) that arise in the context of optimal stochastic control and mean field games. First, we consider PDEs where the function is constrained to be positive and integrate to unity, as is the case with Fokker-Planck eq

Ali Ghanbari

In the context of test case based automated program repair (APR), the research community call the patches that pass all the test cases but fail to actually fix the bug test case overfitted patches. Currently, overfitted patches has to be manually inspected by the users. Being a labor intensive activity that hinders widespread adoption of APR tools, automatic

Anzar Ali, Yogesh Singh

The 3d-metal chromites ACr$_2$O$_4$ where A is a magnetic ion, show the paramagnetic to ferrimagnetic phase transition at T$_C$ while for non-magnetic A-site ion, ACr$_2$O$_4$ show paramagnetic to antiferromagnetic phase transition at T$_N$. In this report, we present the detailed study of magnetic and the magnetocaloric effect (MCE) of the 3d-metal chromite

Ximena Fernández

We introduce a novel combinatorial method to study $Q^{**}$-transformations of group presentations or, equivalently, 3-deformations of CW-complexes of dimension 2. Our procedure is based on a refinement of discrete Morse theory that gives a Whitehead simple homotopy equivalence from a regular CW-complex to the simplified Morse CW-complex, with an explicit de