October 2020 arXiv papers — page 125

François Vernotte, Antoine Baudiquez, Enrico Rubiola

This paper presents a very simple method ensuring the independence of consecutive spectra of the phase or frequency noise of an oscillator. This condition is essential for using cross-spectrum averages.

Sunil Gundapu, Radhika Mamidi

Recent technological advancements in the Internet and Social media usage have resulted in the evolution of faster and efficient platforms of communication. These platforms include visual, textual and speech mediums and have brought a unique social phenomenon called Internet memes. Internet memes are in the form of images with witty, catchy, or sarcastic text

Agnes Lamacz-Keymling, Irwin Yousept

This article examines a linear-quadratic elliptic optimal control problem in which the cost functional and the state equation involve a highly oscillatory periodic coefficient $A^\varepsilon$. The small parameter $\varepsilon>0$ denotes the periodicity length. We propose a high-order effective control problem with constant coefficients that provides an appro

Lucas Ruhstorfer

The Bonnafé-Rouquier equivalence can be seen as a modular analogue of Lusztig's Jordan decomposition for groups of Lie type. In this paper, we show that this equivalence can be lifted to include automorphisms of the finite group of Lie type. Moreover, we prove the existence of a local version of this equivalence which satisfies similar properties.

Xiayang Shi, Vicenţiu D. Rădulescu, Dušan D. Repovš, Qihu Zhang

This paper deals with the existence of multiple solutions for the quasilinear equation $-\mathrm{div}\,\mathbf{A}(x,\nabla u)| u| ^{α(x)-2}u=f(x,u)$ in $ \mathbb{R} ^{N}$, which involves a general variable exponent elliptic operator $\mathbf{ A}$ in divergence form. The problem corresponds to double phase anisotropic phenomena, in the sense that the differen

Konstantin Fackeldey, Mathias Oster, Leon Sallandt, Reinhold Schneider

We consider a stochastic optimal exit time feedback control problem. The Bellman equation is solved approximatively via the Policy Iteration algorithm on a polynomial ansatz space by a sequence of linear equations. As high degree multi-polynomials are needed, the corresponding equations suffer from the curse of dimensionality even in moderate dimensions. We

Jingan Yang, Yang Peng

To construct a robot that can walk as efficiently and steadily as humans or other legged animals, we develop an enhanced elitist-mutated ant colony optimization~(EACO) algorithm with genetic and crossover operators in real-time applications to humanoid robotics or other legged robots. This work presents promoting global search capability and convergence rate

Ya. Yu. Nikitin, E. N. Simarova

U-max statistics were introduced by Lao and Mayer in 2008. Instead of averaging the kernel over all possible subsets of the original sample, they considered the maximum of the kernel. Such statistics are natural in stochastic geometry. Examples are the maximal perimeters and areas of polygons and polyhedra formed by random points on a circle, ellipse, etc. T

Bolin Wei, Yongmin Li, Ge Li, Xin Xia

Code comment generation which aims to automatically generate natural language descriptions for source code, is a crucial task in the field of automatic software development. Traditional comment generation methods use manually-crafted templates or information retrieval (IR) techniques to generate summaries for source code. In recent years, neural network-base

Arthur Capozzi, Gianmarco De Francisci Morales, Yelena Mejova, Corrado Monti

Targeted online advertising is on the forefront of political communication, allowing hyper-local advertising campaigns around elections and issues. In this study, we employ a new resource for political ad monitoring -- Facebook Ads Library -- to examine advertising concerning the issue of immigration in Italy. A crucial topic in Italian politics, it has rece

Hui Zhao, Mohamed-Slim Alouini

In this paper, we investigate the transmission probabilities in three cases (depending only on the legitimate receiver, depending only the eavesdropper, and depending on both legitimate receiver and eavesdropper) in quantum key distribution (QKD) systems over free-space optical links. To be more realistic, we consider a generalized pointing error scenario, w

M. Beaulieu, P. Martinez, L. Abe, C. Gouvret

Future large space- or ground-based telescopes will offer the resolution and sensitivity to probe the habitable zone of a large sample of nearby stars for exo-Earth imaging. To this end, such facilities are expected to be equipped with a high-contrast instrument to efficiently suppress the light from an observed star to image these close-in companions. These

Cédric Colas, Boris Hejblum, Sébastien Rouillon, Rodolphe Thiébaut

Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down, vaccination, etc). Hand-designing such strategies is not trivial because of the number of possible interventions and the difficulty to predict long-term effects. This task can be c

Weitao Song, Xinan Liang, Shiqiang Li, Dongdong Li

Novel display technologies aim at providing the users with increasingly immersive experiences. In this regard, it is a long-sought dream to generate three-dimensional (3D) scenes with high resolution and continuous depth, which can be overlaid with the real world. Current attempts to do so, however, fail in providing either truly 3D information, or a large v

Barnabás Janzer

Given a graph $G$, its orientation covering number $σ(G)$ is the smallest non-negative integer $k$ with the property that we can choose $k$ orientations of $G$ such that whenever $x, y, z$ are vertices of $G$ with $xy,xz\in E(G)$ then there is a chosen orientation in which both $xy$ and $xz$ are oriented away from $x$. Esperet, Gimbel and King showed that $σ

David Castro-Perez, Nobuko Yoshida

This paper presents CAMP, a new static performance analysis framework for message-passing concurrent and distributed systems, based on the theory of multiparty session types (MPST). Understanding the run-time performance of concurrent and distributed systems is of great importance for the identification of bottlenecks and optimisation opportunities. In the m

Rustem Khasanov, Zurab Guguchia, Elvezio Morenzoni, Chris Baines

The magnetic properties of iron-based superconductors $A$Fe$_2$As$_2$ ($A=$K, Cs, and Rb), which are characterized by the V-shaped dependence of the critical temperature ($T_{\rm c}$) on pressure ($P$) were studied by means of the muon spin rotation/relaxation technique. In all three systems studied the magnetism was found to appear for pressures slightly be

Alper Demir

Nanomechanical resonators are used as high performance detectors in a variety of applications such as mass spectrometry and atomic force microscopy. Initial emphasis in nanomechanical resonant sensor research was on increasing the sensitivity to the level of a single molecule, atom and beyond. On the other hand, there are applications where the speed of dete

Wen-Chin Huang, Patrick Lumban Tobing, Yi-Chiao Wu, Kazuhiro Kobayashi

In this paper, we present the voice conversion (VC) systems developed at Nagoya University (NU) for the Voice Conversion Challenge 2020 (VCC2020). We aim to determine the effectiveness of two recent significant technologies in VC: sequence-to-sequence (seq2seq) models and autoregressive (AR) neural vocoders. Two respective systems were developed for the two

Mengjun Ming, Rui Wang, Tao Zhang

This paper contributes to the treatment of extensive constraints in evolutionary many-constraint optimization through consideration of the relationships between pair-wise constraints. In a conflicting relationship, the functional value of one constraint increases as the value in another constraint decreases. In a harmonious relationship, the improvement in o

Shihao Bi, Yan He, Peng Li

We study a non-Hermitian version of XY closed chain with odd number of lattice sites. We consider both anti-ferromagnetic coupling and also a symmetric non-collinear spin coupling. It is found that the energy spectrum is real in certain region of the parameter space. In contrast to previous non-Hermitian models, the ground state is a state with one mode occu

M. Nowak, S. Lacour, A. -M. Lagrange, P. Rubini

Methods used to detect giant exoplanets can be broadly divided into two categories: indirect and direct. Indirect methods are more sensitive to planets with a small orbital period, whereas direct detection is more sensitive to planets orbiting at a large distance from their host star. %, and thus on long orbital period. This dichotomy makes it difficult to c

Yen-Jie chen, Tzonelih Hwang, Chia-Wei Tsai

This paper proposes the first mediated semi-quantum key distribution in randomization-based environment with an untrusted third party(TP) who has the complete quantum capabilities to help two classical users to establish a secure key. The entanglement swapping between the collapsed qubits of Bell states and the Bell states is used to facilitate the design of

Harris Chan, Jamie Kiros, William Chan

A channel corresponds to a viewpoint or transformation of an underlying meaning. A pair of parallel sentences in English and French express the same underlying meaning, but through two separate channels corresponding to their languages. In this work, we present the Multichannel Generative Language Model (MGLM). MGLM is a generative joint distribution model o

Alessandro Fregosi, Carlo Gabbanini, Silvia Gozzini, Lorenzo Lenci

The sensitive detection of either static or radio-frequency \textsc{(rf)} magnetic fields is essential to many fundamental studies and applications. Here, we demonstrate the operation of a cold-atom-based, \textsc{rf} magnetometer in performing {1-D and 2-D imaging} of small metallic objects. It is based on a cold $^{85}$Rb atomic sample, and operates in an

Stephan Walrand, Michel Hesse, François Jamar

Aim: Investigate whether a time walk assessment derived from crystal light sharing and multi-photon time stamps can improved the TOF resolution. Method: Monte Carlo simulations were performed for SiPM (FBK-NUV-HD) coupled to conventional 4x4 mm2 pixelated LSO (0.2%Ca:Ce ) and also coupled to 8x4 mm2 pixelated LSO in which a triangular optical window allows l

Motomi Aoki, Ei Shigematsu, Ryo Ohshima, Syuta Honda

Inplane magnetization reversal of a permalloy/platinum bilayer was detected using the spin rectification effect. Using a sub GHz microwave frequency to excite spin torque ferromagnetic resonance (ST FMR) in the bilayer induces two discrete DC voltages around an external static magnetic field of 0 mT. These discrete voltages depend on the magnetization direct

L. J. Bannenberg, M. Heere, H. Benzidi, J. Montero

The current energy transition imposes a rapid implementation of energy storage systems with high energy density and eminent regeneration and cycling efficiency. Metal hydrides are potential candidates for generalized energy storage, when coupled with fuel cell units and/or batteries. An overview of ongoing research is reported and discussed in this review wo

Annapurni Subramaniam, Sindhu Pandey, Vikrant V. Jadhav, Snehalata Sahu

The blue straggler stars (BSSs) are main-sequence (MS) stars, which have evaded stellar evolution by acquiring mass while on the MS. The detection of extremely low mass (ELM) white dwarf (WD) companions to two BSSs and one yellow straggler star (YSS) from our earlier study using UVIT/ASTROSAT, as well as WD companions to main-sequence stars (known as blue lu

Utkarsh Upadhyay, Graham Lancashire, Christoph Moser, Manuel Gomez-Rodriguez

Machine learning has typically focused on developing models and algorithms that would ultimately replace humans at tasks where intelligence is required. In this work, rather than replacing humans, we focus on unveiling the potential of machine learning to improve how people learn and remember factual material. To this end, we perform a large-scale randomized

Patrick Lumban Tobing, Yi-Chiao Wu, Tomoki Toda

In this paper, we present a description of the baseline system of Voice Conversion Challenge (VCC) 2020 with a cyclic variational autoencoder (CycleVAE) and Parallel WaveGAN (PWG), i.e., CycleVAEPWG. CycleVAE is a nonparallel VAE-based voice conversion that utilizes converted acoustic features to consider cyclically reconstructed spectra during optimization.

Yicheng Wu, Chengwei Pan, Shuqi Wang, Ming Zhang

Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases. Although being extensively studied, segmentation of blood vessels, particularly thin vessels and capillaries, remains challenging mainly due to the lack of an effective interaction between local and

Keondo Park, Wonyoung Jang, Woochul Lee, Kisung Nam

After the COVID-19 outbreak, it has become important to automatically detect whether people are wearing masks in order to reduce risk of front-line workers. In addition, processing user data locally is a great way to address both privacy and network bandwidth issues. In this paper, we present a light-weighted model for detecting whether people in a particula

Jan-Phillip Bäcker, Matthias Röger, Dmitri Kuzmin

We consider a Gierer-Meinhardt system on a surface coupled with a parabolic PDE in the bulk, the domain confined by this surface. Such a model was recently proposed and analyzed for two-dimensional bulk domains by Gomez, Ward and Wei (SIAM J. Appl. Dyn. Syst. 18, 2019). We prove the well-posedness of the bulk-surface system in arbitrary space dimensions and

Sebastian R. van der Voort, Fatih Incekara, Maarten M. J. Wijnenga, Georgios Kapsas

Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is a time-consuming task. Leveraging the latest GPU capabilities, we developed a single multi-task convolutional neural network that uses the full 3D, structural, pre-operative MRI scans to can predict t

C. Klein, Johannes Sjöstrand, N. Stoilov

In a previous work on the large $|k|$ behavior of complex geometric optics solutions to a system of d-bar equations, we treated in detail the situation when a certain potential is the characteristic function of a strictly convex set with real-analytic boundary. We here extend the results to the case of sets with smooth boundary, by using almost holomorphic f

Yu-Hao Deng

Metal halide perovskites have recently emerged as promising materials for the next generation of optoelectronic devices owing to their remarkable intrinsic properties. In the growth of perovskite crystals, the substrates are essential and play a vital role. Herein, substrate engineering in the growth of perovskite crystals have been reviewed. Particularly, v

Jia-Yi Chang, Yan-Feng Lu, Ya-Jun Liu, Bo Zhou

Remote tiny face detection applied in unmanned system is a challeng-ing work. The detector cannot obtain sufficient context semantic information due to the relatively long distance. The received poor fine-grained features make the face detection less accurate and robust. To solve the problem of long-distance detection of tiny faces, we propose an enhanced ne

Alfonso Emilio Gerevini, Roberto Maroldi, Matteo Olivato, Luca Putelli

AI and Machine Learning can offer powerful tools to help in the fight against Covid-19. In this paper we present a study and a concrete tool based on machine learning to predict the prognosis of hospitalised patients with Covid-19. In particular we address the task of predicting the risk of death of a patient at different times of the hospitalisation, on the

J. Cernicharo, N. Marcelino, M. Agundez, Y. Endo

Using the Yebes 40m and IRAM 30m radio telescopes, we detected a series of harmonically related lines with a rotational constant B0=4460.590 +/- 0.001 MHz and a distortion constant D0=0.511 +/- 0.005 kHz towards the cold dense core TMC-1. High-level-of-theory ab initio calculations indicate that the best possible candidate is protonated tricarbon monoxide, H

Bangbang Ren, Ying Han

Many network applications, especially the multimedia applications, often deliver flows with high QoS, like end-to-end delay constraint. Flows of these applications usually need to traverse a series of different network functions orderly before reaching to the host in the customer end, which is called the service function chain (SFC). The emergence of network

Kaushik Das, Qianni Zhang

Since the beginning of this decade, CNN has been a very successful tool in the field of Computer Vision tasks.The invention of CNN was inspired from neuroscience and it shares a lot of anatomical similarities with our visual system.Inspired by the anatomyof humanvisual system, wearguethat the existing U-Net architecture can be improvedin many ways. As human

Guixiang Ma, Yao Xiao, Theodore L. Willke, Nesreen K. Ahmed

High-level applications, such as machine learning, are evolving from simple models based on multilayer perceptrons for simple image recognition to much deeper and more complex neural networks for self-driving vehicle control systems.The rapid increase in the consumption of memory and computational resources by these models demands the use of multi-core paral

Yao Li, Xianggang Yu, Xiaoguang Han, Nianjuan Jiang

In this work, we propose an interactive system to design diverse high-quality garment images from fashion sketches and the texture information. The major challenge behind this system is to generate high-quality and detailed texture according to the user-provided texture information. Prior works mainly use the texture patch representation and try to map a sma

Xiangpeng Wei, Heng Yu, Yue Hu, Rongxiang Weng

As a sequence-to-sequence generation task, neural machine translation (NMT) naturally contains intrinsic uncertainty, where a single sentence in one language has multiple valid counterparts in the other. However, the dominant methods for NMT only observe one of them from the parallel corpora for the model training but have to deal with adequate variations un

J. Kolorenc, K. Kvashnina

We investigate the origin of satellite features that appear in the high-resolution x-ray absorption spectra measured at the uranium M 4 edge in compounds where the uranium atoms are in the U 6+ oxidation state. We employ a material-specific Anderson impurity model derived from the electronic structure obtained by the density-functional theory.

Stefano Biagi, Francesco Esposito, Eugenio Vecchi

We consider positive singular solutions of PDEs arising from double phase functionals. Exploiting a rather new version of the moving plane method originally developed by Sciunzi, we prove symmetry and monotonicity properties of such solutions.

Rui Wang, Xiaojun Yuan

To address the coverage and capacity challenges in fifth-generation (5G) wireless networks, the relay technique has been considered as a promising solution and recently attracted great attentions from academia. The multiway relay channel (mRC), which serves as a fundamental building block of a relay network, defines the family of all possible information-flo

Haikun Liu, Di Chen, Hai Jin, Xiaofei Liao

Non-Volatile Main Memories (NVMMs) have recently emerged as promising technologies for future memory systems. Generally, NVMMs have many desirable properties such as high density, byte-addressability, non-volatility, low cost, and energy efficiency, at the expense of high write latency, high write power consumption and limited write endurance. NVMMs have bec

Miquel Noguer i Alonso, Sonam Srivastava

Reinforcement learning is a machine learning approach concerned with solving dynamic optimization problems in an almost model-free way by maximizing a reward function in state and action spaces. This property makes it an exciting area of research for financial problems. Asset allocation, where the goal is to obtain the weights of the assets that maximize the

Wen-Zhao Zhang, Xian-Ting Liang, Jiong Cheng, Ling Zhou

To investigate the dynamical behavior of a quantum system embedded in a memory environment, it is crucial to obtain the knowledge of the reservoir spectral density. However, such knowledge is usually based on a priori assumptions about the environment. In this paper, we put forward a method to obtain key information about the reservoir spectral density of an

Mehdi Benallegue, Rafael Cisneros, Abdelaziz Benallegue, Yacine Chitour

In this paper, we present an observation scheme, with proven Lyapunov stability, for estimating a humanoid's floating base orientation. The idea is to use velocity aided attitude estimation, which requires to know the velocity of the system. This velocity can be obtained by taking into account the kinematic data provided by contact information with the e

Quentin Bramas, Anissa Lamani, Sébastien Tixeuil

We consider two mobile oblivious robots that evolve in a continuous Euclidean space. We require the two robots to solve the rendezvous problem (meeting in finite time at the same location, not known beforehand) despite the possibility that one of those robots crashes unpredictably. The rendezvous is stand up indulgent in the sense that when a crash occurs, t

Ke Yang, Ning-Hua Tong

Using the recently developed exact numerical renormalization group (NRG) method, we analyse the NRG truncation errors $δχ$ of the local magnetic susceptibility and $δF$ of the free energy for the spin-boson model (SBM). We find that for temperatures higher than a crossover temperature $T_{cr}$, as the number of kept states $M$ increases, both errors have osc

Clement Papadacci, V. Finel, O. Villemain, M. Tanter

The objectives were to develop a novel three-dimensional technology for imaging naturally occurring shear wave (SW) propagation, demonstrate feasibility on human volunteers and quantify SW velocity in different propagation directions. Imaging of natural SWs generated by valve closures has emerged to obtain a direct measurement of cardiac stiffness. Recently,

Sunil Gundapu, Radhika Mamidi

The phenomenon of mixing the vocabulary and syntax of multiple languages within the same utterance is called Code-Mixing. This is more evident in multilingual societies. In this paper, we have developed a system for SemEval 2020: Task 9 on Sentiment Analysis for Code-Mixed Social Media Text. Our system first generates two types of embeddings for the social m

Qianqian Hou

This paper is concerned with the diffusion limit (as $\va\rightarrow 0$) of radial solutions to a chemotaxis system with logarithmic singular sensitivity in a bounded interval with mixed Dirichlet and Robin boundary conditions. We use a Cole-Hopf type transformation to resolve the logarithmic singularity and prove that the solution of the transformed system

Li Wang, Jiaqun Wei, Haicheng Zhang

Let $\mathcal{X}$ be a semibrick in an extriangulated category $\mathscr{C}$. Let $\mathcal{T}$ be the filtration subcategory generated by $\mathcal{X}$. We give a one-to-one correspondence between simple semibricks and length wide subcategories in $\mathscr{C}$. This generalizes a bijection given by Ringel in module categories, which has been generalized by

Fangyuan Zhao, Xuebin Ren, Shusen Yang, Qing Han

Latent Dirichlet Allocation (LDA) is a popular topic modeling technique for hidden semantic discovery of text data and serves as a fundamental tool for text analysis in various applications. However, the LDA model as well as the training process of LDA may expose the text information in the training data, thus bringing significant privacy concerns. To addres

Marlini Simoes, Emilio Martínez-Pañeda

We present a new phase field framework for modelling fracture and fatigue in Shape Memory Alloys (SMAs). The constitutive model captures the superelastic behaviour of SMAs and damage is driven by the elastic and transformation strain energy densities. We consider both the assumption of a constant fracture energy and the case of a fracture energy dependent on

Nicolas Privault, Grzegorz Serafin

We derive Berry-Esseen approximation bounds for general functionals of independent random variables, based on chaos expansions methods. Our results apply to $U$-statistics satisfying the weak assumption of decomposability in the Hoeffding sense, and yield Kolmogorov distance bounds instead of the Wasserstein bounds previously derived in the special case of d

Chandni Menapara, Zalak Shah, Ajay Kumar Rai

The resonance state of $Δ$ baryon existing in four isospin ($I=\frac{3}{2}$) states, has been studied using Hypercentral Constituent Quark Model (hCQM) with a simple linear potential with added first order correction. The calculated data range for 1S-5S, 1P-5P, 1D-4D and 1F-2F with possible spin-parity assignments of all the states. The magnetic moments have

Pengpeng Liu, Xintong Han, Michael Lyu, Irwin King

We present a self-supervised learning approach to learning monocular 3D face reconstruction with a pose guidance network (PGN). First, we unveil the bottleneck of pose estimation in prior parametric 3D face learning methods, and propose to utilize 3D face landmarks for estimating pose parameters. With our specially designed PGN, our model can learn from both

Yan Zhang, Zhijiang Guo, Zhiyang Teng, Wei Lu

AMR-to-text generation is used to transduce Abstract Meaning Representation structures (AMR) into text. A key challenge in this task is to efficiently learn effective graph representations. Previously, Graph Convolution Networks (GCNs) were used to encode input AMRs, however, vanilla GCNs are not able to capture non-local information and additionally, they f

Jiaxin Zhao, Rui Su, Antonio Fieramosca, Weijie Zhao

Atomically thin transition metal dichalcogenides possess valley dependent functionalities that are usually available only at crogenic temperatures, constrained by various valley depolarization scatterings. The formation of exciton polaritons by coherently superimposing excitons and microcavity photons potentially harnesses the valley polarized polariton pola

Shuhao Gu, Jinchao Zhang, Fandong Meng, Yang Feng

There exists a token imbalance phenomenon in natural language as different tokens appear with different frequencies, which leads to different learning difficulties for tokens in Neural Machine Translation (NMT). The vanilla NMT model usually adopts trivial equal-weighted objectives for target tokens with different frequencies and tends to generate more high-

Ryosuke Kohita, Akifumi Wachi, Yang Zhao, Ryuki Tachibana

Unsupervised methods are promising for abstractive text summarization in that the parallel corpora is not required. However, their performance is still far from being satisfied, therefore research on promising solutions is on-going. In this paper, we propose a new approach based on Q-learning with an edit-based summarization. The method combines two key modu

Sabrina H. Streipert, Gail S. K. Wolkowicz

We propose an alternative delayed population growth difference equation model based on a modification of the Beverton-Holt recurrence, assuming a delay only in the growth contribution that takes into account that those individuals that die during the delay, do not contribute to growth. The model introduced differs from existing delay difference equations in

Sarah Masud, Subhabrata Dutta, Sakshi Makkar, Chhavi Jain

Online hate speech, particularly over microblogging platforms like Twitter, has emerged as arguably the most severe issue of the past decade. Several countries have reported a steep rise in hate crimes infuriated by malicious hate campaigns. While the detection of hate speech is one of the emerging research areas, the generation and spread of topic-dependent

George C. Alexandropoulos, Sumudu Samarakoon, Mehdi Bennis, Merouane Debbah

Reconfigurable Intelligent Surfaces (RISs) are recently gaining remarkable attention as a low-cost, hardware-efficient, and highly scalable technology capable of offering dynamic control of electro-magnetic wave propagation. Their envisioned dense deployment over various obstacles of the, otherwise passive, wireless communication environment has been conside

Brian Lester

Many tasks in natural language processing, such as named entity recognition and slot-filling, involve identifying and labeling specific spans of text. In order to leverage common models, these tasks are often recast as sequence labeling tasks. Each token is given a label and these labels are prefixed with special tokens such as B- or I-. After a model assign

Zhengxuan Wu, Desmond C. Ong

Grounding language in contextual information is crucial for fine-grained natural language understanding. One important task that involves grounding contextual modifiers is color generation. Given a reference color "green", and a modifier "bluey", how does one generate a color that could represent "bluey green"? We propose a computatio

Tetsuya Ito

We show that a knot whose minimum crossing number $c(K)$ is even and greater than $30$ is not fertile; there exists a knot $K'$ with crossing number less than $c$ such that $K'$ is not obtained from a minimum crossing number diagram of $K$ by suitably changing the over-under information.

Ramgopal Venkateswaran, Ryan O'Donnell

Approximate Counting refers to the problem where we are given query access to a function $f : [N] \to \{0,1\}$, and we wish to estimate $K = #\{x : f(x) = 1\}$ to within a factor of $1+ε$ (with high probability), while minimizing the number of queries. In the quantum setting, Approximate Counting can be done with $O\left(\min\left(\sqrt{N/ε}, \sqrt{N/K}/ε\ri

Ren Monma, Tufan Roy, Kazuya Suzuki, Tomoki Tsuchiya

MgO-barrier magnetic tunnel junctions with half-metallic Heusler alloy electrodes attracted much attentions for spintronics applications. However, a couples of issues related to materials still remain to be resolved for practical uses. Recently, quarterly equiatomic Heusler alloys attracted attentions as advanced Heusler alloys. CoIrMnZ (Z = Al, Si, Ga, and

Sadegh Aliakbarian

Video anticipation is the task of predicting one/multiple future representation(s) given limited, partial observation. This is a challenging task due to the fact that given limited observation, the future representation can be highly ambiguous. Based on the nature of the task, video anticipation can be considered from two viewpoints: the level of details and

Jianing Qian, Junyu Nan, Siddharth Ancha, Brian Okorn

Current state-of-the-art trackers often fail due to distractorsand large object appearance changes. In this work, we explore the use ofdense optical flow to improve tracking robustness. Our main insight is that, because flow estimation can also have errors, we need to incorporate an estimate of flow uncertainty for robust tracking. We present a novel trackin

Honglu Zhou, Hareesh Ravi, Carlos M. Muniz, Vahid Azizi

Software development is becoming increasingly open and collaborative with the advent of platforms such as GitHub. Given its crucial role, there is a need to better understand and model the dynamics of GitHub as a social platform. Previous work has mostly considered the dynamics of traditional social networking sites like Twitter and Facebook. We propose GitE

Zhou Fang, Tianren Yang, Ying Jin

In countries experiencing unprecedented waves of urbanization, there is a need for rapid and high quality urban street design. Our study presents a novel deep learning powered approach, DeepStreet (DS), for automatic street network generation that can be applied to the urban street design with local characteristics. DS is driven by a Convolutional Neural Net

Vamsi K. Amalladinne, Asit Kumar Pradhan, Cynthia Rush, Jean-Francois Chamberland

Sparse regression codes with approximate message passing (AMP) decoding have gained much attention in recent times. The concepts underlying this coding scheme extend to unsourced random access with coded compressed sensing (CCS), as first demonstrated by Fengler, Jung, and Caire. Specifically, their approach employs a concatenated coding framework with an in

Brian Lester, Daniel Pressel, Amy Hemmeter, Sagnik Ray Choudhury

Current state-of-the-art models for named entity recognition (NER) are neural models with a conditional random field (CRF) as the final layer. Entities are represented as per-token labels with a special structure in order to decode them into spans. Current work eschews prior knowledge of how the span encoding scheme works and relies on the CRF learning which

Tomoharu Iwata, Yusuke Tanaka

We propose a few-shot learning method for spatial regression. Although Gaussian processes (GPs) have been successfully used for spatial regression, they require many observations in the target task to achieve a high predictive performance. Our model is trained using spatial datasets on various attributes in various regions, and predicts values on unseen attr

Finn Larsen, and Shruti Paranjape

We develop the thermodynamics of black holes in AdS$_4$ and AdS$_7$ near their BPS limit. In each setting we study the two distinct deformations orthogonal to the BPS surface as well as their nontrivial interplay with each other and with BPS properties. Our results illuminate recent microscopic calculations of the BPS entropy. We show that these microscopic

Sam Evens, Yu Li

For a semisimple algebraic group $G$ of adjoint type with Lie algebra $\mathfrak g$ over the complex numbers, we establish a bijection between the set of closed orbits of the group $G \ltimes \mathfrak g^{\ast}$ acting on the variety of Lagrangian subalgebras of $\mathfrak g \ltimes \mathfrak g^{\ast}$ and the set of abelian ideals of a fixed Borel subalgebr

Huatang Tan, Jie Li

We propose a deterministic scheme for establishing hybrid Einstein-Podolsky-Rosen (EPR) entanglement channel between a macroscopic mechanical oscillator and a magnon mode in a distant yttrium-iron-garnet (YIG) sphere across about ten gigahertz of frequency difference. The system consists of a driven electromechanical cavity which is unidirectionally coupled

Jin Cao, Jun Wang, Wael Hamza, Kelly Vanee

Neural models have yielded state-of-the-art results in deciphering spoken language understanding (SLU) problems; however, these models require a significant amount of domain-specific labeled examples for training, which is prohibitively expensive. While pre-trained language models like BERT have been shown to capture a massive amount of knowledge by learning

Jiuyi Zhu

We study the sharp doubling inequalities for the gradients and upper bounds for the critical sets of Dirichlet eigenfunctions on the boundary and in the interior of compact Riemannian manifolds. Most efforts are devoted to obtaining the sharp doubling inequalities for the gradients. New technique is developed to overcome the difficulties on the unavailabilit

Hui Xu, Liyao Xiang, Youmin Le, Xiaoying Gan

Graph matching pairs corresponding nodes across two or more graphs. The problem is difficult as it is hard to capture the structural similarity across graphs, especially on large graphs. We propose to incorporate high-order information for matching large-scale graphs. Iterated line graphs are introduced for the first time to describe such high-order informat

M Z Anis

In a recent paper, Mazucheli et al. (2019) introduced the unit-Gompertz (UG) distribution and studied some of its properties. In a complementary work, Anis and De (2020) corrected some of the subtle errors in the original paper and studied some other interesting properties of this new distribution. However, to the best of our knowledge no charcterization res

Andrea Madotto, Etsuko Ishii, Zhaojiang Lin, Sumanth Dathathri

There has been considerable progress made towards conversational models that generate coherent and fluent responses; however, this often involves training large language models on large dialogue datasets, such as Reddit. These large conversational models provide little control over the generated responses, and this control is further limited in the absence o

Styfen Schär, Gabriele Albertini, David S. Kammer

The onset of frictional motion is mediated by the dynamic propagation of a rupture front, analogous to a shear crack. The rupture front nucleates quasi-statically in a localized region of the frictional interface and slowly increases in size. When it reaches a critical nucleation length it becomes unstable, propagates dynamically and eventually breaks the en

Junsen Wang, Wei Zheng, Youjin Deng

Bogoliubov excitations of Bose-Einstein condensates in optical lattices may possess band topology in analogous to topological insulators in class AII of fermions. Using the language of the Krein-space theory, this topological property is shown to be protected by a pseudo-time-reversal symmetry that is pseudo-antiunitary and squares to $-1$, with the associat

Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna

We explore learning pixelwise correspondences between images of deformable objects in different configurations. Traditional correspondence matching approaches such as SIFT, SURF, and ORB can fail to provide sufficient contextual information for fine-grained manipulation. We propose Multi-Modal Gaussian Shape Descriptor (MMGSD), a new visual representation of

Min Fu, Gang Luo, Xi Zheng, Tianyi Zhang

Code clone is a serious problem in software and has the potential to software defects, maintenance overhead, and licensing violations. Therefore, clone detection is important for reducing maintenance effort and improving code quality during software evolution. A variety of clone detection techniques have been proposed to identify similar code in software. Ho

Priyanshu Kumar, Aadarsh Singh

We experiment with COVID-Twitter-BERT and RoBERTa models to identify informative COVID-19 tweets. We further experiment with adversarial training to make our models robust. The ensemble of COVID-Twitter-BERT and RoBERTa obtains a F1-score of 0.9096 (on the positive class) on the test data of WNUT-2020 Task 2 and ranks 1st on the leaderboard. The ensemble of

Lyle Noakes, Luchezar Stoyanov

A construction is given for the recovery of a disjoint union of strictly convex smooth planar obstacles from travelling-time information. The obstacles are required to be such that no Euclidean line meets more than two of them.

Hüseyin Acan, Sankardeep Chakraborty, Seungbum Jo, Kei Nakashima

We consider the problem of designing succinct navigational oracles, i.e., succinct data structures supporting basic navigational queries such as degree, adjacency, and neighborhood efficiently for intersection graphs on a circle, which include graph classes such as {\it circle graphs}, {\it $k$-polygon-circle graphs}, {\it circle-trapezoid graphs}, {\it trap

Takumi Ito, Tatsuki Kuribayashi, Masatoshi Hidaka, Jun Suzuki

Despite the current diversity and inclusion initiatives in the academic community, researchers with a non-native command of English still face significant obstacles when writing papers in English. This paper presents the Langsmith editor, which assists inexperienced, non-native researchers to write English papers, especially in the natural language processin

Keyu Zhu, Pascal Van Hentenryck, Ferdinando Fioretto

Post-processing immunity is a fundamental property of differential privacy: it enables the application of arbitrary data-independent transformations to the results of differentially private outputs without affecting their privacy guarantees. When query outputs must satisfy domain constraints, post-processing can be used to project the privacy-preserving outp

Richmond Addo Danquah

For several years till date, the major issues in terms of solving for classification problems are the issues of Imbalanced data. Because majority of the machine learning algorithms by default assumes all data are balanced, the algorithms do not take into consideration the distribution of the data sample class. The results tend to be unsatisfactory and skewed