December 2020 arXiv papers — page 66

Paolo Falbo, Giorgio Ferrari, Giorgio Rizzini, Maren Diane Schmeck

In this paper we propose and solve a real options model for the optimal adoption of an electric vehicle. A policymaker promotes the abeyance of fossil-fueled vehicles through an incentive, and the representative fossil-fueled vehicle's owner decides the time at which buying an electric vehicle, while minimizing a certain expected cost. This involves a combin

Johann Langemets, Katriin Pirk

We prove that the diametral diameter two properties are inherited by $F$-ideals (e.g., $M$-ideals). On the other hand, these properties are lifted from an $M$-ideal to the superspace under strong geometric assumptions. We also show that all of the diametral diameter two properties are stable under the formation of corresponding K\"othe-Bochner spaces (e.g.,

Quan Quan, Qiyuan Wang, Liu Li, Yuanqi Du

While medical images such as computed tomography (CT) are stored in DICOM format in hospital PACS, it is still quite routine in many countries to print a film as a transferable medium for the purposes of self-storage and secondary consultation. Also, with the ubiquitousness of mobile phone cameras, it is quite common to take pictures of the CT films, which u

Mattia Fogagnolo, Lorenzo Mazzieri

The notion of strictly outward minimising hull is investigated for open sets of finite perimeter sitting inside a complete noncompact Riemannian manifold. Under natural geometric assumptions on the ambient manifold, the strictly outward minimising hull $\Omega^*$ of a set $\Omega$ is characterised as a maximal volume solution of the least area problem with o

Igor V. Minin, Oleg V. Minin, Yinghui Cao, Bing Yan

We show that electric field on the plane surface of truncated sphere or cylinders (so called Janus particles) have sharp resonances versus the depth of removed segment of a sphere or cylinder. These resonances are related to the excited whispering gallery waves caused by truncation. It is a new mechanism of the field localization. Optimization of this effect

Tomás Ramos, Juan José García-Ripoll, Diego Porras

We present a topological approach to the input-output relations of photonic driven-dissipative lattices acting as directional amplifiers. Our theory relies on a mapping from the optical non-Hermitian coupling matrix to an effective topological insulator Hamiltonian. This mapping is based on the singular value decomposition of non-Hermitian coupling matrices,

S. Jahan, M. N. Haque, N. A. Chowdhury, A. Mannan

The modulational instability (MI) of ion-acoustic (IA) waves (IAWs) and associated IA rogue waves (IARWs) in double pair plasma containing non-extensive electrons, iso-thermal positrons, negatively and positively charged ions have been governed by the standard nonlinear Schr\"{o}dinger equation (NLSE). It has been figured out from the numerical study of NLSE

Kevin Denamganaï, James Alfred Walker

Natural languages are powerful tools wielded by human beings to communicate information and co-operate towards common goals. Their values lie in some main properties like compositionality, hierarchy and recurrent syntax, which computational linguists have been researching the emergence of in artificial languages induced by language games. Only relatively rec

Costanza Conti, Sergio Lopez-Urena, Lucia Romani

We investigate properties of differential and difference operators annihilating certain finite-dimensional subspaces of exponential functions in two variables that are connected to the representation of real-valued trigonometric and hyperbolic functions. Although exponential functions appear in a variety of contexts, the motivation behind this work comes fro

Danny Nam, Allan Sly, Lingfu Zhang

We study the ferromagnetic Ising model on the infinite $d$-regular tree under the free boundary condition. This model is known to be a factor of IID in the uniqueness regime, when the inverse temperature $\beta\ge 0$ satisfies $\tanh \beta \le (d-1)^{-1}$. However, in the reconstruction regime ($\tanh \beta > (d-1)^{-\frac{1}{2}}$), it is not a factor of IID

Hector Gisbert

Using Chiral Perturbation Theory to properly account for the dynamics of nonleptonic $K\to 2\,\pi$ decays, we found the Standard Model prediction for the CP violating ratio $\mbox{Re}\left(\varepsilon'/\varepsilon\right)=\left(14\pm 5\right) \times 10^{-4}$, where isospin breaking effects are included, in perfect agreement with the current experimental world

Xiaobo Hou, Xueting Tian, Yiwei Zhang

Pfister and Sullivan proved that if a topological dynamical system $(X,T)$ satisfies almost product property and uniform separation property, then for each nonempty compact %convex subset $K$ of invariant measures, the entropy of saturated set $G_{K}$ satisfies \begin{equation}\label{Bowen's topological entropy} h_{top}^{B}(T,G_{K})=\inf\{h(T,\mu):\mu\in K\}

Zhanhao Liu, Marion Perrodin, Thomas Chambrion, Radu Stoica

1D Total Variation (TV) denoising, considering the data fidelity and the Total Variation (TV) regularization, proposes a good restored signal preserving shape edges. The main issue is how to choose the weight $\lambda$ balancing those two terms. In practice, this parameter is selected by assessing a list of candidates (e.g. cross validation), which is inappr

Thomas Le Reun, Duncan R. Hewitt

We present a numerical study of convection in a horizontal layer comprising a fluid-saturated porous bed overlain by an unconfined fluid layer. Convection is driven by a vertical, destabilising temperature difference applied across the whole system, as in the canonical Rayleigh-B\'enard problem. Numerical simulations are carried out using a single-domain for

Kazuki Sone, Yuto Ashida, Takahiro Sagawa

Synchronization of coupled oscillators is a ubiquitous phenomenon found throughout nature. Its robust realization is crucial to our understanding of various nonlinear systems, ranging from biological functions to electrical engineering. On another front, in condensed matter physics, topology is utilized to realize robust properties like topological edge mode

Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner, Shahin Amiriparian

COVID-19 is a global health crisis that has been affecting many aspects of our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity continuum. A considerable proportion of symptoms are related to pathological changes in the vocal system, leading to the assumption that COVID-19 may also affect voice production.

Abel Torres Montoya

Despite significant achievements and current interest in machine learning and artificial intelligence, the quest for a theory of intelligence, allowing general and efficient problem solving, has done little progress. This work tries to contribute in this direction by proposing a novel framework of intelligence based on three principles. First, the generative

Albert Atserias, Ilario Bonacina, Susanna F. de Rezende, Massimo Lauria

We prove that for $k \ll \sqrt[4]{n}$ regular resolution requires length $n^{\Omega(k)}$ to establish that an Erd\H{o}s-R\'enyi graph with appropriately chosen edge density does not contain a $k$-clique. This lower bound is optimal up to the multiplicative constant in the exponent, and also implies unconditional $n^{\Omega(k)}$ lower bounds on running time f

Magnús M. Halldórsson, Murilo S. de Lima

We study the problem of sorting under incomplete information, when queries are used to resolve uncertainties. Each of $n$ data items has an unknown value, which is known to lie in a given interval. We can pay a query cost to learn the actual value, and we may allow an error threshold in the sorting. The goal is to find a nearly-sorted permutation by performi

Ki-Young Choi, Eung Jin Chun, Jongkuk Kim

We analyze the dispersion relations of Weyl or Majorana, and Dirac neutrinos in a complex scalar medium which interacts with the neutrinos through Yukawa couplings. They are solved by perturbative calculation in various limits representing different physical situations, some of which allow the medium-induced neutrino oscillation to occur. Remarkably, peculia

Debashish Mukherji, Manjesh Kumar Singh

Tuning the heat flow is fundamentally important for the design of advanced functional materials. Here, polymers are of particular importance because they provide different pathways for the energy transfer. More specifically, the heat flow between two covalently bonded monomers is over 100 times faster than between the two non-bonded monomers interacting via

Kelvin Shak, Mundher Al-Shabi, Andrea Liew, Boon Leong Lan

Background and Objective: Early detection of lung cancer is crucial as it has high mortality rate with patients commonly present with the disease at stage 3 and above. There are only relatively few methods that simultaneously detect and classify nodules from computed tomography (CT) scans. Furthermore, very few studies have used semi-supervised learning for

Ya-Fei Guo, Gao-Chan Yong

Based on the relativistic transport model ART with the hadronic equation of state extended to have a phase transition via the use of the MIT bag model, properties of phase transition of dense nuclear matter formed in relativistic heavy-ion collisions are investigated. Proton sideward and directed flows are calculated with different equation of states in Au +

A. Bharucha, G. Cacciapaglia, A. Deandrea, N. Gaur

The next generation electron-positron colliders are designed for precision studies of the Standard Model and its extensions, in particular in the Higgs sector. We consider the potential for discovery of composite Higgs models in Higgs pair production through photon collisions. This process is loop-generated, thus it provides access to all Higgs couplings and

Benjamin Zanger, Christian B. Mendl, Martin Schulz, Martin Schreiber

Identifying computational tasks suitable for (future) quantum computers is an active field of research. Here we explore utilizing quantum computers for the purpose of solving differential equations. We consider two approaches: (i) basis encoding and fixed-point arithmetic on a digital quantum computer, and (ii) representing and solving high-order Runge-Kutta

Mark S. Williamson, Chad W. Thackeray, Peter M. Cox, Alex Hall

Despite major advances in climate science over the last 30 years, persistent uncertainties in projections of future climate change remain. Climate projections are produced with increasingly complex models which attempt to represent key processes in the Earth system, including atmospheric and oceanic circulations, convection, clouds, snow, sea-ice, vegetation

A. Gorsky, D. Pavshinkin, A. Tyutyakina

We consider the $T\bar T$ deformation of 2d large $N$ YM theory on a cylinder, sphere and disk. The collective field theory Hamiltonian for the deformed theory is derived and the particular solutions to the equations of motion of the collective theory are found for the sphere. The account of the non-perturbative branch of the solution amounts to the first-or

Minglun Han, Linhao Dong, Shiyu Zhou, Bo Xu

End-to-end (E2E) models have achieved promising results on multiple speech recognition benchmarks, and shown the potential to become the mainstream. However, the unified structure and the E2E training hamper injecting contextual information into them for contextual biasing. Though contextual LAS (CLAS) gives an excellent all-neural solution, the degree of bi

Vassilis. E. Lembessis, Koray Koksal, Jun Yuan, Mohamed Babiker

We consider the optical dipole potential energy, which arises from the interaction of a two-level atom with a circularly polarized Laguerre-Gaussian laser beam of small waist. The beam is characterized by the existence of a longitudinal electric field component which is responsible for the appearance of a chiral term in the optical dipole potential energy. T

Jozsef Beck, William Chen

Given any rectangular polyhedron 3-manifold $P$ tiled with unit cubes, we find infinitely many explicit directions related to cubic algebraic numbers such that all half-infinite geodesics in these directions are uniformly distributed in $P$.

Sumeru Hazra, Anirban Bhattacharjee, Madhavi Chand, Kishor V. Salunkhe

Qubit coherence and gate fidelity are typically considered the two most important metrics for characterizing a quantum processor. An equally important metric is inter-qubit connectivity as it minimizes gate count and allows implementing algorithms efficiently with reduced error. However, inter-qubit connectivity in superconducting processors tends to be limi

Chiara Arina

Whilst the need for dark matter was established almost a century ago, only its gravitational interaction has been confirmed so far, allowing for plethora of models for dark matter. The Weakly Interacting Massive Particles (WIMPs) category has received by far the biggest attention, however despite the enormous experimental efforts, these particles remain elus

Andrea Giudici, John S. Biggins

A cylindrical rubber fibre subject to twist will also elongate: a manifestation of Poynting's effect in large strain elasticity. Here, we construct an analogous treatment for an active rubber fibre actuated via an axisymmetric pattern of spontaneous distortion. We start by constructing an exact large-deformation solution to the equations of elasticity for su

Jozsef Beck, William Chen, Yuxuan Yang

In this paper, there are two sections. In Section 7, we simplify the eigenvalue-based surplus shortline method for arbitrary finite polysquare translation surfaces. This makes it substantially simpler to determine the irregularity exponents of some infinite orbits, and quicker to find the escape rate to infinity of some orbits in some infinite models. In Sec

Jia-Xiao Dai, Kai Wang, Shengyuan A. Yang, Y. X. Zhao

We present a novel class of topological insulators, termed the Takagi topological insulators (TTIs), which is protected by the sublattice symmetry and spacetime inversion ($\mathcal P\mathcal T$) symmetry. The required symmetries for the TTIs can be realized on any bipartite lattice where the inversion exchanges sublattices. The protecting symmetries lead to

Daniel Perez

This paper investigates the propreties of the persistence diagrams stemming from almost surely continuous random processes on $[0,t]$. We focus our study on two variables which together characterize the barcode : the number of points of the persistence diagram inside a rectangle $]\!-\!\infty,x]\times [x+\varepsilon,\infty[$, $N^{x,x+\varepsilon}$ and the nu

Yuan Wang, Simone De Liberato

Recent interest in the physics of non-perturbative light-matter coupling led to the development of solid-state cavity quantum electrodynamics setups in which the interaction energies are comparable with the bare ones. In such a regime the ground state of the coupled system becomes interaction-dependent and is predicted to contain a population of virtual exci

Peter Mann, Anne Smith, John Mitchell, Simon Dobson

Coinfection is the process by which a host that is infected with a pathogen becomes infected by a second pathogen at a later point in time. An immunosuppressant host response to a primary disease can facilitate spreading of a subsequent emergent pathogen among the population. Social contact patterns within the substrate populace can be modelled using complex

Yaozhong Gan, Zhe Zhang, Xiaoyang Tan

Learning complicated value functions in high dimensional state space by function approximation is a challenging task, partially due to that the max-operator used in temporal difference updates can theoretically cause instability for most linear or non-linear approximation schemes. Mellowmax is a recently proposed differentiable and non-expansion softmax oper

M. Ehret, C. Salgado-Lopez, V. Ospina-Bohorquez, J. A. Perez-Hernandez

We demonstrate laser-driven Helium ion acceleration with cut-off energies above 25 MeV and peaked ion number above $10^8$ /MeV for 22(2) MeV projectiles from near-critical density gas jet targets. We employed shock gas jet nozzles at the high-repetition-rate (HRR) VEGA-2 laser system with 3 J in pulses of 30 fs focused down to intensities in the range betwee

S. Mazevet, A. Licari, F. Soubiran

As Juno is presently measuring Jupiter's gravitational moments to unprecedented accuracy, models for the interior structure of the planet are putted to the test. While equations of state based on first principles or ab initio simulations have been available and used for the two most abundant elements constituting the envelope, hydrogen and helium, significan

Kavita Yadav, Dheeraj Ranaut, K. Mukherjee

Recent studies on weak ferromagnets Fe2-xMnxCrAl (0<x<1) reveal the presence of cluster glass (CG) and Griffiths phase (GP) below and above the ferromagnetic transition temperature (TC) [(2019) Sci. Rep. 9 15888]. In this work, the influence of these inhomogeneous phases on the critical behaviour (around TC) of the above-mentioned series of alloys has been i

Karan Singh, Antik Sihi, Sudhir K. Pandey, K. Mukherjee

Studies connected with the investigations of non-Fermi liquid (NFL) systems continue to attract interest in condensed matter physics community. Understanding the anomalous physical properties exhibited by such systems and its related electronic structures is one of the central research topics in this area. In this context, Ce-based and Ce-site diluted (with

Zhenyu Guo, Mingyu Xiao, Yi Zhou, Dongxiang Zhang

Graph partition is a key component to achieve workload balance and reduce job completion time in parallel graph processing systems. Among the various partition strategies, edge partition has demonstrated more promising performance in power-law graphs than vertex partition and thereby has been more widely adopted as the default partition strategy by existing

Sylvester Eriksson-Bique, Gianmarco Giovannardi, Riikka Korte, Nageswari Shanmugalingam

We study existence, uniqueness, and regularity properties of the Dirichlet problem related to fractional Dirichlet energy minimizers in a complete doubling metric measure space $(X,d_X,\mu_X)$ satisfying a $2$-Poincar\'e inequality. Given a bounded domain $\Omega\subset X$ with $\mu_X(X\setminus\Omega)>0$, and a function $f$ in the Besov class $B^\theta_{2,2

Sebastian Kersting, Michael Kohler

Uncertainty quantification of complex technical systems is often based on a computer model of the system. As all models such a computer model is always wrong in the sense that it does not describe the reality perfectly. The purpose of this article is to give a review of techniques which use observed values of the technical systems in order to take into accou

Yiyan Huang, Cheuk Hang Leung, Xing Yan, Qi Wu

This paper focuses on the expected difference in borrower's repayment when there is a change in the lender's credit decisions. Classical estimators overlook the confounding effects and hence the estimation error can be magnificent. As such, we propose another approach to construct the estimators such that the error can be greatly reduced. The proposed estima

Tomoko L. Suzuki, Masato Onodera, Tadayuki Kodama, Emanuele Daddi

We conducted sub-millimeter observations with the Atacama Large Millimeter/sub-millimeter Array (ALMA) of star-forming galaxies at $z\sim3.3$, whose gas-phase metallicities have been previously measured. We investigate the dust and gas contents of the galaxies at $z\sim3.3$ and study how galaxies are interacting with their circumgalactic/intergalactic medium

Patrick Huber, Giuseppe Carenini

Discourse information, as postulated by popular discourse theories, such as RST and PDTB, has been shown to improve an increasing number of downstream NLP tasks, showing positive effects and synergies of discourse with important real-world applications. While methods for incorporating discourse become more and more sophisticated, the growing need for robust

Jean-Philippe Bouchaud, Roger Farmer

We construct a model of an exchange economy in which agents trade assets contingent on an observable signal, the probability of which depends on public opinion. The agents in our model are replaced occasionally and each person updates beliefs in response to observed outcomes. We show that the distribution of the observed signal is described by a quasi-non-er

Ying Bi, Bing Xue, Mengjie Zhang

Using evolutionary computation algorithms to solve multiple tasks with knowledge sharing is a promising approach. Image feature learning can be considered as a multitask problem because different tasks may have a similar feature space. Genetic programming (GP) has been successfully applied to image feature learning for classification. However, most of the ex

Tristan Guillot, Jonathan Fortney, Emily Rauscher, Mark S. Marley

Uranus and Neptune are the archetypes of "ice giants", a class of planets that may be among the most common in the Galaxy. They hold the keys to understand the atmospheric dynamics and structure of planets with hydrogen atmospheres inside and outside the solar system; however, they are also the last unexplored planets of the Solar System. Their atmospheres a

Bao-dong Sun, Ze-hao Sun, Jian Zhou

We compute trace anomaly contribution to hydrogen atom mass, which turns out to be related to the part of the Lamb shift. This finding might shed new light on our understandings of the mass structure of QCD bound states, such as, proton.

Masahiro Sato, Sho Takemori, Janmajay Singh, Qian Zhang

The business objectives of recommenders, such as increasing sales, are aligned with the causal effect of recommendations. Previous recommenders targeting for the causal effect employ the inverse propensity scoring (IPS) in causal inference. However, IPS is prone to suffer from high variance. The matching estimator is another representative method in causal i

Jérôme Coville

In this article, we analyse the non-local model : $\partial$ t U (t, x) = J $\star$ U (t, x) -- U (t, x) + f (x -- ct, U (t, x)) for t > 0, and x $\in$ R, where J is a positive continuous dispersal kernel and f (x, s) is a heterogeneous KPP type non-linearity describing the growth rate of the population. The ecological niche of the population is assumed to b

L. Weymann, A. Shuvaev, A. Pimenov, A. A. Mukhin

A dense system of independent oscillators, connected only by their interaction with the same cavity excitation mode, will radiate coherently, which effect is termed superradiance. In several cases, especially if the density of oscillators is high, the superradiance may dominate the intrinsic relaxation processes. This limit can be achieved, e.g., with cyclot

Kangcheng Liu, Zhi Gao, Feng Lin, Ben M. Chen

This work presents FG-Net, a general deep learning framework for large-scale point clouds understanding without voxelizations, which achieves accurate and real-time performance with a single NVIDIA GTX 1080 GPU. First, a novel noise and outlier filtering method is designed to facilitate subsequent high-level tasks. For effective understanding purpose, we pro

E Bisceglia, Swaminathan Prasanna, K. Gazeli, X. Aubert

A simplified and straightforward methodology that may be used to measure N(4 S) density by TALIF technique in strongly emissive plasmas is presented. The method makes use of the absorption peak intensities instead of the fully integrated absorption line intensity. The use of this method, along with a physics-based fitting/filtering procedure enables strongly

Jean-François Coulombel, Grégory Faye

We prove a uniform generalized gaussian bound for the powers of a discrete convolution operator in one space dimension. Our bound is derived under the assumption that the Fourier transform of the coefficients of the convolution operator is a trigonometric rational function, which generalizes previous results that were restricted to trigonometric polynomials.

Irène Gannaz

Multivariate processes with long-range dependence properties can be encountered in many fields of application. Two fundamental characteristics in such frameworks are long-range dependence parameters and correlations between component time series. We consider multivariate long-range dependent linear processes, not necessarily Gaussian. We show that the covari

Daniel Jacob, Romain David, Sophie Aubin, Yves Gibon

Making data compliant with the FAIR Data principles (Findable, Accessible, Interoperable, Reusable) is still a challenge for many researchers, who are not sure which criteria should be met first and how. Illustrated from experimental data tables associated with a Design of Experiments, we propose an approach that can serve as a model for a research data mana

Xiaolong Liu, Yao Hu, Song Bai, Fei Ding

Current developments in temporal event or action localization usually target actions captured by a single camera. However, extensive events or actions in the wild may be captured as a sequence of shots by multiple cameras at different positions. In this paper, we propose a new and challenging task called multi-shot temporal event localization, and accordingl

Ashish Kapoor

Commercial aviation is one of the biggest contributors towards climate change. We propose to reduce environmental impact of aviation by considering solutions that would reduce the flight time. Specifically, we first consider improving winds aloft forecast so that flight planners could use better information to find routes that are efficient. Secondly, we pro

Sanjaya Lohani, Thomas A. Searles, Brian T. Kirby, Ryan T. Glasser

We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance in the low-count regime, likely to be encountered in the tomography of high-dimensional systems. Finally, we implement ou

Masahiko Ueda

Zero-determinant strategies are memory-one strategies in repeated games which unilaterally enforce linear relations between expected payoffs of players. Recently, the concept of zero-determinant strategies was extended to the class of memory-$n$ strategies with $n\geq 1$, which enables more complicated control of payoffs by one player. However, what we can d

Li-Chin Yeh, Ing-Guey Jiang, Sridhar Gajendran

We investigate whether certain extra-solar multi-planet systems simultaneously follow the scaling and spacing rules of the angular-momentum-deficit model. The masses and semi-major axes of exoplanets in ten multi-planet systems are considered. It is found that GJ 667C, HD 215152, HD 40307, and Kepler-79 systems are currently close to configurations of the an

A. E. Allahverdyan, N. H. Martirosyan

Maximum entropy (MAXENT) method has a large number of applications in theoretical and applied machine learning, since it provides a convenient non-parametric tool for estimating unknown probabilities. The method is a major contribution of statistical physics to probabilistic inference. However, a systematic approach towards its validity limits is currently m

Mistura Muibideen, Rajesh Prasad

Cardiovascular disease is the number one cause of death all over the world. Data mining can help to retrieve valuable knowledge from available data from the health sector. It helps to train a model to predict patients' health which will be faster as compared to clinical experimentation. Various implementation of machine learning algorithms such as Logistic R

Gleb A. Skorobagatko

General physical background of Peres-Horodecki positive partial transpose (ppt-) separability criterion is revealed. Especially, the physical sense of partial transpose operation is shown to be equivalent to the "local causality reversal" (LCR-) procedure for all separable quantum systems or to the uncertainty in a global time arrow direction in all entangle

Zhuo Yang, Yufei Han, Xiangliang Zhang

Evasion attack in multi-label learning systems is an interesting, widely witnessed, yet rarely explored research topic. Characterizing the crucial factors determining the attackability of the multi-label adversarial threat is the key to interpret the origin of the adversarial vulnerability and to understand how to mitigate it. Our study is inspired by the th

Maria S. Madjarska, Jongchul Chae, Fernando Moreno-Insertis, Zhenyong Hou

We investigate the chromospheric counterpart of small-scale coronal loops constituting a coronal bright point (CBP) and its response to a photospheric magnetic-flux increase accompanied by co-temporal CBP heating. We used co-observations from the AIA and HMI/SDO, together with data from the Fast Imaging Solar Spectrograph taken in the Halpha and Ca II 8542 l

Hongfei Zhu, Zhiwei Cao, Yuping Zhao, Dou Li

A latest coding scheme named polarization-adjusted convolutional (PAC) codes is shown to approach the dispersion bound for the code (128,64) under list decoding. However, to achieve the near-bound performance, the list size of list decoding needs to be excessively large, which leads to insufferable latency. In this paper, to improve the speed of list decodin

Zelong Yang, Yan Wang, Piji Li, Shaobin Lin

The multiplayer online battle arena (MOBA) games have become increasingly popular in recent years. Consequently, many efforts have been devoted to providing pre-game or in-game predictions for them. However, these works are limited in the following two aspects: 1) the lack of sufficient in-game features; 2) the absence of interpretability in the prediction r

Huabing Lu, Xianzhong Xie, Zhaoyuan Shi, Hongjiang Lei

Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has recently received significant research attention due to its outstanding ability of serving grant-free (GF) users with grant-based (GB) users' spectrum, which greatly improves the spectrum efficiency and effectively relieves the massive access problem of 5G and beyond networ

Andrew Bennett, Nathan Kallus

The conditional moment problem is a powerful formulation for describing structural causal parameters in terms of observables, a prominent example being instrumental variable regression. A standard approach reduces the problem to a finite set of marginal moment conditions and applies the optimally weighted generalized method of moments (OWGMM), but this requi

Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng

We consider the problem of learning fair policies in (deep) cooperative multi-agent reinforcement learning (MARL). We formalize it in a principled way as the problem of optimizing a welfare function that explicitly encodes two important aspects of fairness: efficiency and equity. As a solution method, we propose a novel neural network architecture, which is

Jin Lan, Weichao Yu, Jiang Xiao

Spin wave, the collective excitation of magnetic order, is one of the fundamental angular momentum carriers in magnetic systems. Understanding the spin wave propagation in magnetic textures lies in the heart of developing pure magnetic information processing schemes. Here we show that the spin wave propagation across a chiral domain wall follows simple geome

Yuheng Jiao, Yuchen R. He, Mikhail E. Kandel, Xiaojun Liu

Quantitative phase imaging (QPI) has been widely applied in characterizing cells and tissues. Spatial light interference microscopy (SLIM) is a highly sensitive QPI method, due to its partially coherent illumination and common path interferometry geometry. However, its acquisition rate is limited because of the four-frame phase-shifting scheme. On the other

Akihiro Kanemitsu, Kiwamu Watanabe

Let $X$ be a smooth projective variety defined over an algebraically closed field of positive characteristic $p$ whose tangent bundle is nef. We prove that $X$ admits a smooth morphism $X \to M$ such that the fibers are Fano varieties with nef tangent bundle and $T_M$ is numerically flat. We also prove that extremal contractions exist as smooth morphisms. As

Xia Chen, Jianren Wang, David Held, Martial Hebert

Visual data in autonomous driving perception, such as camera image and LiDAR point cloud, can be interpreted as a mixture of two aspects: semantic feature and geometric structure. Semantics come from the appearance and context of objects to the sensor, while geometric structure is the actual 3D shape of point clouds. Most detectors on LiDAR point clouds focu

Lexing Ying, Yuhua Zhu

This note summarizes the optimization formulations used in the study of Markov decision processes. We consider both the discounted and undiscounted processes under the standard and the entropy-regularized settings. For each setting, we first summarize the primal, dual, and primal-dual problems of the linear programming formulation. We then detail the connect

James Stanfield

We study the positive Hermitian curvature flow on the space of left-invariant metrics on complex Lie groups. We show that in the nilpotent case, the flow exists for all positive times and subconverges in the Cheeger-Gromov sense to a soliton. We also show convergence to a soliton when the complex Lie group is almost abelian. That is, when its Lie algebra adm

Svetlana Puzynina, Mathieu Sablik

A subshift $X$ is called $c$-block gluing if for any integer $n\geq c$ and any two blocks $u$ and $v$ from the language of $X$ there exists an element of $X$ which has occurrences of $u$ and $v$ at distance $n$. In this note we study the topological entropies of $c$-block gluing binary one-dimensional subshifts. We define the set $R_c$ to be the set of entro

Noriyuki Abe

In the previous paper, we defined a new category which categorifies the Hecke algebra. This is a generalization of the theory of Soergel bimodules. To prove theorems, the existences of certain homomorphisms between Bott-Samelson bimodules are assumed. In this paper, we prove this assumption. We only assume the vanishing of certain two-colored quantum binomia

Iva Vasic, Bata Vasic, Zorica Nikolic

Ranking vertices of multidimensional networks is crucial in many areas of research, including selecting and determining the importance of decisions. Some decisions are significantly more important than others, and their weight categorization is also imortant. This paper defines a completely new method for determining the weight decisions using artificial int

Sirjan Kafle, Aman Gupta, Xue Xia, Ananth Sankar

Cluster-and-aggregate techniques such as Vector of Locally Aggregated Descriptors (VLAD), and their end-to-end discriminatively trained equivalents like NetVLAD have recently been popular for video classification and action recognition tasks. These techniques operate by assigning video frames to clusters and then representing the video by aggregating residua

Guodong Xu, Ziwei Liu, Chen Change Loy

Knowledge distillation, which involves extracting the "dark knowledge" from a teacher network to guide the learning of a student network, has emerged as an essential technique for model compression and transfer learning. Unlike previous works that focus on the accuracy of student network, here we study a little-explored but important question, i.e., knowledg

Nihal Singh, Jay Karhade, Ishika Bhattacharya, Prathamesh Saraf

Hyperloop is a high-speed ground-based transportation system utilizing sealed tubes, with the aim of ultimately transporting passengers between metropolitan cities in efficiently designed autonomous capsules. In recent years, the design and development of sub-scale prototypes for these Hyperloop pods has set the foundation for realizing more practical and sc

Xiang Hu, Zujie Wen, Yafang Wang, Xiaolong Li

Coping with ambiguous questions has been a perennial problem in real-world dialogue systems. Although clarification by asking questions is a common form of human interaction, it is hard to define appropriate questions to elicit more specific intents from a user. In this work, we propose a reinforcement model to clarify ambiguous questions by suggesting refin

Qiuliang Ye, Yuk-Hee Chan, Michael G. Somekh, Daniel P. K. Lun

Phase retrieval with pre-defined optical masks can provide extra constraint and thus achieve improved performance. The recent progress in optimization theory demonstrates the superiority of random masks in phase retrieval algorithms. However, traditional approaches just focus on the randomness of the masks but ignore their non-bandlimited nature. When using

David Deng, Avideh Zakhor

Anticipating the future in a dynamic scene is critical for many fields such as autonomous driving and robotics. In this paper we propose a class of novel neural network architectures to predict future LiDAR frames given previous ones. Since the ground truth in this application is simply the next frame in the sequence, we can train our models in a self-superv

Chengyu Zheng, Xiulian Peng, Yuan Zhang, Sriram Srinivasan

Speech enhancement is challenging because of the diversity of background noise types. Most of the existing methods are focused on modelling the speech rather than the noise. In this paper, we propose a novel idea to model speech and noise simultaneously in a two-branch convolutional neural network, namely SN-Net. In SN-Net, the two branches predict speech an

Taiga Kashima, Yoshihiro Yamada, Shunta Saito

The common pipeline of training deep neural networks consists of several building blocks such as data augmentation and network architecture selection. AutoML is a research field that aims at automatically designing those parts, but most methods explore each part independently because it is more challenging to simultaneously search all the parts. In this pape

Diego R. Granado, Elisama E. M. Lima

In this paper, we analyze kink-like analytical solutions in a real scalar theory with an arcsin dynamics inspired by the arcsin electrodynamics presented in Kruglov (2015). This analysis is done by means of the first-order formalism. This formalism provides a framework where the equations of motion can be simplified by preserving the linear stability of the

Tatsuro Kawakami, Masaru Nagaoka

In this paper, we classify Du Val del Pezzo surfaces of Picard rank one in characteristic two and three. We also show that if a Du Val del Pezzo surface is Frobenius split, then a general anti-canonical member is smooth. Furthermore, in characteristic two, it is an ordinary elliptic curve.

Samuel Passaglia

We develop in this thesis the principles governing the production of our universe's primordial inhomogeneities during its early phase of inflation. As a guiding thread we ask what physics during inflation can lead to perturbations so large that they form black holes in sufficient abundance to be the dark matter. We start with the simplest single-field slow-r

Jiayu Pan, Ahmed M. Bedewy, Yin Sun, Ness B. Shroff

We consider the problem of minimizing the age of information when a source can transmit status updates over two heterogeneous channels. Our work is motivated by recent developments in 5G mmWave technology, where transmissions may occur over an unreliable but fast (e.g., mmWave) channel or a slow reliable (e.g., sub-6GHz) channel. The unreliable channel is mo

Sai Praneeth Reddy Sunkesula, Rishabh Dabral, Ganesh Ramakrishnan

Analyzing the interactions between humans and objects from a video includes identification of the relationships between humans and the objects present in the video. It can be thought of as a specialized version of Visual Relationship Detection, wherein one of the objects must be a human. While traditional methods formulate the problem as inference on a seque

Soo Ye Kim, Kfir Aberman, Nori Kanazawa, Rahul Garg

Although deep learning has enabled a huge leap forward in image inpainting, current methods are often unable to synthesize realistic high-frequency details. In this paper, we propose applying super-resolution to coarsely reconstructed outputs, refining them at high resolution, and then downscaling the output to the original resolution. By introducing high-re

Srujan Teja Thomdapu, Harshvardhan, Ketan Rajawat

This work studies constrained stochastic optimization problems where the objective and constraint functions are convex and expressed as compositions of stochastic functions. The problem arises in the context of fair classification, fair regression, and the design of queuing systems. Of particular interest is the large-scale setting where an oracle provides t