October 2022 arXiv papers — page 9

Sannara Ek, François Portet, Philippe Lalanda, German Vega

Pervasive computing promotes the integration of smart devices in our living spaces to develop services providing assistance to people. Such smart devices are increasingly relying on cloud-based Machine Learning, which raises questions in terms of security (data privacy), reliance (latency), and communication costs. In this context, Federated Learning (FL) ha

Mitra Hassani, Reza Gholizadeh

Federated learning (FL) is a type of distributed machine learning at the wireless edge that preserves the privacy of clients' data from adversaries and even the central server. Existing federated learning approaches either use (i) secure multiparty computation (SMC) which is vulnerable to inference or (ii) differential privacy which may decrease the test acc

Jin Liu

Longitudinal processes are often associated with each other over time; therefore, it is important to investigate the associations among developmental processes and understand their joint development. The latent growth curve model (LGCM) with a time-varying covariate (TVC) provides a method to estimate the TVC's effect on a longitudinal outcome while simultan

The Viet Bui, Tien Mai, Thanh H. Nguyen

Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim agent) to perform poorly in a multi-agent environment. In existing studies, adversarial policies are directly trained based on experiences of interacting with the victim agent. There

Riad Ibadulla, Thomas M. Chen, Constantino Carlos Reyes-Aldasoro

This paper describes the transformation of a traditional in-silico classification network into an optical fully convolutional neural network with high-resolution feature maps and kernels. When using the free-space 4f system to accelerate the inference speed of neural networks, higher resolutions of feature maps and kernels can be used without the loss in fra

Yao Zhao, Connor James Stephens, Csaba Szepesvári, Kwang-Sung Jun

Simple regret is a natural and parameter-free performance criterion for pure exploration in multi-armed bandits yet is less popular than the probability of missing the best arm or an $\epsilon$-good arm, perhaps due to lack of easy ways to characterize it. In this paper, we make significant progress on minimizing simple regret in both data-rich ($T\ge n$) an

Shibananda Biswas, Gadadhar Misra, Samrat Sen

Let $\Omega \subseteq \mathbb C^m$ be a bounded connected open set and $\mathcal H \subseteq \mathcal O(\Omega)$ be an analytic Hilbert module, i.e., the Hilbert space $\mathcal H$ possesses a reproducing kernel $K$, the polynomial ring $\mathbb C[\boldsymbol{z}]\subseteq \mathcal H$ is dense and the point-wise multiplication induced by $p\in \mathbb C[\bold

Rodrigo Clemente, João Marcos do Ó, Esteban da Silva, Evelina Shamarova

We study general equations modeling electrostatic MEMS devices \begin{equation} \begin{cases} \label{P} \varphi\big(r,- u'(r)\big)=\lambda\int_0^r\frac{f(s)}{g(u(s))}\,\mathrm{d}s, & r\in(0,1), \\ 0 < u(r) < 1, & r\in(0,1), \\ u(1) = 0, \tag{$P_\lambda$} \end{cases} \end{equation} where $\varphi$, $g$, $f$ are some functions on $[0,1]$ and $\lambda>0$ is a p

John W. Blanchard, Dmitry Budker, David DeMille, Mikhail G. Kozlov

An experiment utilizing a TlF molecular beam is being developed by the CeNTREX collaboration to search for hadronic interactions that violate both time-reversal (T) and parity (P) invariance. Here we propose to use the same beam to look for a T-invariance conserving but P-nonconserving (PNC) effect induced by the anapole moment of the Tl nucleus, via a vecto

Yunwei Deng, Zhi-Yu Zhang, Ping Zhou, Junzhi Wang

Supernovae and their remnants provide energetic feedback to the ambient interstellar medium (ISM), which is often distributed in multiple gas phases. Among them, warm molecular hydrogen (H$_2$) often dominates the cooling of the shocked molecular ISM, which has been observed with the H$_2$ emission lines at near-infrared wavelengths. Such studies, however, w

Ao Cai, Pedro Duarte, Silvius Klein

We establish an abstract, effective, exponential large deviations type estimate for Markov systems satisfying a weaker form of mixing. We employ this result to derive such estimates, as well as a central limit theorem, for the skew product encoding a random torus translation, a model we call a mixed random-quasiperiodic dynamical system. This abstract scheme

Dan Li, Chunmei Wang, Junping Wang

A mathematical analysis is established for the weak Galerkin finite element methods for the Poisson equation with Dirichlet boundary value when the curved elements are involved on the interior edges of the finite element partition or/and on the boundary of the whole domain in two dimensions. The optimal orders of error estimates for the weak Galerkin approxi

Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates

Temporal graph neural networks have shown promising results in learning inductive representations by automatically extracting temporal patterns. However, previous works often rely on complex memory modules or inefficient random walk methods to construct temporal representations. To address these limitations, we present an efficient yet effective attention-ba

Svetlana Boyarchenko, Sergei Levendorskiĭ

In the paper, we develop a very fast and accurate method for pricing double barrier options with continuous monitoring in wide classes of L\'evy models; the calculations are in the dual space, and the Wiener-Hopf factorization is used. For wide regions in the parameter space, the precision of the order of $10^{-15}$ is achievable in seconds, and of the order

Sherry Hu, Kose John, Balbinder Singh Gill

In this study, we evaluate the effects of natural disasters on the stock (market) values of firms located in the affected counties. We are able to measure the change in stock prices of the firms affected by the 2021 Texas winter storm. To measure the abnormal return due to the storm, we use four different benchmark models: (1) the market-adjusted model, (2)

Eleftheria Malami

We provide an overview of the latest progress in the study of CP violation and mixing in the $B$ meson decays. Studying the $B^0_d \to J/\psi K^0_S$ and $B^0_s \to J/\psi \phi$ decays, we focus on the determination of the mixing phases $\phi_d$ and $\phi_s$, including hadronic uncertainties with the help of the data. CP violation in the non-leptonic decays $

Olakunle Abawonse, Laura Anderson

In 1992 Gelfand and MacPherson gave a local and combinatorial formula for the Pontrjagin classes of a differential manifold. We give an expanded version of their discussion and highlight the origins of combinatorial differential manifolds in their work.

Qiang Liu, Nakjung Choi, Tao Han

Network slicing achieves cost-efficient slice customization to support heterogeneous applications and services. Configuring cross-domain resources to end-to-end slices based on service-level agreements, however, is challenging, due to the complicated underlying correlations and the simulation-to-reality discrepancy between simulators and real networks. In th

Travis Munyer, Daniel Brinkman, Xin Zhong, Chenyu Huang

Supervised object detection methods provide subpar performance when applied to Foreign Object Debris (FOD) detection because FOD could be arbitrary objects according to the Federal Aviation Administration (FAA) specification. Current supervised object detection algorithms require datasets that contain annotated examples of every to-be-detected object. While

Azin Jahedi, Maximilian Luz, Lukas Mehl, Marc Rivinius

In this report, we present our optical flow approach, MS-RAFT+, that won the Robust Vision Challenge 2022. It is based on the MS-RAFT method, which successfully integrates several multi-scale concepts into single-scale RAFT. Our approach extends this method by exploiting an additional finer scale for estimating the flow, which is made feasible by on-demand c

Jason Chen, Kathy Fogel, Kose John

This paper discusses a decentralized finance (DeFi) application called MakerDAO. The Maker Protocol, built on the Ethereum blockchain, enables users to create and hold currency. Current elements of the Maker Protocol are the Dai stable coin, Maker Vaults, and Voting. MakerDAO governs the Maker Protocol by deciding on key parameters (e.g., stability fees, col

Ehsan Khodapanah Aghdam, Reza Azad, Maral Zarvani, Dorit Merhof

Melanoma is caused by the abnormal growth of melanocytes in human skin. Like other cancers, this life-threatening skin cancer can be treated with early diagnosis. To support a diagnosis by automatic skin lesion segmentation, several Fully Convolutional Network (FCN) approaches, specifically the U-Net architecture, have been proposed. The U-Net model with a s

Shan Zhang, Naila Murray, Lei Wang, Piotr Koniusz

In this paper, we tackle the challenging problem of Few-shot Object Detection. Existing FSOD pipelines (i) use average-pooled representations that result in information loss; and/or (ii) discard position information that can help detect object instances. Consequently, such pipelines are sensitive to large intra-class appearance and geometric variations betwe

Alireza Olama, Eduardo Camponogara, Jan Kronqvist

This paper proposes an open-source distributed solver for solving Sparse Convex Optimization (SCO) problems over computational networks. Motivated by past algorithmic advances in mixed-integer optimization, the Sparse Convex Optimization Toolkit (SCOT) adopts a mixed-integer approach to find exact solutions to SCO problems. In particular, SCOT brings togethe

Michael F. Bietenholz, Norbert Bartel, Vikram V. Dwarkadas, Leon Mtshweni

We present broadband radio flux-density measurements supernova (SN) 1996cr, made with MeerKAT, ATCA and ALMA, and images made from very long baseline interferometry (VLBI) observations with the Australian Long Baseline Array. The spectral energy distribution of SN 1996cr in 2020, at age, $t \sim$8700 d, is a power-law, with flux density, $S \propto \nu^{-0.5

Akram S. Awad, George K. Atia

Domain Adaptation (DA) has recently received significant attention due to its potential to adapt a learning model across source and target domains with mismatched distributions. Since DA methods rely exclusively on the given source and target domain samples, they generally yield models that are vulnerable to noise and unable to adapt to unseen samples from t

Nicola Garofalo, Annunziata Loiudice, Dimiter Vassilev

In this paper we establish the sharp asymptotic decay of positive solutions of the Yamabe type equation $\frlap u=u^{\frac{Q+2s}{Q-2s}}$ in a homogeneous Lie group, where $\frlap$ represents a suitable pseudodifferential operator modelled on a class of nonlocal operators arising in conformal CR geometry.

Ashish Mittal, Durga Sivasubramanian, Rishabh Iyer, Preethi Jyothi

Training state-of-the-art ASR systems such as RNN-T often has a high associated financial and environmental cost. Training with a subset of training data could mitigate this problem if the subset selected could achieve on-par performance with training with the entire dataset. Although there are many data subset selection(DSS) algorithms, direct application t

Vladimir Zhdankin, Matthew W. Kunz, Dmitri A. Uzdensky

We demonstrate using linear theory and particle-in-cell (PIC) simulations that a synchrotron-cooling collisionless plasma acquires pressure anisotropy and, if the plasma beta is sufficiently high, becomes unstable to the firehose instability, in a process that we dub the synchrotron firehose instability (SFHI). The SFHI channels free energy from the pressure

Xinjian Wei, Congkuan Tian, Hang Cui, Yongkai Li

Linear nonsaturating magnetoresistance (LMR) represents a class of anomalous resistivity response to external magnetic field that has been observed in a variety of materials including but not limited to topological semi-metals, high-Tc superconductors and materials with charge/spin density wave (CDW/SDW) orders. Here we report the observation of LMR in layer

Alexander Lukin, Anton Artemyev, Dmitri Vainchtein, Anatoli Petrukovich

Current sheets are spatially localized almost-1D structures with intense plasma currents. They play a key role in storing the magnetic field energy and they separate different plasma populations in planetary magnetospheres, the solar wind, and the solar corona. Current sheets are primary regions for the magnetic field line reconnection responsible for plasma

Graham G. Brown, Álvaro Jiménez-Galán, Rui E. F. Silva, Misha Ivanov

We develop and demonstrate a fully real-space perspective on HHG in crystals. Due to Wannier-Stark localization induced on sub-cycle timescales in the presence of a strong field, real-space descriptions are natural for strongly driven solids. Our approach allows us to address the origin of the extremely short dephasing times, which appear necessary for agree

Lei Wang, Piotr Koniusz

Dynamic Time Warping (DTW) is used for matching pairs of sequences and celebrated in applications such as forecasting the evolution of time series, clustering time series or even matching sequence pairs in few-shot action recognition. The transportation plan of DTW contains a set of paths; each path matches frames between two sequences under a varying degree

Dimiter Vassilev

Corrigenda to "$L^p$ estimates and asymptotic behavior for finite energy solutions of extremals to Hardy-Sobolev inequalities", Trans. Amer. Math. Soc. 363 (2011), no. 1, 37--62.

M. Tyushev, M. Papahn Zadeh, V. Sharma, M. Sengupta

Azimuthal structures in cylindrical Penning discharge are studied with 2D3V radial-azimuthal PIC/MCC model with the axial magnetic field. The discharge is self-consistently supported by ionization due to the axial injection of electrons. It is shown that the steady-state discharge can be supported in two different regimes with different type of observed azim

Machel Reid, Vincent J. Hellendoorn, Graham Neubig

In text generation, models that generate text from scratch one token at a time are currently the dominant paradigm. Despite being performant, these models lack the ability to revise existing text, which limits their usability in many practical scenarios. We look to address this, with DiffusER (Diffusion via Edit-based Reconstruction), a new edit-based genera

José Carlos R. Alcantud, Domenico Cantone, Alfio Giarlotta, Stephen Watson

We describe a model that explains possibly indecisive choice behavior, that is, quasi-choices (choice correspondences that may be empty on some menus). The justification is here provided by a proportion of ballots, which are quasi-choices rationalizable by an arbitrary binary relation. We call a quasi-choice $s$-majoritarian if all options selected from a me

Fuyang Li, Jiying Zhang, Xi Xiao, Bin Zhang

Kernels on discrete structures evaluate pairwise similarities between objects which capture semantics and inherent topology information. Existing kernels on discrete structures are only developed by topology information(such as adjacency matrix of graphs), without considering original attributes of objects. This paper proposes a two-phase paradigm to aggrega

B. Maddox, C. Deans, H. Yao, Y. Cohen

We present an apparatus to overcome the limitations of mechanical raster-scanning in electromagnetic induction imaging (EMI) techniques by instead performing a 2D optical raster-scan within the vapour cell of a radio-frequency atomic magnetometer (RF-AM). A large cuboidal 87Rb vapour cell is employed to act as the medium of an RF-AM with the pump and probe b

Kenneth H. Karlsen, Michael Kunzinger, Darko Mitrovic

We consider a dynamic capillarity equation with stochastic forcing on a compact Riemannian manifold $(M,g)$. \begin{equation*}\tag{P} d \left(u_{\varepsilon,\delta}-\delta \Delta u_{\varepsilon,\delta}\right) +\operatorname{div} f_{\varepsilon}(x, u_{\varepsilon,\delta})\, dt =\varepsilon \Delta u_{\varepsilon,\delta}\, dt \Phi(x, u_{\varepsilon,\delta})\, d

Sathvik Udupa, Prasanta Kumar Ghosh

Real-Time Magnetic resonance imaging (rtMRI) of the midsagittal plane of the mouth is of interest for speech production research. In this work, we focus on estimating utterance level rtMRI video from the spoken phoneme sequence. We obtain time-aligned phonemes from forced alignment, to obtain frame-level phoneme sequences which are aligned with rtMRI frames.

Yunran Wei, Ricardas Zitikis

This paper offers a mathematical invention that shows how to convert integrated quantiles, which often appear in risk measures, into integrated cumulative distribution functions, which are technically more tractable from various perspectives. The invention helps to avoid a number of technical assumptions that have been traditionally imposed when working with

Takao Yuyama

Elder, Kambites, and Ostheimer showed that if the word problem of a finitely generated group $H$ is accepted by a $G$-automaton for an abelian group $G$, then $H$ is virtually abelian. We give a new, elementary, and purely combinatorial proof to the theorem. Furthermore, our method extracts an explicit connection between the two groups $G$ and $H$ from the a

Esther Bou Dagher, Jean Dolbeault

This paper is devoted to the study of phase transitions associated to a large family of Gagliardo-Nirenberg-Sobolev interpolation inequalities on the sphere depending on one parameter. We characterize symmetry and symmetry breaking regimes, with a phase transition that can be of first or second order. We establish various new results and study the qualitativ

Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy

Throughout the cognitive-science literature, there is widespread agreement that decision-making agents operating in the real world do so under limited information-processing capabilities and without access to unbounded cognitive or computational resources. Prior work has drawn inspiration from this fact and leveraged an information-theoretic model of such be

Gili Golan, Mark Sapir

We prove that Thompson's group $F$ has a generating set with two elements such that every two powers of them generate a finite index subgroup of $F$.

Xinyu Zhang, Yuanhao Huang, Kangyao Huang, Xiaoyu Wang

Single locomotion robots often struggle to adapt in highly variable or uncertain environments, especially in emergencies. In this paper, a multi-modal deformable robot is introduced that can both fly and drive. Compatibility issues with multi-modal locomotive fusion for this hybrid land-air robot are solved using proposed design conceptions, including power

S. M. Elahi, R. Tavakoli, I. Romero, D. Tourret

A broad range of computational models have been proposed to predict microstructure development during solidification processing but they have seldom been compared to each other on a quantitative and systematic basis. In this paper, we compare phase-field (PF) and cellular automaton (CA) simulations of polycrystalline growth in a two-dimensional melt pool und

Zhiming Xu, Wenhui Duan, Yong Xu

Finding guiding principles to optimize properties of quantum anomalous Hall (QAH) insulators is of pivotal importance to fundamental science and applications. Here, we build a first-principles QAH material database of chirality and band gap, explore microscopic mechanisms determining the QAH material properties, and obtain a general physical picture that can

Dilip Arumugam, Satinder Singh

The Bayes-Adaptive Markov Decision Process (BAMDP) formalism pursues the Bayes-optimal solution to the exploration-exploitation trade-off in reinforcement learning. As the computation of exact solutions to Bayesian reinforcement-learning problems is intractable, much of the literature has focused on developing suitable approximation algorithms. In this work,

Sathvik Udupa, Siddarth C, Prasanta Kumar Ghosh

In this work, we investigate the effectiveness of pretrained Self-Supervised Learning (SSL) features for learning the mapping for acoustic to articulatory inversion (AAI). Signal processing-based acoustic features such as MFCCs have been predominantly used for the AAI task with deep neural networks. With SSL features working well for various other speech tas

Shlok Mishra, Joshua Robinson, Huiwen Chang, David Jacobs

We introduce CAN, a simple, efficient and scalable method for self-supervised learning of visual representations. Our framework is a minimal and conceptually clean synthesis of (C) contrastive learning, (A) masked autoencoders, and (N) the noise prediction approach used in diffusion models. The learning mechanisms are complementary to one another: contrastiv

Sergei Avdonin, Nina Avdonina, Olha Sus

In this paper, we consider the inverse dynamic problem for the Dirac system on finite metric tree graphs. Our main goal is to recover the topology (connectivity) of a tree, lengths of edges, and a matrix potential function on each edge. We use the dynamic response operator as our inverse data and apply the Leaf peeling method. In addition, we present a new d

Maksym Obrizan

This paper identifies the causal effects of full-scale kremlin aggression on socio-economic outcomes in Ukraine three months into the full-scale war. First, forced migration after February 24th, 2022 is associated with an elevated risk of becoming unemployed by 7.5% points. Second, difference-in-difference regressions show that in regions with fighting on th

Guanglu Yuan, Ruifeng Lu, Shicheng Jiang, Konstantin Dorfman

Nonadiabatic dynamics around an avoid crossing or a conical intersection play a crucial role in the photoinduced processes of most polyatomic molecules. The present work shows that the topological phase in conical intersection makes the behavior of pump-probe high-order harmonic spectroscopy different from the case of avoid crossing. The coherence built up w

Anthony David, Julia S. Meyer, Manuel Houzet

We consider a quantum Hall (QH) region in contact with a superconductor (SC), i.e., a QH-SC junction. Due to successive Andreev reflections, the QH-SC interface hosts hybridized electron and hole edge states called chiral Andreev edge states (CAES). We theoretically study the transport properties of these CAES by using a microscopic, tight-binding model. We

José Mancias, Vahid Attari, Raymundo Arróyave, Damien Tourret

We carry out an extensive comparison between Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory of first-order phase transformation kinetics and phase-field (PF) results of a benchmark problem on nucleation. To address the stochasticity of the problem, several hundreds of simulations are performed to establish a comprehensive, statistically-significant analysis of

Ben Zhou, Kyle Richardson, Xiaodong Yu, Dan Roth

Explicit decomposition modeling, which involves breaking down complex tasks into more straightforward and often more interpretable sub-tasks, has long been a central theme in developing robust and interpretable NLU systems. However, despite the many datasets and resources built as part of this effort, the majority have small-scale annotations and limited sco

Liang Zhang, Juan-Juan Luo, Yong-Feng Huang, Yu-Jun Gong

Using four mixed bivariate distributions (Normal distribution, Skew-Normal distribution, Student distribution, Skew-Student distribution) and bootstrap re-sampling analysis, we analyze the samples of CGRO/BATSE, Swift/BAT and Fermi/GBM gamma-ray bursts in detail on the t90-hardness ratio plane. The Bayesian information criterion is used to judge the goodness

Chengxiang Jin, Jiajun Zhou, Jie Jin, Jiajing Wu

With the development of Web 3.0 which emphasizes decentralization, blockchain technology ushers in its revolution and also brings numerous challenges, particularly in the field of cryptocurrency. Recently, a large number of criminal behaviors continuously emerge on blockchain, such as Ponzi schemes and phishing scams, which severely endanger decentralized fi

Guangyu Xu

This thesis studies the algebro-geometric aspects of supersymmetric abelian gauge theories in three dimensions. The supersymmetric vacua are demonstrated to exhibit a window phenomenon in Chern-Simons levels, which is analogous to the window phenomenon in quantum K-theory with level structures. This correspondence between three-dimensional gauge theories and

Daniel Kapec, Adam Tropper

We compute the Mellin transforms of various two-dimensional integrable $S$-matrices, providing the first explicit, non-perturbative realizations of celestial CFT. In two dimensions, the Mellin transform is simply the Fourier transform in rapidity space, and the "celestial correlator" has no position dependence. The simplified setting allows us to study the a

Tao Zhang, Hui-Jun Yao

We introduce the concept of braided left-symmetric bialgebras and construct cocycle bicrossproduct left-symmetric bialgebras. As an application, we solve the extending problem for left-symmetric bialgebras by using some non-abelian cohomology theory.

Yihong Fan, Pengxiang Zhang, Jiahao Han, Yang Lv

Unidirectional magnetoresistance (UMR) has been observed in a variety of stacks with ferromagnetic/spin Hall material bilayer structures. In this work, we reported UMR in antiferromagnetic insulator Fe2O3/Pt structure. The UMR has a negative value, which is related to interfacial Rashba coupling and band splitting. Thickness-dependent measurement reveals a p

Alexander Maloney, Daniel A. Roberts, James Sully

Large language models with a huge number of parameters, when trained on near internet-sized number of tokens, have been empirically shown to obey neural scaling laws: specifically, their performance behaves predictably as a power law in either parameters or dataset size until bottlenecked by the other resource. To understand this better, we first identify th

Yangqin Fang

In this paper, we will solve the Reifenberg Plateau Problem in Hilbert space.

Cheng Chu, Grant Skipper, Martin Swany, Fan Chen

In this work, we propose IQGAN, a quantum Generative Adversarial Network (GAN) framework for multiqubit image synthesis that can be efficiently implemented on Noisy Intermediate Scale Quantum (NISQ) devices. We investigate the reasons for the inferior generative performance of current quantum GANs in our preliminary study and conclude that an adjustable inpu

Yen Chin Ong

Many fundamental issues remain for black hole thermodynamics after almost half a century of its conception. For example, what are the underlying degrees of freedom of a black hole horizon that give rise to said thermodynamical properties? Furthermore, classical black holes also harbor a spacetime singularity. Although it is often believed that quantum gravit

Rainer Backofen, Marco Salvalaglio, Axel Voigt

The amplitude expansion for a magnetic phase-field-crystal (magnetic APFC) model enables a convenient coarse-grained description of crystalline structures under the influence of magnetic fields. Considering higher-order magnetic coupling terms, we demonstrate the possibility of tuning the magnetic anisotropy in these models. This allows for reproducing the e

Anupama Ray, Sai Sakunthala Guddanti, Vishnu Ajith, Dhinakaran Vinayagamurthy

Ethereum is one of the most valuable blockchain networks in terms of the total monetary value locked in it, and arguably been the most active network where new blockchain innovations in research and applications are demonstrated. But, this also leads to Ethereum network being susceptible to a wide variety of threats and attacks in an attempt to gain unreason

Zhonghua Li, Zhenlu Wang

We study the relations of multiple $t$-values of general level. The generating function of sums of multiple $t$-(star) values of level $N$ with fixed weight, depth and height is represented by the generalized hypergeometric function $_3F_2$, which generalizes the results for multiple zeta(-star) values and multiple $t$-(star) values. As applications, we obta

Debanjan Sarkar, Ely D. Kovetz

The fluctuations in the dark matter-baryon relative velocity field are imprinted as acoustic oscillations in the 21-cm power spectrum during cosmic dawn (CD). These velocity acoustic oscillations (VAOs) keep the imprints of the comoving sound horizon scale. In a previous work by Mu\~noz, it has been demonstrated that these VAOs can be treated as standard rul

Robin Neumayer

Examples show that Riemannian manifolds with almost-Euclidean lower bounds on scalar curvature and Perelman entropy need not be close to Euclidean space in any metric space sense. Here we show that if one additionally assumes an almost-Euclidean upper bound on volumes of geodesic balls, then unit balls in such a space are Gromov-Hausdorff close, and in fact

Eduardo H. Gomes Tavares, Marcio A. Jorge Silva, Vando Narciso, André Vicente

This work is concerned with new results on long-time dynamics of a class of hyperbolic evolution equations related to extensible beams with three distinguished nonlocal nonlinear damping terms. In the first possibly degenerate case, the results feature the existence of a family of compact global attractors and a thickness estimate for their Kolmogorov's $\va

Byung-Hak Kim

Prediction of medical codes from clinical notes is a practical and essential need for every healthcare delivery organization within current medical systems. Automating annotation will save significant time and excessive effort that human coders spend today. However, the biggest challenge is directly identifying appropriate medical codes from several thousand

Yiwen Wang, Zijian Lan, Xihong Wu, Tianshu Qu

In the current method for the sound field translation tasks based on spherical harmonic (SH) analysis, the solution based on the additive theorem usually faces the problem of singular values caused by large matrix condition numbers. The influence of different distances and frequencies of the spherical radial function on the stability of the translation matri

Jiangbin Zheng, Yile Wang, Ge Wang, Jun Xia

Although contextualized embeddings generated from large-scale pre-trained models perform well in many tasks, traditional static embeddings (e.g., Skip-gram, Word2Vec) still play an important role in low-resource and lightweight settings due to their low computational cost, ease of deployment, and stability. In this paper, we aim to improve word embeddings by

Zhuang Liu, Zhichao Zhao, Ye Yuan, Zhi Qiao

In this technical report, we briefly introduce the solution of our team ''summer'' for Atomospheric Turbulence Mitigation in UG$^2$+ Challenge in CVPR 2022. In this task, we propose a unified end-to-end framework to reconstruct a high quality image from distorted frames, which is mainly consists of a Restormer-based image reconstruction module and a NIMA-bas

Teng Andrea Xu, Jiahua Xu, Kristof Lommers

As of August 2022, blockchain-based assets boast a combined market capitalisation exceeding one trillion USD, among which the most prominent are the decentralised autonomous organisation (DAO) tokens associated with decentralised finance (DeFi) protocols. In this work, we seek to value DeFi tokens using the canonical multiples and discount cash flow (DCF) ap

Gilad Lifschytz, Milan Patra

We continue the program of bulk reconstruction for fermionic fields. We reconstruct, from the CFT, the Dirac fermion field in $AdS_{3}$ coupled to a Chern-Simon gauge field. We show that the three conditions; solving the equation of motion, satisfying expected transformation under modular flow and a simple charge distribution at infinity are all compatible a

Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li

Generative models for graph data are an important research topic in machine learning. Graph data comprise two levels that are typically analyzed separately: node-level properties such as the existence of a link between a pair of nodes, and global aggregate graph-level statistics, such as motif counts. This paper proposes a new multi-level framework that join

Shuaiqun Pan, Sergio J. Rodríguez Méndez, Kerry Taylor

Data mining techniques can transform massive amounts of unstructured data into quantitative data that quickly reveal insights, trends, and patterns behind the original data. In this paper, a data mining model is applied to analyse the 2019 grant applications submitted to an Australian Government research funding agency to investigate whether grant schemes su

Yi Li

In \cite{FGP}, Fei, Guo and Phong established a criteria for the long-time existence of their parabolic flow from $11$-dimensional supergravity, which involves Riemannian curvatures ${\rm Rm}(g(t))$ and 4-forms $F(t)$. In this paper, we obtain a new criteria for the long-time existence of the same flow, which involves only Ricci curvatures ${\rm Ric}(g(t))$,

Adit Magotra

Actionable sentences are terms that, in the most basic sense, imply the necessity of taking a specific action. In Linguistic terms, they are steps to achieve an operation, often through the usage of action verbs. For example, the sentence, `Get your homework finished by tomorrow` qualifies as actionable since it demands a specific action (In this case, finis

Jingwei Chen, Zifan Wang, Chrysanthi Papadaki, Alexander M. Korsunsky

Understanding the creep mechanisms and deformation response at different stresses and temperatures is crucial for design using nickel-base superalloys for high-temperature applications. In this study, the creep behaviour of a newly designed superalloy (nominated Alloy 11) at different stress and temperature was systematically investigated using SEM, STEM, EB

Lissa Keersmaekers

We discuss a recently proposed branching algorithm which incorporates transverse momentum dependent (TMD) parton splitting probabilities, and can be used for Monte Carlo event generators based on TMD distributions.

Jiao Ou, Jinchao Zhang, Yang Feng, Jie Zhou

The construction of open-domain dialogue systems requires high-quality dialogue datasets. The dialogue data admits a wide variety of responses for a given dialogue history, especially responses with different semantics. However, collecting high-quality such a dataset in most scenarios is labor-intensive and time-consuming. In this paper, we propose a data au

Marian Kupczynski

In 1976, I met John Bell several times in CERN and we talked about a possible violation of optical theorem, purity tests, EPR paradox, Bell inequalities and their violation. I review our discussions, and explain how they were related to my earlier research. I also reproduce handwritten notes, which I gave to Bell during our first meeting and a handwritten le

Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou

In this technical report, we present our solutions to the Traffic4cast 2022 core challenge and extended challenge. In this competition, the participants are required to predict the traffic states for the future 15-minute based on the vehicle counter data in the previous hour. Compared to other competitions in the same series, this year focuses on the predict

Valfride Nascimento, Rayson Laroca, Jorge de A. Lambert, William Robson Schwartz

The License Plate Recognition (LPR) field has made impressive advances in the last decade due to novel deep learning approaches combined with the increased availability of training data. However, it still has some open issues, especially when the data come from low-resolution (LR) and low-quality images/videos, as in surveillance systems. This work focuses o

Mengmeng Wu, Ruoxi Jia, Changle Lin, Wei Huang

Data valuation, especially quantifying data value in algorithmic prediction and decision-making, is a fundamental problem in data trading scenarios. The most widely used method is to define the data Shapley and approximate it by means of the permutation sampling algorithm. To make up for the large estimation variance of the permutation sampling that hinders

Jing Xu, Xu Luo, Xinglin Pan, Wenjie Pei

Few-shot learning (FSL) targets at generalization of vision models towards unseen tasks without sufficient annotations. Despite the emergence of a number of few-shot learning methods, the sample selection bias problem, i.e., the sensitivity to the limited amount of support data, has not been well understood. In this paper, we find that this problem usually o

Kaijian Sha, Yun Wang, Chunjing Xie

In this paper, we investigate the Leray problem for steady Navier-Stokes system under full slip boundary conditions in a two dimensional channel with straight outlets. The existence of solutions with arbitrary flux in a general channel with slip boundary conditions is established, which tend to the shear flows at far fields. Furthermore, if the flux is suita

Hideki Murahara, Tatsushi Tanaka, Noriko Wakabayashi

In this paper, we show the image of rooted tree maps themselves forms a subspace of the kernel of the evaluation map of multiple $L$-values. For its proof, we define the diamond product as a modified harmonic product and find its properties. We also show that $\tau$-conjugate rooted tree maps are their antipodes.

Shoukang Chang, Wei Ye, Xuan Rao, Huan Zhang

The angular displacement estimation is one of significant branches of quantum parameter estimation. However, most of the studies have focused on the single-angular displacement estimation, while the multiple angular displacement estimation in ideal and noisy scenarios is still elusive. In this paper, we investigate the simultaneous multiple angular displacem

Henggeng Han, Song Wang, Yu Bai, Huiqin Yang

By using the LAMOST time-domain survey data, we study stellar activities based on the $\rm{H_{\alpha}}$ lines for about 2000 stars in four $K$2 plates. Two indices, $R_{\rm{H\alpha}}^{'}$ and $R_{\rm{H\alpha}}^{+}$, are computed from LAMOST spectra, the former of which is derived by excluding the photospheric contributions to the $\rm{H_{\alpha}}$ lines, whi

Henghui Ding, Hui Zhang, Xudong Jiang

The deep CNNs in image semantic segmentation typically require a large number of densely-annotated images for training and have difficulties in generalizing to unseen object categories. Therefore, few-shot segmentation has been developed to perform segmentation with just a few annotated examples. In this work, we tackle the few-shot segmentation using a self

Wei Zhang

In this paper, we consider $k$-free numbers over Beatty sequences. New results are given.

Tosson Elalaily, Martin Berke, Máté Kedves, Gergő Fülöp

Understanding the microscopic origin of the gate-controlled supercurrent (GCS) in superconducting nanobridges is crucial for engineering superconducting switches suitable for a variety of electronic applications. The origin of GCS is controversial, and various mechanisms have been proposed to explain it. In this work, we have investigated the GCS in a Ta lay

Yue-Feng She, Hai-Liang Wu

In this paper, with the help of trinomial coefficients we study some arithmetic properties of certain determiants involving reciprocals of binary quadratic forms over finite fields.