May 2022 arXiv papers — page 31

Pratheek S. Upadhyaya, Aly S. Abdalla, Vuk Marojevic, Jeffrey H. Reed

Open RAN (O-RAN) defines an emerging cellular radio access network (RAN) architecture for future 6G wireless networks, emphasizing openness and intelligence which are considered the foundations of future 6G wireless networks. While the inherent complexity and flexibility of the RAN give rise to many new research problems, progress in developing solutions is

Yukio Tanaka, Bo Lu, Naoto Nagaosa

Nonreciprocal responses of noncentrosymmetric quantum materials attract recent intensive interests, which is essential for the rectification function in diodes. A recent breakthrough is the discovery of superconducting diode effect. The principle to enlarge rectification effect is highly desired to guide the design of superconducting diode. Here, we study th

Ruoxin Chen, Zenan Li, Jie Li, Chentao Wu

Bootstrap aggregating (bagging) is an effective ensemble protocol, which is believed can enhance robustness by its majority voting mechanism. Recent works further prove the sample-wise robustness certificates for certain forms of bagging (e.g. partition aggregation). Beyond these particular forms, in this paper, \emph{we propose the first collective certific

Rareş Ambrosie, Cezar Oniciuc, Ye-Lin Ou

In this paper we first prove a characterization formula for biharmonic maps in Euclidean spheres and, as an application, we construct a family of biharmonic maps from a flat $2$-dimensional torus $\mathbb{T}$ into the $3$-dimensional unit Euclidean sphere $\mathbb{S}^3$. Then, for the special case of maps between spheres whose components are given by homogen

Hui-Min Wang, Zi-Chao Lin, Shao-Wen Wei

In Einstein-{\AE}ther theory, the Lorentz symmetry is locally broken in the high-energy regime due to the presence of the{\AE}ther field. This shall leave significant imprint on astronomical observation. In this paper, we investigate the optical appearance of two types of the static and spherically symmetric black holes in Einstein-{\AE}ther theory. Via Eule

Yong Geng, Yanlan Xiao, Xinjie Han, Kun Qiu

We demonstrate polarization multiplexed dissipative Kerr solitons in an on-chip silicon nitride micro-resonator. In our experiment, TE- and TM-polarized soliton can be individually generated and controlled, thanks to their weak mutual interaction as the result of sufficiently different repetition rates and orthogonal polarization states. Furthermore, we find

Sergei V. Ketov

A novel superstring-inspired gravitational theory in four spacetime dimensions is proposed as a sum of the modified $(R+\alpha R^2)$ gravity motivated by the Starobinsky inflation and the Bel-Robinson-tensor-squared term motivated by the eleven-dimensional M-theory dimensionally reduced to four dimensions. The proposed Starobinsky-Bel-Robinson action has onl

Shayegheh Ashourizadeh, Mehrzad Saeedikiya

The authors hypothesised that export develops in the network of business collaborations that are embedded in migration status. In that, collaborative networking positively affects export performance and immigrant entrepreneurs enjoy higher collaborative networking than native entrepreneurs due to their advantage of being embedded in the home and the host cou

Sanae Amani, Tor Lattimore, András György, Lin F. Yang

We study distributed contextual linear bandits with stochastic contexts, where $N$ agents act cooperatively to solve a linear bandit-optimization problem with $d$-dimensional features over the course of $T$ rounds. For this problem, we derive the first ever information-theoretic lower bound $\Omega(dN)$ on the communication cost of any algorithm that perform

Ananya Appan, Anirudh Chandramouli, Ashish Choudhury

In this paper, we design secure multi-party computation (MPC) protocols in the asynchronous communication setting with optimal resilience. Our protocols are secure against a computationally-unbounded malicious adversary, characterized by an adversary structure $\mathcal{Z}$, which enumerates all possible subsets of potentially corrupt parties. Our protocols

Hayat Bensella, Bijan Kumar Patel, Djilali Behloul

In this paper, we explicitly find all solutions of the title Diophantine equation, using lower bounds for linear forms in logarithms and properties of continued fractions. Further, we use a version of the Baker-Davenport reduction method in Diophantine approximation, due to Dujella and Peth\"o. This paper extends the previous work of \cite{Patel}.

Alexander Moretó, Benjamin Sambale

Let G be a finite group with Sylow p-subgroup P. We show that the character table of G determines whether P has maximal nilpotency class and whether P is a minimal non-abelian group. The latter result is obtained from a precise classification of the corresponding groups G in terms of their composition factors. For p-constrained groups G we prove further that

Avishek Ghosh, Arya Mazumdar, Soumyabrata Pal, Rajat Sen

While mixture of linear regressions (MLR) is a well-studied topic, prior works usually do not analyze such models for prediction error. In fact, {\em prediction} and {\em loss} are not well-defined in the context of mixtures. In this paper, first we show that MLR can be used for prediction where instead of predicting a label, the model predicts a list of val

Dong Jing, Shuo Zhang, Song Chang, Youfang Lin

The Light Field Raindrop Removal (LFRR) aims to restore the background areas obscured by raindrops in the Light Field (LF). Compared with single image, the LF provides more abundant information by regularly and densely sampling the scene. Since raindrops have larger disparities than the background in the LF, the majority of texture details occluded by raindr

Divyam Goel, Raksha Sharma

The last few years have witnessed an exponential rise in the propagation of offensive text on social media. Identification of this text with high precision is crucial for the well-being of society. Most of the existing approaches tend to give high toxicity scores to innocuous statements (e.g., "I am a gay man"). These false positives result from over-general

Linjian Ma, Edgar Solomonik

This work discusses tensor network embeddings, which are random matrices ($S$) with tensor network structure. These embeddings have been used to perform dimensionality reduction of tensor network structured inputs $x$ and accelerate applications such as tensor decomposition and kernel regression. Existing works have designed embeddings for inputs $x$ with sp

Kantaro Honda, Shintaro Taie, Yosuke Takasu, Naoki Nishizawa

We report the observation of the sign reversal of the magnetic correlation from antiferromagnetic to ferromagnetic in a dissipative Fermi gas in double wells, utilizing the dissipation caused by on-site two-body losses in a controlled manner. We systematically measure dynamics of the nearest-neighbor spin correlation in an isolated double-well optical lattic

Lingjun Liu, Danli Wang, Lingda Xu

Considering the space-periodic perturbations, we prove the time-asymptotic stability of the composite wave of a viscous contact wave and two rarefaction waves for the Cauchy problem of 1-D compressible Navier-Stokes equations in this paper. This kind of perturbations keep oscillating at the far field and are not integrable. The key is to construct a suitable

He Xue, Dajiang Chen, Ning Zhang, Hong-Ning Dai

As an important technology to ensure data security, consistency, traceability, etc., blockchain has been increasingly used in Internet of Things (IoT) applications. The integration of blockchain and edge computing can further improve the resource utilization in terms of network, computing, storage, and security. This paper aims to present a survey on the int

Minghao Xu, Yuanfan Guo, Xuanyu Zhu, Jiawen Li

Learning self-supervised image representations has been broadly studied to boost various visual understanding tasks. Existing methods typically learn a single level of image semantics like pairwise semantic similarity or image clustering patterns. However, these methods can hardly capture multiple levels of semantic information that naturally exists in an im

Yuan Hu, Lei Chen, Zhibin Wang, Hao Li

Data-driven approaches for medium-range weather forecasting are recently shown extraordinarily promising for ensemble forecasting for their fast inference speed compared to traditional numerical weather prediction (NWP) models, but their forecast accuracy can hardly match the state-of-the-art operational ECMWF Integrated Forecasting System (IFS) model. Previ

Ruinan Li, Ran Wang, Beibei Zhang

We study Freidlin-Wentzell's large deviation principle for one dimensional nonlinear stochastic heat equation driven by a Gaussian noise: $$\frac{\partial u^\varepsilon(t,x)}{\partial t} = \frac{\partial^2 u^\varepsilon(t,x)}{\partial x^2}+\sqrt{\varepsilon} \sigma(t, x, u^\varepsilon(t,x))\dot{W}(t,x),\quad t> 0,\, x\in\mathbb{R},$$ where $\dot W$ is white

Jinchuan Bai, Yong Luo

Let $M^n$ be an $n$-dimensional complete and locally conformally flat hypersurface in the unit sphere $\mathbb{S}^{n+1}$ with constant scalar curvature $n(n-1)$. We show that if the total curvature $\left( \int _ { M } | H | ^ { n } d v \right) ^ { \frac { 1 } { n } }$ of $M$ is sufficiently small, then $M^n$ is totally geodesic.

Euijin Choo, Mohamed Nabeel, Ravindu De Silva, Ting Yu

VirusTotal (VT) provides aggregated threat intelligence on various entities including URLs, IP addresses, and binaries. It is widely used by researchers and practitioners to collect ground truth and evaluate the maliciousness of entities. In this work, we provide a comprehensive analysis of VT URL scanning reports containing the results of 95 scanners for 1.

Ming-Hung Wang, Wei-Yang Chang, Kuan-Hung Kuo, Kuo-Yu Tsai

With the increasing popularity of social network services, paradigm-shifting has occurred in political communication. Politicians, candidates, and political organizations establish their fan pages to interact with online citizens. Initially, they publish text-only content on sites; then, they create multimedia content such as photos, images, and videos to ap

Namita Uppal, Shashikiran Ganesh, D. Bisht

We present the optical linear polarization observation of stars towards the core of the Czernik 3 cluster in the Sloan i-band. The data were obtained using the EMPOL instrument on the 1.2 m telescope at Mount Abu Observatory. We study the dust distribution towards this cluster by combining the results from our polarization observations with the data from Gai

Yi Huang, Adams Wai-Kin Kong

The vulnerability of deep neural networks to adversarial examples has drawn tremendous attention from the community. Three approaches, optimizing standard objective functions, exploiting attention maps, and smoothing decision surfaces, are commonly used to craft adversarial examples. By tightly integrating the three approaches, we propose a new and simple al

Yongxin Zeng, Nemin Wei, Allan H. MacDonald

Spontaneous order of layer pseudospins in two-dimensional bilayers is common in quantum Hall systems, where it is responsible for hysteretic responses to gate fields in states with Ising order, and giant drag voltages in states with XY (spontaneous inter-layer phase coherence) order. In this article we predict that layer pseudospin order will also occur in d

Tiancheng Zhi, Bowei Chen, Ivaylo Boyadzhiev, Sing Bing Kang

We describe a novel approach to decompose a single panorama of an empty indoor environment into four appearance components: specular, direct sunlight, diffuse and diffuse ambient without direct sunlight. Our system is weakly supervised by automatically generated semantic maps (with floor, wall, ceiling, lamp, window and door labels) that have shown success o

Qiwei Yu, Yuhai Tu

We study the energy cost of flocking in the active Ising model (AIM) and show that besides the energy cost for self-propelled motion, an additional energy dissipation is required to power the alignment of spins. We find that this additional alignment dissipation reaches its maximum at the flocking transition point in the form of a cusp with a discontinuous f

Surya Teja Chavali, Charan Tej Kandavalli, Sugash T M

Grammar Detection, also referred to as Parts of Speech Tagging of raw text, is considered an underlying building block of the various Natural Language Processing pipelines like named entity recognition, question answering, and sentiment analysis. In short, forgiven a sentence, Parts of Speech tagging is the task of specifying and tagging each word of a sente

Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford

Learned representations are a central component in modern ML systems, serving a multitude of downstream tasks. When training such representations, it is often the case that computational and statistical constraints for each downstream task are unknown. In this context rigid, fixed capacity representations can be either over or under-accommodating to the task

Dongwon Son

Although, in the task of grasping via a data-driven method, closed-loop feedback and predicting 6 degrees of freedom (DoF) grasp rather than conventionally used 4DoF top-down grasp are demonstrated to improve performance individually, few systems have both. Moreover, the sequential property of that task is hardly dealt with, while the approaching motion nece

Sergei Artemov

Traditionally, Epistemic Logic represents epistemic scenarios using a single model. This, however, covers only complete descriptions that specify truth values of all assertions. Indeed, many -- and perhaps most -- epistemic descriptions are not complete. Syntactic Epistemic Logic, SEL, suggests viewing an epistemic situation as a set of syntactic conditions

Jinpeng An, Shaobo Gan, Ruihao Gu, Yi Shi

Let $f$ be a non-invertible irreducible Anosov map on $d$-torus. We show that if the stable bundle of $f$ is one-dimensional, then $f$ has the integrable unstable bundle, if and only if, every periodic point of $f$ admits the same Lyapunov exponent on the stable bundle with its linearization. For higher-dimensional stable bundle case, we get the same result

Shuhei A. Horiguchi, Tetsuya J. Kobayashi

In multicellular systems, the single-cell behaviors should be coordinated consistently with the overall population dynamics and functions. However, the interrelation between single-cell rules and the population-level goal is still elusive. In this work, we reveal that these two levels are naturally connected via a gradient flow structure of the heterogeneous

Andrey G. Tlatov

On modern satellite observations of the Sun in the continuum with high spatial resolution, as well as on high-quality ground observations, a large number of small dark areas can be observed. These regions have no penumbra, have a contrast of up to 20% and are similar to solar pores. The characteristic area of such structures is $0.3\div5\ \mu$hm or $0.5\div5

Takafumi D. Yamamoto, Takeya Hiroyuki, Pedro Baptista de Castro, Akiko T. Saito

We fabricate gas-atomized particles by inductively melting electrode rods of HoB2-x (x = -0.3, 0, 0.3, and 1.0) and investigate the effect of non-stoichiometry on the phase fraction, microstructure, and physical properties. Shifting the stoichiometric ratio of the electrode rod to the B (Ho)-rich side increases HoB4 (Ho) phase in the resulting atomized parti

Sahory Canseco J., Andrea Valdés-Hernández

We consider the simplest identical-fermion system that exhibits the phenomenon of entanglement (beyond exchange correlations) to analyze its speed of evolution towards an orthogonal state, and revisit the relation between this latter and the amount of fermionic entanglement. A characterization of the quantum speed limit and the orthogonality times is perform

Yuexin Wu, Xiaolei Huang

Class imbalance naturally exists when train and test models in different domains. Unsupervised domain adaptation (UDA) augments model performance with only accessible annotations from the source domain and unlabeled data from the target domain. However, existing state-of-the-art UDA models learn domain-invariant representations and evaluate primarily on clas

Kevin L. G. Parkin

Laser-accelerated lightsails enable new types of missions that are very different from the Breakthrough Starshot mission to the Centauri system that aims to send 1 gram of payload at 0.2 c. The present work widens the mission design space to 0.1 mg to 100 kt payload and 0.0001-0.99 c cruise velocity. Drawing up to 5 GW directly from the grid (to augment powe

Jihao Liu, Xin Huang, Jinliang Zheng, Yu Liu

In this paper, we propose Mixed and Masked AutoEncoder (MixMAE), a simple but efficient pretraining method that is applicable to various hierarchical Vision Transformers. Existing masked image modeling (MIM) methods for hierarchical Vision Transformers replace a random subset of input tokens with a special [MASK] symbol and aim at reconstructing original ima

Rianna Bell, Khaled Said, Tamara Davis, T. H. Jarrett

In this paper, we present our calibrations of the TF relation in the mid-infrared W1 ($3.4\mu$m) and W2 ($4.6\mu$m) bands, using large samples 848 galaxies and 857 galaxies in the W1 and W2 bands respectively. In this calibration we performed a correction for the cluster population incompleteness bias, and a morphological type correction. The calibration was

Yun Chang, Kamak Ebadi, Christopher E. Denniston, Muhammad Fadhil Ginting

Search and rescue with a team of heterogeneous mobile robots in unknown and large-scale underground environments requires high-precision localization and mapping. This crucial requirement is faced with many challenges in complex and perceptually-degraded subterranean environments, as the onboard perception system is required to operate in off-nominal conditi

Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun

Nonlinear dynamics is ubiquitous in nature and commonly seen in various science and engineering disciplines. Distilling analytical expressions that govern nonlinear dynamics from limited data remains vital but challenging. To tackle this fundamental issue, we propose a novel Symbolic Physics Learner (SPL) machine to discover the mathematical structure of non

Changzhu Liu, Ruisi He, Yong Niu, Bo Ai

Reconfigurable intelligent surface (RIS) has received increasing attention due to its capability of extending cell coverage by reflecting signals toward receivers. This paper considers a RIS-assisted high-speed train (HST) communication system to improve the coverage probability. We derive the closed-form expression of coverage probability. Moreover, we anal

Marion Scheepers

We consider the preservation under products, finite powers, and forcing, of a selection principle based covering property of $T_0$ topological groups. Though the paper is in part a survey, it contributes some new information, including: 1. The product of a strictly o-bounded group with an o-bounded group is an o-bounded group - Corollary 18 2. In the generic

Rafael B. Audibert, Henrique Lemos, Pedro Avelar, Anderson R. Tavares

Artificial Intelligence is now recognized as a general-purpose technology with ample impact on human life. This work aims at understanding the evolution of AI and, in particular Machine learning, from the perspective of researchers' contributions to the field. In order to do so, we present several measures allowing the analyses of AI and machine learning res

Oleksii Sokoliuk, Alexander Baransky, P. K. Sahoo

For the spherically symmetric static traversable wormholes, supported by the Casimir energy in $f(\mathcal{R})=\mathcal{R}+\alpha \mathcal{R}^2$ Quadratic, $f(\mathcal{R})=f_0 \mathcal{R}^n$ power-law Modified Gravity (MOG) theories we investigate energy conditions and dynamical stability of the wormhole solutions. Especially, we study Zero Tidal Forces (ZTF

Kamil Khan, Sudeep Pasricha, Ryan Gary Kim

Network-on-chip (NoC) architectures rely on buffers to store flits to cope with contention for router resources during packet switching. Recently, reversible multi-function channel (RMC) buffers have been proposed to simultaneously reduce power and enable adaptive NoC buffering between adjacent routers. While adaptive buffering can improve NoC performance by

Sixian Wang, Jincheng Dai, Zijian Liang, Kai Niu

In this paper, we design a new class of high-efficiency deep joint source-channel coding methods to achieve end-to-end video transmission over wireless channels. The proposed methods exploit nonlinear transform and conditional coding architecture to adaptively extract semantic features across video frames, and transmit semantic feature domain representations

Mingshi Yan, Zhiyong Cheng, Chen Gao, Jing Sun

Multi-behavior recommendation exploits multiple types of user-item interactions to alleviate the data sparsity problem faced by the traditional models that often utilize only one type of interaction for recommendation. In real scenarios, users often take a sequence of actions to interact with an item, in order to get more information about the item and thus

Soojin Park, Suyeon Kang, Chioun Lee, Shujie Ma

A key objective of decomposition analysis is to identify a factor (the 'mediator') contributing to disparities in an outcome between social groups. In decomposition analysis, a scholarly interest often centers on estimating how much the disparity (e.g., health disparities between Black women and White men) would be reduced/remain if we set the mediator (e.g.

Yi Chen, Wei Ruan, Jeffrey D. Cain, Ryan L. Lee

The interplay between electron-electron interactions and structural ordering can yield exceptionally rich correlated electronic phases. We have used scanning tunneling microscopy to investigate bulk 1T-TaSe2 and have uncovered surprisingly diverse correlated surface states thereof. These surface states exhibit the same in-plane charge density wave ordering b

Peipei Zhu, Xiao Wang, Lin Zhu, Zhenglong Sun

Unpaired Image Captioning (UIC) has been developed to learn image descriptions from unaligned vision-language sample pairs. Existing works usually tackle this task using adversarial learning and visual concept reward based on reinforcement learning. However, these existing works were only able to learn limited cross-domain information in vision and language

Heng Zhou, Chunna Tian, Zhenxi Zhang, Chengyang Li

A key challenge of infrared small target segmentation (ISTS) is to balance false negative pixels (FNs) and false positive pixels (FPs). Traditional methods combine FNs and FPs into a single objective by weighted sum, and the optimization process is decided by one actor. Minimizing FNs and FPs with the same strategy leads to antagonistic decisions. To address

Gabriel Cáceres-Aravena, Diego Guzmán-Silva, Ignacio Salinas, Rodrigo A. Vicencio

The induction of synthetic magnetic fields on lattice structures allows to effectively control their localization and transport properties. In this work, we generate effective $\pi$ magnetic fluxes on a multi-orbital diamond lattice, where first ($S$) and second ($P$) order modes effectively interact. We implement a $z$-scan method on femtosecond laser writt

Bijie Bai, Yi Luo, Tianyi Gan, Jingtian Hu

Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing problem by, e.g., encrypting camera images or obscuring/blurring the imaged information through digital algorithms. Here, we demonstrate a camera design that performs class-specif

Zhitao Zhu, Shijing Si, Jianzong Wang, Jing Xiao

The increasingly stringent regulations on privacy protection have sparked interest in federated learning. As a distributed machine learning framework, it bridges isolated data islands by training a global model over devices while keeping data localized. Specific to recommendation systems, many federated recommendation algorithms have been proposed to realize

Jun Wang, Sixian Wang, Jincheng Dai, Zhongwei Si

As one novel approach to realize end-to-end wireless image semantic transmission, deep learning-based joint source-channel coding (deep JSCC) method is emerging in both deep learning and communication communities. However, current deep JSCC image transmission systems are typically optimized for traditional distortion metrics such as peak signal-to-noise rati

Omkar Patil, Rahul Singh, Tarun Joshi

Paraphrase generation is a difficult problem. This is not only because of the limitations in text generation capabilities but also due that to the lack of a proper definition of what qualifies as a paraphrase and corresponding metrics to measure how good it is. Metrics for evaluation of paraphrasing quality is an on going research problem. Most of the existi

Seungjoon Lee, Yorgos M. Psarellis, Constantinos I. Siettos, Ioannis G. Kevrekidis

We propose a machine learning framework for the data-driven discovery of macroscopic chemotactic Partial Differential Equations (PDEs) -- and the closures that lead to them -- from high-fidelity, individual-based stochastic simulations of E.coli bacterial motility. The fine scale, detailed, hybrid (continuum - Monte Carlo) simulation model embodies the under

Shao-Long Chen, Yu-Qi Xiao

We study the neutrinoless double beta decay in the colored Zee-Babu model. We consider three cases of the colored Zee-Babu model with a leptoquark and a diquark introduced. The neutrino masses are generated at two-loop level, and the constraints given by tree-level flavor violation processes and muon anomalous magnetic moment $(g-2)_{\mu}$ have been consider

Junfu Liu, Di Qiu, Pengfei Yan, Xiaolin Wei

Face clustering plays an essential role in exploiting massive unlabeled face data. Recently, graph-based face clustering methods are getting popular for their satisfying performances. However, they usually suffer from excessive memory consumption especially on large-scale graphs, and rely on empirical thresholds to determine the connectivities between sample

Armin Aligholian, Hamed Mohsenian-Rad

This paper is concerned with the complex task of identifying the type and cause of the events that are captured by distribution-level phasor measurement units (D-PMUs) in order to enhance situational awareness in power distribution systems. Our goal is to address two fundamental challenges in this field: a) scarcity in measurement locations due to the high c

Jaemin Cho, Seunghyun Yoon, Ajinkya Kale, Franck Dernoncourt

Modern image captioning models are usually trained with text similarity objectives. However, since reference captions in public datasets often describe the most salient common objects, models trained with text similarity objectives tend to ignore specific and detailed aspects of an image that distinguish it from others. Toward more descriptive and distinctiv

Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli, Orestis Papadigenopoulos

Pandora's Box is a fundamental stochastic optimization problem, where the decision-maker must find a good alternative while minimizing the search cost of exploring the value of each alternative. In the original formulation, it is assumed that accurate distributions are given for the values of all the alternatives, while recent work studies the online variant

Yuhang Chen, Renwang Li, Chong Han, Shu Sun

Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for 6G and beyond Terahertz (0.1-10 THz) communications, to effectively bypass the barriers of limited coverage and line-of-sight blockage. However, excessive dimensions of UM-MIMO and IRS enlarge the near-field region, while stron

Hidetoshi Masuda, Takeshi Seki, Yoichi Nii, Hiroto Masuda

Helimagnetic structures, in which the magnetic moments are spirally ordered, host an internal degree of freedom called chirality (or helicity) corresponding to the handedness of the helix. The chirality seems quite robust against disturbances and is therefore promising for next-generation magnetic memory. While the chirality control was recently achieved by

Xuhui Zhang, Jose Blanchet, Youssef Marzouk, Viet Anh Nguyen

We study a distributionally robust optimization formulation (i.e., a min-max game) for two representative problems in Bayesian nonparametric estimation: Gaussian process regression and, more generally, linear inverse problems. Our formulation seeks the best mean-squared error predictor, in an infinite-dimensional space, against an adversary who chooses the w

Justin Forlano

We study the real-valued modified KdV equation on the real line and the circle, in both the focusing and the defocusing case. By employing the method of commuting flows introduced by Killip and Vi\c{s}an (2019), we prove global well-posedness in $H^{s}$ for $0\leq s<\tfrac{1}{2}$. On the line, we show how the arguments in the recent paper by Harrop-Griffiths

Lavanya Umapathy, Zhiyang Fu, Rohit Philip, Diego Martin

Obtaining manual annotations for large datasets for supervised training of deep learning (DL) models is challenging. The availability of large unlabeled datasets compared to labeled ones motivate the use of self-supervised pretraining to initialize DL models for subsequent segmentation tasks. In this work, we consider two pre-training approaches for driving

Seongmin Park, Jihwa Lee

We advance the state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs. Starting from well-founded assumptions about word graphs, we present simple but reliable path-reranking and topic segmentation schemes. Robustness of our method is demonstrated on datasets across multiple domains, including meeti

Hao Lee

Let $G$ be a $p$-adic Lie group associated to a connected reductive group over $\mathbb{Q}_{p}$. Let $P$ be a parabolic subgroup of $G$ and let $M$ be a Levi quotient of $P$. In this paper, we define a $\delta$-functor $H^{\star}J_{P}$ from the category of admissible locally analytic $G$-representations to the category of essentially admissible locally analy

Yi Cui, Y. Fan, Z. Hu, Zhangzhen He

We investigate the low-temperature properties of the Ising-like screw chain antiferromagnet SrCo$_2$V$_2$O$_8$ under a longitudinal magnetic field by susceptibility and $^{51}$V NMR measurements. The bulk susceptibility $\chi$ shows an onset of long-range Ising-antiferromagnetic (AFM) order and the suppression of the order by field with the N\'{e}el temperat

Raluca M. Balan, Wangjun Yuan

In this article, we investigate the asymptotic behaviour of the spatial integral of the solution to the parabolic Anderson model with time independent noise in dimension $d\geq 1$, as the domain of the integral becomes large. We consider 3 cases: (a) the case when the noise has an integrable covariance function; (b) the case when the covariance of the noise

Tao Li, Zhehao Huang, Yingwen Wu, Zhengbao He

Weight averaging is a widely used technique for accelerating training and improving the generalization of deep neural networks (DNNs). While existing approaches like stochastic weight averaging (SWA) rely on pre-set weighting schemes, they can be suboptimal when handling diverse weights. We introduce Trainable Weight Averaging (TWA), a novel optimization met

Bingcheng Yu, Jiangjian Shi, Yiming Li, Shan Tan

Operational stability of perovskite solar cells is remarkably influenced by the device temperature, therefore, decreasing the interior temperature of the device is one of the most effective approaches to prolong the service life. Herein, we introduce the spontaneous radiative cooling effect into the perovskite solar cell and amplified this effect via functio

Patrick Kin Man Tung, Amalia Yunita Halim, Huixin Wang, Anne Rich

The rapid development of X-ray micro-computed tomography (micro-CT) opens new opportunities for 3D analysis of particle and grain-size characterisation, determination of particle densities and shape factors, estimation of mineral associations and liberation and locking. Current practices in mineral liberation analysis are based on 2D representations leading

I. Mahboob, H. Toida, K. Kakuyanagi, Y. Nakamura

A Josephson parametric amplifier (JPA) is executed in a three-dimensional (3D) microwave cavity by coupling it to a superconducting quantum interference device (SQUID) that is embedded in a two-dimensional resonator. The JPA is activated in a three-wave mixing configuration by injecting ac magnetic flux, at twice the 3D cavity frequency, into the SQUID. An 8

Man Ho Chan, Chak Man Lee

Recent radio observations have obtained stringent constraints for annihilating dark matter. In this article, we use the radio continuum spectral data of the Large Magellanic Cloud (LMC) to analyze the dark matter annihilation signals. We have discovered a slightly positive signal of dark matter annihilation with a $1.5\sigma$ statistical significance. The ov

Alex Milham, Christopher L. Rogers

Complete filtered $A_\infty$-algebras model certain deformation problems in the noncommutative setting. The formal deformation theory of a group representation is a classical example. With such applications in mind, we provide the $A_\infty$ analogs of several key theorems from the Maurer-Cartan theory for $L_\infty$-algebras. In contrast with the $L_\infty$

Yifei Wang, Peng Chen, Mert Pilanci, Wuchen Li

The computation of Wasserstein gradient direction is essential for posterior sampling problems and scientific computing. The approximation of the Wasserstein gradient with finite samples requires solving a variational problem. We study the variational problem in the family of two-layer networks with squared-ReLU activations, towards which we derive a semi-de

Kan Takase, Akito Kawasaki, Byung Kyu Jeong, Takahiro Kashiwazaki

Controlling the waveform of light is the key for a versatile light source in classical and quantum electronics. Although pulse shaping of classical light is a mature technique and has been used in various fields, more advanced applications would be realized by a light source that generates arbitrary quantum light with arbitrary temporal waveform. We call suc

Arunima Bhattacharya, Connor Mooney, Ravi Shankar

In this paper, we prove interior gradient estimates for the Lagrangian mean curvature equation, if the Lagrangian phase is critical and supercritical and $C^{2}$. Combined with the a priori interior Hessian estimates proved in [Bha21, Bha22], this solves the Dirichlet boundary value problem for the critical and supercritical Lagrangian mean curvature equatio

Faraz Waseem, Sanjit Menon, Haotian Xu, Debashis Mondal

Traditional vision based Automated Optical Inspection (referred to as AOI in paper) systems present multiple challenges in factory settings including inability to scale across multiple product lines, requirement of vendor programming expertise, little tolerance to variations and lack of cloud connectivity for aggregated insights. The lack of flexibility in t

Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto

While a broad range of techniques have been proposed to tackle distribution shift, the simple baseline of training on an $\textit{undersampled}$ balanced dataset often achieves close to state-of-the-art-accuracy across several popular benchmarks. This is rather surprising, since undersampling algorithms discard excess majority group data. To understand this

Anvay Patil, Christian M. Heil, Bram Vanthournout, Saranshu Singla

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorpti

Tao Pu, Tianshui Chen, Hefeng Wu, Yukai Shi

Despite achieving impressive progress, current multi-label image recognition (MLR) algorithms heavily depend on large-scale datasets with complete labels, making collecting large-scale datasets extremely time-consuming and labor-intensive. Training the multi-label image recognition models with partial labels (MLR-PL) is an alternative way, in which merely so

Yang Wang, Alexander N. Craddock, Rourke Sekelsky, Mael Flament

High-performance quantum memories are an essential component for regulating temporal events in quantum networks. As a component in quantum-repeaters, they have the potential to support the distribution of entanglement beyond the physical limitations of fiber loss. This will enable key applications such as quantum key distribution, network-enhanced quantum se

Sudesh Pathak, Gagan Dangi, Farhad Farzbod

Periodic structures are a type of metamaterial in which the physical properties depend not only on the details of the unit cell but also on how unit cells are arranged and interact with each other. In conventional engineering structures, each unit cell interacts with adjacent cells. Methods developed for vibrational and wave propagation analysis in periodic

Marco Bellini, Hyukjoon Kwon, Nicola Biagi, Saverio Francesconi

The principle of microscopic reversibility lies at the core of fluctuation theorems, which have extended our understanding of the second law of thermodynamics to the statistical level. In the quantum regime, however, this elementary principle should be amended as the system energy cannot be sharply determined at a given quantum phase space point. In this Let

Qi Li, Khalique Newaz, Tijana Milenković

Identification of human genes involved in the aging process is critical due to the incidence of many diseases with age. A state-of-the-art approach for this purpose infers a weighted dynamic aging-specific subnetwork by mapping gene expression (GE) levels at different ages onto the protein-protein interaction network (PPIN). Then, it analyzes this subnetwork

Hao Chen

Sum-rank-metric codes have wide applications in universal error correction, multishot network coding, space-time coding and the construction of partial-MDS codes for repair in distributed storage. Fundamental properties of sum-rank-metric codes have been studied and some explicit or probabilistic constructions of good sum-rank-metric codes have been proposed

Yashish M. Siriwardena, Ahmed Adel Attia, Ganesh Sivaraman, Carol Espy-Wilson

Data augmentation has proven to be a promising prospect in improving the performance of deep learning models by adding variability to training data. In previous work with developing a noise robust acoustic-to-articulatory speech inversion system, we have shown the importance of noise augmentation to improve the performance of speech inversion in noisy speech

Eric V. Strobl, Thomas A. Lasko

Complex diseases are caused by a multitude of factors that may differ between patients even within the same diagnostic category. A few underlying root causes may nevertheless initiate the development of disease within each patient. We therefore focus on identifying patient-specific root causes of disease, which we equate to the sample-specific predictivity o

Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang

Detecting fraudulent transactions is an essential component to control risk in e-commerce marketplaces. Apart from rule-based and machine learning filters that are already deployed in production, we want to enable efficient real-time inference with graph neural networks (GNNs), which is useful to catch multihop risk propagation in a transaction graph. Howeve

L. M. Rebull, J. R. Stauffer, L. A. Hillenbrand, A. M. Cody

We present stellar rotation rates derived from Transiting Exoplanet Survey Satellite (TESS) light curves for stars in Upper Centaurus-Lupus (UCL; ~136 pc, ~16 Myr) and Lower Centaurus-Crux (LCC; ~115 pc, ~17 Myr). We find spot-modulated periods (P) for ~90% of members. The range of light curve and periodogram shapes echoes that found for other clusters with

A. Poci, R. M. McDermid, M. Lyubenova, I. Martin-Navarro

[arXiv Abridged] In this work, we explore new spatially-resolved measurements of the IMF for three edge-on lenticular galaxies in the Fornax cluster. Specifically, we utilise existing orbit-based dynamical models, which re-produce the measured stellar kinematics, in order to fit the new IMF maps within this orbital framework. We then investigate correlations

Daniel Munoz George, James A. Mingo

We compute the third order moments of a complex Wigner matrix. We provide a formula for the third order moments $\alpha_{m_1,m_2,m_3}$ in terms of quotient graphs $T_{m_1,m_2,m_3}^{\pi}$ where $\pi$ is the Kreweras complement of a non-crossing pairing on the annulus. We prove that these graphs can be counted using the set of partitioned permutations, this pe