November 2022 arXiv papers — page 24

Zihan Chen, Ziyue Wang, Junjie Huang, Wentao Zhao

Adding perturbations via utilizing auxiliary gradient information or discarding existing details of the benign images are two common approaches for generating adversarial examples. Though visual imperceptibility is the desired property of adversarial examples, conventional adversarial attacks still generate traceable adversarial perturbations. In this paper,

Zhengfu He, Tianxiang Sun, Kuanning Wang, Xuanjing Huang

We present DiffusionBERT, a new generative masked language model based on discrete diffusion models. Diffusion models and many pre-trained language models have a shared training objective, i.e., denoising, making it possible to combine the two powerful models and enjoy the best of both worlds. On the one hand, diffusion models offer a promising training stra

Li Yuan, Yi Cai, Jin Wang, Qing Li

Multimodal named entity recognition (MNER) and multimodal relation extraction (MRE) are two fundamental subtasks in the multimodal knowledge graph construction task. However, the existing methods usually handle two tasks independently, which ignores the bidirectional interaction between them. This paper is the first to propose jointly performing MNER and MRE

Xiaoquan Xu

In this paper, we mainly investigate the conditions under which the Scott topology on the product of two posets is equal to the product of the individual Scott topologies and under which the Scott topology on a dcpo is sober. Some such conditions are given.

Chin-Yuan Ong, Chun-Shing Lee, Xin-Yuan Gao, Qiang Zhai

Glass formers are in general classified as strong or fragile depending on whether their relaxation rates follow Arrhenius or super-Arrhenius temperature dependence. There are however notable exceptions such as water, which exhibit a fragile-to-strong (FTS) transition and behave as fragile and strong respectively at high and low temperatures. In this work, th

Pilhwa Lee

We consider Biot model with block preconditioners and generalized eigenvalue problems for scalability and robustness to parameters. A discontinuous Galerkin discretization is employed with the displacement and Darcy flow flux discretized as piecewise continuous in $P_1$ elements, and the pore pressure as piecewise constant in the $P_0$ element with a stabili

Jie Xu

In this article, we first show that given a smooth function $ S $ either on closed manifolds $ (M, g) $ or compact manifolds $ (\bar{M}, g) $ with non-empty boundary, both for dimensions at least $ 3 $, the condition $ S \equiv 0 $, or $ S $ changes sign and $ \int_{M} S \dvol < 0 $ (with zero mean curvature if the boundary is not empty), is both the necessa

Pilhwa Lee

Dual-Primal Finite Element Tearing and Interconnecting (FETI-DP) algorithms are developed for a 2D Biot model. The model is formulated with mixed-finite elements as a saddle-point problem. The displacement $\mathbf{u}$ and the Darcy flux flow $\mathbf{z}$ are represented with $P_1$ piecewise continuous elements and pore-pressure $p$ with $P_0$ piecewise cons

Hongjie Zhang

Deep reinforcement learning has achieved great success in various fields with its super decision-making ability. However, the policy learning process requires a large amount of training time, causing energy consumption. Inspired by the redundancy of neural networks, we propose a lightweight parallel training framework based on neural network compression, Acc

Ernan Li, Fandong Meng, Jie Zhou

This paper introduces WeChat's participation in WMT 2022 shared biomedical translation task on Chinese to English. Our systems are based on the Transformer, and use several different Transformer structures to improve the quality of translation. In our experiments, we employ data filtering, data generation, several variants of Transformer, fine-tuning and mod

Avik Roy

In recent years, digital object management practices to support findability, accessibility, interoperability, and reusability (FAIR) have begun to be adopted across a number of data-intensive scientific disciplines. These digital objects include datasets, AI models, software, notebooks, workflows, documentation, etc. With the collective dataset at the Large

Manzi Huang, Zhihao Xu

In this paper, we first prove that any power quasi-symmetry of two metric spaces induces a rough quasi-isometry between their infinite hyperbolic cones. Second, we prove that for a complete metric space $Z$, there exists a point $\omega$ in the Gromov boundary of its infinite hyperbolic cone such that $Z$ can be seen as the Gromov boundary relative to $\omeg

Minwoo Kim, Jonghyeok Lee, Seung Woo Kwak, Sungkyu Jung

Differential privacy (DP) has become a rigorous central concept for privacy protection in the past decade. We use Gaussian differential privacy (GDP) in gauging the level of privacy protection for releasing statistical summaries from data. The GDP is a natural and easy-to-interpret differential privacy criterion based on the statistical hypothesis testing fr

Jian Sun, Bo Fu

Causal inference in observational studies can be challenging when confounders are subject to missingness. Generally, the identification of causal effects is not guaranteed even under restrictive parametric model assumptions when confounders are missing not at random. To address this, We propose a general framework to establish the identification of causal ef

Wenming Hong, Shengli Liang

We consider a random walk $\{S_n\}_{n\in \mathbb{N}}$ in time-inhomogeneous random environment $\xi$. For almost each realization of $\xi$, we formulate a quenched harmonic function, based on which we can define the random walk in random environment conditioned to stay positive by the Doob's $h$-transform. Furthermore, we prove a quenched invariance principl

Christof Gattringer

Worldline representations were established as a powerful tool for studying bosonic lattice field theories at finite density. For fermions, however, the worldlines still may carry signs that originate from the Dirac algebra and from the Grassmann nature of the fermion fields. We show that a density of states approach can be set up to deal with this remaining

Michael J. Hertaeg, Suzanne M. Fielding, Dapeng Bi

During embryonic morphogenesis, tissues undergo dramatic deformations in order to form functional organs. Similarly, in adult animals, living cells and tissues are continually subjected to forces and deformations. Therefore, the success of embryonic development and the proper maintenance of physiological functions rely on the ability of cells to withstand me

Yasuki Tada

E. Bunch, P. Lofgren, A. Rapp and D. N. Yetter [J. Knot theory Ramifications (2010)] pointed out that by considering inner automorphism groups of quandles, one have a functor from the category of quandles with surjective homomorphisms to that of groups with surjective homomorphisms. In this paper, we focus on faithful quandles. As main results, we give categ

Anichur Rahman, Md. Jahidul Islam, Rafiqul Islam, Ayesha Aziz

Blockchain (BC) and Software Defined Networking (SDN) are some of the most prominent emerging technologies in recent research. These technologies provide security, integrity, as well as confidentiality in their respective applications. Cloud computing has also been a popular comprehensive technology for several years. Confidential information is often shared

Soon Wei Daniel Lim, Joon-Suh Park, Dmitry Kazakov, Christina M. Spaegele

Phase singularities are loci of darkness surrounded by monochromatic light in a scalar field, with applications in optical trapping, super-resolution imaging, and structured light-matter interactions. Although 1D singular structures, such as optical vortices, are the most common due to their robust topological properties, uncommon 0D (point) and 2D (sheet) s

Jie Qin

We make a progress towards describing the semi-commutants of Toeplitz operators on Fock-Sobolev spaces of nonnegative orders. We generalize the results in \cite{Bauer1,Qin}. For the certain symbol spaces, we obtain two Toeplitz operators can semi-commute only in the trivial cases, which is different from what is known for the classical Fock spaces. As an app

Daniel López Neumann, Roland van der Veen

By twisted quantum invariants we mean polynomial invariants of knots in the three-sphere endowed with a representation of the fundamental group into the automorphism group of a Hopf algebra $H$. These are obtained by the Reshetikhin-Turaev construction extended to the $\mathrm{Aut}(H)$-twisted Drinfeld double of $H$, provided $H$ is finite dimensional and $\

Yunlong Liang, Fandong Meng, Jinan Xu, Yufeng Chen

This paper introduces the joint submission of the Beijing Jiaotong University and WeChat AI to the WMT'22 chat translation task for English-German. Based on the Transformer, we apply several effective variants. In our experiments, we utilize the pre-training-then-fine-tuning paradigm. In the first pre-training stage, we employ data filtering and synthetic da

Kohei Shinohara, Atsushi Togo, Isao Tanaka

A crystal symmetry search is crucial for computational crystallography and materials science. Although algorithms and implementations for the crystal symmetry search have been developed, their extension to magnetic space groups (MSGs) remains limited. In this paper, algorithms for determining magnetic symmetry operations of magnetic crystal structures, ident

Dong Wang, Patanamon Thongtanunam, Raula Gaikovina Kula, Kenichi Matsumoto

Contemporary development projects benefit from code review as it improves the quality of a project. Large ecosystems of inter-dependent projects like OpenStack generate a large number of reviews, which poses new challenges for collaboration (improving patches, fixing defects). Review tools allow developers to link between patches, to indicate patch dependenc

Michiel A. Bakker, Martin J. Chadwick, Hannah R. Sheahan, Michael Henry Tessler

Recent work in large language modeling (LLMs) has used fine-tuning to align outputs with the preferences of a prototypical user. This work assumes that human preferences are static and homogeneous across individuals, so that aligning to a a single "generic" user will confer more general alignment. Here, we embrace the heterogeneity of human preferences to co

Maolin Bo, Hanze Li, Zhihong Wang, Yunqian Zhong

The ground state energy is great importance for studying the properties of a material. In this study, we computed both the Hartree-Fock approximation and the random phase approximation of the ground state energy. Considering the effect of the electrostatic shielding potential, we utilized the Thomas-Fermi dielectric function to obtain the Thomas-Fermi formul

Régis de la Bretèche, Gérald Tenenbaum

Hildebrand proved that the smooth approximation for the number $\Psi(x,y)$ of $y$-friable integers not exceeding $x$ holds for $y>(\log x)^{2+\varepsilon}$ under the Riemann hypothesis and conjectured that it fails when $y\leqslant (\log x)^{2-\varepsilon}$. This conjecture has been recently confirmed by Gorodetsky by an intricate argument. We propose a shor

Shuo Liang, Wei Wei, Xian-Ling Mao, Yuanyuan Fu

Aspect Sentiment Triplet Extraction (ASTE) has become an emerging task in sentiment analysis research, aiming to extract triplets of the aspect term, its corresponding opinion term, and its associated sentiment polarity from a given sentence. Recently, many neural networks based models with different tagging schemes have been proposed, but almost all of them

Yu Ren, Xiaoling Zhang, Xu Zhan, Jun Shi

Deep learning (DL)-based tomographic SAR imaging algorithms are gradually being studied. Typically, they use an unfolding network to mimic the iterative calculation of the classical compressive sensing (CS)-based methods and process each range-azimuth unit individually. However, only one-dimensional features are effectively utilized in this way. The correlat

Jonathan Schirmer, J. K. Jain, C. -X. Liu

Topological superconductors support Majorana modes, which are quasiparticles that are their own antiparticles and which obey non-Abelian statistics in which successive exchanges of particles do not always commute. Here we investigate whether a two-dimensional superconductor with ordinary s-wave pairing can be rendered topological by the application of a stro

Carly A. Bobak, Yifan Zhao, Joshua J. Levy, A. James O'Malley

Protecting medical privacy can create obstacles in the analysis and distribution of healthcare graphs and statistical inferences accompanying them. We pose a graph simulation model which generates networks using degree and property augmentation (GRANDPA) and provide a flexible R package that allows users to create graphs that preserve vertex attribute relati

Peiji Zhou, Ting Li, Yucheng Lin, Lipeng Xia

Dense waveguide arrays with half-wavelength-pitch, low-crosstalk, broadband, and flexible routing capability are essential for integrated photonics. However, achieving such performance is challenging due to the relatively weaker confinement of dielectric waveguides and the increased interactions among densely packed waveguides. Here, leveraging the artificia

Mingyu Park, Jaeuk Shin, Insoon Yang

Partially observable Markov decision processes (POMDPs) is a rich mathematical framework that embraces a large class of complex sequential decision-making problems under uncertainty with limited observations. However, the complexity of POMDPs poses various computational challenges, motivating the need for an efficient algorithm that rapidly finds a good enou

Huaming Du, Cancan Feng, Yuqian Lei, Chenyang Zhang

Enterprise financial risk analysis aims at predicting the future financial risk of enterprises. Due to its wide and significant application, enterprise financial risk analysis has always been the core research topic in the fields of Finance and Management. Based on advanced computer science and artificial intelligence technologies, enterprise risk analysis r

Jialu Wang, Yeh-Fong Chen, Thomas Gwise

Conventional methods for analyzing composite endpoints in clinical trials often only focus on the time to the first occurrence of all events in the composite. Therefore, they have inherent limitations because the individual patients' first event can be the outcome of lesser clinical importance. To overcome this limitation, the concept of the win ratio (WR),

Ahnaf Mozib Samin, Behrooz Nikandish, Jingyan Chen

Handling and digesting a huge amount of information in an efficient manner has been a long-term demand in modern society. Some solutions to map key points (short textual summaries capturing essential information and filtering redundancies) to a large number of arguments/opinions have been provided recently (Bar-Haim et al., 2020). To complement the full pict

Hao-Nan Wang, Li-Sheng Geng, Qian Wang, Ju-Jun Xie

We investigate the decays of $B^0 \to K^0 X(3872)$ and $B^+ \to K^+ X(3872)$ based on the picture where the $X(3872)$ resonance is strongly coupled to the $D\bar{D}^* + c.c.$ channel. In addition to the decay mechanism where the $X(3872)$ resonance is formed from the $c\bar{c}$ pair hadronization with the short-distance interaction, we have also considered t

Qi Xin, Zhi-Gang Wang

In this paper, we apply the QCD sum rules to study the vector fully-light tetraquark states with an explicit P-wave between the diquark and antidiquark pair. We observed that the $C\gamma_\alpha\otimes\stackrel{\leftrightarrow}{\partial}_\mu\otimes\gamma^\alpha C$ (or $C\gamma_\alpha\otimes\stackrel{\leftrightarrow}D_\mu\otimes\gamma^\alpha C$) type current

Tao Li, Yu Chen, Shaobo Wang, Ke Han

The tracks left by charged particles in a gaseous time projection chamber~(TPC) incorporate important information about the interaction process and drift of electrons in gas. The electron diffusion information carried by the tracks is an effective signature to reconstruct $z_0$, the vertex position in drift direction at which the event takes place. In this p

Taiki Haga, Masaya Nakagawa, Ryusuke Hamazaki, Masahito Ueda

The relaxation dynamics of an open quantum system is determined by the competition between the coherent Hamiltonian dynamics of a system and the dissipative dynamics due to interactions with environments. It is therefore of fundamental interest to understand the transition from the coherent to incoherent regimes. We find that hitherto unrecognized quasiparti

Xu Zhan, Xiaoling Zhang, Wensi Zhang, Jun Shi

Benefiting from a relatively larger aperture's angle, and in combination with a wide transmitting bandwidth, near-field synthetic aperture radar (SAR) provides a high-resolution image of a target's scattering distribution-hot spots. Meanwhile, imaging result suffers inevitable degradation from sidelobes, clutters, and noises, hindering the information retrie

Xu Zhan, Xiaoling Zhang, Mou Wang, Jun Shi

This work focuses on 3D Radar imaging inverse problems. Current methods obtain undifferentiated results that suffer task-depended information retrieval loss and thus don't meet the task's specific demands well. For example, biased scattering energy may be acceptable for screen imaging but not for scattering diagnosis. To address this issue, we propose a new

Daya Bay collaboration, F. P. An, W. D. Bai, A. B. Balantekin

We present a new determination of the smallest neutrino mixing angle ${\theta}_{13}$ and the mass-squared difference ${\Delta}{\rm m}^{2}_{32}$ using a final sample of $5.55 \times 10^{6}$ inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample was selected from the complete data set obtained by the Daya Bay react

Jia-Qi Lin, Man-Sheng Chen, Xi-Ran Zhu, Chang-Dong Wang

Multi-view attributed graph clustering is an important approach to partition multi-view data based on the attribute feature and adjacent matrices from different views. Some attempts have been made in utilizing Graph Neural Network (GNN), which have achieved promising clustering performance. Despite this, few of them pay attention to the inherent specific inf

Yuzhou Zhuang, Hong Liu, Enmin Song, Coskun Cetinkaya

The crossMoDA challenge aims to automatically segment the vestibular schwannoma (VS) tumor and cochlea regions of unlabeled high-resolution T2 scans by leveraging labeled contrast-enhanced T1 scans. The 2022 edition extends the segmentation task by including multi-institutional scans. In this work, we proposed an unpaired cross-modality segmentation framewor

Dev Churiwala, Bhaskar Krishnamachari

MEV attacks have been an omnipresent evil in the blockchain world, an implicit tax that uninformed users pay for using the service. The problem arises from the miners' ability to reorder and insert arbitrary transactions in the blocks they mine. This paper proposes a 2-phased transaction protocol to eliminate MEV attacks. The user requests an interaction tok

Panpan Li, Yong Niu, Hao Wu, Zhu Han

With the rapid development of high-speed railway systems and railway wireless communication, the application of ultra-wideband millimeter wave band is an inevitable trend. However, the millimeter wave channel has large propagation loss and is easy to be blocked. Moreover, there are many problems such as eavesdropping between the base station (BS) and the tra

Daniel Garces, Sushmita Bhattacharya, Stephanie Gil, Dimitri Bertsekas

We derive a learning framework to generate routing/pickup policies for a fleet of autonomous vehicles tasked with servicing stochastically appearing requests on a city map. We focus on policies that 1) give rise to coordination amongst the vehicles, thereby reducing wait times for servicing requests, 2) are non-myopic, and consider a-priori potential future

Giorgi Kvernadze, Putu Ayu G. Sudyanti, Nishan Subedi, Mohammad Hajiaghayi

Embedding based product recommendations have gained popularity in recent years due to its ability to easily integrate to large-scale systems and allowing nearest neighbor searches in real-time. The bulk of studies in this area has predominantly been focused on similar item recommendations. Research on complementary item recommendations, on the other hand, st

Inha Cha, Juhyun Oh, Cheul Young Park, Jiyoon Han

We thought data to be simply given, but reality tells otherwise; it is costly, situation-dependent, and muddled with dilemmas, constantly requiring human intervention. The ML community's focus on quality data is increasing in the same vein, as good data is vital for successful ML systems. Nonetheless, few works have investigated the dataset builders and the

Rui Zhang, Rui Xin, Margo Seltzer, Cynthia Rudin

Regression trees are one of the oldest forms of AI models, and their predictions can be made without a calculator, which makes them broadly useful, particularly for high-stakes applications. Within the large literature on regression trees, there has been little effort towards full provable optimization, mainly due to the computational hardness of the problem

Ryo Nozaki, Yoshiro Sato, Yoshitaka Shimada, Taku Suzuki

Bright sources of polarization-entangled photon pairs are essential components for quantum information technologies. In general, it is necessary to introduce a resonator that combines active optical components such as an electric optical modulator to enhance the stimulated emission of polarization-entangled photons. It is technically difficult to perform the

Juan E. Jacobo

The article examines how institutions, automation, unemployment and income distribution interact in the context of a neoclassical growth model where profits are interpreted as a surplus over costs of production. Adjusting the model to the experience of the US economy, I show that joint variations in labor institutions and technology are required to provide r

Çağkan Yapar, Fabian Jaensch, Ron Levie, Giuseppe Caire

In this paper, we study the localization problem in dense urban settings. In such environments, Global Navigation Satellite Systems fail to provide good accuracy due to low likelihood of line-of-sight (LOS) links between the receiver (Rx) to be located and the satellites, due to the presence of obstacles like the buildings. Thus, one has to resort to other t

Dev Churiwala, Bhaskar Krishnamachari

Automated Market Makers (AMMs) have cemented themselves as an integral part of the decentralized finance (DeFi) space. AMMs are a type of exchange that allows users to trade assets without the need for a centralized exchange. They form the foundation for numerous decentralized exchanges (DEXs), which help facilitate the quick and efficient exchange of on-cha

D. H. Delphenich

The authors previous derivation of a variational principle from the total work functional, as a generalization of the first variation of an action functional, is extended by deriving a corresponding generalization of the Hamiltonian formulation of that action functional. Some consequences of it are that one can decompose the Lie brackets of arbitrary vector

Yun Soo Myung, De-Cheng Zou, Meng-Yun Lai

It was confirmed that the negative modes of the Euclidean section for asymptotically flat black holes reveal the thermodynamic instability of these black holes in the grand canonical ensemble (GCE). These include Schwarzschild, Reissner-Nordstr\"{o}m, Kerr, and Kerr-Newman black holes. In this work, we develop the relation between thermodynamic instability i

Pawel Sarkowicz

When $\mathcal D$ is strongly self-absorbing we say an inclusion $B \subseteq A$ is $\mathcal D$-stable if it is isomorphic to the inclusion $B \otimes \mathcal D \subseteq A \otimes \mathcal D$. We give ultrapower characterizations and show that if a unital inclusion is $\mathcal D$-stable, then $\mathcal D$-stability can be exhibited for countably many int

Steven J. Miller, Eliel Sosis, Jingkai Ye

Zeckendorf proved that every positive integer $n$ can be written uniquely as the sum of non-adjacent Fibonacci numbers; a similar result holds for other positive linear recurrence sequences. These legal decompositions can be used to construct a game that starts with a fixed integer $n$, and players take turns using moves relating to a given recurrence relati

Andreas A. Malikopoulos

Cyber-physical systems (CPS) encounter a large volume of data which is added to the system gradually in real time and not altogether in advance. As the volume of data increases, the domain of the control strategies also increases, and thus it becomes challenging to search for an optimal strategy. Even if an optimal control strategy is found, implementing suc

K. S. Rabinovich, A. N. Yaresko, R. D. Dawson, M. J. Krautloher

Achieving fundamental understanding of insulator-to-metal transitions (IMTs) in strongly correlated systems and their persistent and reversible control via nonequilibrium drive are prime targets of current condensed matter research. Photoinduced switching between competing orders in correlated insulators requires a free-energy landscape with nearly degenerat

Naveen Gupta, Sanjay Kumar Pant

This note investigates the relation between squeezing function and its generalizations. Using the relation obtained, we present an alternate method to find expression of generalized squeezing function of unit ball corresponding to the generalized complex ellipsoids.

Carson Connard, Benjamin Ingimarson, Roger Nichols, Andrew Paul

We study convergence of the spectral shift function for the finite interval restrictions of a pair of full-line Schr\"odinger operators to an interval of the form $(-\ell,\ell)$ with coupled boundary conditions at the endpoints as $\ell\to \infty$ in the case when the finite interval restrictions are relatively prime to those with Dirichlet boundary conditio

Xueqing Liu, Tao Tu, Paul Sajda

Simultaneous EEG-fMRI is a multi-modal neuroimaging technique that provides complementary spatial and temporal resolution. Challenging has been developing principled and interpretable approaches for fusing the modalities, specifically approaches enabling inference of latent source spaces representative of neural activity. In this paper, we address this infer

Jie Yang, Baibhab Chatterjee, Mohammad Abu Khater, Mattias Thorsell

One of the major challenges in communication, radar, and electronic warfare receivers arises from nearby device interference. The paper presents a 2-6 GHz GaN LNA front-end with onboard sensing, processing, and feedback utilizing microcontroller-based controls to achieve adaptation to a variety of interference scenarios through power and linearity regulation

Anna Yesypenko, Per-Gunnar Martinsson

This manuscript presents GPU optimizations for the 2D Hierarchical Poincar\'e-Steklov (HPS) discretization scheme. HPS is a multi-domain spectral collocation method that combines high-order discretizations with direct solvers to accurately resolve highly oscillatory solutions. The domain decomposition approach of HPS connects domains directly via a sparse di

Mamoru Ueda

We construct a non-trivial homomorphism from the Guay's affine Yangian associated with $\widehat{\mathfrak{sl}}(n)$ to the universal enveloping algebra of the $W$-algebra associated with a Lie algebra $\mathfrak{gl}(m+n)$ and its nilpotent element whose Jordan block of type $(2^{n},1^{m-n})$ for $m>n$.

K. R. Goodearl

This is a survey of what is known and/or conjectured about the prime and primitive spectra of quantum algebras, of quantized coordinate rings in particular. The topological structure of these spectra, their relations to classical affine algebraic varieties, and their relations to each other are discussed.

Shuai You, Xiaolin Huang, Li Xing, Mary Lesperance

The vast coastline provides Canada with a flourishing seafood industry including bivalve shellfish production. To sustain a healthy bivalve molluscan shellfish production, the Canadian Shellfish Sanitation Program was established to monitor the health of shellfish harvesting habitats, and fecal coliform bacteria data have been collected at nearly 15,000 mari

Adriaan de Clercq

In his 1918 paper 'A General Form of Integral', Percy John Daniell developed a theory of integration capable of dealing with functions on arbitrary sets. Daniell's method differs from the measure-theoretic notion of integration. Linear functionals over vector lattices were considered as the fundamental objects on which he built the theory, rather than measur

Mateusz Wójcik, Witold Kościukiewicz, Tomasz Kajdanowicz, Adam Gonczarek

Continual learning with an increasing number of classes is a challenging task. The difficulty rises when each example is presented exactly once, which requires the model to learn online. Recent methods with classic parameter optimization procedures have been shown to struggle in such setups or have limitations like non-differentiable components or memory buf

Devin Jean, Suk Seo

A detection system, modeled in a graph, uses "detectors" on a subset of vertices to uniquely identify an "intruder" at any vertex. We consider two types of detection systems: open-locating-dominating (OLD) sets and identifying codes (ICs). An OLD set gives each vertex a unique, non-empty open neighborhood of detectors, while an IC provides a unique, non-empt

Albert J. Wakhloo, Tamara J. Sussman, SueYeon Chung

Understanding how the statistical and geometric properties of neural activity relate to performance is a key problem in theoretical neuroscience and deep learning. Here, we calculate how correlations between object representations affect the capacity, a measure of linear separability. We show that for spherical object manifolds, introducing correlations betw

Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo

Recent work has highlighted the label alignment property (LAP) in supervised learning, where the vector of all labels in the dataset is mostly in the span of the top few singular vectors of the data matrix. Drawing inspiration from this observation, we propose a regularization method for unsupervised domain adaptation that encourages alignment between the pr

Erin. S. Grant, Mina Barzegar Amiri Olia, Ella. P. Walsh, Liam T. Hall

Fluorescent nanodiamonds (FNDs) have been exploited as sensitive quantum probes for nanoscale chemical and biological sensing applications, with the majority of demonstrations to date relying on the detection of single FNDs. This places significant limits on the measurement time, throughput and statistical significance of a measured result as there is usuall

Zilong Wang, Jiuxiang Gu, Chris Tensmeyer, Nikolaos Barmpalios

Document images are a ubiquitous source of data where the text is organized in a complex hierarchical structure ranging from fine granularity (e.g., words), medium granularity (e.g., regions such as paragraphs or figures), to coarse granularity (e.g., the whole page). The spatial hierarchical relationships between content at different levels of granularity a

A. Morozov, N. Tselousov

This paper describes our attempt to understand the recent success of Na Wang in constructing the 3-Schur polynomials, associated with the plane partitions. We provide a rather detailed review and try to figure out the new insights, which allowed to overcome the problems of the previous efforts. In result we provide a very simple definition of time-variables

Gregory B. Cook, Suhan Lu

In addition to the well-known quasinormal modes, the gravitational modes of the Kerr geometry also include sets of total-transmission modes. Each mode can be considered as an element of a sequence of modes parameterized by the angular momentum of the black hole. One family of gravitational total-transmission modes of Kerr have been known for some time. Modes

Reshmi Ghosh, Harjeet Singh Kajal, Sharanya Kamath, Dhuri Shrivastava

Breaking down a document or a conversation into multiple contiguous segments based on its semantic structure is an important and challenging problem in NLP, which can assist many downstream tasks. However, current works on topic segmentation often focus on segmentation of structured texts. In this paper, we comprehensively analyze the generalization capabili

Yiming Fan, Huaiqian You, Yue Yu

We present OBMeshfree, an Optimization-Based Meshfree solver for compactly supported nonlocal integro-differential equations (IDEs) that can describe material heterogeneity and brittle fractures. OBMeshfree is developed based on a quadrature rule calculated via an equality constrained least square problem to reproduce exact integrals for polynomials. As such

Yao Chen, Yijie Gui, Hong Lin, Wensheng Gan

In terms of artificial intelligence, there are several security and privacy deficiencies in the traditional centralized training methods of machine learning models by a server. To address this limitation, federated learning (FL) has been proposed and is known for breaking down ``data silos" and protecting the privacy of users. However, FL has not yet gained

Hong Lin, Shicheng Wan, Wensheng Gan, Jiahui Chen

Traditional education has been updated with the development of information technology in human history. Within big data and cyber-physical systems, the Metaverse has generated strong interest in various applications (e.g., entertainment, business, and cultural travel) over the last decade. As a novel social work idea, the Metaverse consists of many kinds of

Fadi Khatib, Yuval Margalit, Meirav Galun, Ronen Basri

This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images. Given two images of the same scene captured from different viewpoints, our method predicts the relative rotation and translation (including direction and scale) between the two respective cameras. Inspired by the classical pipeline, our

Zhe Cheng, Yu-Ju Huang, Beniamin Zahiri, Patrick Kwon

The coupled transport of charge and heat provide fundamental insights into the microscopic thermodynamics and kinetics of materials. We describe a sensitive ac differential resistance bridge that enables measurements of the temperature difference on two sides of a coin cell with a resolution of better than 10 uK. We use this temperature difference metrology

Zefeng Chen, Jiayang Wu, Wensheng Gan, Zhenlian Qi

Metaverse is a living space and cyberspace that realizes the process of virtualizing and digitizing the real world. It integrates a plethora of existing technologies with the goal of being able to map the real world, even beyond the real world. Metaverse has a bright future and is expected to have many applications in various scenarios. The support of the Me

Nicolas Arnaud

Sources of geophysical noise (such as wind, sea waves and earthquakes) or of anthropogenic noise (nearby activities, road traffic, etc.) impact ground-based gravitational-wave (GW) interferometric detectors, causing transient sensitivity worsening and gaps in data taking. During the one year-long third Observing Run (O3: from April 01, 2019 to March 27, 2020

Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky

A growing ecosystem of large, open-source foundation models has reduced the labeled data and technical expertise necessary to apply machine learning to many new problems. Yet foundation models pose a clear dual-use risk, indiscriminately reducing the costs of building both harmful and beneficial machine learning systems. Policy tools such as restricted model

Yiqi Liu, Hsiang-Chih Hwang, Nadia L. Zakamska, John R. Thorstensen

CSS1603+19 is a cataclysmic variable (CV) with an orbital period of 81.96 min, near the minimal period of cataclysmic variables. It is unusual in having a strong mid-infrared excess inconsistent with thermal emission from a brown dwarf companion. Here we present time-resolved multi-wavelength observations of this system. WISE photometry indicates that the mi

Luca Valente, Yvan Tortorella, Mattia Sinigaglia, Giuseppe Tagliavini

IoT applications span a wide range in performance and memory footprint, under tight cost and power constraints. High-end applications rely on power-hungry Systems-on-Chip (SoCs) featuring powerful processors, large LPDDR/DDR3/4/5 memories, and supporting full-fledged Operating Systems (OS). On the contrary, low-end applications typically rely on Ultra-Low-Po

R. Muthuganesan, S. Balakrishnan

In this article, we define a faithful quantifiers of bipartite quantum correlation, namely geometric version of quantum discord using affinity based metric. It is shown that the newly-minted measure resolves the local ancilla problem of Hilbert-Schmidt measures. Exploiting the notion of affinity-based discord, we derive Margolus-Levitin (ML) and Mandelstamm-

R. Baggio, O. U. Salman, L. Truskinovsky

Dislocation nucleation in homogeneous crystals initially unfolds as a linear symmetry-breaking elastic instability. In the absence of explicit nucleation centers, such instability develops simultaneously all over the crystal and due to the dominance of long range elastic interactions it advances into the nonlinear stage as a collective phenomenon through pat

Marcel Celaya, Stefan Kuhlmann, Joseph Paat, Robert Weismantel

We develop a technique that can be applied to provide improved upper bounds for two important questions in linear integer optimization. - Proximity bounds: Given an optimal vertex solution for the linear relaxation, how far away is the nearest optimal integer solution (if one exists)? - Flatness bounds: If a polyhedron contains no integer point, what is the

Avdhoot Datar, Catherine Wright, Devin A. Matthews

We have studied the Stark effect in the soft x-ray region for various small molecules by calculating the field-dependent x-ray absorption spectra. This effect is explained in terms of the response of molecular orbitals (core and valence), the molecular dipole moment, and the molecular geometry to the applied electric field. A number of consistent trends are

Mohammad Amin Maleki Sadr, Yeying Zhu, Peng Hu

Recently, there has been a significant amount of interest in satellite telemetry anomaly detection (AD) using neural networks (NN). For AD purposes, the current approaches focus on either forecasting or reconstruction of the time series, and they cannot measure the level of reliability or the probability of correct detection. Although the Bayesian neural net

Djordje Baralić, Aleš Vavpetič, Aleksandar Vučić

We study combinatorial and topological properties of the universal complexes $X(\mathbb{F}_p^n)$ and $K(\mathbb{F}_p^n)$ whose simplices are certain unimodular subsets of $\mathbb{F}_p^n$. We calculate their $\mathbf f$-vectors and their Tor-algebras, show that they are shellable but not shifted, and find their applications in toric topology and number theor

Alonso Rodriguez-Navarro, Ricardo Brito

Although not explicitly declared, most research rankings of countries and institutions are supposed to reveal their contribution to the advancement of knowledge. However, such advances are based on very highly cited publications with very low frequency, which can only very exceptionally be counted with statistical reliability. Percentile indicators enable ca

Sahil Verma, Chirag Shah, John P. Dickerson, Anurag Beniwal

Recommender systems influence many of our interactions in the digital world -- impacting how we shop for clothes, sorting what we see when browsing YouTube or TikTok, and determining which restaurants and hotels we are shown when using hospitality platforms. Modern recommender systems are large, opaque models trained on a mixture of proprietary and open-sour

Pete Rigas

To obtain Russo-Seymour-Welsh estimates for the height function of the six-vertex model under sloped boundary conditions, which can be leveraged to demonstrate that the height function logarithmically delocalizes under a broader class of boundary conditions, we formulate crossing probability estimates in strips of the square lattice and the cylinder, for par

Mingqiang Li, Yidi Shen, Kun Luo, Qi An

Dislocations, line defects in crystalline materials, play an essential role in the mechanical[1,2], electrical[3], optical[4], thermal[5], and phase transition[6] properties of these materials. Dislocation motion, an important mechanism underlying crystal plasticity, is critical for the hardening, processing, and application of a wide range of structural and