April 2023 arXiv papers — page 141

Shinichiro Akiyama

We formulate the path integral of two- and three-flavor Wilson fermion in two dimensions as a multilayer Grassmann tensor network by the matrix product decomposition. Thanks to this new description, the memory cost scaling is reduced from $\mathrm{O}(\mathrm{e}^{N_{f}})$ for the conventional construction to $\mathrm{O}(N_{f})$. Based on this representation,

Xinru Zhang, Ni Ou, Chenghao Liu, Zhizheng Zhuo

Automated brain tumor segmentation based on deep learning (DL) has achieved promising performance. However, it generally relies on annotated images for model training, which is not always feasible in clinical settings. Therefore, the development of unsupervised DL-based brain tumor segmentation approaches without expert annotations is desired. Motivated by t

Y. T. Albert Law

In this short note, we review some recent progress in understanding the 1-loop corrections to the Gibbons-Hawking entropy, which amounts to studying free fields on the de Sitter static patch and the round sphere. After briefly surveying the unitary irreducible representations of the de Sitter group $SO(1,d+1)$ and their Harish-Chandra characters, we discuss

Dan Xu, Changjia Chen, Brian T. Kirby, Li Qian

Entanglement distillation has many applications in quantum information processing and is an important tool for improving the quality and efficiency of quantum communication, cryptography, computing, and simulation. We propose an entanglement distillation scheme using only one pair of polarization-frequency hyperentangled photons, which can be equivalently vi

Tyler Natoli, Bradford Benson, John Carlstrom, Eric Chauvin

We have demonstrated the fabrication of a monolithic, 5-meter diameter, aluminum reflector with 17.4 $\mu$m RMS surface error. The reflector was designed to avoid the problem of pickup due to scattering from panel gaps in a large, millimeter-wavelength telescope that will be used for measurements on the cosmic microwave background.

Qinlong Wang, Tingfeng Lan, Yinghao Tang, Ziling Huang

Deep learning recommendation models (DLRM) rely on large embedding tables to manage categorical sparse features. Expanding such embedding tables can significantly enhance model performance, but at the cost of increased GPU/CPU/memory usage. Meanwhile, tech companies have built extensive cloud-based services to accelerate training DLRM models at scale. In thi

Nachuan Xiao, Xin Liu, Kim-Chuan Toh

In this paper, we focus on a class of constrained nonlinear optimization problems (NLP), where some of its equality constraints define a closed embedded submanifold $\mathcal{M}$ in $\mathbb{R}^n$. Although NLP can be solved directly by various existing approaches for constrained optimization in Euclidean space, these approaches usually fail to recognize the

Yihua Ma, Zhifeng Yuan, Yu Xin, Jiang Hua

Recently, a two-dimension (2D) modulation waveform of orthogonal time-frequency-space (OTFS) has been a popular 6G candidate to replace existing orthogonal frequency division multiplexing (OFDM). The extensive OTFS researches help to make both the advantages and limitations of OTFS more and more clear. The limitations are not easy to overcome as they come fr

Shaolin Chen, Hidetaka Hamada

The main purpose of this paper is to develop some methods to investigate equivalent norms and Hardy-Littlewood type Theorems on Lipschitz type spaces of analytic functions and complex-valued harmonic functions. Initially, some characterizations of equivalent norms on Lipschitz type spaces of analytic functions and complex-valued harmonic functions will be gi

Chuandong Liu, Chenqiang Gao, Fangcen Liu, Pengcheng Li

State-of-the-art 3D object detectors are usually trained on large-scale datasets with high-quality 3D annotations. However, such 3D annotations are often expensive and time-consuming, which may not be practical for real applications. A natural remedy is to adopt semi-supervised learning (SSL) by leveraging a limited amount of labeled samples and abundant unl

Mohsen Moradi

Polarization-adjusted convolutional (PAC) codes are a new family of linear block codes that can perform close to the theoretical bounds in the short block-length regime. These codes combine polar coding and convolutional coding. In this study, we show that PAC codes are equivalent to a new class of codes consisting of inner cyclic codes and outer polar- and

Vikram Giri, Noah Kravitz

For each subtorus $T$ of $(\mathbb{R}/\mathbb{Z})^n$, let $D(T)$ denote the (infimal) $L^\infty$-distance from $T$ to the point $(1/2,\ldots, 1/2)$. The $n$-th Lonely Runner spectrum $\mathcal{S}(n)$ is defined to be the set of all values achieved by $D(T)$ as $T$ ranges over the $1$-dimensional subtori of $(\mathbb{R}/\mathbb{Z})^n$ that are not contained i

Zhengqing Miao, Meirong Zhao

Low-channel EEG devices are crucial for portable and entertainment applications. However, the low spatial resolution of EEG presents challenges in decoding low-channel motor imagery. This study introduces TSFF-Net, a novel network architecture that integrates time-space-frequency features, effectively compensating for the limitations of single-mode feature e

G. Adhikari, N. Carlin, J. J. Choi, S. Choi

We present results of a search for bosonic super-weakly interacting massive particles (BSW) as keV scale dark matter candidates that is based on an exposure of 97.7 kg$\cdot$year from the COSINE experiment. In this search, we employ, for the first time, Compton-like as well as absorption processes for pseudoscalar and vector BSWs. No evidence for BSWs is fou

Alfred Geroldinger, Jun Seok Oh

Let $G_1$ and $G_2$ be torsion groups. We prove that the monoids of product-one sequences over $G_1$ and over $G_2$ are isomorphic if and only if the groups $G_1$ and $G_2$ are isomorphic. This was known before for abelian groups.

Yong Wang, Jianyun Guan

By some SL(2, Z) modular forms introduced in [11] and [4] , we get some interesting anomaly cancellation formulas. As corollaries, we get some divisibility results of index of twisted Dirac operators.

Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng

Vision-Language models (VLMs) that use contrastive language-image pre-training have shown promising zero-shot classification performance. However, their performance on imbalanced dataset is relatively poor, where the distribution of classes in the training dataset is skewed, leading to poor performance in predicting minority classes. For instance, CLIP achie

Mohamadreza Fazel, Kristin S. Grussmayer, Boris Ferdman, Aleksandra Radenovic

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected at scales on par or smaller than light's wavelength. Here we review the optics responsible for generating fluorescent images, fluorophore prop

Gong Chen, Jason Murphy

We consider a class of one-dimensional nonlinear Schr\"odinger equations of the form \[ (i\partial_t+\Delta)u = [1+a]|u|^2 u. \] For suitable localized functions $a$, such equations admit a small-data modified scattering theory, which incorporates the standard logarithmic phase correction. In this work, we prove that the small-data modified scattering behavi

Yu Kumagai

Recently, effective one-dimensional configuration coordinate diagrams have been utilized to calculate the line shapes of luminescence spectra and non-radiative carrier capture coefficients via point defects. Their calculations necessitate accurate total energies as a function of configuration coordinates. Although supercells under periodic boundary condition

Huai-Dong Cao, Meng Zhu

In this paper, we continue investigating the second variation of Perelman's $\nu$-entropy for compact shrinking Ricci solitons. In particular, we improve some of our previous work in "H.-D. Cao and M. Zhu, Math. Ann. 353 (2012), No. 3, 747-763", as well as the more recent work in "M. Mehrmohamadi and A. Razavi, arXiv:2104.08343", and obtain a necessary and s

Junzhu Mao, Yazhou Yao, Zeren Sun, Xingguo Huang

Due to its significant capability of modeling long-range dependencies, vision transformer (ViT) has achieved promising success in both holistic and occluded person re-identification (Re-ID) tasks. However, the inherent problems of transformers such as the huge computational cost and memory footprint are still two unsolved issues that will block the deploymen

Kiril Bangachev, S. Matthew Weinberg

For a set $M$ of $m$ elements, we define a decreasing chain of classes of normalized monotone-increasing valuation functions from $2^M$ to $\mathbb{R}_{\geq 0}$, parameterized by an integer $q \in [2,m]$. For a given $q$, we refer to the class as $q$-partitioning. A valuation function is subadditive if and only if it is $2$-partitioning, and fractionally sub

Pablo Andretta Jaskowiak, Ivan Gesteira Costa

Confusion matrices and derived metrics provide a comprehensive framework for the evaluation of model performance in machine learning. These are well-known and extensively employed in the supervised learning domain, particularly classification. Surprisingly, such a framework has not been fully explored in the context of clustering validation. Indeed, just rec

Yuzuru Inahama

In this paper we prove the Wong-Zakai approximation of probability density functions of solutions at a fixed time of rough differential equations driven by fractional Brownian rough path with Hurst parameter $H$ $(1/4 <H \leq 1/2)$. Besides rough path theory, we use Hu-Watanabe's approximation theorem in the framework of Watanabe's distributional Malliavin c

Anurag Kumar, Ke Tan, Zhaoheng Ni, Pranay Manocha

Measuring quality and intelligibility of a speech signal is usually a critical step in development of speech processing systems. To enable this, a variety of metrics to measure quality and intelligibility under different assumptions have been developed. Through this paper, we introduce tools and a set of models to estimate such known metrics using deep neura

Ariyan Bighashdel, Daan de Geus, Pavol Jancura, Gijs Dubbelman

Learning anticipation in Multi-Agent Reinforcement Learning (MARL) is a reasoning paradigm where agents anticipate the learning steps of other agents to improve cooperation among themselves. As MARL uses gradient-based optimization, learning anticipation requires using Higher-Order Gradients (HOG), with so-called HOG methods. Existing HOG methods are based o

Navya Martin Kollapally, Vipina Kuttichi Keloth, Julia Xu, James Geller

The objectives of this research are 1) to develop an ontology for CDoH by utilizing PubMed articles and ChatGPT; 2) to foster ontology reuse by integrating CDoH with an existing SDoH ontology into a unified structure; 3) to devise an overarching conception for all non-clinical determinants of health and to create an initial ontology, called N-CODH, for them;

Marcos M. Vasconcelos, Behrouz Touri

We study the problem of achieving decentralized coordination by a group of strategic decision makers choosing to engage or not in a task in a stochastic setting. First, we define a class of symmetric utility games that encompass a broad class of coordination games, including the popular framework known as \textit{global games}. With the goal of studying the

Yusaku Shinoda, Yoshihiko Okamoto, Youichi Yamakawa, Haruka Matsumoto

We report the discovery of bulk superconductivity in Sc6MTe2 with seven kinds of transition-metal elements M. The critical temperatures for M = 3d elements are higher than those for 4d and 5d elements and increase in the order of M = Ni, Co, and Fe with the highest Tc of 4.7 K in Sc6FeTe2. First principles calculations indicate the presence of significant co

Joseph Chang

The Metaverse through VR headsets is a rapidly growing concept, but the high cost of entry currently limits access for many users. This project aims to provide an accessible entry point to the immersive Metaverse experience by leveraging web technologies. The platform developed allows users to engage with rendered avatars using only a web browser, microphone

Yu-qiang Liu, Yi-jia Yang, Chang-shui Yu

Precisely controlling heat transfer in a quantum mechanical system is particularly significant for designing quantum thermodynamical devices. With the technology of experiment advances, circuit quantum electrodynamics (circuit QED) has become a promising system due to controllable light matter interactions as well as flexible coupling strengths. In this pape

Jung-Woo Chang, Nojan Sheybani, Shehzeen Samarah Hussain, Mojan Javaheripi

Video compression plays a significant role in IoT devices for the efficient transport of visual data while satisfying all underlying bandwidth constraints. Deep learning-based video compression methods are rapidly replacing traditional algorithms and providing state-of-the-art results on edge devices. However, recently developed adversarial attacks demonstra

Sepideh Bahadoripour, Ethan MacDonald, Hadis Karimipour

The growing number of cyber-attacks against Industrial Control Systems (ICS) in recent years has elevated security concerns due to the potential catastrophic impact. Considering the complex nature of ICS, detecting a cyber-attack in them is extremely challenging and requires advanced methods that can harness multiple data modalities. This research utilizes n

Shubham Pande, Bhaswar Chakrabarti, Anjan Chakravorty

As the packing density of resistive random access memory (RRAM) devices increases, the effect of thermal cross-talk across the devices in a crossbar array arrangement influences their overall operation significantly. The electro-thermal effects in a densely packed RRAM crossbar can accelerate the retention and endurance degradation; hence poses a serious rel

Ofer Grossman, Meghal Gupta, Mark Sellke

We investigate one of the most basic problems in streaming algorithms: approximating the number of elements in the stream. In 1978, Morris famously gave a randomized algorithm achieving a constant-factor approximation error for streams of length at most N in space $O(\log \log N)$. We investigate the pseudo-deterministic complexity of the problem and prove a

Namrata Roy, Alaina Henry, Tommaso Treu, Tucker Jones

Ly$\alpha$ emission is possibly the best indirect diagnostic of Lyman continuum (LyC) escape since the conditions that favor the escape of Ly$\alpha$ photons are often the same that allows for the escape of LyC photons. In this work, we present the rest UV-optical spectral characteristics of 11 Ly$\alpha$ emitting galaxies at 3 $<$ z $<$ 6 - the optimal reds

Ziqian Bai, Feitong Tan, Zeng Huang, Kripasindhu Sarkar

We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achieve user-controlled facial expressions and head poses. Our hybrid pipeline combines the geometry prior and dynamic tracking of a 3DMM with a neural radiance field to achieve fine-gr

Xianzhong Ding, Wan Du

Agricultural irrigation is a significant contributor to freshwater consumption. However, the current irrigation systems used in the field are not efficient. They rely mainly on soil moisture sensors and the experience of growers, but do not account for future soil moisture loss. Predicting soil moisture loss is challenging because it is influenced by numerou

Jaeill Kim, Suhyun Kang, Duhun Hwang, Jungwook Shin

Since the introduction of deep learning, a wide scope of representation properties, such as decorrelation, whitening, disentanglement, rank, isotropy, and mutual information, have been studied to improve the quality of representation. However, manipulating such properties can be challenging in terms of implementational effectiveness and general applicability

Temiloluwa Prioleau, Abigail Bartolome, Richard Comi, Catherine Stanger

Objective digital data is scarce yet needed in many domains to enable research that can transform the standard of healthcare. While data from consumer-grade wearables and smartphones is more accessible, there is critical need for similar data from clinical-grade devices used by patients with a diagnosed condition. The prevalence of wearable medical devices i

Norman P. Jouppi, George Kurian, Sheng Li, Peter Ma

In response to innovations in machine learning (ML) models, production workloads changed radically and rapidly. TPU v4 is the fifth Google domain specific architecture (DSA) and its third supercomputer for such ML models. Optical circuit switches (OCSes) dynamically reconfigure its interconnect topology to improve scale, availability, utilization, modularity

Zhaoyue Chen, Yifan Sun

The Frank-Wolfe algorithm is a popular method in structurally constrained machine learning applications, due to its fast per-iteration complexity. However, one major limitation of the method is a slow rate of convergence that is difficult to accelerate due to erratic, zig-zagging step directions, even asymptotically close to the solution. We view this as an

Zhongyang Li

Semi-transitive graphs, defined in \cite{hps98} as examples where ``uniform percolation" holds whenever $p>p_c$, are a large class of graphs more general than quasi-transitive graphs. Let $G$ be a semi-transitive graph with one end which can be properly embedded into the plane with uniformly bounded face degree for finite faces and minimal vertex degree at l

Dong Lao, Zhengyang Hu, Francesco Locatello, Yanchao Yang

We investigate the emergence of objects in visual perception in the absence of any semantic annotation. The resulting model has received no supervision, does not use any pre-trained features, and yet it can segment the domain of an image into multiple independently moving regions. The resulting motion segmentation method can handle an unknown and varying num

Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti, Chris Holmes

Missing data are an unavoidable complication in many machine learning tasks. When data are `missing at random' there exist a range of tools and techniques to deal with the issue. However, as machine learning studies become more ambitious, and seek to learn from ever-larger volumes of heterogeneous data, an increasingly encountered problem arises in which mis

Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas, Rohan Baijal

The fast-growing demand for fully autonomous aerial operations in shared spaces necessitates developing trustworthy agents that can safely and seamlessly navigate in crowded, dynamic spaces. In this work, we propose Social Robot Tree Search (SoRTS), an algorithm for the safe navigation of mobile robots in social domains. SoRTS aims to augment existing social

K. Rana, D. V. Ambika, S. L. Bud'ko, A. E. Böhmer

The sulfur-substituted FeSe, FeSe$_{1-x}$S$_{x} $, is one of the unique systems that provides an independent tunability of nematicity, antiferromagnetism and superconductivity under pressure ($p$). Recently Rana et al. [Phys. Rev. B 101, 180503(R) (2020)] reported, from $^{77}$Se nuclear magnetic resonance (NMR) measurements on FeSe$_{0.91}$S$_{0.09}$ under

Ahmed M. Alaa, Zeshan Hussain, David Sontag

We develop a predictive inference procedure that combines conformal prediction (CP) with unconditional quantile regression (QR) -- a commonly used tool in econometrics that involves regressing the recentered influence function (RIF) of the quantile functional over input covariates. Unlike the more widely-known conditional QR, unconditional QR explicitly capt

Lev-Arcady Sellem, Alain Sarlette, Zaki Leghtas, Mazyar Mirrahimi

We propose a novel approach to generate, protect and control GKP qubits. It employs a microwave frequency comb parametrically modulating a Josephson circuit to enforce a dissipative dynamics of a high impedance circuit mode, autonomously stabilizing the finite-energy GKP code. The encoded GKP qubit is robustly protected against all dominant decoherence chann

Swapnil Mane, Vaibhav Khatavkar

Sarcasm detection in product reviews requires balancing domain-specific symbolic pattern recognition with deep semantic understanding. Symbolic representations capture explicit linguistic phenomena that are often decisive for sarcasm detection. Existing work either favors interpretable symbolic representation or semantic neural modeling, but rarely achieves

Vaibhav Khatavkar, Swapnil Mane, Parag Kulkarni

Keyword extraction is a crucial process in text mining. The extraction of keywords with respective contextual events in Twitter data is a big challenge. The challenging issues are mainly because of the informality in the language used. The use of misspelled words, acronyms, and ambiguous terms causes informality. The extraction of keywords with informal lang

Xinran Ma, Kui Cao, Xiaoran Wang, Zheng Wei

The interplay between non-Hermitian effects and topological insulators has become a frontier of research in non-Hermitian physics. However, the existence of a non-Hermitian skin effect for topological-protected edge states remains controversial. In this paper, we discover an alternative form of the non-Hermitian skin effect called the non-Hermitian chiral sk

Kevin Coulembier

We review some recent results on $K$-theory of perfection of commutative $\mF_p$-algebras and provide an alternative proof.

Meredith Ringel Morris

Generative AI models, including large language models and multimodal models that include text and other media, are on the cusp of transforming many aspects of modern life, including entertainment, education, civic life, the arts, and a range of professions. There is potential for Generative AI to have a substantive impact on the methods and pace of discovery

Veronica Vinciotti, Ernst Wit, Francisco Richter

The microbiome constitutes a complex microbial ecology of interacting components that regulates important pathways in the host. Measurements of microbial abundances are key to learning the intricate network of interactions amongst microbes. Microbial communities at various body sites tend to share some overall common structure, while also showing diversity r

Nafis Sadeq, Byungkyu Kang, Prarit Lamba, Julian McAuley

Masked language modeling (MLM) plays a key role in pretraining large language models. But the MLM objective is often dominated by high-frequency words that are sub-optimal for learning factual knowledge. In this work, we propose an approach for influencing MLM pretraining in a way that can improve language model performance on a variety of knowledge-intensiv

Ata Keşkekler, Vincent Bos, Alejandro M. Aragón, Peter G. Steeneken

Mechanical nonlinearities dominate the motion of nanoresonators already at relatively small oscillation amplitudes. Although single and coupled two-degrees-of-freedom models have been used to account for experimentally observed nonlinear effects, it is shown that these models quickly deviate from experimental findings when multiple modes influence the nonlin

M. Lazar, P. C. N. Verheijen

Data-driven predictive control (DPC) is becoming an attractive alternative to model predictive control as it requires less system knowledge for implementation and reliable data is increasingly available in smart engineering systems. Two main approaches exist within DPC, which mostly differ in the construction of the predictor: estimated prediction matrices (

Kaveh Safavigerdini, Aria Alasty, Mohammad Reza Movahhedy

The objective of this research is to develop an advanced controller for CNC machines equipped with Hexaglide parallel mechanisms. While traditional CNC machines employ mechanisms with perpendicular axes, accuracy may be compromised when processing high force loads. Parallel mechanisms, such as Hexaglide, have gained attention in the CNC industry due to their

Hadley Black, Deeparnab Chakrabarty, C. Seshadhri

Monotonicity testing of Boolean functions on the hypergrid, $f:[n]^d \to \{0,1\}$, is a classic topic in property testing. Determining the non-adaptive complexity of this problem is an important open question. For arbitrary $n$, [Black-Chakrabarty-Seshadhri, SODA 2020] describe a tester with query complexity $\widetilde{O}(\varepsilon^{-4/3}d^{5/6})$. This c

James D. Shemilt, Alex Horsley, Oliver E. Jensen, Alice B. Thompson

To assess how the presence of surfactant in lung airways alters the flow of mucus that leads to plug formation and airway closure, we investigate the effect of insoluble surfactant on the instability of a viscoplastic liquid coating the interior of a cylindrical tube. Evolution equations for the layer thickness using thin-film and long-wave approximations ar

Y. A. Antipov

The model problem of scattering of a sound wave by an infinite plane structure formed by a semi-infinite acoustically hard screen and a semi-infinite sandwich panel perforated from one side and covered by a membrane from the other is exactly solved. The model is governed by two Helmholtz equations for the velocity potentials in the upper and lower half-plane

Yang An

Seeking for the proper situation of Emergent Gravity, we recent reveal that the entropic mechanism only happens when extremal surfaces are varied, which is similar to the non-gravitational-bath-coupled setup of the island development. In this paper, we consider perturbing thin shell state outside horizon during equilibrating, to find the evolution of these E

Rebbecca TY Thien, Shanon L. Vuglar, Ian R. Petersen

We propose a method to design a suboptimal, coherent quantum LQG controller to solve a quantum equalization problem. Our method involves reformulating the problem as a control problem and then designing a classical LQG controller and implementing it as a quantum system. Illustrative examples are included which demonstrate the algorithm for both active and pa

Xing Han Lu, Siva Reddy, Harm de Vries

We introduce the StatCan Dialogue Dataset consisting of 19,379 conversation turns between agents working at Statistics Canada and online users looking for published data tables. The conversations stem from genuine intents, are held in English or French, and lead to agents retrieving one of over 5000 complex data tables. Based on this dataset, we propose two

Chengyi Luo, Haoqing Zhang, Vanessa P. W. Koh, John D. Wilson

Quantum simulation and sensing hold great promise for providing new insights into nature, from understanding complex interacting systems to searching for undiscovered physics. Large ensembles of laser-cooled atoms interacting via infinite-range photon mediated interactions are a powerful platform for both endeavours. Here, we realize for the first time momen

Richard Hain

This paper has 3 principal goals: (1) to survey what is know about mapping class and Torelli groups of simply connected compact Kaehler manifolds, (2) supplement these results, and (3) present a list of questions and open problems to stimulate future work. Apart from reviewing general background, the paper focuses on the case of hypersurfaces in projective s

Ling Zhang, Daniel Tabas, Baosen Zhang

In this paper, we consider the scenario-based two-stage stochastic DC optimal power flow (OPF) problem for optimal and reliable dispatch when the load is facing uncertainty. Although this problem is a linear program, it remains computationally challenging to solve due to the large number of scenarios needed to accurately represent the uncertainties. To mitig

Riley J. Preston, Daniel S. Kosov

We propose a model for a molecular motor in a molecular electronic junction driven by a natural manifestation of Landauer's blowtorch effect. The effect emerges via the interplay of the electronic friction and diffusion coefficients, each calculated quantum mechanically using nonequilibrium Green's functions, within a semi-classical Langevin description of t

Mantas Mikaitis

In the literature on algorithms for performing the multi-term addition $s_n=\sum_{i=1}^n x_i$ using floating-point arithmetic it is often shown that a hardware unit that has single normalization and rounding improves precision, area, latency, and power consumption, compared with the use of standard add or fused multiply-add units. However, non-monotonicity c

Huzi Cheng, Joshua W. Brown

While error backpropagation (BP) has dominated the training of nearly all modern neural networks for a long time, it suffers from several biological plausibility issues such as the symmetric weight requirement and synchronous updates. Feedback Alignment (FA) was proposed as an alternative to BP to address those dilemmas and has been demonstrated to be effect

Vrushank Phadnis, Kristin Moore, Mar Gonzalez Franco

While avatars have grown in popularity in social settings, their use in the workplace is still debatable. We conducted a large-scale survey to evaluate knowledge worker sentiment towards avatars, particularly the effects of realism on their acceptability for work meetings. Our survey of 2509 knowledge workers from multiple countries rated five avatar styles

Shota Hozumi, Kentaro Kutsukake, Kota Matsui, Syunya Kusakawa

In material characterization, identifying defective areas on a material surface is fundamental. The conventional approach involves measuring the relevant physical properties point-by-point at the predetermined mesh grid points on the surface and determining the area at which the property does not reach the desired level. To identify defective areas more effi

Zeyu Guo, Zihan Zhang

This paper shows that, with high probability, randomly punctured Reed-Solomon codes over fields of polynomial size achieve the list decoding capacity. More specifically, we prove that for any $\epsilon>0$ and $R\in (0,1)$, with high probability, randomly punctured Reed-Solomon codes of block length $n$ and rate $R$ are $\left(1-R-\epsilon, O({1}/{\epsilon})\

Mohit Garg, Mélanie Bouroche

Connected Autonomous Vehicles (CAVs) are widely expected to improve traffic safety and efficiency by exploiting information from surrounding vehicles via V2V communication. A CAV typically adapts its speed based on information from the vehicle it follows. CAVs can also use information from vehicles further ahead within their communication range, and this res

Sheng He, Rina Bao, P. Ellen Grant, Yangming Ou

The combination of the U-Net based deep learning models and Transformer is a new trend for medical image segmentation. U-Net can extract the detailed local semantic and texture information and Transformer can learn the long-rang dependencies among pixels in the input image. However, directly adapting the Transformer for segmentation has ``token-flatten" prob

Bartosz Malman

For a positive finite Borel measure $\mu$ compactly supported in the complex plane, the space $\mathcal{P}^2(\mu)$ is the closure of the analytic polynomials in the Lebesgue space $L^2(\mu)$. According to Thomson's famous result, any space $\mathcal{P}^2(\mu)$ decomposes as an orthogonal sum of pieces which are essentially analytic, and a residual $L^2$-spac

Md Abdul Kadir, Fabrizio Nunnari, Daniel Sonntag

In this paper, we propose a CNN fine-tuning method which enables users to give simultaneous feedback on two outputs: the classification itself and the visual explanation for the classification. We present the effect of this feedback strategy in a skin lesion classification task and measure how CNNs react to the two types of user feedback. To implement this a

Rongqi Pan, Taher A. Ghaleb, Lionel Briand

Test suites tend to grow when software evolves, making it often infeasible to execute all test cases with the allocated testing budgets, especially for large software systems. Test suite minimization (TSM) is employed to improve the efficiency of software testing by removing redundant test cases, thus reducing testing time and resources, while maintaining th

Patil Shubham Suresh, Gautham Narayan Narasimhan

State estimation of oncoming vehicles: Earlier research has been based on determining states like position, velocity, orientation , angular velocity, etc of ego-vehicle. Our approach focuses on estimating the states of non-ego vehicles which is crucial for Motion planning and decision-making. Dynamic Scene Based Localization: Our project will work on dynamic

Leonardo F. Toso, Han Wang, James Anderson

We address the problem of learning linear system models from observing multiple trajectories from different system dynamics. This framework encompasses a collaborative scenario where several systems seeking to estimate their dynamics are partitioned into clusters according to their system similarity. Thus, the systems within the same cluster can benefit from

David Wahiche

We explore some connections between vectors of integers and integer partitions seen as bi-infinite words. This methodology enables us to give a combinatorial interpretation of the Macdonald identities for affine root systems of the seven infinite families in terms of symplectic and special orthogonal Schur functions. From these results, we are able to derive

Erik D. Demaine, Martin L. Demaine

We propose a new standard for writing author names on papers and in bibliographies, which places every author as a first author -- superimposed. This approach enables authors to write papers as true equals, without any advantage given to whoever's name happens to come first alphabetically (for example). We develop the technology for implementing this standar

Sander Greenland

Mathematics is a limited component of solutions to real-world problems, as it expresses only what is expected to be true if all our assumptions are correct, including implicit assumptions that are omnipresent and often incorrect. Statistical methods are rife with implicit assumptions whose violation can be life-threatening when results from them are used to

Lizhou Fan, Lingyao Li, Zihui Ma, Sanggyu Lee

Large language models (LLMs) are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks and have become a highly sought-after research area, because of their ability to generate human-like language and their potential to revolutionize science and technology. In this study, we conduc

Zhimeng Guo, Teng Xiao, Zongyu Wu, Charu Aggarwal

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks. Graph neural networks (GNNs) have achieved great success in representation learning on graphs, facilitating various downstream tasks. However, GNNs have several drawbacks such as lacking interpretability, can easily inherit the bias of da

James M. De Buizer, Wanggi Lim, James T. Radomski, Mengyao Liu

We present our fifth set of results from our mid-infrared imaging survey of Milky Way Giant HII (GHII) regions with our detailed analysis of DR7 and K3-50. We obtained 20/25 and 37um imaging maps of both regions using the FORCAST instrument on the Stratospheric Observatory For Infrared Astronomy (SOFIA). We investigate the multi-scale properties of DR7 and K

Soham Pal, Shiplu Sarker, Patrick J. Fasano, Pieter Maris

Chiral effective field theory ($\chi$EFT) provides a framework for obtaining internucleon interactions in a systematically improvable fashion from first principles, while also providing for the derivation of consistent electroweak current operators. In this work, we apply consistently derived interactions and currents towards calculating the magnetic dipole

J. M. Cabarcas, Alexander Parada, Nestor Quintero-Poveda

Recently the neutrino experiments ANTARES and IceCube have released new constraints to the non-standard neutrino interaction (NSI) parameter $\epsilon^d_{\mu\tau}$ (flavor off-diagonal). These new constraints are stronger than those obtained from a combination of COHERENT and neutrino oscillation data. In the light of the recent constraints from ANTARES and

Alan Junzhe Zhou, Scott Dodelson

Extracting information from cosmic surveys is often done in a two-step process, construction of maps and then summary statistics such as two-point functions. We use simulations to demonstrate the advantages of a general Bayesian framework that consistently combines different cosmological experiments on the field level, and reconstructs both the maps and cosm

Anthony Goeckner, Xinliang Li, Ermin Wei, Qi Zhu

Multi-agent patrolling is a key problem in a variety of domains such as intrusion detection, area surveillance, and policing which involves repeated visits by a group of agents to specified points in an environment. While the problem is well-studied, most works do not provide performance guarantees and either do not consider agent attrition or impose signifi

Amarjit Budhiraja, Adam Waterbury, Pavlos Zoubouloglou

Let $\Delta^o$ be a finite set and, for each probability measure $m$ on $\Delta^o$, let $G(m)$ be a transition probability kernel on $\Delta^o$. Fix $x_0 \in \Delta^o$ and consider the chain $\{X_n, \; n \in \mathbb{N}_0\}$ of $\Delta^o$-valued random variables such that $X_0=x$, and given $X_0, \ldots , X_n$, the conditional distribution of $X_{n+1}$ is $G(

Alice Garbagnati, Cecília Salgado

We survey our contributions on the classification of elliptic fibrations on K3 surfaces with a non-symplectic involution. We place them in the more general framework of K3 surfaces with an involution without any hypothesis on its fixed locus or on the action on the symplectic 2-form. We revisit the complete classification of elliptic fibrations on K3 surface

Pedro Castro, Tae-Kyun Kim

Estimating the pose of an unseen object is the goal of the challenging one-shot pose estimation task. Previous methods have heavily relied on feature matching with great success. However, these methods are often inefficient and limited by their reliance on pre-trained models that have not be designed specifically for pose estimation. In this paper we propose

Xianglong Ni, Jerzy Weyman

We construct two families of free resolutions that resolve the ideals of certain opposite Schubert varieties restricted to the big open cell. We conjecture that these examples have genericity properties translating to structure theorems for perfect ideals with given Betti numbers, extending the well-known theorem of Buchsbaum and Eisenbud on Gorenstein ideal

Alexander Nolte

The $\text{PSL}(4,\mathbb{R})$ Hitchin component of a closed surface group $\pi_1(S)$ consists of holonomies of properly convex foliated projective structures on the unit tangent bundle of $S$. We prove that the leaves of the codimension-$1$ foliation of any such projective structure are all projectively equivalent if and only if its holonomy is Fuchsian. Th

Anicet Mougabe-Peurkor, Ibrahima Drame, Modeste N'zi, Etienne Pardoux

This paper studies the distribution function of the time of extinction of a subcritical epidemic, when a large enough proportion of the population has been immunized and/or the infectivity of the infectious individuals has been reduced, so that the effective reproduction number is less than one. We do that for a SIR/SEIR model, where infectious individuals h

J. -S. Huang, Zi-Jian Li, Cheng Cheng, Meicun Hou

Four ultra-luminous infrared galaxies (ULIRGs) observed with JWST/NIRcam in the Cosmos Evolution Early Release Science program offer an unbiased preview of the $z\approx2$ ULIRG population. The objects were originally selected at 24 $\mu$m and have strong polycyclic aromatic hydrocarbon emission features observed with Spitzer/IRS. The four objects have simil

Walter Bridges, Kathrin Bringmann

In this paper we prove an exact formula for the number of partitions without sequences. By work of Andrews, the corresponding generating function is a product of a modular form and a mock theta function, giving an overall weight of 0. The proof requires evaluating and bounding Kloosterman sums and the Circle Method