March 2023 arXiv papers — page 116

Changhao Liu, Fan Yang, Shenheng Xu, Maokun Li

Reconfigurable transmitarray antennas (RTAs) are rapidly gaining popularity, but optimizing their performance requires systematic design theories. In particular, establishing a performance limit theory for RTA elements is valuable. This paper presents a transmission efficiency limit theory for single-switch RTA elements and their cascaded extensions. Employi

Fang Kong, Canzhe Zhao, Shuai Li

The linear bandit problem has been studied for many years in both stochastic and adversarial settings. Designing an algorithm that can optimize the environment without knowing the loss type attracts lots of interest. \citet{LeeLWZ021} propose an algorithm that actively detects the loss type and then switches between different algorithms specially designed fo

Jizhou Li, Keisuke Fujioka, Akira Shudo

As a continuation of a previous paper (arXiv:2303.05769 [nlin.CD]), we introduce examples of H\'enon-type mappings that exhibit new horseshoe topologies in three and four dimensional spaces that are otherwise impossible in two dimensions.

Atul Dhingra, Gaurav Sood

India has twenty-two official languages. Serving such a diverse language base is a challenge for survey statisticians, call center operators, software developers, and other such service providers. To help provide better services to different language communities via better localization, we introduce a new machine learning model that predicts the language(s)

Chen Yang, Zinan Ma, Peng Liang, Xiaohua Liu

In software development, due to the lack of knowledge or information, time pressure, complex context, and many other factors, various uncertainties emerge during the development process, leading to assumptions scattered in projects. Being unaware of certain assumptions can result in critical problems (e.g., system vulnerability and failures). The prerequisit

Lutao Jiang, Ruyi Ji, Libo Zhang

In this paper, we develop a new method, termed SDF-3DGAN, for 3D object generation and 3D-Aware image synthesis tasks, which introduce implicit Signed Distance Function (SDF) as the 3D object representation method in the generative field. We apply SDF for higher quality representation of 3D object in space and design a new SDF neural renderer, which has high

Mohit Kumar, Keith Kelly

This article develops the applicability of non-linear processing techniques such as Compressed Sensing (CS), Principal Component Analysis (PCA), Iterative Adaptive Approach (IAA) and Multiple-input-multiple-output (MIMO) for the purpose of enhanced UAV detections using portable radar systems. The combined scheme has many advantages and the potential for bett

Qidan Zhu, Jing Li, Fei Yuan, Quan Gan

The goal of continuous sign language recognition(CSLR) research is to apply CSLR models as a communication tool in real life, and the real-time requirement of the models is important. In this paper, we address the model real-time problem through cross-resolution knowledge distillation. In our study, we found that keeping the frame-level feature scales consis

Haocong Rao, Chunyan Miao

Person re-identification (re-ID) via 3D skeleton data is an emerging topic with prominent advantages. Existing methods usually design skeleton descriptors with raw body joints or perform skeleton sequence representation learning. However, they typically cannot concurrently model different body-component relations, and rarely explore useful semantics from fin

Zaixi Zhang, Qi Liu, Zhicai Wang, Zepu Lu

Deep neural networks (DNNs) are recently shown to be vulnerable to backdoor attacks, where attackers embed hidden backdoors in the DNN model by injecting a few poisoned examples into the training dataset. While extensive efforts have been made to detect and remove backdoors from backdoored DNNs, it is still not clear whether a backdoor-free clean model can b

Nanqing Liu, Xun Xu, Turgay Celik, Zongxin Gan

Object detection in remote sensing images relies on a large amount of labeled data for training. However, the increasing number of new categories and class imbalance make exhaustive annotation impractical. Few-shot object detection (FSOD) addresses this issue by leveraging meta-learning on seen base classes and fine-tuning on novel classes with limited label

Jean-François Fortin, Wen-Jie Ma, Valentina Prilepina, Witold Skiba

We describe how to implement the conformal bootstrap program in the context of the embedding space OPE formalism introduced in previous work. To take maximal advantage of the known properties of the scalar conformal blocks for symmetric-traceless exchange, we construct tensorial generalizations of the three-point and four-point scalar conformal blocks that h

Chenyang Li, Jihoon Chung, Mengnan Du, Haimin Wang

Model compression is a crucial part of deploying neural networks (NNs), especially when the memory and storage of computing devices are limited in many applications. This paper focuses on two model compression techniques: low-rank approximation and weight pruning in neural networks, which are very popular nowadays. However, training NN with low-rank approxim

Shao-Wen Wei, Yu-Peng Zhang, Yu-Xiao Liu, Robert B. Mann

Unique features of particle orbits produce novel signatures of gravitational observable phenomena, and are quite useful in testing compact astrophysical objects in general relativity or modified theories of gravity. Here we observe a representative example that a static, spherically symmetric black hole solution with nonlinear electrodynamics admits static p

Susannah Kate Devitt

21st Century war is increasing in speed, with conventional forces combined with massed use of autonomous systems and human-machine integration. However, a significant challenge is how humans can ensure moral and legal responsibility for systems operating outside of normal temporal parameters. This chapter considers whether humans can stand outside of real ti

Juan Chen, Yingchun Zhou

In many scientific fields such as biology, psychology and sociology, there is an increasing interest in estimating the causal effect of a matrix exposure on an outcome. Covariate balancing is crucial in causal inference and both exact balancing and approximate balancing methods have been proposed in the past decades. However, due to the large number of const

Xiaopeng Yan, Yindi Yang, Zhihao Guo, Liangliang Peng

This paper describes our NPU-Elevoc personalized speech enhancement system (NAPSE) for the 5th Deep Noise Suppression Challenge at ICASSP 2023. Based on the superior two-stage model TEA-PSE 2.0, our system particularly explores better strategy for speaker embedding fusion, optimizes the model training pipeline, and leverages adversarial training and multi-sc

Ziqi He, Mengjia Xue, Yunhao Du, Zhicheng Zhao

Unsupervised Re-ID methods aim at learning robust and discriminative features from unlabeled data. However, existing methods often ignore the relationship between module parameters of Re-ID framework and feature distributions, which may lead to feature misalignment and hinder the model performance. To address this problem, we propose a dynamic clustering and

Jianwei Zhang, Jinyu Lei, Wenzhang Tian, Guangzhao Zhang

We performed molecular dynamics simulations with a coarse-grained model to investigate the capillary filling dynamics of polymer chains in nanopores. Short chains fill slower than predicted by the Lucas-Washburn equation but long chains fill faster. The analysis shows that the combination of the confinement effect on the free energy of chains and the reducti

Zeming Dong, Qiang Hu, Yuejun Guo, Zhenya Zhang

Recent studies have demonstrated remarkable advancements in source code learning, which applies deep neural networks (DNNs) to tackle various software engineering tasks. Similar to other DNN-based domains, source code learning also requires massive high-quality training data to achieve the success of these applications. Data augmentation, a technique used to

Shuhan Li, Dong Zhang, Xiaomeng Li, Chubin Ou

Optical Coherence Tomography Angiography (OCTA) is a crucial tool in the clinical screening of retinal diseases, allowing for accurate 3D imaging of blood vessels through non-invasive scanning. However, the hardware-based approach for acquiring OCTA images presents challenges due to the need for specialized sensors and expensive devices. In this paper, we in

Yusuke Fujita, Tatsuya Komatsu, Robin Scheibler, Yusuke Kida

End-to-end neural diarization (EEND) with encoder-decoder-based attractors (EDA) is a promising method to handle the whole speaker diarization problem simultaneously with a single neural network. While the EEND model can produce all frame-level speaker labels simultaneously, it disregards output label dependency. In this work, we propose a novel EEND model t

Andrea L. Gallo, Pablo Román

We study algebras of differential and difference operators acting on matrix valued orthogonal polynomials (MVOPs) with respect to a weight matrix of the form $W^{(\nu)}_{\phi}(x) = x^{\nu}e^{-\phi(x)} W^{(\nu)}_{pol}(x)$, where $\nu>0$, $W^{(\nu)}_{pol}(x)$ is certain matrix valued polynomial and $\phi$ an entire function. We introduce a pair differential op

Jiake Wei, Masato Yoshiya, Feng Bin, Naoya Shibata

The surface steps play dramatic roles in surface dominated processes and the related properties, in which these roles would be significantly enhanced for the low-dimensional nano or quantum materials since the ratio of surface atoms is largely increased. However, the atomic structures of surface steps in the nano/quantum systems are poorly understood because

Yuri V. Lvov, Victor S. L'vov

We use the Dyson-Wyld diagrammatic technique to analyze the infinite series for the correlation functions of the velocity in the hydrodynamic turbulence. We demonstrate the fundamental role played by the triple correlator of the velocity in determining the entire statistics of the hydrodynamic turbulence. All higher order correlation functions are expressed

Xin Li

A long line of work in the past two decades or so established close connections between several different pseudorandom objects and applications. These connections essentially show that an asymptotically optimal construction of one central object will lead to asymptotically optimal solutions to all the others. However, despite considerable effort, previous wo

Geoffrey Exoo, Dan Ismailescu

The chromatic number of the plane problem asks for the minimum number of colors so that each point of the plane can be assigned a single color with the property that no two points unit-distance apart are identically colored. It is now known that the answer is 5, 6, or 7. Here we consider the problem in the context of the hyperbolic plane. We prove that there

Hyeongseok Son, Sangil Jung, Solae Lee, Seongeun Kim

Human is one of the most essential classes in visual recognition tasks such as detection, segmentation, and pose estimation. Although much effort has been put into individual tasks, multi-task learning for these three tasks has been rarely studied. In this paper, we explore a compact multi-task network architecture that maximally shares the parameters of the

Ziyu Cao, Kailai Li

We present a principled study on defining Gaussian processes (GPs) with inputs on the product of directional manifolds. A circular kernel is first presented according to the von Mises distribution. Based thereon, the hypertoroidal von Mises (HvM) kernel is proposed to establish GPs on hypertori with consideration of correlated circular components. The propos

Huynh Viêt Khánh

In this paper, we classify all Leavitt path algebras which have the property that every Lie ideal is an ideal. As an application, we show that Leavitt path algebras with this property provide a class of locally finite, infinite-dimensional Lie algebras whose locally solvable radical is completely determined. This particularly gives us a new class of semisimp

Hongyi Pan, Emadeldeen Hamdan, Xin Zhu, Salih Atici

In this paper, we propose a set of transform-based neural network layers as an alternative to the $3\times3$ Conv2D layers in Convolutional Neural Networks (CNNs). The proposed layers can be implemented based on orthogonal transforms such as the Discrete Cosine Transform (DCT), Hadamard transform (HT), and biorthogonal Block Wavelet Transform (BWT). Furtherm

Xuesheng Bian, Cheng Wang, Shuting Chen, Weiquan Liu

Adenosine triphosphate (ATP) is a high-energy phosphate compound and the most direct energy source in organisms. ATP is an essential biomarker for evaluating cell viability in biology. Researchers often use ATP bioluminescence to measure the ATP of organoid after drug to evaluate the drug efficacy. However, ATP bioluminescence has some limitations, leading t

Tianyi Huang, Stan Z. Li, Xin Yuan, Shenghui Cheng

Metaverse is a perpetual and persistent multi-user environment that merges physical reality with digital virtuality. It is widely considered to be the next revolution of the Internet. Digital humans are a critical part of Metaverse. They are driven by artificial intelligence (AI) and deployed in many applications. However, it is a complex process to construc

Anna Kawakami, Shreya Chowdhary, Shamsi T. Iqbal, Q. Vera Liao

With the heightened digitization of the workplace, alongside the rise of remote and hybrid work prompted by the pandemic, there is growing corporate interest in using passive sensing technologies for workplace wellbeing. Existing research on these technologies often focus on understanding or improving interactions between an individual user and the technolog

Prateek R. Srivastava, Apratim Majumdar, Rajesh Menon, Grover A. Swartzlander

The radiation pressure force and torque on a one-dimensional bi-grating composed of a Si-SiO_2 high contrast binary metagrating is analyzed for the purpose of stable beam riding whereupon a high power laser having an expanding Gaussian irradiance distribution propels the grating in outer space, free from gravitational forces. The binary metagrating structure

Hsu Kao, Vijay Subramanian

Distributed optimization algorithms have been studied extensively in the literature; however, underlying most algorithms is a linear consensus scheme, i.e. averaging variables from neighbors via doubly stochastic matrices. We consider nonlinear consensus schemes with a set of time-varying and agent-dependent monotonic Lipschitz nonlinear transformations, whe

Arun Tejasvi Chaganty, Megan Leszczynski, Shu Zhang, Ravi Ganti

Users in consumption domains, like music, are often able to more efficiently provide preferences over a set of items (e.g. a playlist or radio) than over single items (e.g. songs). Unfortunately, this is an underexplored area of research, with most existing recommendation systems limited to understanding preferences over single items. Curating an item set ex

Jonathan M. Schuster, Carlos E. Schvezov, Mario R. Rosenberger

The Neumann Equation of State (EQS) allows obtaining the value of the surface free energy of a solid ${\gamma}_{SV}$ from the contact angle $({\theta})$ of a probe liquid with known surface tension ${\gamma}_{LV}$. The value of ${\gamma}_{SV}$ is obtained by numerical methods solving the corresponding EQS. In this work, we analyzed the discrepancies between

Kristóf Huszár, Jonathan Spreer

Motivated by the algorithmic study of 3-dimensional manifolds, we explore the structural relationship between the JSJ decomposition of a given 3-manifold and its triangulations. Building on work of Bachman, Derby-Talbot and Sedgwick, we show that a "sufficiently complicated" JSJ decomposition of a 3-manifold enforces a "complicated structure" for all of its

Eleni-Alexandra Kontou, Veronica Sacchi

Hawking's black hole area theorem was proven using the null energy condition (NEC), a pointwise condition violated by quantum fields. The violation of the NEC is usually cited as the reason that black hole evaporation is allowed in the context of semiclassical gravity. Here we provide two generalizations of the classical black hole area theorem: First, a pro

Paolo Lipparini

We devise exact conditions under which a join semilattice with a weak contact relation can be semilattice embedded into a Boolean algebra with an overlap contact relation, equivalently, into a distributive lattice with additive contact relation. A similar characterization is proved with respect to Boolean algebras and distributive lattices with weak contact,

Marc S. Klinger, Robert G. Leigh, Pin-Chun Pai

In a recent paper, it was shown that in diffeomorphism-invariant theories, Noether charges associated with a given codimension-2 surface become integrable if one introduces an extended phase space. In this paper we extend the notion of extended phase space to all gauge theories with arbitrary combinations of internal and spacetime local symmetries. We formul

Darshan Chalise, David G. Cahill

Thermal management of integrated circuits (ICs) is important to prevent thermal hotspots which are the leading cause of IC failure. Thermal management is even more critical in 3D integrated circuits (3D ICs) as the prevalence of thermal hotspots is expected to increase due to the presence of polymers and solder materials that are of low thermal conductivity.

Madeline Hennessey, Benjamin Whitefield, Angus Gale, John A Scott

Hexagonal boron nitride (hBN) is gaining interest as a wide bandgap van der Waals host of optically active spin defects for quantum technologies. Most studies of the spin-photon interface in hBN focus on the negatively charged boron vacancy (VB-) defect, which is typically fabricated by ion irradiation. However, VB- fabrication methods often lack robustness

Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman, Vishwa S. Parekh

Federated learning is a recent development in the machine learning area that allows a system of devices to train on one or more tasks without sharing their data to a single location or device. However, this framework still requires a centralized global model to consolidate individual models into one, and the devices train synchronously, which both can be pot

SM Hasan Mansur, Sabiha Salma, Damilola Awofisayo, Kevin Moran

Past studies have illustrated the prevalence of UI dark patterns, or user interfaces that can lead end-users toward (unknowingly) taking actions that they may not have intended. Such deceptive UI designs can result in adverse effects on end users, such as oversharing personal information or financial loss. While significant research progress has been made to

Jens Hemelaer

Let $M$ be a monoid that is embeddable in a group. We consider the topos $\mathbf{PSh}(M)$ of sets equipped with a right $M$-action, and we study the subtoposes that are of monoid type, i.e. the subtoposes that are again of the form $\mathbf{PSh}(N)$ for $N$ a monoid. Our main result is that every subtopos of monoid type can be obtained by localization at a

Ala-Eddine Yahiaoui, Sohaib Afifi, Hamid Afifi

Most public facilities in the European countries, including France, Germany, and the UK, were built during the reconstruction projects between 1950 and 1980. Owing to the deteriorating state of such vital infrastructure has become relatively expensive in the recent decades. A significant part of the maintenance operation costs is spent on the technical staff

Elena Angelini, Luca Chiantini, Alessandro Oneto

We prove the existence of ternary forms admitting apolar sets of points of cardinality equal to the Waring rank, but having different Hilbert function and different regularity. This is done exploiting liaison theory and Cayley-Bacharach properties for sets of points in the projective plane

S. Mashdour, R. C. de Lamare, J. P. Sales

In this work, we investigate the sum-rate performance of multicell and cell-free massive MIMO systems using linear precoding and multiuser scheduling algorithms. We consider the use of a network-centric clustering approach to reduce the computational complexity of the techniques applied to the cell-free system. We then develop a greedy algorithm that conside

Morgan Jones

Under what circumstances does the ``closeness" of two functions imply the ``closeness" of their respective sublevel sets? In this paper, we answer this question by showing that if a sequence of functions converges strictly from above/below to a function, $V$, in the $L^\infty$ (or $L^1$) norm then these functions yield a sequence sublevel sets that converge

Joshua Horowitz, Jeffrey Heer

Efforts to push programming beyond static textual code have sought to imbue programming with multiple distinct qualities. One long-acknowledged quality is liveness: providing programmers with in-depth feedback about a program's dynamic behavior as the program is edited. A second quality, long-explored but lacking a shared term of art, is richness: allowing p

Aniketh Ramesh, Madeleine Englund, Andreas Theodorou, Rustam Stolkin

Using different Levels of Autonomy (LoA), a human operator can vary the extent of control they have over a robot's actions. LoAs enable operators to mitigate a robot's performance degradation or limitations in the its autonomous capabilities. However, LoA regulation and other tasks may often overload an operator's cognitive abilities. Inspired by video game

Hyeonchang Jeon, Kyung-Joong Kim

Ad-hoc team cooperation is the problem of cooperating with other players that have not been seen in the learning process. Recently, this problem has been considered in the context of Hanabi, which requires cooperation without explicit communication with the other players. While in self-play strategies cooperating on reinforcement learning (RL) process has sh

Max Wenqiang Xu

We investigate when the better than square-root cancellation phenomenon exists for $\sum_{n\le N}a(n)f(n)$, where $a(n)\in \mathbb{C}$ and $f(n)$ is a random multiplicative function. We focus on the case where $a(n)$ is the indicator function of $R$ rough numbers. We prove that $\log \log R \asymp (\log \log x)^{\frac{1}{2}}$ is the threshold for the better

E. Villaseñor, M. S. Winnel, T. C. Ralph, R. Aguinaldo

Due to turbulence and tracking errors, free-space optical channels involving mobile transceivers are characterized by a signal's partial loss or complete erasure. This work presents an error correction protocol capable of protecting a signal passing through such channels by encoding it with an ancillary entangled bipartite state. Beyond its ability to offer

Matthew J. Fyfe, Yesenia Hernandez, Pietro Paparella, Malini Rajbhandari

In this work, it is shown that if $A$ is an $n$-by-$n$ convexoid matrix (i.e., its field of values coincides with the convex hull of its eigenvalues), then the field of any $(n-1)$-by-$(n-1)$ principal submatrix of $A$ is inscribed in the field of $A$, i.e., the field is tangent to every side of the polygon corresponding to the boundary of the field of $A$.

A. Danehkar

The dust properties of the line-of-sight materials in neutron star low-mass X-ray binaries (LMXBs) can be probed by X-ray observations and laboratory experiments. We use a Markov chain Monte Carlo (MCMC) method to conduct a spectral analysis of Chandra ACIS-S/HETG archival data of a sample of LMXBs, including GX 5-1 and GX 13+1. Our MCMC-based analysis puts

T. Neidhart, E. K. Sansom, K. Miljković, G. S. Collins

We investigated 634 crater clusters on Mars detected between 2007 and 2021, which represent more than half of all impacts discovered in this period. Crater clusters form when meteoroids in the 10 kg to 10 ton mass range break-up in Mars' atmosphere to produce a few to a few hundred fragments that hit the ground. The properties of the clusters can inform our

Bin Han, Michelle Michelle

The Helmholtz equation with variable wavenumbers is challenging to solve numerically due to the pollution effect, which often results in a huge ill-conditioned linear system. In this paper, we present a high-order wavelet Galerkin method to numerically solve an electromagnetic scattering from a large cavity problem modeled by the 2D Helmholtz equation with v

Kallol Sen

We generalize the coin operator of \cite{Zahed_2023}, to include a step dependent feature which induces localization in $2d$. This is evident from the probability distributions which can be further used to categorize the localized walks. Localization is also evident from the entropic measures. We compute and compare three distinct measures (a) Shannon Entrop

Yiyuan Lee, Katie Lee, Panpan Cai, David Hsu

Identifying internal parameters for planning is crucial to maximizing the performance of a planner. However, automatically tuning internal parameters which are conditioned on the problem instance is especially challenging. A recent line of work focuses on learning planning parameter generators, but lack a consistent problem definition and software framework.

Michał Morayne, Robert Rałowski

In $T_1$ compact topological spaces the Hutchinson operator of a contractive IFS (iterated function system; a finite family of closed mappings from the space into itself) may not be closed. Nevertheless, the Hutchinson operator of a contractive IFS has always a unique fixed point.

Jun Yang, Jason Rebello, Steven L. Waslander

Robotic eye-in-hand calibration is the task of determining the rigid 6-DoF pose of the camera with respect to the robot end-effector frame. In this paper, we formulate this task as a non-linear optimization problem and introduce an active vision approach to strategically select the robot pose for maximizing calibration accuracy. Specifically, given an initia

Ovidiu-Zeno Lipan, Aldo De Sabata

Pendry and MacKinnon meaningful discretization of Maxwell's equations was put forward specifically as part of a finite-element numerical algorithm. By contrast with a numerical approach, in the same spirit evoked by the relationships between the difference and the differential equations, we provide an analytical solution for the transfer matrix elements gene

Cristina Ballantine

We give combinatorial proofs of several recent results due to Merca on the sum of different parts congruent to $r$ modulo $m$ in all partitions of $n$. The proofs make use of some well known involutions from the literature and some new involutions introduced here.

Nirbhaya Shajia, Florbela Nunes, M. Ines Rocha, Elsa Ferreira Gomes

Background and objective: Cell migration is essential for many biological phenomena with direct impact on human health and disease. One conventional approach to study cell migration involves the quantitative analysis of individual cell trajectories recorded by time-lapse video microscopy. Dedicated software tools exist to assist the automated or semi-automat

Guosheng Fu, Wenzheng Kuang

In this study, we present an $hp$-multigrid preconditioner for a divergence-conforming HDG scheme for the generalized Stokes and the Navier-Stokes equations using an augmented Lagrangian formulation. Our method relies on conforming simplicial meshes in two- and three-dimensions. The $hp$-multigrid algorithm is a multiplicative auxiliary space preconditioner

Yuzhou Qiu, E. Alper Yıldırım

Quadratic programs with box constraints involve minimizing a possibly nonconvex quadratic function subject to lower and upper bounds on each variable. This is a well-known NP-hard problem that frequently arises in various applications. We focus on two convex relaxations, namely the RLT (Reformulation-Linearization Technique) relaxation and the SDP-RLT relaxa

Samuel Christensen, Marcus Roper

Within microcentrifuge devices, a microfluidic vortex separates larger particles from a heterogeneous suspension using inertial migration, a phenomenon that causes particles to migrate across streamlines. The ability to selectively capture particles based on size differences of a few microns makes microcentrifuges useful diagnostic tools for trapping rare ce

Symon Serbenyuk

The present research deals with generalizations of the Salem function with arguments defined in terms of certain alternating expansions of real numbers. The special attention is given to modelling such functions by systems of functional equations.

Benjamin Qi, Richard Qi, Xinyang Chen

We analyze the touring regions problem: find a ($1+\epsilon$)-approximate Euclidean shortest path in $d$-dimensional space that starts at a given starting point, ends at a given ending point, and visits given regions $R_1, R_2, R_3, \dots, R_n$ in that order. Our main result is an $\mathcal O \left(\frac{n}{\sqrt{\epsilon}}\log{\frac{1}{\epsilon}} + \frac{1}

Dominik Bork, Syed Juned Ali, Ben Roelens

In conceptual modeling (CM), humans apply abstraction to represent excerpts of reality for means of understanding and communication, and processing by machines. Artificial Intelligence (AI) is applied to vast amounts of data to automatically identify patterns or classify entities. While CM produces comprehensible and explicit knowledge representations, the o

Prakash Chandra Chhipa, Muskaan Chopra, Gopal Mengi, Varun Gupta

This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge transfer is achieved by joint optimization of self-supervised learning pseudo task and supervised learning task, improving supervised learning task performance. Recent progress in sel

Randy Kwende, Theodore White, Ofer Naaman

We demonstrate a 3-port Josephson parametric circulator, matched to 50 Ohm using second order Chebyshev networks. The device notably operates with two of its signal ports at the same frequency and uses only two out-of-phase pumps at a single frequency. As a consequence, when operated as an isolator it does not require phase coherence between the pumps and th

Stein Andreas Bethuelsen, Florian Völlering

We study the asymptotic behaviour of a random walk whose evolution is dependent on the state of an itself dynamically evolving environment. In particular, we extend our previous results in [Bethuelsen and V\"ollering, 2016] and prove a strong law of large numbers and large deviation estimates assuming that the dynamic environment is "path-cone"-mixing. Under

Elia Portnoy

For $n \ge 3$, we demonstrate the existence of quantum codes which are local in dimension $n$ with $V$ qubits, distance $V^{\frac{n-1}{n}}$, and dimension $V^{\frac{n-2}{n}}$, up to a $polylog(V)$ factor. The distance is optimal up to the polylog factor. The dimension is also optimal for this distance up to the polylog factor. The proof combines the existenc

Or Sattath, Shai Wyborski

Current solutions to quantum vulnerabilities of widely used cryptographic schemes involve migrating users to post-quantum schemes before quantum attacks become feasible. This work deals with protecting quantum procrastinators: users that failed to migrate to post-quantum cryptography in time. To address this problem in the context of digital signatures, we i

Saqib Javed, Chengkun Li, Andrew Price, Yinlin Hu

Edge applications, such as collaborative robotics and spacecraft rendezvous, demand efficient 6D object pose estimation on resource-constrained embedded platforms. Existing 6D pose estimation networks are often too large for such deployments, necessitating compression while maintaining reliable performance. To address this challenge, we introduce Modular Qua

Wan-Bing He, Yu-Gang Ma, Long-Gang Pang, Huichao Song

Though being seemingly disparate and with relatively new intersection, high energy nuclear physics and machine learning have already begun to merge and yield interesting results during the last few years. It's worthy to raise the profile of utilizing this novel mindset from machine learning in high energy nuclear physics, to help more interested readers see

Francesc Castella, Kim Tuan Do

We construct a new Euler system for the Galois representation $V_{f,\chi}$ attached to a newform $f$ of weight $2r\geq 2$ twisted by an anticyclotomic Hecke character $\chi$. The Euler system is anticyclotomic in the sense of Jetchev-Nekovar-Skinner. We then show some arithmetic applications of the constructed Euler system, including new results on the Bloch

Maxim Dzero

I consider relaxation of the pairing amplitude in a disordered Bardeen-Cooper-Schrieffer (BCS) superconductor in the absence of the two-particle collisions. My main assumption is that nonmagnetic and magnetic disorder scattering rates are much smaller than the value of the superconducting pairing gap $\Delta_0$. I derive a system of nonlinear equations which

David Pinzon, Emma Frejinger, Bernard Gendron

We introduce a strategic decision-making problem faced by logistics providers (LPs) seeking facility location decisions that lead to profitable operations. The profitability depends on the revenue generated through agreements with shippers, and the costs arising when satisfying those agreements. The latter depend in turn on service levels and on characterist

Arash Dargahi Nobari, Davood Rafiei

Many organizations rely on data from government and third-party sources, and those sources rarely follow the same data formatting. This introduces challenges in integrating data from multiple sources or aligning external sources with internal databases. Commercial database systems do not offer adequate support for integrating data from heterogeneous sources,

Chenzhong Yin, Zhihong Pan, Xin Zhou, Le Kang

Normalizing flow models using invertible neural networks (INN) have been widely investigated for successful generative image super-resolution (SR) by learning the transformation between the normal distribution of latent variable $z$ and the conditional distribution of high-resolution (HR) images gave a low-resolution (LR) input. Recently, image rescaling mod

Hristu Culetu

A modified extremal Reissner-Nordstrom geometry, void of singularities, is proposed in this work, by means of an exponential factor depending on a positive constant $k$. All the metric coefficients are positive and finite and the spacetime has no any horizon. The curvature invariants are regular at the origin of coordinates and at infinity. The energy condit

Mahya Morid Ahmadi, Lilas Alrahis, Ozgur Sinanoglu, Muhammad Shafique

Extracting the architecture of layers of a given deep neural network (DNN) through hardware-based side channels allows adversaries to steal its intellectual property and even launch powerful adversarial attacks on the target system. In this work, we propose DNN-Alias, an obfuscation method for DNNs that forces all the layers in a given network to have simila

Arthur Bik, Alessandro Neri

Over fields of characteristic unequal to $2$, we can identify symmetric matrices with homogeneous polynomials of degree $2$. This allows us to view symmetric rank-metric codes as living inside the space of such polynomials. In this paper, we generalize the construction of symmetric Gabidulin codes to polynomials of degree $d>2$ over field of characteristic $

Ralph E. Spencer, Justin D. Bray, David A. Green, Michael A. Garrett

The cm-wavelength radio flares on Cygnus X-3 have been studied for many years. Our recent paper (Spencer et al., 2022) looked again at the minor flares (flux density S of a few 100 mJy) and compared their properties with those of a sample of major flares (S > 1 Jy). We find that the minor flares have rise times and duration of ~ 1 hour, as opposed to ~ days

Nguyen Tuan, Phi Nguyen, Dai Tran, Hung Pham

Early detection and localization of myocardial infarction (MI) can reduce the severity of cardiac damage through timely treatment interventions. In recent years, deep learning techniques have shown promise for detecting MI in echocardiographic images. However, there has been no examination of how segmentation accuracy affects MI classification performance an

Merlin Carl

The Diproche system is an automated proof checker for texts written in a controlled fragment of German, designed for didactical applications in classes introducing students to proofs for the first time. The first version of the system used a controlled natural language for which a Prolog formalization routine was written. In this paper, we explore the possib

Yinling Zhang, Nan Chen, Curt A. Bronkhorst, Hansohl Cho

Predicting the process of porosity-based ductile damage in polycrystalline metallic materials is an essential practical topic. Ductile damage and its precursors are represented by extreme values in stress and material state quantities, the spatial PDF of which are highly non-Gaussian with strong fat tails. Traditional deterministic forecasts using physical m

Mathias Anselmann, Markus Bause, Nils Margenberg, Pavel Shamko

We present families of space-time finite element methods (STFEMs) for a coupled hyperbolic-parabolic system of poro- or thermoelasticity. Well-posedness of the discrete problems is proved. Higher order approximations inheriting most of the rich structure of solutions to the continuous problem on computationally feasible grids are naturally embedded. However,

Mohsen Sombolestan, Quan Nguyen

Despite the potential benefits of collaborative robots, effective manipulation tasks with quadruped robots remain difficult to realize. In this paper, we propose a hierarchical control system that can handle real-world collaborative manipulation tasks, including uncertainties arising from object properties, shape, and terrain. Our approach consists of three

Salah Zaiem, Robin Algayres, Titouan Parcollet, Slim Essid

Self-supervised learning (SSL) has allowed substantial progress in Automatic Speech Recognition (ASR) performance in low-resource settings. In this context, it has been demonstrated that larger self-supervised feature extractors are crucial for achieving lower downstream ASR error rates. Thus, better performance might be sanctioned with longer inferences. Th

Max Wenqiang Xu, Daodao Yang

We study extreme values of Dirichlet polynomials with multiplicative coefficients, namely \[D_N(t) : = D_{f,\, N}(t)= \frac{1}{\sqrt{N}} \sum_{n\leqslant N} f(n) n^{it}, \] where $f$ is a completely multiplicative function with $|f(n)|=1$ for all $n\in\mathbb{N}$. We use Soundararajan's resonance method to produce large values of $\left|D_N(t)\right|$ unifor

David Beltran, Paata Ivanisvili, José Madrid

We prove the sharp isoperimetric inequality $$ \mathbb{E} \,h_{A}^{\log_{2}(3/2)} \geq \mu(A)^{*} (\log_{2}(1/\mu(A)^{*}))^{\log_{2}(3/2)} $$ for all sets $A \subseteq \{0,1\}^n$, where $\mu$ denotes the uniform probability measure, $\mu(A)^{*}=\min\{\mu(A), 1-\mu(A)\}$, $h_A$ is supported on $A$ and to each vertex $x$ assigns the number of neighbour vertice

Sagar Suhas Joshi, Panagiotis Tsiotras

In recent years, learning-based approaches have revolutionized motion planning. The data generation process for these methods involves caching a large number of high quality paths for different queries (start, goal pairs) in various environments. Conventionally, a uniform random strategy is used for sampling these queries. However, this leads to inclusion of

Zahra Sobhaninia, Nasrin Abharian, Nader Karimi, Shahram Shirani

Endoscopy is a valuable tool for the early diagnosis of colon cancer. However, it requires the expertise of endoscopists and is a time-consuming process. In this work, we propose a new multi-label classification method, which considers two aspects of learning approaches (local and global views) for endoscopic image classification. The model consists of a Swi

A. Parente, H. Navarro, N. M. Vargas, P. Lapa

Controlling the magnetic ground states at the nanoscale is a long-standing basic research problem and an important issue in magnetic storage technologies. Here, we designed a nanostructured material that exhibits very unusual hysteresis loops due to a transition between vortex and double pole states. Arrays of 700 nm diamond-shape nanodots consisting of Py(3