August 2022 arXiv papers — page 76

Shreshth Tuli, Giuliano Casale, Nicholas R. Jennings

Edge Federation is a new computing paradigm that seamlessly interconnects the resources of multiple edge service providers. A key challenge in such systems is the deployment of latency-critical and AI based resource-intensive applications in constrained devices. To address this challenge, we propose a novel memory-efficient deep learning based model, namely

Andrei Andrusenko, Rauf Nasretdinov, Aleksei Romanenko

Optimization of modern ASR architectures is among the highest priority tasks since it saves many computational resources for model training and inference. The work proposes a new Uconv-Conformer architecture based on the standard Conformer model. It consistently reduces the input sequence length by 16 times, which results in speeding up the work of the inter

Yongmin Yoon, Changbom Park

Based on $16,283$ early-type galaxies (ETGs) in $0.025\le z_\mathrm{spec}<0.055$ from Sloan Digital Sky Survey data, we show that the fundamental plane (FP) of ETGs is not a plane in the strict sense but is a curved surface with a twisted shape whose orthogonal direction to the surface is shifted as the central velocity dispersion ($\sigma_0$) or mean surfac

Chulong Zhang, Yuming Jiang, Na Li, Zhicheng Zhang

Pathologists need to combine information from differently stained pathology slices for accurate diagnosis. Deformable image registration is a necessary technique for fusing multi-modal pathology slices. This paper proposes a hybrid deep feature-based deformable image registration framework for stained pathology samples. We first extract dense feature points

Omiros Pantazis, Mathew Salvaris

Representation learning approaches typically rely on images of objects captured from a single perspective that are transformed using affine transformations. Additionally, self-supervised learning, a successful paradigm of representation learning, relies on instance discrimination and self-augmentations which cannot always bridge the gap between observations

Robert Penner

This survey for mathematicians summarizes several works by the author on protein geometry and protein function with applications to viral glycoproteins in general and the spike glycoprotein of the SARS-CoV-2 virus in particular. Background biology and biophysics are sketched. This body of work culminates in a postulate that protein secondary structure regula

Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Yiqun Liu

Knowledge-intensive language tasks (KILT) usually require a large body of information to provide correct answers. A popular paradigm to solve this problem is to combine a search system with a machine reader, where the former retrieves supporting evidences and the latter examines them to produce answers. Recently, the reader component has witnessed significan

Charlotte de Blois, Simon J. Haward, Amy Q. Shen

In a viscoelastic flow over a microfluidic canopy of polymeric pillars, we report the spontaneous emergence of waves in the form of propagating regions of low flow velocity compared to the surrounding flow. The occurrence of the wave is chaotic and shows characteristics of elastic turbulence. We systematically study the coupling between the low velocity wave

Pierre Sutra

Atomic broadcast is a group communication primitive to order messages across a set of distributed processes. Atomic multicast is its natural generalization where each message $m$ is addressed to $dst(m)$, a subset of the processes called its destination group. A solution to atomic multicast is genuine when a process takes steps only if a message is addressed

Thomas Louf, Bruno Gonçalves, Jose J. Ramasco, David Sanchez

Cultural areas represent a useful concept that cross-fertilizes diverse fields in social sciences. Knowledge of how humans organize and relate their ideas and behavior within a society helps to understand their actions and attitudes towards different issues. However, the selection of common traits that shape a cultural area is somewhat arbitrary. What is nee

Giuliano Vitali

The present study is aimed at analysing the benefits of an ontological approach in Functional Structural Plant Modelling. The ontological approach has been used at two levels, to refine the conceptual modelling approach, and to define the nomenclature of the plant. To the scope available domain-specific ontologies describing plant entities and their relation

Bhavya Jain, Sasikumar Periyasamy

Early and precise diagnosis of diseases in plants can help to develop an early treatment technique. Plant diseases degrade both the quantity and quality of crops, thus posing a threat to food security and resulting in huge economic losses. Traditionally identification is performed manually, which is inaccurate, time-consuming, and expensive. This paper prese

R. Basalgète, D. Torres-Díaz, A. Lafosse, L. Amiaud

X-ray photodesorption yields of $^{15}$N$_2$ and $^{13}$CO are derived as a function of the incident photon energy near the N ($\sim$400 eV) and O K-edge ($\sim$500 eV) for pure $^{15}$N$_2$ ice and mixed $^{13}$CO:$^{15}$N$_2$ ices. The photodesorption spectra from the mixed ices reveal an indirect desorption mechanism for which the desorption of $^{15}$N$_

G S R Murthy, T R Lalita

This paper deals with operational models for integrated shift and task scheduling problem. Staff scheduling problem is a special case of this with staff requirements as given input to the problem. Both problems become hard to solve when the problems are considered with flexible shifts. Current literature on these problems leaves good scope for potential rese

Bas van den Heuvel, Jorge A. Pérez

We present Concurrent GV (CGV), a functional calculus with message-passing concurrency governed by session types. With respect to prior calculi, CGV has increased support for concurrent evaluation and for cyclic network topologies. The design of CGV draws on APCP, a session-typed asynchronous pi-calculus developed in prior work. Technical contributions are (

Olusola T. Odeyomi, Olubiyi O. Akintade, Temitayo O. Olowu, Gergely Zaruba

The convergence of 5G architecture and deep learning has gained a lot of research interests in both the fields of wireless communication and artificial intelligence. This is because deep learning technologies have been identified to be the potential driver of the 5G technologies, that make up the 5G architecture. Hence, there have been extensive surveys on t

Amin Maghami, Evrim Ursavas, Ashish Cherukuri

This paper considers a security constrained dispatch problem involving generation and line contingencies in the presence of the renewable generation. The uncertainty due to renewables is modeled using joint chance-constraint and the mismatch caused by contingencies and renewables are handled using reserves. We consider a distributionally robust approach to s

Friedrich Götze, Holger Sambale

We prove higher order concentration bounds for functions on Stiefel and Grassmann manifolds equipped with the uniform distribution. This partially extends previous work for functions on the unit sphere. Technically, our results are based on logarithmic Sobolev techniques for the uniform measures on the manifolds. Applications include Hanson--Wright type ineq

Torgeir Dingsøyr

Feedback is critical in education. This Innovative Practice Full Paper reports lessons learned from improving the quality of feedback in a semi-capstone software engineering course, with particular focus on how to deliver productive feedback in large scale during project work. The bachelor-level introduction to software engineering course is taken by about 5

Wooseok Jeong, Seung-Won Jung

Image compression is an essential and last processing unit in the camera image signal processing (ISP) pipeline. While many studies have been made to replace the conventional ISP pipeline with a single end-to-end optimized deep learning model, image compression is barely considered as a part of the model. In this paper, we investigate the designing of a full

Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen

Knowledge graph (KG) embeddings have been a mainstream approach for reasoning over incomplete KGs. However, limited by their inherently shallow and static architectures, they can hardly deal with the rising focus on complex logical queries, which comprise logical operators, imputed edges, multiple source entities, and unknown intermediate entities. In this w

Adriana M. Pires, Christian Motch, Jan Kurpas, Axel D. Schwope

We report the results of follow-up investigations of a possible new thermally emitting isolated neutron star (INS), 4XMM J022141.5-735632, using observations from XMM-Newton and Spectrum Roentgen Gamma (SRG) eROSITA. The analysis is complemented by Legacy Survey imaging in the optical and near-infrared wavelengths. The X-ray source, the first to be targeted

Marko Berghoff

We derive a variant of the loop-tree duality for Feynman integrals in the Schwinger parametric representation. This is achieved by decomposing the integration domain into a disjoint union of cells, one for each spanning tree of the graph under consideration. Each of these cells is the total space of a fiber bundle with contractible fibers over a cube. Loop-t

Mahdi Shariatzadeh, Mahdi Eftekhari, Mohammad Javad Rostami

Providing security in the transmission of images and other multimedia data has become one of the most important scientific and practical issues. In this paper, a method for compressing and encryption images is proposed, which can safely transmit images in low-bandwidth data transmission channels. At first, using the autoencoding generative adversarial networ

Julian Mak, Alexandros Avdis, Tomos W. David, Han Seul Lee

A physically plausible lower bound on the spatially varying geostrophic mesoscale eddy energy dissipation time-scale within the ocean, related to the geographical energy transfer rate out of the geostrophic mesoscales, is provided by means of a simple and computational inexpensive inverse calculation. Data diagnosed from a high resolution global configuratio

Ward van der Schoot, Daan Leermakers, Robert Wezeman, Niels Neumann

We report the Atos Q-score for D-Wave's quantum devices, classical algorithms and hybrid quantum-classical solver. Computing the Q-score entails solving the Max-Cut problem for increasingly large graphs. This work presents the first computation of the Q-score on a quantum device and shows how these quantum devices compare to classical devices at solving opti

Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou

In this paper, we revisit the online non-monotone continuous DR-submodular maximization problem over a down-closed convex set, which finds wide real-world applications in the domain of machine learning, economics, and operations research. At first, we present the Meta-MFW algorithm achieving a $1/e$-regret of $O(\sqrt{T})$ at the cost of $T^{3/2}$ stochastic

K. Rezazadeh, A. Ashoorioon, D. Grin

The standard cosmological model is in the midst of a stress test, thanks to the tension between supernovae-based measurements of the Hubble constant $H_{0}$ and inferences of its values from Cosmic Microwave Background (CMB) anisotropies. Numerous explanations for the present-day cosmic acceleration require the presence of a new fundamental scalar field, as

Shigeru Wakita, Hidenori Genda, Kosuke Kurosawa, Thomas M. Davison

The record of impact induced shock-heating in meteorites is an important key for understanding the collisional history of the solar system. Material strength is important for impact heating, but the effect of impact angle and impact velocity on shear heating remains poorly understood. Here, we report three-dimensional oblique impact simulations, which confir

O. Bourrion, C. Hoarau, J. Bounmy, D. Tourres

The CONCERTO spectral-imaging instrument was installed at the Atacama Pathfinder EXperiment (APEX) 12-meter telescope in April 2021. It has been designed to look at radiation emitted by ionised carbon atoms, [CII], and use the "intensity Mapping" technique to set the first constraints on the power spectrum of dusty star-forming galaxies. The instrument featu

Tilman Hinnerichs, Zhenwei Tang, Xi Peng, Xiangliang Zhang

Ontologies are one of the richest sources of knowledge. Real-world ontologies often contain thousands of axioms and are often human-made. Hence, they may contain inconsistency and incomplete information which may impair classical reasoners to compute entailments that are considered as useful. To overcome these two challenges, we propose FALCON, a Fuzzy Ontol

José Figueroa-O'Farrill, Ross Grassie, Stefan Prohazka

We exhibit all spatially isotropic homogeneous Galilean spacetimes of dimension $(n+1) \geq 4$, including the novel torsional ones, as null reductions of homogeneous pp-wave spacetimes. We also show that the pp-waves are sourced by pure radiation fields and analyse their global properties.

Bryce McLaughlin, Jann Spiess

When an algorithm provides risk assessments, we typically think of them as helpful inputs to human decisions, such as when risk scores are presented to judges or doctors. However, a decision-maker may react not only to the information provided by the algorithm. The decision-maker may also view the algorithmic recommendation as a default action, making it cos

Zahra Ghalenovi, Masoumeh Moazzen Sorkhi

The static properties and semileptonic decays of ground-state doubly heavy baryons are studied working in the framework of a non-relativistic quark model. Using a phenomenological potential model, we calculate the ground-state masses and magnetic moments of doubly heavy $ \Omega $ and $ \Xi $ baryons. In the heavy quark limit, we introduce a simple form of t

Rosalia Tufano, Emad Aghajani, Gabriele Bavota

Reusing code is a common practice in software development: It helps developers speedup the implementation task while also reducing the chances of introducing bugs, given the assumption that the reused code has been tested, possibly in production. Despite these benefits, opportunities for reuse are not always in plain sight and, thus, developers may miss them

Matthew J. Wilkinson, Aaron D. Ludlow, Claudia del P. Lagos, S. Michael Fall

We use a suite of idealised N-body simulations to study the impact of spurious heating of star particles by dark matter particles on the kinematics and morphology of simulated galactic discs. We find that spurious collisional heating leads to a systematic increase of the azimuthal velocity dispersion ($\sigma_\phi$) of stellar particles and a corresponding d

Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang

Knowledge Graph Embeddings (KGE) aim to map entities and relations to low dimensional spaces and have become the \textit{de-facto} standard for knowledge graph completion. Most existing KGE methods suffer from the sparsity challenge, where it is harder to predict entities that appear less frequently in knowledge graphs. In this work, we propose a novel frame

Johannes Selisko, Maximilian Amsler, Thomas Hammerschmidt, Ralf Drautz

We present a variational quantum thermalizer (VQT), called quantum-VQT (qVQT), which extends the variational quantum eigensolver (VQE) to finite temperatures. The qVQT makes use of an intermediate measurement between two variational circuits to encode a density matrix on a quantum device. A classical optimization provides the thermal state and, simultaneousl

Florian Gebhard, Kevin Bauerbach, Örs Legeza

We investigate the charge-density wave (CDW) transition for one-dimensional spinless fermions at half band-filling with nearest-neighbor electron transfer amplitude $t$ and interaction $V$. The model is equivalent to the anisotropic XXZ Heisenberg model for which the Bethe Ansatz provides an exact solution. For $V> V_{\rm c}= 2t$, the CDW order parameter and

Simon Mundinar, Alexander Hahn, Jürgen König, Alfred Hucht

On the basis of the method of iterative summation of path integrals (ISPI), we develop a numerically exact transfer-matrix method to describe the nonequilibrium properties of interacting quantum-dot systems. For this, we map the ISPI scheme to a transfer-matrix approach, which is more accessible to physical interpretation, allows for a more transparent formu

Eduard Muslimov, Gennadiy Valyavin, Vincent Chambouleyron, Felipe Pedreros Bustos

We propose a design of an adaptive optics (AO) system for the high-resolution fiber-fed echelle spectrograph installed at the Nasmyth focus of the 6-m BTA telescope at the Special Astrophysical Observatory (SAO) of the Russian Academy of Sciences (RAS). The system will be based on a pyramid wavefront sensor and benefit from the experience of the Laboratoire

P. A. Maksimov, A. L. Chernyshev

We provide analytical and numerical insights into the phase diagram and other properties of the extended Kitaev-Heisenberg model on the honeycomb lattice in the {\it easy-plane} limit, in which interactions are only between spin components that belong to the plane of magnetic ions. This parameter subspace allows for a much-needed systematic {\it quantitative

Georg Schmidt, Bikash Das-Mohapatra, Evangelos Th. Papaioannou

We show that to correctly describe the ultrafast currents in spintronic THz emitters it is necessary to take charge equilibration into account. The charge current which is locally induced by a fs laser pulse and the inverse spin-Hall effect (ISHE) leads to ultrafast charging phenomena at the edge of the illuminated area. Subsequent discharging leads to a cur

Mahmoud Sebtosheikh, Ali Naji

We use a standard minimal active Brownian model to investigate the osmotic-like effective pressure generated by active fluids on fixed hollow inclusions. These inclusions are enclosed by a permeable (albeit nonflexible) membrane, and the interior and exterior regions of the inclusions have different particle motility strengths. We consider both rectangular a

Jeong Yin Park

We study the optimal portfolio selection problem under relative performance criteria in the market model with random coefficients from the perspective of many players game theory. We consider five random coefficients which consist of three market parameters which are used in the risky asset price modeling and two preference parameters which are related to ri

Bénédicte Colnet, Julie Josse, Gaël Varoquaux, Erwan Scornet

Randomized Controlled Trials (RCTs) may suffer from limited scope. In particular, samples may be unrepresentative: some RCTs over- or under- sample individuals with certain characteristics compared to the target population, for which one wants conclusions on treatment effectiveness. Re-weighting trial individuals to match the target population can improve th

Seyma Yucer, Matt Poyser, Noura Al Moubayed, Toby P. Breckon

Yes - This study investigates the impact of commonplace lossy image compression on face recognition algorithms with regard to the racial characteristics of the subject. We adopt a recently proposed racial phenotype-based bias analysis methodology to measure the effect of varying levels of lossy compression across racial phenotype categories. Additionally, we

Şener Özönder, H. Kübra Küçükkartal

Density functional theory (DFT) is a powerful computational method used to obtain physical and chemical properties of materials. In the materials discovery framework, it is often necessary to virtually screen a large and high-dimensional chemical space to find materials with desired properties. However, grid searching a large chemical space with DFT is ineff

José Figueroa-O'Farrill, Can Görmez, Dieter Van den Bleeken

We study free particle motion on homogeneous kinematical spacetimes of galilean type. The three well-known cases of Galilei and (A)dS--Galilei spacetimes are included in our analysis, but our focus will be on the previously unexplored torsional galilean spacetimes. We show how in well-chosen coordinates free particle motion becomes equivalent to the dynamics

Muriel Felipe Pérez-Ortiz, Tyron Lardy, Rianne de Heide, Peter Grünwald

We study worst-case-growth-rate-optimal (GROW) e-statistics for hypothesis testing between two group models. It is known that under a mild condition on the action of the underlying group G on the data, there exists a maximally invariant statistic. We show that among all e-statistics, invariant or not, the likelihood ratio of the maximally invariant statistic

Marco Drewes, Lei Ming

We show that next generation Cosmic Microwave Background experiments will be capable of the first ever measurement of the inflaton coupling to other particles, opening a new window to probe the connection between cosmic inflation and particle physics. This sensitivity is based on the impact that the reheating phase after cosmic inflation has on the redshifti

Sarah Casura, Jochen Liske, Aaron S. G. Robotham, Sarah Brough

We derive single S\'ersic fits and bulge-disk decompositions for 13096 galaxies at redshifts z < 0.08 in the GAMA II equatorial survey regions in the Kilo-Degree Survey (KiDS) g, r and i bands. The surface brightness fitting is performed using the Bayesian two-dimensional profile fitting code ProFit. We fit three models to each galaxy in each band independen

Chi-Ching Hsu, Gaetan Frusque, Mahir Muratovic, Christian M. Franck

Circuit breakers (CBs) play an important role in modern society because they make the power transmission and distribution systems reliable and resilient. Therefore, it is important to maintain their reliability and to monitor their operation. A key to ensure a reliable operation of CBs is to monitor their condition. In this work, we performed an accelerated

Tuo Wu, Hong Ren, Cunhua Pan, Yijin Pan

Reconfigurable intelligent surface (RIS)-aided localization systems are increasingly recognized for enhancing accuracy in internet of things (IoT) networks. However, prevailing studies tend to either assume a Gaussian distribution for angle estimation error (AEE) or directly neglect the impact of the AEE, overlooking its non-Gaussian nature in real-world sce

Felix Voigtlaender

In this paper, we consider Barron functions $f : [0,1]^d \to \mathbb{R}$ of smoothness $\sigma > 0$, which are functions that can be written as \[ f(x) = \int_{\mathbb{R}^d} F(\xi) \, e^{2 \pi i \langle x, \xi \rangle} \, d \xi \quad \text{with} \quad \int_{\mathbb{R}^d} |F(\xi)| \cdot (1 + |\xi|)^{\sigma} \, d \xi < \infty. \] For $\sigma = 1$, these functi

Yang, Tan

Zoom Meeting is an enterprise online video conferencing solution with real-time messaging and content sharing. However, it's lack of privacy protection since centralized Zoom servers are capable of monitoring user's messages. Thereby, to solve the privacy problem, in May 2020, Zoom acquired Keybase so that Keybase's team can help it to build end-to-end encry

Jiankun Zhang, Hao Wang

The fifth-generation (5G) wireless communication is useful for positioning due to its large bandwidth and low cost. However, the presence of obstacles that block the line-of-sight (LOS) path between devices would affect localization accuracy severely. In this paper, we propose an online learning approach to mitigate ranging error directly in non-line-of-sigh

Tuo Wu, Cunhua Pan, Yijin Pan, Sheng Hong

In this paper, we propose a comprehensive framework to jointly analyze the angle estimation error and design the three-dimensional (3D) positioning algorithm for a millimeter wave (mmWave) positioning system. First, we estimate the angles of arrival (AoAs) at the anchors by applying the two-dimensional discrete Fourier transform (2D-DFT) algorithm. Based on

Wenhao Ye, Huihui Wu, Shitong Wu, Yizhu Wang

Mismatch capacity characterizes the highest information rate for a channel under a prescribed decoding metric, and is thus a highly relevant fundamental performance metric when dealing with many practically important communication scenarios. Compared with the frequently used generalized mutual information (GMI), the LM rate has been known as a tighter lower

Laura Duarte, Victor P. Goncalves, Daniel E. Martins, Téssio B. de Melo

The type II seesaw model predicts the existence of a doubly charged Higgs boson ($H ^{\pm\pm}$), which can be produced through the Drell - Yan process and photon -- induced interactions at hadronic colliders. In recent years, such reactions have been largely investigated in inclusive processes, where both incident protons breakup and a large number of partic

Benedict Philippi, Thomas Slawig

In this work the parallel-in-time algorithm Parareal was applied to the ocean-circulation and sea-ice model FESOM2 developed by the Alfred-Wegener Institut (AWI). The climate model provides one time integration method and hence, the coarse and fine propagators were defined by time step width. The coarse method was executed at the CFL condition limit, while f

Ryuichi Takanobu, Hao Zhou, Yankai Lin, Peng Li

How to build and use dialogue data efficiently, and how to deploy models in different domains at scale can be two critical issues in building a task-oriented dialogue system. In this paper, we propose a novel manual-guided dialogue scheme to alleviate these problems, where the agent learns the tasks from both dialogue and manuals. The manual is an unstructur

Meghali Garg, Bibekananda Maji

In the present paper, we prove that the generalized Riemann hypothesis for the Dirichlet $L$-function $L(s,\chi)$ is equivalent to the following bound: Let $k \geq 1$ and $\ell$ be positive real numbers. For any $\epsilon >0$, we have \begin{align*} \sum_{n=1}^{\infty} \frac{\chi(n) \mu(n)}{n^{k}} \exp \left(- \frac{ x}{n^{\ell}}\right) = O_{\epsilon,k,\ell}

Chiara Lindner, Jachin Kunz, Simon J. Herr, Jens Kiessling

Recent years have seen the development of quantum sensing concepts utilizing nonlinear interferometers based on correlated photon pairs generated by spontaneous parametric down-conversion (SPDC). Using SPDC far from frequency degeneracy allows a 'division of labor' between the mid-infrared photon for strongest sample interaction and the correlated near-infra

Han Hao, Dandan Jiang, Lu Yang, Hao Wu

Wireless network capacity can be regarded as the most important performance metric for wireless communication systems. With the fast development of wireless communication technology, future wireless systems will become more and more complicated. As a result, the channel gain matrix will become a large-dimensional random matrix, leading to an extremely high c

Harald G Svendsen, Til Kristian Vrana, Andrzej Holdyk, Heiner Schümann

This article introduces and describes the integrated energy system of a the Low Emission Oil&Gas Open (LEOGO) reference platform. It is a hypothetical case meant to represent a typical oil&gas installation in the North Sea. The aim of this detailed specification is to serve as an open reference case where all information about it can be publicly shared, faci

Guoliang Li, Shuai Wang, Kejiang Ye, Miaowen Wen

Integrated sensing and communication (ISAC) represents a paradigm shift, where previously competing wireless transmissions are jointly designed to operate in harmony via the shared use of the hardware platform for improving the spectral and energy efficiencies. However, due to adversarial factors such as fading and interference, ISAC may suffer from high sen

Subhankar Roy, Martin Trapp, Andrea Pilzer, Juho Kannala

Source-free domain adaptation (SFDA) aims to adapt a classifier to an unlabelled target data set by only using a pre-trained source model. However, the absence of the source data and the domain shift makes the predictions on the target data unreliable. We propose quantifying the uncertainty in the source model predictions and utilizing it to guide the target

Olivier C. Pasche, Sebastian Engelke

Risk assessment for extreme events requires accurate estimation of high quantiles that go beyond the range of historical observations. When the risk depends on the values of observed predictors, regression techniques are used to interpolate in the predictor space. We propose the EQRN model that combines tools from neural networks and extreme value theory int

Licai Sun, Zheng Lian, Bin Liu, Jianhua Tao

With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA) has attracted increasing attention recently. Despite significant progress, there are still two major challenges on the way towards robust MSA: 1) inefficiency when modeling cross-modal interactions in unaligned multimodal data; and 2) vulnerability to random modality

Anna Reithmeir, Luis Figueredo, Sami Haddadin

Manipulability ellipsoids efficiently capture the human pose and reveal information about the task at hand. Their use in task-dependent robot teaching - particularly their transfer from a teacher to a learner - can advance emulation of human-like motion. Although in recent literature focus is shifted towards manipulability transfer between two robots, the ad

Maël Franceschetti, Coline Lacoux, Ryan Ohouens, Antonin Raffin

The SWIMMER environment is a standard benchmark in reinforcement learning (RL). In particular, it is often used in papers comparing or combining RL methods with direct policy search methods such as genetic algorithms or evolution strategies. A lot of these papers report poor performance on SWIMMER from RL methods and much better performance from direct polic

Cui-Fang Sun, Hao Pan

Let $\mathbb{N}$ be the set of all nonnegative integers. For any integer $r$ and $m$, let $r+m\mathbb{N}=\{r+mk: k\in\mathbb{N}\}$. For $S\subseteq \mathbb{N}$ and $n\in \mathbb{N}$, let $R_{S}(n)$ denote the number of solutions of the equation $n=s+s'$ with $s, s'\in S$ and $s<s'$. Let $r_{1}, r_{2}, m$ be integers with $0<r_{1}<r_{2}<m$ and $2\mid r_{1}$.

Zhaoxia Yin, Heng Yin, Xinpeng Zhang

Deep neural networks are vulnerable to malicious fine-tuning attacks such as data poisoning and backdoor attacks. Therefore, in recent research, it is proposed how to detect malicious fine-tuning of neural network models. However, it usually negatively affects the performance of the protected model. Thus, we propose a novel neural network fragile watermarkin

O. V. Pavlovsky, V. I. Dorozhinsky, S. D. Mostovoy

We consider a model of an artificial neural network based on quantum-mechanical particles in $W$ potential. These particles play the role of neurons in our model. To simulate such a quantum-mechanical system the Monte-Carlo integration method is used. A form of the self-potential of a particle as well as two interaction potentials (exciting and inhibiting) a

Jian Jin, Yuan Xue, Xingxing Zhang, Lili Meng

Significant improvement has been made on just noticeable difference (JND) modelling due to the development of deep neural networks, especially for the recently developed unsupervised-JND generation models. However, they have a major drawback that the generated JND is assessed in the real-world signal domain instead of in the perceptual domain in the human br

Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard

Maximizing a submodular function is a fundamental task in machine learning and in this paper we study the deletion robust version of the problem under the classic matroids constraint. Here the goal is to extract a small size summary of the dataset that contains a high value independent set even after an adversary deleted some elements. We present constant-fa

Conrad D. Hougen, Lance M. Kaplan, Magdalena Ivanovska, Federico Cerutti

In second-order uncertain Bayesian networks, the conditional probabilities are only known within distributions, i.e., probabilities over probabilities. The delta-method has been applied to extend exact first-order inference methods to propagate both means and variances through sum-product networks derived from Bayesian networks, thereby characterizing episte

Jordan Richards, Raphaël Huser

Risk management in many environmental settings requires an understanding of the mechanisms that drive extreme events. Useful metrics for quantifying such risk are extreme quantiles of response variables conditioned on predictor variables that describe, e.g., climate, biosphere and environmental states. Typically these quantiles lie outside the range of obser

Massimo Notarnicola, Giovanni Peccati, Anna Vidotto

We consider Berry's random planar wave model (1977), and prove spatial functional limit theorems - in the high-energy limit - for discretized and truncated versions of the random field obtained by restricting its nodal length to rectangular domains. Our analysis is crucially based on a detailed study of the projection of nodal lengths onto the so-called seco

Valerio Bertone, Chris A. Flett, Alan D. Martin, Misha G. Ryskin

We describe the impact on PDF extractions of the 'Physical Scheme', a heavy-quark mass scheme that accounts for the effects of intrinsic heavy-quarks and provides a way to smoothly transition over the heavy-quark thresholds. The modifications made to the conventional $\overline{\text{MS}}$ scheme splitting functions and $\alpha_s$ running will be emphasised,

Corentin C. L. Laudicina, Chengjie Luo, Kunimasa Miyazaki, Liesbeth M. C. Janssen

Building on the recently derived inhomogeneous mode-coupling theory, we extend the generalised mode-coupling theory of supercooled liquids to inhomogeneous environments. This provides a first-principles-based, systematic and rigorous way of deriving high-point dynamical susceptibilities from variations of the many-body dynamic structure factors with respect

Bartosz Bednarczyk

We establish coNExpTime-completeness of the problem of deciding order-invariance of a given two variable first-order formula, improving and significantly simplifying coTwoNExpTime bound by Zeume and Harwath.

Jinhwan Seo, Wonho Bae, Danica J. Sutherland, Junhyug Noh

Weakly Supervised Object Detection (WSOD) is a task that detects objects in an image using a model trained only on image-level annotations. Current state-of-the-art models benefit from self-supervised instance-level supervision, but since weak supervision does not include count or location information, the most common ``argmax'' labeling method often ignores

Andrea Campoleoni, Luca Ciambelli, Arnaud Delfante, Charles Marteau

Relaxing the Bondi gauge, the solution space of three-dimensional gravity in the metric formulation has been shown to contain an additional free function that promotes the boundary metric to a Lorentz or Carroll frame, in asymptotically AdS or flat spacetimes. We pursue this analysis and show that the solution space also admits a finite symplectic structure,

Valeria Pontillo, Dario Amoroso d'Aragona, Fabiano Pecorelli, Dario Di Nucci

Context: Test smells are symptoms of sub-optimal design choices adopted when developing test cases. Previous studies have proved their harmfulness for test code maintainability and effectiveness. Therefore, researchers have been proposing automated, heuristic-based techniques to detect them. However, the performance of such detectors is still limited and dep

Meijia Shao, Dong Xia, Yuan Zhang, Qiong Wu

Two-sample hypothesis testing for network comparison presents many significant challenges, including: leveraging repeated network observations and known node registration, but without requiring them to operate; relaxing strong structural assumptions; achieving finite-sample higher-order accuracy; handling different network sizes and sparsity levels; fast com

Monika Henzinger, Ami Paz, A. R. Sricharan

A dynamic graph algorithm is a data structure that answers queries about a property of the current graph while supporting graph modifications such as edge insertions and deletions. Prior work has shown strong conditional lower bounds for general dynamic graphs, yet graph families that arise in practice often exhibit structural properties that the existing lo

Jingwen Zhao, Ming Chen, Cunhua Pan, Zhiyang Li

It is challenging to precisely configure the phase shifts of the reflecting elements at the reconfigurable intelligent surface (RIS) due to inherent hardware impairments (HIs). In this paper, the mean square error (MSE) performance is investigated in an RIS-aided single-user multiple-input multipleoutput (MIMO) communication system with transceiver HIs and R

Jingyao Zhang, Elaheh Sadredini

In the age of big data, information security has become a major issue of debate, especially with the rise of the Internet of Things (IoT), where attackers can effortlessly obtain physical access to edge devices. The hash algorithm is the current foundation for data integrity and authentication. However, it is challenging to provide a high-performance, high-t

Mainak Bhowmik, Poornendu Kumar

Inner functions are the backbone of holomorphic function theory. This paper studies the inner functions on quotient domains of the open unit polydisc, $\bD^d$, arising from the group action of finite pseudo-reflection groups. Such quotient domains are known to be biholomorphic to the proper image $\theta(\bD^d)$ of $\bD^d$ under certain polynomial maps $\the

Chia-Min Lin

In this note, we compare two different definitions for the cosmological perturbation $\zeta$ which is conserved on large scales, and study their non-conservation on small scales. We derive an equation for the time evolution of the curvature perturbation on a uniform density slice through a calculation solely in longitudinal (conformal-Newtonian) gauge. The r

Antonios Antoniadis, Mark de Berg, Sándor Kisfaludi-Bak, Antonis Skarlatos

A polygon C is an intersecting polygon for a set O of objects in the plane if C intersects each object in O, where the polygon includes its interior. We study the problem of computing the minimum-perimeter intersecting polygon and the minimum-area convex intersecting polygon for a given set O of objects. We present an FPTAS for both problems for the case whe

Priscille de Dumast, Hamza Kebiri, Vincent Dunet, Mériam Koob

The fetal cortical plate (CP) undergoes drastic morphological changes during the in utero development. Therefore, CP growth and folding patterns are key indicator in the assessment of the brain development and maturation. Magnetic resonance imaging (MRI) offers specific insights for the analysis of quantitative imaging biomarkers. Nonetheless, accurate and,

Koyu Mizutani, Haruki Mitarai, Kakeru Miyazaki, Ryugo Shimamura

The ground motion prediction equation is commonly used to predict the seismic intensity distribution. However, it is not easy to apply this method to seismic distributions affected by underground plate structures, which are commonly known as abnormal seismic distributions. This study proposes a hybrid of regression and classification approaches using neural

Tian-Fu Chen, Jie-Hong R. Jiang, Min-Hsiu Hsieh

Equivalence checking of quantum circuits is an essential element in quantum program compilation, in which a quantum program can be synthesized into different quantum circuits that may vary in the number of qubits, initialization requirements, and output states. Verifying the equivalences among the implementation variants requires proper generality. Although

Yiteng Tu, Zhichao Xu, Tao Yang, Weihang Su

Learning to rank (LTR) plays a crucial role in various Information Retrieval (IR) tasks. Although supervised LTR methods based on fine-grained relevance labels (e.g., document-level annotations) have achieved significant success, their reliance on costly and potentially biased annotations limits scalability and alignment with realistic goals. In contrast, co

Guntur Dharma Putra, Volkan Dedeoglu, Salil S Kanhere, Raja Jurdak

6G is envisioned to enable futuristic technologies, which exhibit more complexities than the previous generations, as it aims to bring connectivity to a large number of devices, many of which may not be trustworthy. Proper authentication can protect the network from unauthorized adversaries. However, it cannot guarantee in situ reliability and trustworthines

Frank Allaire

In RSST, they "replace the mammoth hand-checking of unavoidability that A&H required, by another mammoth hand-checkable proof " (page 18). Here, the proof of unavoidability is accomplished in a lengthy structured hand-checkable proof whose entirety is presented in this document.

Debolina Ghatak, Debasis Sengupta, Bimal Roy

Protecting the privacy of individuals in a data-set is no less important than making statistical inferences from it. In case the data in hand is quantitative, the usual way to protect it is to add a noise to the individual data values. But, what should be an ideal density used to generate the noise, so that we can get the maximum use of the data, without com