December 2023 arXiv papers — page 76

Ismael Calomino, Gustavo Pelaitay, William Zuluaga Botero

In this paper we introduce and study an alternative definition of tense operators on residuated lattices. We give a categorical equivalence for the class of tense residuated lattices, which is motivated by an old construction due to J. Kalman. The paper concludes with some applications regarding the description of congruences and a 2-contextual translation.

Guowei Yan, Long Feng

In this paper, we considier the limiting distribution of the maximum interpoint Euclidean distance $M_n=\max _{1 \leq i<j \leq n}\left\|\boldsymbol{X}_i-\boldsymbol{X}_j\right\|$, where $\boldsymbol{X}_1, \boldsymbol{X}_2, \ldots, \boldsymbol{X}_n$ be a random sample coming from a $p$-dimensional population with dependent sub-gaussian components. When the di

Gang Bahadur Acharya, Se-Hun Kim, Madhav Prasad Ghimire

The application of semiconductors with optical properties has grown significantly in the development of semiconductor photovoltaics. Here, we explore the electronic and optical properties of ternary transition metal sulfide Rb$_{2}$Ni$_{3}$S$_4$ by means of density functional theory. From the structural perspective, Ni atoms are found to form a kagome-like l

Sergio Celani, Agustín Nagy, William Zuluaga Botero

In this paper we introduce the class of weak Heyting Brouwer algebras (WHB-algebras, for short). We extend the well known duality between distributive lattices and Priestley spaces, in order to exhibit a relational Priestley-like duality for WHB-algebras. Finally, as an application of the duality, we build the tense extension of a WHB-algebra and we employ i

Joaquin Gajardo, Michele Volpi, Daniel Onwude, Thijs Defraeye

Cropland maps are essential for remote sensing-based agricultural monitoring, providing timely insights without extensive field surveys. Machine learning enables large-scale mapping but depends on geo-referenced ground-truth data, which is costly to collect, motivating the use of global datasets in data-scarce regions. A key challenge is understanding how th

Genqiang Liu, Yufang Zhao

For any positive integer $n$, let $W_n=\text{Der}(\mathbb{C}[t_1,\dots,t_n])$. The subspaces $\mathfrak{h}_n=\text{Span}\{t_1\frac{\partial}{\partial{t_1}},\dots,t_n\frac{\partial}{\partial{t_n}}\}$ and $\Delta_n=\text{Span}\{\frac{\partial}{\partial{t_1}},\dots,\frac{\partial}{\partial{t_n}}\}$ are two abelian subalgebras of $W_n$. We show that a full subca

Ha-Young Shin, Hee-Seok Oh

This paper develops a notion of geometric quantiles on Hadamard spaces, also known as global non-positive curvature spaces. After providing some definitions and basic properties, including scaled isometry equivariance and a necessary condition on the gradient of the quantile loss function at quantiles on Hadamard manifolds, we investigate asymptotic properti

Wenke Ren, Junxian Wang, Zhenyi Cai, Xufan Hu

We previously built a sample of 14,012 extremely variable quasars (EVQs) based on SDSS and Pan-STARRS1 photometric observations. In this work we present the spectral fitting to their SDSS spectra, and study the spectral variation in 1,259 EVQs with multi-epoch SDSS spectra (after prudently excluding spectra with potentially unreliable spectroscopic photometr

Timothy R. McIntosh, Teo Susnjak, Tong Liu, Paul Watters

This comprehensive survey explored the evolving landscape of generative Artificial Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts (MoE), multimodal learning, and the speculated advancements towards Artificial General Intelligence (AGI). It critically examined the current state and future trajectory of generative

Masayuki Iio, Tomohiro Yokoyama, Takeshi Inaoka, Hajime Ishihara

In bulk materials, the collective modes and individual modes are orthogonal each other, and no connection occurs if there is no damping processes. In the presence of damping, the collective modes, i.e., plasmons decay into the hot carriers. In finite systems, the collective and individual modes are coupled by the Coulomb interaction. Such couplings by longit

Christian Aebi, Grant Cairns

We classify perimeter dominant triangles whose side lengths are in $\sqrt3\mathbb N$ and whose area is in $\frac{\sqrt3}4\mathbb N$. There is one exceptional example, which is equilateral, and three infinite families determined by certain Pell, or Pell-like, equations.

Yingheng Li, Aditya Pawar, Zewei Mo, Youtao Zhang

Measurement-based quantum computing (MBQC) is a promising quantum computing paradigm that performs computation through ``one-way'' measurements on entangled quantum qubits. It is widely used in photonic quantum computing (PQC), where the computation is carried out on photonic cluster states (i.e., a 2-D mesh of entangled photons). In MBQC-based PQC, the clus

Hongzhi Yin, Tong Chen, Liang Qu, Bin Cui

Given the sheer volume of contemporary e-commerce applications, recommender systems (RSs) have gained significant attention in both academia and industry. However, traditional cloud-based RSs face inevitable challenges, such as resource-intensive computation, reliance on network access, and privacy breaches. In response, a new paradigm called on-device recom

Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc

In "The 2020 Census Disclosure Avoidance System TopDown Algorithm," Abowd et al. (2022) describe the concepts and methods used by the Disclosure Avoidance System (DAS) to produce formally private output in support of the 2020 Census statistical data product releases, with a particular focus on the DAS implementation that was used to create the 2020 Census Re

Haobo Xia, Yunhe Sheng, Rong Tang

In this paper, first we give the controlling algebra of Lie triple systems. In particular, the cohomology of Lie triple systems can be characterized by the controlling algebra. Then using controlling algebras, we introduce the notions of homotopy Nambu algebras and homotopy Lie triple systems. We show that $2$-term homotopy Lie triple systems is equivalent t

Jiawen Wen, Dong Yuan, Lei Ma, Huaming Chen

As open-source AI software projects become an integral component in the AI software development, it is critical to develop a novel methods to ensure and measure the security of the open-source projects for developers. Code ownership, pivotal in the evolution of such projects, offers insights into developer engagement and potential vulnerabilities. In this pa

Fang Feng, Yue Yu

This paper is dedicated to the numerical solution of a fourth-order singular perturbation problem using the interior penalty virtual element method (IPVEM) proposed in [42]. The study introduces modifications to the jumps and averages in the penalty term, as well as presents an automated mesh-dependent selection of the penalty parameter. Drawing inspiration

Julia Bernatska

In the present paper reality conditions for quasi-periodic solutions of the KdV equation are determined completely. As a result, solutions in the form of non-linear waves can be plotted and investigated. The full scope of obtaining finite-gap solutions of the KdV equation is presented. It is proven that the multiply periodic $\wp_{1,1}$-function on the Jacob

Ahmad Chamma, Bertrand Thirion, Denis A. Engemann

Explaining the decision process of machine learning algorithms is nowadays crucial for both model's performance enhancement and human comprehension. This can be achieved by assessing the variable importance of single variables, even for high-capacity non-linear methods, e.g. Deep Neural Networks (DNNs). While only removal-based approaches, such as Permutatio

Christian Kindermann, Anne-Marie George, Bijan Parsia, Uli Sattler

In this paper, we introduce the problem of rewriting finite formal languages using syntactic macros such that the rewriting is minimal in size. We present polynomial-time algorithms to solve variants of this problem and show their correctness. To demonstrate the practical relevance of the proposed problems and the feasibility and effectiveness of our algorit

Amirhossein D. Naghdi, Franco Pellegrini, Emine Küçükbenli, Dario Massa

Material characterization in nano-mechanical tests requires precise interatomic potentials for the computation of atomic energies and forces with near-quantum accuracy. For such purposes, we develop a robust neural-network interatomic potential (NNIP), and we provide a test for the example of molecular dynamics (MD) nanoindentation, and the case of body-cent

Kenneth Barrese

In 2006, Briggs and Remmel gave a factorization theorem for $m$-level rook placements on singleton boards, a special subset of Ferrers boards. Subsequently, Barrese, Loehr, Remmel, and Sagan defined the $m$-weighted file placements to give a combinatorial interpretation to the aforementioned factorization theorem for all Ferrers boards. An unintended consequ

Mahmoud Ahmed, Omer Moussa, Ismail Shaheen, Mohamed Abdelfattah

One of the major challenges in training deep neural networks for text-to-image generation is the significant linguistic discrepancy between ground-truth captions of each image in most popular datasets. The large difference in the choice of words in such captions results in synthesizing images that are semantically dissimilar to each other and to their ground

Lenny Fukshansky, Sehun Jeong

Let $K$ be a number field of degree $d$. Then every ideal $I$ in the ring of integers ${\mathcal O}_K$ contains infinitely many primitive elements, i.e. elements of degree $d$. A bound on smallest height of such an element in $I$ follows from some recent developments in the direction of a 1998 conjecture of W. Ruppert. We prove a very explicit bound like thi

Lajos Horváth, Lorenzo Trapani

We propose a family of weighted statistics based on the CUSUM process of the WLS residuals for the online detection of changepoints in a Random Coefficient Autoregressive model, using both the standard CUSUM and the Page-CUSUM process. We derive the asymptotics under the null of no changepoint for all possible weighing schemes, including the case of the stan

Trang Quynh Nguyen, Michelle C. Carlson, Elizabeth A. Stuart

The study of treatment effects is often complicated by noncompliance and missing data. In the one-sided noncompliance setting where of interest are the complier and noncomplier average causal effects (CACE and NACE), we address outcome missingness of the \textit{latent missing at random} type (LMAR, also known as \textit{latent ignorability}). That is, condi

J. Peltonen, Erik Rosolowsky, Thomas G. Williams, Eric W. Koch

Young stellar objects (YSOs) are the gold standard for tracing star formation in galaxies but have been unobservable beyond the Milky Way and Magellanic Clouds. But that all changed when the James Webb Space Telescope was launched, which we use to identify YSOs in the Local Group galaxy M33, marking the first time that individual YSOs have been identified at

Haruki Hayano, Akira Furukawa

We explore a mechanism of the anomalous rheology of active suspensions by hydrodynamic simulations using model pusher swimmers. Our simulations demonstrate that hydrodynamic interactions under shear flow systematically orient swimmers along the extension direction, which is responsible for determining the global swimming states and the resulting significant

Shilin Huang, Kenneth R. Brown, Marko Cetina

Quantum states can quickly decohere through interaction with the environment. Quantum error correction is a method for preserving coherence through active feedback. Quantum error correction encodes the quantum information into a logical state with a high-degree of symmetry. Perturbations are first detected by measuring the symmetries of the quantum state and

Hong-Fei Zhang, Xue-Mei Mo, Yu-Peng Yan

In 2020, a di-$J/\psi$ resonance centered at around 6.9 $\mathrm{GeV}$ was discovered by the LHCb Collaboration, and was later confirmed by the ATLAS and CMS Collaborations. In addition to the 6.9-$\mathrm{GeV}$ resonance, its low energy counterpart centered at around 6552 $\mathrm{MeV}$ was also observed by the CMS Collaboration. In this paper, we calculate

Samuel Davenport, Armin Schwartzman, Thomas E. Nichols, Fabian J. E. Telschow

Historically, applications of RFT in fMRI have relied on assumptions of smoothness, stationarity and Gaussianity. The first two assumptions have been addressed in Part 1 of this article series. Here we address the severe non-Gaussianity of (real) fMRI data to greatly improve the performance of voxelwise RFT in fMRI group analysis. In particular, we introduce

Yaru Qian, Qingna Li, Alain Zemkoho

Support vector classification (SVC) is an effective tool for classification tasks in machine learning. Its performance relies on the selection of appropriate hyperparameters. This paper focuses on optimizing the regularization hyperparameter C and determining feature bounds for feature selection within SVC, leading to a potentially large hyperparameter space

J. Metzner, A. Quinn, S. Brudney, I. D. Moore

We experimentally implement circuits of one and two mode operations on two motional modes of a single trapped ion. This is achieved by implementing the required displacement, squeezing, two-mode squeezing, and beamsplitter operations using oscillating electric potentials applied to the trap electrodes. The resulting electric fields drive the modes resonantly

Abdellatif Lfounoune, Abdelilah Karara, Mohamed Rossafi

In this paper, we will introduce the concept of a continuous biframe for Hilbert $ C^{\ast}- $modules. Then, we examine some characterizations of this biframe with the help of an invertible and adjointable operator is given. Moreover, we study continuous biframe Bessel multiplier and dual continuous biframe in Hilbert $ C^{\ast}- $modules. Also, we develop t

Raphaël Beuzart-Plessis, Chen Wan

In this paper, we prove the geometric expansion of a local twisted trace formula for the Whittaker induction of any symmetric pairs that are coregular. This generalizes the local (twisted) trace formula for reductive groups proved by Arthur \cite{A91} and Waldspurger \cite{WalFTLtordue}. We also prove a formula for the regular germs of quasi-characters assoc

Behrooz Mosallaei, Moein Afrouzmehr, Danial Abshari, Sepideh Farivar

In this paper, we study zero divisors in Hurwitz series rings and Hurwitz polynomial rings over general noncommutative rings. We first construct Armendariz rings that are not Armendariz of the Hurwitz series type and find various properties of (Hurwitz series) Armendariz rings. We show that for a semiprime Armendariz of Hurwitz series type (so reduced) ring

Xinyu Yang, Hongbo Bo

Face swapping has gained significant traction, driven by the plethora of human face synthesis facilitated by deep learning methods. However, previous face swapping methods that used generative adversarial networks (GANs) as backbones have faced challenges such as inconsistency in blending, distortions, artifacts, and issues with training stability. To addres

Yuhao Zhou, Stavros Tripakis

The integration of neural networks into safety-critical systems has shown great potential in recent years. However, the challenge of effectively verifying the safety of Neural Network Controlled Systems (NNCS) persists. This paper introduces a novel approach to NNCS safety verification, leveraging the inductive invariant method. Verifying the inductiveness o

En Yu, Jie Lu, Bin Zhang, Guangquan Zhang

Multistream classification poses significant challenges due to the necessity for rapid adaptation in dynamic streaming processes with concept drift. Despite the growing research outcomes in this area, there has been a notable oversight regarding the temporal dynamic relationships between these streams, leading to the issue of negative transfer arising from i

Norbertus Krisnu Prabowo, Irwanto Irwanto

The name "Arduino" made its international debut in 2005, marking the age of Arduino as one of the most user-friendly and cost-effective microcontroller boards (MCBs) for novices. The science implementation of Arduino boards in automation, networking and data acquisition has been increasing steadily. This study provides a thorough Bibliometric analysis from 1

Mahfuzur Rahman, Zoheb Hassan, Jeffrey H. Reed, Lingjia Liu

Non-terrestrial network (NTN) communication has garnered considerable attention from government entities, industries, and academia in recent times. NTN networks encompass a variety of systems, including Low Earth Orbit (LEO) satellites, Medium Earth Orbit (MEO) satellites, Geostationary Earth Orbit (GEO) satellites, High Altitude Platforms (HAPS), and Low Al

Valentin Leeb, Alexander Mook, Libor Šmejkal, Johannes Knolle

Altermagnetism has emerged as a third type of collinear magnetism. In contrast to standard ferromagnets and antiferromagnets, altermagnets exhibit extra even-parity wave spin order parameters resulting in a spin-splitting of electronic bands in momentum space. In real space, sublattices of opposite spin polarization are anisotropic and related by rotational

Jihang Zhu, Sankar Das Sarma

In bilayer systems, the additional layer pseudospin enables the emergence of interlayer coherence (IC), which is a direct consequence of the interlayer Coulomb interaction. This study presents a comprehensive HF investigation of IC in 2D bilayers, uncovering ground-state behaviors and temperature-dependent phase transitions that are distinct from single-laye

H. O. Cildiroglu

The effects of Aharonov-Casher (AC) and He-McKellar-Wilkens (HMW) phases on entangled spin-1/2 quantum systems are investigated. We use linear charge distributions positioned at the center of resulting closed orbits, capitalizing on Mach Zender-type interferometers modified with phase retarders to unveil the topological effects. We analyze how AC-HMW phases

K. Al Moulla, X. Dumusque, M. Cretignier

Context. Radial velocities (RVs) of stars contain both the Doppler reflex motion of potential planetary companions and the drowning and sometimes imitating effect of stellar activity. To separate the two, previous efforts have sought for proxys which only trace the activity signals, yet the sub-meter-per-second floor required for the detection of Earth-like

Nikita Starodubcev, Artem Fedorov, Artem Babenko, Dmitry Baranchuk

Knowledge distillation methods have recently shown to be a promising direction to speedup the synthesis of large-scale diffusion models by requiring only a few inference steps. While several powerful distillation methods were recently proposed, the overall quality of student samples is typically lower compared to the teacher ones, which hinders their practic

Jonathan I. Katz

The fraction of planetary mass objects in the Trapezium cluster that are in wide binaries is much greater than implied by extrapolation to lower masses of the fraction of stars that are in wide binaries. Wide binaries may be produced by gravitational collapse of a medium with fluid vorticity. In a uniform medium with uniform vorticity the collapse criterion

Ehsan Latif, Xiaoming Zhai, Lei Liu

This study delves into the pervasive issue of gender issues in artificial intelligence (AI), specifically within automatic scoring systems for student-written responses. The primary objective is to investigate the presence of gender biases, disparities, and fairness in generally targeted training samples with mixed-gender datasets in AI scoring outcomes. Uti

Zhengdong Zhang, Zihan Dong, Yang Shi, Noboru Matsuda

The rapid evolution of artificial intelligence (AI), specifically large language models (LLMs), has opened opportunities for various educational applications. This paper explored the feasibility of utilizing ChatGPT, one of the most popular LLMs, for automating feedback for Java programming assignments in an introductory computer science (CS1) class. Specifi

S. A. Jafari

Motivated by observations of zero-biased photocurrent on the surface of topological insulators, we show that the in-plane effective magnetic field $\tilde B$ implements a moving frame transformation on the topological insulators' helical surface states. As a result, photo-excited electrons on the surface undergo a Galilean boost proportional to the effective

Anton Braverman, Han L. Gan

The Wright-Fisher model, originating in Wright (1931) is one of the canonical probabilistic models used in mathematical population genetics to study how genetic type frequencies evolve in time. In this paper we bound the rate of convergence of the stationary distribution for a finite population Wright-Fisher Markov chain with parent independent mutation to t

Martin Milanič, Irena Penev, Nevena Pivač, Kristina Vušković

A minimal separator of a graph $G$ is a set $S \subseteq V(G)$ such that there exist vertices $a,b \in V(G) \setminus S$ with the property that $S$ separates $a$ from $b$ in $G$, but no proper subset of $S$ does. For an integer $k\ge 0$, we say that a minimal separator is $k$-simplicial if it can be covered by $k$ cliques and denote by $\mathcal{G}_k$ the cl

Jack Holligan, Huey-Wen Lin

We present a first study of the effects of renormalization-group resummation (RGR) and leading-renormalon resummation (LRR) on the systematic errors of the unpolarized isovector nucleon generalized parton distribution in the framework of large-momentum effective theory (LaMET). This work is done using lattice gauge ensembles generated by the MILC collaborati

Marcin Kuźniak

Dark matter accounts for 26% of the mass-energy density of the Universe, however, its nature and origins remain the most important open questions in physics. The search for Weakly Interacting Massive Particles (WIMPs), one of the leading dark matter particle candidates, is now in a decisive phase, with experiments targeting both the high-mass and the low-mas

Olamide Oladeji, Seyed Shahabeddin Mousavi

AI has been proposed as an important tool to support several efforts related to nature-based climate solutions such as the detection of wildfires that affect forests and vegetation-based offsets. While this and other use-cases provide important demonstrative value of the power of AI in climate change mitigation, such efforts have typically been undertaken in

Mizna Ashraf, Jessy Jose, Ho-Gyu Lee, Carlos Contreras Peña

Strong accretion outbursts onto protostars are associated with emission dominated by a viscously heated disk, which is characterized by high luminosities. We report the discovery and characterization of a strong mid-IR (3.4, 4.6 $\mu$m) outburst in the embedded protostar SSTgbs J21470601+4739394 (hereafter SSTgbsJ214706). SSTgbsJ214706 has steadily brightene

Conrad Borchers, Yeyu Wang, Shamya Karumbaiah, Muhammad Ashiq

Learning analytics research increasingly studies classroom learning with AI-based systems through rich contextual data from outside these systems, especially student-teacher interactions. One key challenge in leveraging such data is generating meaningful insights into effective teacher practices. Quantitative ethnography bears the potential to close this gap

Vincent Tao Hu, David W Zhang, Pascal Mettes, Meng Tang

This paper strives for image editing via generative models. Flow Matching is an emerging generative modeling technique that offers the advantage of simple and efficient training. Simultaneously, a new transformer-based U-ViT has recently been proposed to replace the commonly used UNet for better scalability and performance in generative modeling. Hence, Flow

Michał Gutowski, Mateusz Kwaśnicki

For an arbitrary regular Dirichlet form $\mathscr{E}$ and the associated symmetric Markovian semigroup $T_t$, we consider the corresponding Sobolev-Bregman form $\mathscr{E}_p(u) = -\tfrac{1}{p} \frac{d}{d t}\bigr\vert_{t = 0} \|T_t u\|_p^p$, where $p \in (1, \infty)$. We prove a variant of the Beurling-Deny formula for $\mathscr{E}_p$. As an application, we

Jin Lu, Xingpeng Li

The increasing interest in hydrogen as a clean energy source has led to extensive research into its transmission, storage, and integration with bulk power systems. With the evolution of hydrogen technologies towards greater efficiency, and cost-effectiveness, it becomes essential to examine the operation and expansion of grids that include both electric powe

Andre Rodrigues, Alberto Rodrigues da Silva

Despite being an essential step in software development, writing requirements specifications is frequently performed in natural language, leading to issues like inconsistency, incompleteness, or ambiguity. The ITLingo initiative has introduced a requirements specification language named RSL to enhance the rigor and consistency of technical documentation. On

Mari Kawakatsu, Taylor A. Kessinger, Joshua B. Plotkin

Social reputations facilitate cooperation: those who help others gain a good reputation, making them more likely to receive help themselves. But when people hold private views of one another, this cycle of indirect reciprocity breaks down, as disagreements lead to the perception of unjustified behavior that ultimately undermines cooperation. Theoretical stud

Kevin Broughan

Using a result of recursive function theory and results of the complex analysis of Takeuti, which is based on a type theory and the work of Kreisel, and which gives a conservative extension of first order Peano arithmetic (PA), assuming all critical zeros of the Riemann zeta function are simple, we show that RH is decidable in PA.

Chon-Fai Kam, Xuedong Hu

Fast and high-fidelity qubit measurement is essential for realizing quantum error correction, which is in turn a key ingredient to universal quantum computing. For electron spin qubits, fast readout is one of the significant road blocks toward error correction. Here we examine the dispersive readout of a single spin in a semiconductor double quantum dot coup

Hannah Kerner, Catherine Nakalembe, Benjamin Yeh, Ivan Zvonkov

The Tigray War was an armed conflict that took place primarily in the Tigray region of northern Ethiopia from November 3, 2020 to November 2, 2022. Given the importance of agriculture in Tigray to livelihoods and food security, determining the impact of the war on cultivated area is critical. However, quantifying this impact was difficult due to restricted m

Deyuan Qu, Sudip Dhakal, Dominic Carrillo

In this project, we have implemented a model to recognize real-time facial emotions given the camera images. Current approaches would read all data and input it into their model, which has high space complexity. Our model is based on the Convolutional Neural Network utilizing the PyTorch library. We believe our implementation will significantly improve the s

Yuwei Jin, Xiangyu Gao, Minghao Guo, Henry Chen

In this research paper, our primary focus revolves around the domain-specific hardware mapping strategy tailored for Quantum Fourier Transformation (QFT) circuits. While previous approaches have heavily relied on SAT solvers or heuristic methods to generate hardware-compatible QFT circuits by inserting SWAP gates to realign logical qubits with physical qubit

Daniel Gerbi Duguma, Juliana Zhang, Meysam Aboutalebi, Shiliang Zhang

This manuscript aims to formalize and conclude the discussions initiated during the PriTEM workshop 22-23 March 2023. We present important ideas and discussion topics in the context of transactive energy systems. Moreover, the conclusions from the discussions articulate potential aspects to be explored in future studies on transactive energy management. Part

Na Li, Yiyang Qi, Ruyue Xin, Zhiming Zhao

Ocean and climate research benefits from global ocean observation initiatives such as Argo, GLOSS, and EMSO. The Argo network, dedicated to ocean profiling, generates a vast volume of observatory data. However, data quality issues from sensor malfunctions and transmission errors necessitate stringent quality assessment. Existing methods, including machine le

Renata Ferrero, Markus B. Fröb, William C. C. Lima

We compute the heat kernel coefficients that are needed for the regularization and renormalization of massive gravity. Starting from the Stueckelberg action for massive gravity, we determine the propagators of the different fields (massive tensor, vector and scalar) in a general linear covariant gauge depending on four free gauge parameters. We then compute

Guojun Xiong, Gang Yan, Shiqiang Wang, Jian Li

Decentralized learning has emerged as an alternative method to the popular parameter-server framework which suffers from high communication burden, single-point failure and scalability issues due to the need of a central server. However, most existing works focus on a single shared model for all workers regardless of the data heterogeneity problem, rendering

Luke Hagar, Nathaniel T. Stevens

Businesses frequently run online controlled experiments (i.e., A/B tests) to learn about the effect of an intervention on multiple business metrics. To account for multiple hypothesis testing, multiple metrics are commonly aggregated into a single composite measure, losing valuable information, or strict family-wise error rate adjustments are imposed, leadin

Tianxiang Hao, Mengyao Lyu, Hui Chen, Sicheng Zhao

With the advancement of large pre-trained vision-language models, effectively transferring the knowledge embedded within these foundational models to downstream tasks has become a pivotal topic, particularly in data-scarce environments. Recently, parameter-efficient fine-tuning approaches, especially prompt tuning, have garnered considerable attention. To be

Dominik Schmidt, Minqi Jiang

Pre-training large models on vast amounts of web data has proven to be an effective approach for obtaining powerful, general models in domains such as language and vision. However, this paradigm has not yet taken hold in reinforcement learning. This is because videos, the most abundant form of embodied behavioral data on the web, lack the action labels requi

Athanasios Laliotis

In this habilitation thesis, I briefly present my work at Imperial College London on trapping atomic clouds in micro-pyramids fabricated on silicon chips, which led to the fabrication of an on-chip integrated atom source. Next, I describe the research carried out at the Laboratoire de Physique des Lasers in the SAI group. Our experiments demonstrated the tem

Adrien Petralia, Philippe Charpentier, Themis Palpanas

Over the past decade, millions of smart meters have been installed by electricity suppliers worldwide, allowing them to collect a large amount of electricity consumption data, albeit sampled at a low frequency (one point every 30min). One of the important challenges these suppliers face is how to utilize these data to detect the presence/absence of different

Peter Kostolányi

Complexity classes such as $\#\mathbf{P}$, $\oplus\mathbf{P}$, $\mathbf{GapP}$, $\mathbf{OptP}$, $\mathbf{NPMV}$, or the class of fuzzy languages realised by polynomial-time fuzzy nondeterministic Turing machines, can all be described in terms of a class $\mathbf{NP}[S]$ for a suitable semiring $S$, defined via weighted Turing machines over $S$ similarly as

Elaheh Sabziyan Varnousfaderani, Syed A. M. Shihab, Esrat F. Dulia

Near future air taxi operations with electric vertical take-off and landing (eVTOL) aircraft will be constrained by the need for frequent recharging of eVTOLs, limited takeoff and landing pads in vertiports, and subject to time-varying demand and electricity prices, making the eVTOL dispatch problem unique and particularly challenging to solve. Previously, w

Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang

Spatial networks are networks whose graph topology is constrained by their embedded spatial space. Understanding the coupled spatial-graph properties is crucial for extracting powerful representations from spatial networks. Therefore, merely combining individual spatial and network representations cannot reveal the underlying interaction mechanism of spatial

Jeonghun Baek, Yusuke Matsui, Kiyoharu Aizawa

In this paper, we investigate cross-lingual learning (CLL) for multilingual scene text recognition (STR). CLL transfers knowledge from one language to another. We aim to find the condition that exploits knowledge from high-resource languages for improving performance in low-resource languages. To do so, we first examine if two general insights about CLL disc

Elaheh Sabziyan Varnousfaderani, Syed A. M. Shihab

The number of collisions between aircraft and birds in the airspace has been increasing at an alarming rate over the past decade due to increasing bird population, air traffic and usage of quieter aircraft. Bird strikes with aircraft are anticipated to increase dramatically when emerging Advanced Air Mobility aircraft start operating in the low altitude airs

Md. Jalal Uddin Chowdhury, Ashab Hussan

This research paper presents a comprehensive review-based study on various Text-to-Speech (TTS) technologies. TTS technology is an important aspect of human-computer interaction, enabling machines to convert written text into audible speech. The paper examines the different TTS technologies available, including concatenative TTS, formant synthesis TTS, and s

Y. Wu, A. Roy, S. Dutta, J. Jesudasan

The hexatic phase is an intermediate stage in the melting process of a 2D crystal due to topological defects. Recently, this exotic phase was experimentally identified in the vortex lattice of 2D weakly disordered superconducting MoGe by scanning tunneling microscopic measurements. Here we study this vortex state by the Nernst effect, which is an effective a

Sandra Smyth

As per Adusumilli (2015),'70% of corporate business systems today are legacy applications. Recent statistics prove that over 60% of IT budget is spent on maintaining these Legacy systems, showing the rigidity and the fragile nature of these systems.' Usually, testing is included during the software development cycle, using testing techniques such as unit tes

Marc Coppens

Let $\Gamma$ be a chain of cycles of genus $g$. Let $d$,$r$ be integers with $1 \leq r \leq g-2$ and $2r\leq d \leq g-3+r$. Then $w^r_d(\Gamma)=d-2r$ implies $\Gamma$ is hyperelliptic. For each $g \geq 2r+3$ there exist non-hyperelliptic chains of cycles satisfying $w^r_{g-2+r}(\Gamma)=g-2-r$. In the case of algebraic curves such equality implies the curve i

Andrey Saveliev, Rafael Alves Batista

Lorentz invariance violation (LIV) is a phenomenon featuring in various quantum gravity models whereby Lorentz symmetry is broken at high energies, potentially impacting the behaviour of particles and their interactions. Here we investigate the phenomenology of LIV within the context of gamma-ray-induced electromagnetic cascades. We conduct detailed numerica

Abhinav Jain, Vaibhav Unhelkar

Offline imitation learning (IL) refers to learning expert behavior solely from demonstrations, without any additional interaction with the environment. Despite significant advances in offline IL, existing techniques find it challenging to learn policies for long-horizon tasks and require significant re-training when task specifications change. Towards addres

Al-Harith Farhad, Ioannis Sorokos, Mohammed Naveed Akram, Koorosh Aslansefat

The zeitgeist of the digital era has been dominated by an expanding integration of Artificial Intelligence~(AI) in a plethora of applications across various domains. With this expansion, however, questions of the safety and reliability of these methods come have become more relevant than ever. Consequently, a run-time ML model safety system has been develope

Kazuma Shimomoto

The purpose of this paper is to explain a method on the generalization of the Bertini-type theorem on standard graded rings to the non-standard graded case of certain type.

Masood Aryapoor

Using the Rabinowitsch trick, we prove a version of Nullstellensatz over quaternions, which generalizes Hilbert's Nullstellensatz over complex numbers.

Shivam Pande

The study explores the synergistic combination of Synthetic Aperture Radar (SAR) and Visible-Near Infrared-Short Wave Infrared (VNIR-SWIR) imageries for land use/land cover (LULC) classification. Image fusion, employing Bayesian fusion, merges SAR texture bands with VNIR-SWIR imageries. The research aims to investigate the impact of this fusion on LULC class

Jingtao Tang, Hang Ma

We study graph-based Multi-Robot Coverage Path Planning (MCPP) that aims to compute coverage paths for multiple robots to cover all vertices of a given 2D grid terrain graph $G$. Existing graph-based MCPP algorithms first compute a tree cover on $G$ -- a forest of multiple trees that cover all vertices -- and then employ the Spanning Tree Coverage (STC) para

Xiucai Ding, Yichen Hu, Zhenggang Wang

In this paper, we propose a new test for testing the equality of two population covariance matrices in the ultra-high dimensional setting that the dimension is much larger than the sizes of both of the two samples. Our proposed methodology relies on a data splitting procedure and a comparison of a set of well selected eigenvalues of the sample covariance mat

Dimos Tsouros, Senne Berden, Tias Guns

Constraint Programming (CP) has been successfully used to model and solve complex combinatorial problems. However, modeling is often not trivial and requires expertise, which is a bottleneck to wider adoption. In Constraint Acquisition (CA), the goal is to assist the user by automatically learning the model. In (inter)active CA, this is done by interactively

Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet

Transformers play a central role in the inner workings of large language models. We develop a mathematical framework for analyzing Transformers based on their interpretation as interacting particle systems, which reveals that clusters emerge in long time. Our study explores the underlying theory and offers new perspectives for mathematicians as well as compu

Renxi Wang, Haonan Li, Minghao Wu, Yuxia Wang

Instruction tuning significantly enhances the performance of large language models (LLMs) across various tasks. However, the procedure to optimizing the mixing of instruction datasets for LLM fine-tuning is still poorly understood. This study categorizes instructions into three primary types: NLP downstream tasks, coding, and general chat. We explore the eff

Giorgio Mentasti, Carlo R. Contaldi, Marco Peloso

We employ the formalism developed in \cite{Mentasti:2023gmg} and \cite{Bartolo_2022} to study the prospect of detecting an anisotropic Stochastic Gravitational Wave Background (SGWB) with the Laser Interferometer Space Antenna (LISA) alone, and combined with the proposed space-based interferometer Taiji. Previous analyses have been performed in the frequency

Tessa Cookmeyer, Sankar Das Sarma

We theoretically consider bilayers of two dimensional (2D) electron gases as in semiconductor quantum wells, and investigate possible spontaneous symmetry breaking transitions at low carrier densities driven by interlayer Coulomb interactions. We use a self-consistent technique implementing mean field truncations of the interacting four-fermion terms, and fi

Eric Brillaux, Andrei A. Fedorenko, Ilya A. Gruzberg

We study a non-Anderson disorder driven quantum phase transition in a semi-infinite Dirac semimetal with a flat boundary. The conformally invariant boundary conditions, which include those that are time-reversal invariant, lead to nodal-like surface states on the boundary. In this case the boundary becomes metallic at a critical disorder that is weaker than

Kunlong Liu, Trinabh Gupta

Federated learning for training models over mobile devices is gaining popularity. Current systems for this task exhibit significant trade-offs between model accuracy, privacy guarantee, and device efficiency. For instance, Oort (OSDI 2021) provides excellent accuracy and efficiency but requires a trusted central server. On the other hand, Orchard (OSDI 2020)