March 2023 arXiv papers — page 26

Yuhao Cheng, Yichao Yan, Wenhan Zhu, Ye Pan

Head generation with diverse identities is an important task in computer vision and computer graphics, widely used in multimedia applications. However, current full head generation methods require a large number of 3D scans or multi-view images to train the model, resulting in expensive data acquisition cost. To address this issue, we propose Head3D, a metho

Sergey K. Ivanov, Yaroslav V. Kartashov, Lluis Torner

We introduce a different class of thresholdless three-dimensional soliton states that form in higher-order topological insulators based on a two-dimensional Su-Schrieffer-Heeger array of coupled waveguides. The linear spectrum of such structures is characterized by the presence of a topological gap with corner states residing in them. We find that a focusing

Tabea Trummel, Zonglin Liu, Olaf Stursberg

This paper proposes a novel method to achieve and preserve synchronization for a set of connected heterogeneous Van der Pol oscillators. Unlike the state-of-the-art synchronization methods, in which a large coupling gain is applied to couple any pair of connected oscillators, the proposed method first casts the whole synchronization process into two phases.

Iris Dominguez-Catena, Daniel Paternain, Mikel Galar

Demographic biases in source datasets have been shown as one of the causes of unfairness and discrimination in the predictions of Machine Learning models. One of the most prominent types of demographic bias are statistical imbalances in the representation of demographic groups in the datasets. In this paper, we study the measurement of these biases by review

Antonio Carta, Andrea Cossu, Vincenzo Lomonaco, Davide Bacciu

Distributed learning on the edge often comprises self-centered devices (SCD) which learn local tasks independently and are unwilling to contribute to the performance of other SDCs. How do we achieve forward transfer at zero cost for the single SCDs? We formalize this problem as a Distributed Continual Learning scenario, where SCD adapt to local tasks and a C

Mingyao Ai, Holger Dette, Zhengfu Liu, Jun Yu

Optimal designs are usually model-dependent and likely to be sub-optimal if the postulated model is not correctly specified. In practice, it is common that a researcher has a list of candidate models at hand and a design has to be found that is efficient for selecting the true model among the competing candidates and is also efficient (optimal, if possible)

Mauri J. Valtonen, Staszek Zola, Gopakumar, Anne Lähteenmäki

The bright blazar OJ~287 routinely parades high brightness bremsstrahlung flares, which are explained as being a result of a secondary supermassive black hole (SMBH) impacting the accretion disc of a more massive primary SMBH in a binary system. The accretion disc is not rigid but rather bends in a calculable way due to the tidal influence of the secondary.

Qiuliang Ye, Bingo Wing-Kuen Ling, Li-Wen Wang, Daniel Pak-Kong Lun

Phase retrieval, a long-established challenge for recovering a complex-valued signal from its Fourier intensity measurements, has attracted significant interest because of its far-flung applications in optical imaging. To enhance accuracy, researchers introduce extra constraints to the measuring procedure by including a random aperture mask in the optical pa

Saeid Azam, Fatemeh Parishani, Shaobin Tan

Extended affine root systems appear as the root systems of extended affine Lie algebras. A subclass of extended affine root systems, whose elements are called ``minimal" turns out to be of special interest mostly because of the geometric properties of their Weyl groups; they possess the so-called ``presentation by conjugation". In this work, we characterize

Oscar Cosserat, Camille Laurent-Gengoux, Vladimir Salnikov

We recall the question of geometric integrators in the context of Poisson geometry, and explain their construction. These Poisson integrators are tested in some mechanical examples. Their properties are illustrated numerically and they are compared to traditional methods.

Lei Wang, Xin Liu

Recently, decentralized optimization over the Stiefel manifold has attacked tremendous attentions due to its wide range of applications in various fields. Existing methods rely on the gradients to update variables, which are not applicable to the objective functions with non-smooth regularizers, such as sparse PCA. In this paper, to the best of our knowledge

Luca Seravalli, Fiorenza Esposito, Matteo Bosi, Lucrezia Aversa

Strain engineering is an efficient tool to tune and tailor the electrical and optical properties of 2D materials. The built-in strain can be tuned during the synthesis process of a two dimensional semiconductor, as molybdenum disulfide, by employing different growth substrate with peculiar thermal properties. In this work we demonstrate that the built-in str

Guillaume Rochette, Chris Russell, Richard Bowden

We present a new approach for synthesizing novel views of people in new poses. Our novel differentiable renderer enables the synthesis of highly realistic images from any viewpoint. Rather than operating over mesh-based structures, our renderer makes use of diffuse Gaussian primitives that directly represent the underlying skeletal structure of a human. Rend

Tao Wu, Mengqi Cao, Ziteng Gao, Gangshan Wu

Traditional video action detectors typically adopt the two-stage pipeline, where a person detector is first employed to generate actor boxes and then 3D RoIAlign is used to extract actor-specific features for classification. This detection paradigm requires multi-stage training and inference, and cannot capture context information outside the bounding box. R

Yingying Guan, Qingyang Song, Weijing Qi, Ke Li

The increasing demand for diverse emerging applications has resulted in the interconnection of multi-access edge computing (MEC) systems via metro optical networks. To cater to these diverse applications, network slicing has become a popular tool for creating specialized virtual networks. However, resource fragmentation caused by uneven utilization of multid

Erik Bartoš, Stanislav Dubnička, Anna Zuzana Dubničková

The damped oscillating structures recently revealed by a three parametric formula from the proton ``effective'' form factor data extracted of the measured total cross section $\sigma^{bare}_{tot}(e^+e^-\to p\bar p)$ still seem to have an unknown origin. The conjectures of their direct manifestation of the quark-gluon structure of the proton indicate that the

Joanna Marciniak, Mirosław Werwiński

Ultrathin L1$_0$ films with different $c$-axis orientations relative to the film plane are promising candidates for data storage materials. In this work, within the framework of density functional theory, we calculated the magnetic properties of ultrathin L1$_0$ (111) and (010) films with thicknesses ranging from 4 to 16 atomic monolayers (from about 0.8 to

Herbert Boerner

After more than 180 years of research, ball lightning is still an unsolved problem in atmospheric physics. Since no progress can be expected without a controlled production of such objects in a laboratory, this report analyses a carefully selected subset of the observations, focusing on cases where the creation of ball lightning has been witnessed in order t

Jisun Park, Ernest K. Ryu

As first-order optimization methods become the method of choice for solving large-scale optimization problems, optimization solvers based on first-order algorithms are being built. Such general-purpose solvers must robustly detect infeasible or misspecified problem instances, but the computational complexity of first-order methods for doing so has yet to be

Shyamal Guchhait, Devarshi Chakrabarty, Avijit Dhara, Ankit Kumar Singh

We show an intriguing connection between the coherence of spectral domain interference of two electromagnetic modes in Fano resonance and the resulting degree of polarization of light. A theoretical treatment is developed by combining a general electromagnetic model of partially coherent interference of a spectrally narrow and a broad continuum mode leading

Joanna Jureczko

We prove that the existence of a complete metric space of cardinality at most $2^{\kappa}$ admitting Kuratowski partition is a consequence of $\kappa$ being the smallest real-valued measurable cardinal not greater than $ 2^{\aleph_0}$.

Martin Rapaport, Paul-Marie Samson

In this paper we establish new simple local geometric criteria for discrete entropic curvature introduced in [47] that are powerful enough to capture many geometric properties of complex models arising in mathematical physics. These results are robust in the sense that they apply to any discrete graph equipped with a Markov reversible generator. Our definiti

Dhanyamol Antony, Sagartanu Pal, R. B. Sandeep

For a class $\mathcal{G}$ of graphs, the objective of \textsc{Subgraph Complementation to} $\mathcal{G}$ is to find whether there exists a subset $S$ of vertices of the input graph $G$ such that modifying $G$ by complementing the subgraph induced by $S$ results in a graph in $\mathcal{G}$. We obtain a polynomial-time algorithm for the problem when $\mathcal{

Joanna Jureczko

The aim of this paper is to provide the results that answer the Kuratowski problem posed in 1935 concerning the existence of nonmeasurable sets. The Kuratowski problem was considered for partitions, here we provide a generalization to point-finite families for tree structures and structures in Ellentuck space. The main result of this paper generalizes previo

Francesco Sanfedino, Daniel Alazard, Ervan Kassarian, Franca Somers

The level of maturity reached by robust control theory techniques nowadays contributes to a considerable minimization of the development time of an end-to-end control design of a spacecraft system. The advantage offered by this framework is twofold: all system uncertainties can be included from the very beginning of the design process; the validation and ver

Manan Tayal, Rajpal Singh, Jishnu Keshavan, Shishir Kolathaya

Unmanned aerial vehicles (UAVs), specifically quadrotors, have revolutionized various industries with their maneuverability and versatility, but their safe operation in dynamic environments heavily relies on effective collision avoidance techniques. This paper introduces a novel technique for safely navigating a quadrotor along a desired route while avoiding

Chunyuan Yuan, Yiming Qiu, Mingming Li, Haiqing Hu

Query intent classification, which aims at assisting customers to find desired products, has become an essential component of the e-commerce search. Existing query intent classification models either design more exquisite models to enhance the representation learning of queries or explore label-graph and multi-task to facilitate models to learn external info

Joanna Jureczko

In this paper we show that the existence of Kuratowski partitions of Hausdorff Baire space is equivalent to the existence of point-finite covers of the same space.

Albin Dahlin, Yiannis Karayiannidis

This paper proposes a motion control scheme for robots operating in a dynamic environment with concave obstacles. A Model Predictive Controller (MPC) is constructed to drive the robot towards a goal position while ensuring collision avoidance without direct use of obstacle information in the optimization problem. This is achieved by guaranteeing tracking per

Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio

In smart electrical grids, fault detection tasks may have a high impact on society due to their economic and critical implications. In the recent years, numerous smart grid applications, such as defect detection and load forecasting, have embraced data-driven methodologies. The purpose of this study is to investigate the challenges associated with the securi

Yapeng Guo, Peng Zhong, Yi Zhuo, Fanzeng Meng

Because of the advantages of easy deployment, low cost and non-contact, computer vision-based structural displacement acquisition technique has received wide attention and research in recent years. However, the displacement field acquisition of large-scale structures is a challenging topic due to the contradiction of camera field of view and resolution. This

Sergio Gimeno-Soler, Oscar. M. Pimentel, Fabio D. Lora-Clavijo, Alejandro Cruz-Osorio

Analytical models of magnetized, geometrically thick disks are relevant to understand the physical conditions of plasma around compact objects and to explore its emitting properties. This has become increasingly important in recent years in the light of the Event Horizon Telescope observations of Sgr A$^*$ and M87. Models of thick disks around black holes us

Teng-Hui Huang, Hesham El Gamal

In this work, we adopt Wyner common information framework for unsupervised multi-view representation learning. Within this framework, we propose two novel formulations that enable the development of computational efficient solvers based on the alternating minimization principle. The first formulation, referred to as the {\em variational form}, enjoys a linea

Hongtao Cui, Yi Zhuo, Dongyuan Ke, Zhonglong Li

The erosion of chloride ions in concrete bridges will accelerate the corrosion of reinforcement, which is an important reason for the decline of bridge durability. The erosion process of chloride ion, especially deicing salt solution in cold regions, is complex and has many influencing factors. It is very important to use accurate and effective methods to an

Jaume Alonso, Yuri B. Suris, Kangning Wei

In this paper we address the problem of computing $\text{deg}(f^n)$, the degrees of iterates of a birational map $f:\mathbb{P}^N\rightarrow\mathbb{P}^N$. For this goal, we develop a method based on two main ingredients: the factorization of a polynomial under pull-back of $f$, based on local indices of a polynomial associated to blow-ups used to resolve the

Jiajia Xia

Government-run (Government-led) restoration has become a common and effective approach to the mitigation of financial risks triggered by corporation credit defaults. However, in practice, it is often challenging to come up with the optimal plan of those restorations, due to the massive search space associated with defaulted corporation networks (DCNs), as we

Jiuzhao Hua

We provide a list of canonical forms for all pairs of commuting nilpotent $4\times 4$ matrices over an algebraically closed field under simultaneous similarity.

Marco Caliari, Fabio Cassini, Lukas Einkemmer, Alexander Ostermann

In this paper we consider an approach to improve the performance of exponential Runge--Kutta integrators and Lawson schemes} in cases where the solution of a related, but usually much simpler, problem can be computed efficiently. While for implicit methods such an approach is common (e.g. by using preconditioners), for exponential integrators this has proven

Teng-Hui Huang, Thilini Dahanayaka, Kanchana Thilakarathna, Philip H. W. Leong

Wireless fingerprinting refers to a device identification method leveraging hardware imperfections and wireless channel variations as signatures. Beyond physical layer characteristics, recent studies demonstrated that user behaviors could be identified through network traffic, e.g., packet length, without decryption of the payload. Inspired by these results,

Cheng Wang, Guoli Wang, Qian Zhang, Peng Guo

Open-world instance segmentation has recently gained significant popularitydue to its importance in many real-world applications, such as autonomous driving, robot perception, and remote sensing. However, previous methods have either produced unsatisfactory results or relied on complex systems and paradigms. We wonder if there is a simple way to obtain state

Joanna Jureczko

In this paper, several generalizations of the classical Halpern-L\"{a}uchli Theorem are proven for Marczewski and Ellentuck structures using only combinatorial methods.

Lan Zhou, Bao-Wen Xu, Wei Zhong, Yu-Bo Sheng

Quantum secure direct communication (QSDC) can directly transmit secrete messages through quantum channel. Device-independent (DI) QSDC can guarantee the communication security relying only on the observation of the Bell inequality violation, but not on any detailed description or trust of the inner workings of users' devices. In the paper, we propose a DI-Q

Maxime Adjigble, Brahim Tamadazte, Cristiana de Farias, Rustam Stolkin

This paper presents a spectral domain registration-based visual servoing scheme that works on 3D point clouds. Specifically, we propose a 3D model/point cloud alignment method, which works by finding a global transformation between reference and target point clouds using spectral analysis. A 3D Fast Fourier Transform (FFT) in R3 is used for the translation e

Antonio Alarcon, Franc Forstneric

In this paper we begin a systematic study of the class of complex manifolds which are universal targets of holomorphic maps from open Riemann surfaces. We call them Oka-1 manifolds, by analogy with Oka manifolds that are universal targets of holomorphic maps from Stein manifolds of arbitrary dimension. We prove that every complex manifold which is dominable

Joanna Jureczko

This paper deals with two notions: a polarized partition relations $\left( \begin{array}{c} \alpha \beta \end{array} \right) \to \left( \begin{array}{cc} \gamma & \eta \delta & \lambda \end{array} \right)$ and product of generalized strong sequences. Strong sequences were introduced by Efimov in 1965 as a usefull tool for proving famous theorems in dyadic sp

Emanuele Sobacchi, Tsvi Piran, Luca Comisso

Gamma-ray flares from Active Galactic Nuclei (AGN) show substantial variability on ultrafast timescales (i.e. shorter than the light crossing time of the AGN's supermassive black hole). We propose that ultrafast variability is a byproduct of the turbulent dissipation of the jet Poynting flux. Due to the intermittency of the turbulent cascade, the dissipation

Piyush Sharda, Omri Ginzburg, Mark R. Krumholz, John C. Forbes

The recent decade has seen an exponential growth in spatially-resolved metallicity measurements in the interstellar medium (ISM) of galaxies. To first order, these measurements are characterised by the slope of the radial metallicity profile, known as the metallicity gradient. In this work, we model the relative role of star formation feedback, gas transport

Joanna Jureczko

The paper deals with two notions: polarized partition relations and product of generalized strong sequences. Strong sequences were introduced by Efimov in 1965 as a usefull tool for proving famous theorems in dyadic spaces, i.e. continuous images of Cantor cube. In this paper we introduce the notion of product of generalized strong sequences and give pure co

Aakash Singh, Vivek Kumar Singh

Images generated by high-resolution SAR have vast areas of application as they can work better in adverse light and weather conditions. One such area of application is in the military systems. This study is an attempt to explore the suitability of current state-of-the-art models introduced in the domain of computer vision for SAR target classification (MSTAR

Yuxuan Li, Shi Zhou

Metastatic prostate cancer is one of the most common cancers in men. In the advanced stages of prostate cancer, tumours can metastasise to other tissues in the body, which is fatal. In this thesis, we performed a genetic analysis of prostate cancer tumours at different metastatic sites using data science, machine learning and topological network analysis met

Kilian Zepf, Eike Petersen, Jes Frellsen, Aasa Feragen

Segmentation uncertainty models predict a distribution over plausible segmentations for a given input, which they learn from the annotator variation in the training set. However, in practice these annotations can differ systematically in the way they are generated, for example through the use of different labeling tools. This results in datasets that contain

Joanna Jureczko

The aim of this paper is to construct ultrafilters without immediate predecessors in the Rudin-Frolik order in $\beta \kappa\setminus \kappa$, where $\kappa$ is a regular cardinal. This generalizes the problem posed by Peter Simon more than 40 years ago.

Yuling Jiao, Di Li, Xiliang Lu, Jerry Zhijian Yang

With the recent study of deep learning in scientific computation, the Physics-Informed Neural Networks (PINNs) method has drawn widespread attention for solving Partial Differential Equations (PDEs). Compared to traditional methods, PINNs can efficiently handle high-dimensional problems, but the accuracy is relatively low, especially for highly irregular pro

Zhuoran Zheng, Xiuyi Jia

Currently, mobile and IoT devices are in dire need of a series of methods to enhance 4K images with limited resource expenditure. The absence of large-scale 4K benchmark datasets hampers progress in this area, especially for dehazing. The challenges in building ultra-high-definition (UHD) dehazing datasets are the absence of estimation methods for UHD depth

Hiroki Nakano, Daiki Chiba, Takashi Koide, Naoki Fukushi

The rise in phishing attacks via e-mail and short message service (SMS) has not slowed down at all. The first thing we need to do to combat the ever-increasing number of phishing attacks is to collect and characterize more phishing cases that reach end users. Without understanding these characteristics, anti-phishing countermeasures cannot evolve. In this st

Joanna Jureczko

We show that there is a set of $2^{2^{\kappa}}$ ultrafilters incomparable in Rudin-Frol\'ik order of $\beta \kappa \setminus \kappa$, where $\kappa$ is regular, for which no subset with more than one element has an infimum.

Auke Elfrink, Iacopo Vagliano, Ameen Abu-Hanna, Iacer Calixto

We investigate different natural language processing (NLP) approaches based on contextualised word representations for the problem of early prediction of lung cancer using free-text patient medical notes of Dutch primary care physicians. Because lung cancer has a low prevalence in primary care, we also address the problem of classification under highly imbal

Fabian Altekrüger, Paul Hagemann, Gabriele Steidl

Conditional generative models became a very powerful tool to sample from Bayesian inverse problem posteriors. It is well-known in classical Bayesian literature that posterior measures are quite robust with respect to perturbations of both the prior measure and the negative log-likelihood, which includes perturbations of the observations. However, to the best

Olusanmi Hundogan, Xixi Lu, Yupei Du, Hajo A. Reijers

Predictive process analytics focuses on predicting future states, such as the outcome of running process instances. These techniques often use machine learning models or deep learning models (such as LSTM) to make such predictions. However, these deep models are complex and difficult for users to understand. Counterfactuals answer ``what-if'' questions, whic

Joanna Jureczko

The aim of this paper is to prove that for there exist a chain in the Rudin-Frol\'ik order of $\beta\kappa\setminus \kappa$ of length $\mu$ with $\kappa \leqslant \mu \leqslant 2^\kappa$ for regular $\kappa> \omega$ without a lower bound.

Tomasz Adamowicz, Giona Veronelli

We investigate the logarithmic and power-type convexity of the length of the level curves for $a$-harmonic functions on smooth surfaces and related isoperimetric inequalities. In particular, our analysis covers the $p$-harmonic and the minimal surface equations. As an auxiliary result, we obtain higher Sobolev regularity properties of the solutions, includin

Zukai Li, Wei Tian, Jingjin Wu

In the era of the Internet of Things (IoT), blockchain is a promising technology for improving the efficiency of healthcare systems, as it enables secure storage, management, and sharing of real-time health data collected by the IoT devices. As the implementations of blockchain-based healthcare systems usually involve multiple conflicting metrics, it is esse

Joanna Jureczko

The aim of this paper is to construct chains of length $(2^\kappa)^+$ in the sense of Rudin-Frol\'ik order in $\beta \kappa$ for $\kappa$ regular.

Qishuang Fu, Dan Lin, Yiyue Cao, Jiajing Wu

As the largest blockchain platform that supports smart contracts, Ethereum has developed with an incredible speed. Yet due to the anonymity of blockchain, the popularity of Ethereum has fostered the emergence of various illegal activities and money laundering by converting ill-gotten funds to cash. In the traditional money laundering scenario, researchers ha

Jia-Wei Guo, Hung-Chyun Chou, Sen-Hua Zhu, Chang-Zheng Zhang

This paper proposes a novel method for depth completion, which leverages multi-view improved monitored distillation to generate more precise depth maps. Our approach builds upon the state-of-the-art ensemble distillation method, in which we introduce a stereo-based model as a teacher model to improve the accuracy of the student model for depth completion. By

Lakhan V. Jaybhaye, Raja Solanki, Sanjay Mandal, Pradyumn Kumar Sahoo

In this article, we attempt to describe cosmic late-time acceleration of the universe in the framework of $f(R,L_m)$ gravity by using an effective equation of state when the account is taken of bulk viscosity. We presume a non-linear $f(R,L_m)$ functional form, specifically, $f(R,L_m)=\frac{R}{2}+L_m^\alpha $, where $\alpha$ is free model parameter. We obtai

Dan You, Pengcheng Xia, Qiuzhu Chen, Minghui Wu

Automated chromosome instance segmentation from metaphase cell microscopic images is critical for the diagnosis of chromosomal disorders (i.e., karyotype analysis). However, it is still a challenging task due to lacking of densely annotated datasets and the complicated morphologies of chromosomes, e.g., dense distribution, arbitrary orientations, and wide ra

Hyukgun Kwon, Changhun Oh, Youngrong Lim, Hyunseok Jeong

Noise is the main source that hinders us from fully exploiting quantum advantages in various quantum informational tasks. However, characterizing and calibrating the effect of noise is not always feasible in practice. Especially for quantum parameter estimation, an estimator constructed without precise knowledge of noise entails an inevitable bias. Recently,

A. Maghraoui, F. Fras, M. Vomir, Y. Brelet

We report about element specific measurements of ultrafast demagnetization and magnetization precession damping in Permalloy (Py) thin films. Magnetization dynamics induced by optical pump at $1.5$eV is probed simultaneously at the $M_{2,3}$ edges of Ni and Fe with High order Harmonics for moderate demagnetization rates (less than $50$%). The role of the int

Angelo Feraudo, Alessando Calvio, Armir Bujari, Paolo Bellavista

IoT and edge computing are profoundly changing the information era, bringing a hyper-connected and context-aware computing environment to reality. Connected vehicles are a critical outcome of this synergy, allowing for the seamless interconnection of autonomous mobile/fixed objects, giving rise to a decentralized vehicle-to-everything (V2X) paradigm. On this

Gheorghe Ivan

We determine the fractional almost Poisson realizations for fractional Euler top system with one control. These realizations allow us to introduce a fractional Leibniz algebroid structure on R3 and also to define the q-fractional Euler top system with one control on a fractional Leibniz algebroid. Finally, the numerical integration of them are discussed.

Robin Hirt, Niklas Kühl, Dominik Martin, Gerhard Satzger

Successful analytics solutions that provide valuable insights often hinge on the connection of various data sources. While it is often feasible to generate larger data pools within organizations, the application of analytics within (inter-organizational) business networks is still severely constrained. As data is distributed across several legal units, poten

Wonguk Cho, Jinha Park, Taesup Kim

Continual domain shift poses a significant challenge in real-world applications, particularly in situations where labeled data is not available for new domains. The challenge of acquiring knowledge in this problem setting is referred to as unsupervised continual domain shift learning. Existing methods for domain adaptation and generalization have limitations

Ricardo Vinuesa, Steven L. Brunton, Beverley J. McKeon

The field of machine learning has rapidly advanced the state of the art in many fields of science and engineering, including experimental fluid dynamics, which is one of the original big-data disciplines. This perspective will highlight several aspects of experimental fluid mechanics that stand to benefit from progress advances in machine learning, including

Lina-Estelle Linelle Louis, Saïd Moussaoui, Vincent Roualdes, Aurélien van Langhenhove

During an activity, knowing the mental workload (MWL) of the user allows to improve the Human-Machine Interactions (HMI). Indeed, the MWL has an impact on the individual and its interaction with the environment. Monitoring it is therefore a crucial issue. In this context, we have created the virtual game Back to Pizza which is based on the N-back task (commo

Weiping Wu, Yu Lin, Jianjun Gao, Ke Zhou

This paper addresses the importance of incorporating various risk measures in portfolio management and proposes a dynamic hybrid portfolio optimization model that combines the spectral risk measure and the Value-at-Risk in the mean-variance formulation. By utilizing the quantile optimization technique and martingale representation, we offer a solution framew

Yatir Halevi

Given an elliptic curve $E$ over a perfect defectless henselian valued field $(F,\mathrm{val})$ with perfect residue field $\textbf{k}_F$ and valuation ring $\mathcal{O}_F$, there exists an integral separated smooth group scheme $\mathcal{E}$ over $\mathcal{O}_F$ with $\mathcal{E}\times_{\text{Spec } \mathcal{O}_F}\text{Spec } F\cong E$. If $\text{char}(\tex

Ahlem Abdelouahab, Sabri Bensid

We study the existence and multiplicity of solutions of the following free boundary problem $$ (P)\left\{ \begin{array}{rcll} \del u &=& \lam ( \eps +(1-\eps ) H(u-\mu))~ \hspace{3mm}&\text{in}~\Omega (t)\\ u&=& \overline{u}_{\infty}~\hspace{3mm} &\text{on } ~ \partial \Omega(t) \end{array} \right. $$ where $\Omega(t) \subset \RR^3$ a regular domain at $t>0$

Shaohui Liu, Xien Liu, Ji Wu

The purpose of write-missing diagnosis detection is to find diseases that have been clearly diagnosed from medical records but are missed in the discharge diagnosis. Unlike the definition of missed diagnosis, the write-missing diagnosis is clearly manifested in the medical record without further reasoning. The write-missing diagnosis is a common problem, oft

Ori Linial, Orly Avner, Dotan Di Castro

We introduce a method for inferring an explicit PDE from a data sample generated by previously unseen dynamics, based on a learned context. The training phase integrates knowledge of the form of the equation with a differential scheme, while the inference phase yields a PDE that fits the data sample and enables both signal prediction and data explanation. We

Ziyuan Zhao, Kaixin Xu, Huai Zhe Yeo, Xulei Yang

Domain shift has been a long-standing issue for medical image segmentation. Recently, unsupervised domain adaptation (UDA) methods have achieved promising cross-modality segmentation performance by distilling knowledge from a label-rich source domain to a target domain without labels. In this work, we propose a multi-scale self-ensembling based UDA framework

F. Irshad, C. Eberle, F. M. Foerster, K. v. Grafenstein

Optimization of accelerator performance parameters is limited by numerous trade-offs and finding the appropriate balance between optimization goals for an unknown system is challenging to achieve. Here we show that multi-objective Bayesian optimization can map the solution space of a laser wakefield accelerator in a very sample-efficient way. Using a Gaussia

Daniel Hoff, Patrick Mehlitz

This paper is concerned with the value function approach to multiobjective bilevel optimization which exploits a lower level frontier-type mapping in order to replace the hierarchical model of two interdependent multiobjective optimization problems by a single-level multiobjective optimization problem. As a starting point, different value-function-type refor

Ludwig Bothmann, Lisa Wimmer, Omid Charrakh, Tobias Weber

Wildlife camera trap images are being used extensively to investigate animal abundance, habitat associations, and behavior, which is complicated by the fact that experts must first classify the images manually. Artificial intelligence systems can take over this task but usually need a large number of already-labeled training images to achieve sufficient perf

Deze Wang, Boxing Chen, Shanshan Li, Wei Luo

As pre-trained models automate many code intelligence tasks, a widely used paradigm is to fine-tune a model on the task dataset for each programming language. A recent study reported that multilingual fine-tuning benefits a range of tasks and models. However, we find that multilingual fine-tuning leads to performance degradation on recent models UniXcoder an

Yu-Peng Wu, Hong Qian, Rong-Jun Qin, Yi Chen

In the field of security, multi-objective security games (MOSGs) allow defenders to simultaneously protect targets from multiple heterogeneous attackers. MOSGs aim to simultaneously maximize all the heterogeneous payoffs, e.g., life, money, and crime rate, without merging heterogeneous attackers. In real-world scenarios, the number of heterogeneous attackers

Kensuke Tamura, Hosho Katsura

We develop a general theory of flat-band ferromagnetism in the SU($N$) Fermi-Hubbard model, which describes the behavior of $N$-component fermions with SU($N$) symmetric interactions. We focus on the case where the single-particle spectrum has a flat band and establish a necessary and sufficient condition for the SU($N$) Hubbard model to exhibit ferromagneti

Monika Dalal, Sucheta Dutt, Ranjeet Sehmi

In this work, a unique set of generators for a cyclic code over a finite chain ring has been established. The minimal spanning set and rank of the code have also been determined. Further, sufficient as well as necessary conditions for a cyclic code to be an MDS code and for a cyclic code to be an MHDR code have been obtained. Some examples of optimal cyclic

Xiao Yang, Chang Liu, Longlong Xu, Yikai Wang

Face recognition is a prevailing authentication solution in numerous biometric applications. Physical adversarial attacks, as an important surrogate, can identify the weaknesses of face recognition systems and evaluate their robustness before deployed. However, most existing physical attacks are either detectable readily or ineffective against commercial rec

Clément Cancès, Jean Cauvin-Vila, Claire Chainais-Hillairet, Virginie Ehrlacher

We propose a two-point flux approximation finite-volume scheme for the approximation of two cross-diffusion systems coupled by a free interface to account for vapor deposition. The moving interface is addressed with a cut-cell approach, where the mesh is locally deformed around the interface. The scheme preserves the structure of the continuous system, namel

Yunxiao Zhang, Moritz Kalhöfer-Köchling, Eberhard Bodenschatz, Yong Wang

Left ventricular (LV) stiffness and contractility, characterized by the end-diastolic and end-systolic pressure-volume relationships (EDPVR & ESPVR), are two important indicators of the performance of the human heart. Although much research has been conducted on EDPVR and ESPVR, no model with physically interpretable parameters combining both relationships h

Nicholas Cazet

The axioms of a quandle imply that the columns of its Cayley table are permutations. This paper studies quandles with exactly one non-trivially permuted column. Their automorphism groups, quandle polynomials, (symmetric) cohomology groups, and $Hom$ quandles are studied. The quiver and cocycle invariant of links using these quandles are shown to relate to li

Kazuhiro Ito

For a smooth affine group scheme $G$ over the ring of $p$-adic integers $\mathbb{Z}_p$ and a cocharacter $\mu$ of $G$, we study $G$-$\mu$-displays over the prismatic site of Bhatt-Scholze. In particular, we obtain several descent results for them. If $G=\mathrm{GL}_n$, then our $G$-$\mu$-displays can be thought of as Breuil-Kisin modules with some additional

Vivek Khatua, B. Gurumoorthy, G. K. Ananthasuresh

Fiber-Reinforced Polymer Composite (FRPC) parts are mostly made as laminates, shells, or surfaces wound with 2D fiber patterns even after the emergence of additive manufacturing. Making FRPC parts with embedded continuous fibers in 3D is not reported previously even though topology optimization shows that such designs are optimal. Earlier attempts in 3D fibe

Antoine Bouvet, Salima El Kolei, Matthieu Marbac

Investigating technical skills of swimmers is a challenge for performance improvement, that can be achieved by analyzing multivariate functional data recorded by Inertial Measurement Units (IMU). To investigate technical levels of front-crawl swimmers, a new model-based approach is introduced to obtain two complementary partitions reflecting, for each swimme

Florian Müller, Daniel Schmitt, Andrii Matviienko, Dominik Schön

From carrying grocery bags to holding onto handles on the bus, there are a variety of situations where one or both hands are busy, hindering the vision of ubiquitous interaction with technology. Voice commands, as a popular hands-free alternative, struggle with ambient noise and privacy issues. As an alternative approach, research explored movements of vario

Haoran Xu, Li Jiang, Jianxiong Li, Zhuoran Yang

Most offline reinforcement learning (RL) methods suffer from the trade-off between improving the policy to surpass the behavior policy and constraining the policy to limit the deviation from the behavior policy as computing $Q$-values using out-of-distribution (OOD) actions will suffer from errors due to distributional shift. The recently proposed \textit{In

Yicheng Li, Haobo Zhang, Qian Lin

One of the most interesting problems in the recent renaissance of the studies in kernel regression might be whether the kernel interpolation can generalize well, since it may help us understand the `benign overfitting henomenon' reported in the literature on deep networks. In this paper, under mild conditions, we show that for any $\varepsilon>0$, the genera

Indranil Biswas, Krishna Hanumanthu, Snehajit Misra

We study Seshadri constants of certain ample vector bundles on projective varieties. Our main motivation is the following question: Under what conditions are the Seshadri constants of ample vector bundles at least 1 at all points of the variety. We exhibit some conditions under which this question has an affirmative answer. We primarily consider ample bundle

Yubin Wang, Huawen Xu, Xinyi Deng, Timothy Liew

We develop a scheme of generating highly indistinguishable single photons from an active quantum Su-Schrieffer-Heeger chain made from a collection of noisy quantum emitters. Surprisingly, the single photon emission spectrum of the active quantum chain is extremely narrow compared to that of a single emitter or topologically trivial chain. Moreover, this effe