October 2022 arXiv papers — page 102

Meysam Shamsi, Marie Tahon

There are two paradigms of emotion representation, categorical labeling and dimensional description in continuous space. Therefore, the emotion recognition task can be treated as a classification or regression. The main aim of this study is to investigate the relation between these two representations and propose a classification pipeline that uses only dime

Giovanni Pistone

The dually flat structure of statistical manifolds can be derived in a non-parametric way from a particular case of affine space defined on a qualified set of probability measures. The statistically natural displacement mapping of the affine space depends on the notion of Fisher's score. The model space must be carefully defined if the state space is not fin

Sarah Kaakai, Anis Matoussi, Achraf Tamtalini

We study a robust utility maximization problem in the unbounded case with a general penalty term and information including jumps. We focus on time consistent penalties and we prove that there exists an optimal probability measure solution of the robust problem. Then, we characterize the dynamic value process of our stochastic control problem as the unique so

Leah Epstein

We study ordinal makespan scheduling on small numbers of identical machines, with respect to two parallel solutions. In ordinal scheduling, it is known that jobs are sorted by non-increasing sizes, but the specific sizes are not known in advance. For problems with two parallel solutions, it is required to design two solutions, and the performance of algorith

Tongrui Wang

For a closed Riemannian manifold $M^{n+1}$ with a compact Lie group $G$ acting as isometries, the equivariant min-max theory gives the existence and the potential abundance of minimal $G$-invariant hypersurfaces provided $3\leq {\rm codim}(G\cdot p) \leq 7$ for all $p\in M$. In this paper, we show a compactness theorem for these min-max minimal $G$-hypersurf

Friedrich Knop

A quasi-Hamiltonian manifold is called multiplicity free if all of its symplectic reductions are 0-dimensional. In this paper, we classify compact, multiplicity free, twisted quasi-Hamiltonian manifolds for simply connected, compact Lie groups. Thereby, we recover old and find new examples of these structures.

Jifeng Hu, Yanchao Sun, Hechang Chen, Sili Huang

Multi-agent reinforcement learning has drawn increasing attention in practice, e.g., robotics and automatic driving, as it can explore optimal policies using samples generated by interacting with the environment. However, high reward uncertainty still remains a problem when we want to train a satisfactory model, because obtaining high-quality reward feedback

Andrés Viña

Considering the $B$-branes over the complex projective space ${\mathbb P}^n$ as the objects of the bounded derived category $D^b({\mathbb P}^n)$, we prove that the cardinal of the set of holomorphic gauge fields on a given $B$-brane ${\mathscr G}^{\bullet}$ is $\leq 1$. Moreover, the cardinal is $1$ iff each ${\mathscr G}^p$ is isomorphic to a direct sum of

Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen

Designing feasible and effective architectures under diverse computational budgets, incurred by different applications/devices, is essential for deploying deep models in real-world applications. To achieve this goal, existing methods often perform an independent architecture search process for each target budget, which is very inefficient yet unnecessary. Mo

Zishen Wang, Jingyang You, Chuan Chen, Jinchao Mo

Many-body instabilities and topological physics are two attractive topics in condensed matter physics. It is intriguing to explore the interplay between these phenomena in a single quantum material. Here, using the prototypical charge density wave (CDW) material monolayer 1H-NbSe$_2$ as an example, we show how momentum-dependent electron-phonon coupling driv

Hu Fu, Qun Hu, Jia'nan Lin

Gaitonde and Tardos recently studied a model of queueing networks where queues compete for servers and re-send returned packets in future rounds. They quantify the amount of additional processing power that guarantees a decentralized system's stability, both when the queues adapt their strategies from round to round using no-regret learning algorithms, and w

Swaroop Mishra, Anjana Arunkumar, Chris Bryan, Chitta Baral

Evaluation of models on benchmarks is unreliable without knowing the degree of sample hardness; this subsequently overestimates the capability of AI systems and limits their adoption in real world applications. We propose a Data Scoring task that requires assignment of each unannotated sample in a benchmark a score between 0 to 1, where 0 signifies easy and

Konstantinos Makantasis, Kosmas Pinitas, Antonios Liapis, Georgios N. Yannakakis

Affective computing strives to unveil the unknown relationship between affect elicitation, manifestation of affect and affect annotations. The ground truth of affect, however, is predominately attributed to the affect labels which inadvertently include biases inherent to the subjective nature of emotion and its labeling. The response to such limitations is u

Ionut Chiose, Matei Toma

We present some properties of positive closed currents of type $(1,1)$ on compact non-k\"ahlerian surfaces related to our previous study of these objects started in \cite{ChiTo2}.

Angel Valle

In this paper, we report a theoretical study of the phase diffusion in a gain-switched single-mode semiconductor laser. We use stochastic rate equations for the electrical field to analyze the phase statistics of the gain-switched laser. Their use avoid the instabilities obtained with rate equations for photon number and optical phase when the photon number

Azhar A Pirzado, Guillaume Dalmas, Lam Nguyen-Dinh, Ivan Komissarov

Few layer graphene (FLG) was synthesized by $\mu$-wave assisted exfoliation of expanded graphite in toluene with an overall yield from c.a. 7% to 20%. A significant difference in the absorption of $\mu$-waves by the expanded graphite and toluene allowed a rapid heating of the medium. The number of FLG sheets varies from 3 to 12, while the lateral size of the

Tianxiang Sun, Junliang He, Xipeng Qiu, Xuanjing Huang

Automatic evaluation metrics are crucial to the development of generative systems. In recent years, pre-trained language model (PLM) based metrics, such as BERTScore, have been commonly adopted in various generation tasks. However, it has been demonstrated that PLMs encode a range of stereotypical societal biases, leading to a concern on the fairness of PLMs

C. Romo-Luque, N. Salor-Iguiñiz, J. M. Benlloch-Rodríguez, R. Esteve

We report on a new measurement of the energy resolution that can be attained in liquid xenon when recording only the scintillation light. Our setup is optimized to maximize light collection, and uses state-of-the-art, high-PDE, VUV-sensitive silicon photomultipliers. We find a value of 3.7 $\pm$ 0.4% at 511 keV, once saturation effects are corrected for, a r

Hamza El Marouazi, Benoit van der Schueren, Damien Favier, Anaëlle Bolley

Four series of PLA based composite films containing horizontally aligned few layer graphene (FLG) flakes of high aspect ratio and adsorbed albumin are prepared. The mechanical and thermal properties vary with percentage, dispersion degree and size of FLG flakes. Great improvement up to 290 and 360% of tensile modulus and strength respectively was obtained fo

Alexander Ivashkin, Dzhonrid Abdurashitov, Alexander Baranov, Fedor Guber

We present the results of a new experimental study of the quantum entanglement of photon pairs produced in positron-electron annihilation at rest. The experimental setup includes a system of Compton polarimeters to measure the Compton scattering of annihilation photons in entangled and decoherent states. Decoherent states are prepared by pre-scattering of on

Claudio Bonanno, Massimo D'Elia, Biagio Lucini, Davide Vadacchino

Standard local updating algorithms experience a critical slowing down close to the continuum limit, which is particularly severe for topological observables. In practice, the Markov chain tends to remain trapped in a fixed topological sector. This problem further worsens at large $N$, and is known as $\mathit{topological}~\mathit{freezing}$. To mitigate it,

Dilini Rajapaksha, Kacper Sokol, Jeffrey Chan, Flora Salim

With the advancement and proliferation of technology, non-profit organisations have embraced social media platforms to improve their operational capabilities through brand advocacy, among many other strategies. The effect of such social media campaigns on these institutions, however, remains largely underexplored, especially during disaster periods. This wor

Xiangqing Shen, Siwei Wu, Rui Xia

ATOMIC is a large-scale commonsense knowledge graph (CSKG) containing everyday if-then knowledge triplets, i.e., {head event, relation, tail event}. The one-hop annotation manner made ATOMIC a set of independent bipartite graphs, which ignored the numerous links between events in different bipartite graphs and consequently caused shortages in knowledge cover

E. E. Perepelkin, B. I. Sadovnikov, N. G. Inozemtseva, A. A. Korepanova

A full consideration of classical and quantum systems with radiation (electromagnetic/gravitational) requires the involvement of a mathematical description in the generalized phase space of high kinematical values. Based on the dispersion chain of equations of quantum mechanics, we construct a generalization of the von Neumann equation for the density matrix

Jakob Möderl, Erik Leitinger, Franz Pernkopf, Klaus Witrisal

We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using multistatic ultra-wideband (UWB) radar. In the process, the respiratory motion is estimated for contact-free vital sign monitoring. The received signal is modeled by a backscatter channel and the respiratory motion and prop

Roman V. Buniy, Robert P. Feger, Thomas W. Kephart

Self-interactions and interaction with the environment tend to push quantum systems toward states of maximal entanglement. This is a definition of decoherence. We argue that these maximally entangled states fall into the well-defined classes that can be uniquely described by the values of certain entanglement invariants. After discussing these ideas we prese

Alireza Koochali, Maria Walch, Sankrutyayan Thota, Peter Schichtel

Generative models are designed to address the data scarcity problem. Even with the exploding amount of data, due to computational advancements, some applications (e.g., health care, weather forecast, fault detection) still suffer from data insufficiency, especially in the time-series domain. Thus generative models are essential and powerful tools, but they s

João Carnevale

A classical result by Solodov states that if a group acts on the line such that any non-trivial element has at most one fixed point, then the action is either abelian or semi-conjugate to an affine action. We show that the same holds if we relax the assumption, requiring that any non-trivial element has at most 2 fixed points.

Rui Ye, Zhenyang Ni, Chenxin Xu, Jianyu Wang

One of the key challenges in federated learning (FL) is local data distribution heterogeneity across clients, which may cause inconsistent feature spaces across clients. To address this issue, we propose a novel method FedFM, which guides each client's features to match shared category-wise anchors (landmarks in feature space). This method attempts to mitiga

Sergey Sadov

The function $\inf_n nx^{1/n}$ has the asymptotics $eu+e d^2(u)/(2u)+O(1/u^2)$ as $x\to\infty$, where $u=\log x$ and $d(u)$ is the distance from $u$ to the nearest integer. We generalize this observation. First, the curves $y=nx^{1/n}$ can be written parametrically as $\log x=nt$, $y=nt$. In general, let $(u_n(t),v_n(t))$ be a family of parametric curves wit

Kamel Shoueir, Anurag Mohanty, Izabela Janowska

In view of clean environment, the industry needs to address multiple demands at different levels of production and processes via the sustainable approach including recycling or smart use of produced waste. On the other hand, a development and success of green energy requires the crucial materials synthesized via efficient, sustainable methodology. Herein, we

Liam Hodgkinson, Chris van der Heide, Fred Roosta, Michael W. Mahoney

Despite their importance for assessing reliability of predictions, uncertainty quantification (UQ) measures for machine learning models have only recently begun to be rigorously characterized. One prominent issue is the curse of dimensionality: it is commonly believed that the marginal likelihood should be reminiscent of cross-validation metrics and that bot

Panagiotis Kasnesis, Lazaros Toumanidis, Alessio Burrello, Christos Chatzigeorgiou

Nowadays, Hearth Rate (HR) monitoring is a key feature of almost all wrist-worn devices exploiting photoplethysmography (PPG) sensors. However, arm movements affect the performance of PPG-based HR tracking. This issue is usually addressed by fusing the PPG signal with data produced by inertial measurement units. Thus, deep learning algorithms have been propo

Srikrishna Jaganathan, Maximilian Kukla, Jian Wang, Karthik Shetty

Deep Learning-based 2D/3D registration enables fast, robust, and accurate X-ray to CT image fusion when large annotated paired datasets are available for training. However, the need for paired CT volume and X-ray images with ground truth registration limits the applicability in interventional scenarios. An alternative is to use simulated X-ray projections fr

Ziqi Gao, Yuntao Wang, Jianguo Chen, Junliang Xing

Multimodal sensors provide complementary information to develop accurate machine-learning methods for human activity recognition (HAR), but introduce significantly higher computational load, which reduces efficiency. This paper proposes an efficient multimodal neural architecture for HAR using an RGB camera and inertial measurement units (IMUs) called Multim

Daniel Pook-Kolb, Bruce Allen, Erik Agrell

We present an algorithm for the exact computer-aided construction of the Voronoi cells of lattices with known symmetry group. Our algorithm scales better than linearly with the total number of faces and is applicable to dimensions beyond 12, which previous methods could not achieve. The new algorithm is applied to the Coxeter-Todd lattice $K_{12}$ as well as

Aitor Garcia-Ruiz, Sergey Slizovskiy, Vladimir I. Fal'ko

Topologically protected flat surface bands make thin films of rhombohedral graphite an appealing platform for searching for strongly correlated states of 2D electrons. In this work, we study rhombohedral graphite with a twin boundary stacking fault and analyse the semimetallic and topological properties of low-energy bands localised at the surfaces and at th

Ajaz Mir, Sanat Tiwari, Abhijit Sen, Chris Crabtree

The synchronization of dust acoustic waves to an external periodic source is studied in the framework of a driven Korteweg-de Vries-Burgers equation that takes into account the appropriate nonlinear and dispersive nature of low frequency waves in a dusty plasma medium. For a spatio-temporally varying source term the system is shown to demonstrate harmonic (1

Jean-Bernard Lasserre

We first interpret Pell's equation satisfied by Chebyshev polynomials for each degree t, as a certain Positivstellensatz, which then yields for each integer t, what we call a generalized Pell's equation, satisfied by reciprocals of Christoffel functions of ''degree'' 2t, associated with the equilibrium measure $\mu$ of the interval [--1, 1] and the measure (

Yingzhen Cui, Xiangcun Meng, Philipp Podsiadlowski, Ren Song

The single-degenerate (SD) model is one of the leading models for the progenitors of Type Ia supernovae (SNe Ia). Recently, a new version of the SD model, the common-envelope wind (CEW) model, has been proposed, which, in principle, has the potential to resolve most of the difficulties encountered by previous SD models. This model is still being developed an

Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu

Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using graph structures based on the relational inductive bias (homophily assumption). While GNNs have been commonly believed to outperform NNs in real-world tasks, recent work has identified a non-trivial set of datasets where their performance compared to NNs is not satisfactory. Heterophily

Yuangang Xie, Chong Wang, Fucong Fei, Yuqi Li

Naturally existing in-plane hyperbolic polaritons and the associated optical topological transitions, which avoid the nano-structuring to achieve hyperbolicity, can outperform their counterparts in artificial metasurfaces. Such plasmon polaritons are rare, but experimentally revealed recently in WTe2 van der Waals thin films. Different from phonon polaritons

Johannes Heinz, Peter Munch, Manfred Kaltenbacher

This work compares two Nitsche-type approaches to treat non-conforming triangulations for a high-order discontinuous Galerkin (DG) solver for the acoustic conservation equations. The first approach (point-to-point interpolation) uses inexact integration with quadrature points prescribed by a primary element. The second approach uses exact integration (mortar

Nicole Bardy-Panse, Auguste Hebert, Guy Rousseau

Let $\mathfrak{G}$ be a split reductive group, $\mathbb{k}$ be a field and $\varpi$ be an indeterminate. In order to study $\mathfrak{G}(\mathbb{k}[\varpi,\varpi^{-1}])$ and $\mathfrak{G}(\mathbb{k}(\varpi))$, one can make them act on their twin building $\mathcal{I} = \mathcal{I}_\oplus\times \mathcal{I}_\ominus$, where $\mathcal{I}_\oplus$ and $\mathcal{I}

Nupoor Gandhi, Anjalie Field, Emma Strubell

Although recent neural models for coreference resolution have led to substantial improvements on benchmark datasets, transferring these models to new target domains containing out-of-vocabulary spans and requiring differing annotation schemes remains challenging. Typical approaches involve continued training on annotated target-domain data, but obtaining ann

Weiming Li, Lihui Xue, Xueqian Wang, Gang Li

For the task of change detection (CD) in remote sensing images, deep convolution neural networks (CNNs)-based methods have recently aggregated transformer modules to improve the capability of global feature extraction. However, they suffer degraded CD performance on small changed areas due to the simple single-scale integration of deep CNNs and transformer m

Kostas Karpouzis, Stavros Kaperonis, Yannis Skarpelos

Social Media have been extensively used for commercial and political communication, besides their initial scope of providing an easy-to-use outlet to produce and consume user-generated content. Besides being a popular medium, Social Media have definitely changed the way we express ourselves or where we look for emerging news and commentary, especially during

Masanori Takano, Fumiaki Taka, Chiki Ogiue, Natsuki Nagata

Famous people, such as celebrities and influencers, are harassed online on a daily basis. Online harassment mentally disturbs them and negatively affects society. However, limited studies have been conducted on the online harassment victimization of famous people, and its effects remain unclear. We surveyed Japanese famous people ($N=213$), who were influent

Hanlin Wu, Ning Ni, Libao Zhang

Deep learning-based algorithms have greatly improved the performance of remote sensing image (RSI) super-resolution (SR). However, increasing network depth and parameters cause a huge burden of computing and storage. Directly reducing the depth or width of existing models results in a large performance drop. We observe that the SR difficulty of different reg

Jan Horak, Jan M. Pawlowski, Nicolas Wink

We calculate the spectral function of light quark flavours in 2+1 flavour vacuum QCD in the isospin-symmetric approximation. We employ spectral Dyson-Schwinger equations and compute the non-perturbative quark propagator directly in real-time, using recent spectral reconstruction results from Gaussian process regression of gluon propagator data in 2+1 flavour

Ovidiu Cristinel Stoica

I analyze the possibility of free-will in the many-worlds interpretation (MWI), arguing for their compatibility. I use as a starting point Nicolas Gisin's "The Multiverse Pandemic" (preprint arXiv:2210.05377, after Gisin, N., "L'\'epid\'emie du multivers", in "Le Plus Grand des Hasards", Belin, Paris, 2010), in which he makes an interesting case that MWI is

Debora Nozza, Dirk Hovy

Work on hate speech has made the consideration of rude and harmful examples in scientific publications inevitable. This raises various problems, such as whether or not to obscure profanities. While science must accurately disclose what it does, the unwarranted spread of hate speech is harmful to readers, and increases its internet frequency. While maintainin

Xiaoyan Zhang, Gaoyang Tang, Yingying Zhu, Qi Tian

The issue of image haze removal has attracted wide attention in recent years. However, most existing haze removal methods cannot restore the scene with clear blue sky, since the color and texture information of the object in the original haze image is insufficient. To remedy this, we propose a cycle generative adversarial network to construct a novel end-to-

Patrick M. Koch, Ya-Wen Tang, Paul T. P. Ho, Pei-Ying Hsieh

We present 230 GHz continuum polarization observations with the Atacama Large Milimeter/Submillimeter Array (ALMA) at a resolution of 0$\farcs1$ ($\sim 540$~au) in the high-mass star-forming regions W51 e2 and e8. These observations resolve a network of core-connecting dust lanes, marking a departure from earlier coarser more spherical continuum structures.

Daeun Song, Eunjung Lim, Jiyoon Park, Minjung Jung

TSP art is an art form for drawing an image using piecewise-continuous line segments. We present TSP-Bot, a robotic pen drawing system capable of creating complicated TSP pen art on a planar surface using multiple colors. The system begins by converting a colored raster image into a set of points that represent the image's tone, which can be controlled by ad

E. Aprile, K. Abe, F. Agostini, S. Ahmed Maouloud

In this work, we expand on the XENON1T nuclear recoil searches to study the individual signals of dark matter interactions from operators up to dimension-eight in a Chiral Effective Field Theory (ChEFT) and a model of inelastic dark matter (iDM). We analyze data from two science runs of the XENON1T detector totaling 1\,tonne$\times$year exposure. For these a

Ivaylo Ilinkin, Daeun Song, Young J. Kim

We present a new robotic drawing system based on stroke-based rendering (SBR). Our motivation is the artistic quality of the whole performance. Not only should the generated strokes in the final drawing resemble the input image, but the stroke sequence should also exhibit a human artist's planning process. Thus, when a robot executes the drawing task, both t

Bangti Jin, Yavar Kian, Zhi Zhou

Inverse problems of recovering space-dependent parameters, e.g., initial condition, space-dependent source or potential coefficient, in a subdiffusion model from the terminal observation have been extensively studied in recent years. However, all existing studies have assumed that the terminal time at which one takes the observation is exactly known. In this

Yang Jiao, Kai Yang, Dongjin Song

Distributionally Robust Optimization (DRO), which aims to find an optimal decision that minimizes the worst case cost over the ambiguity set of probability distribution, has been widely applied in diverse applications, e.g., network behavior analysis, risk management, etc. However, existing DRO techniques face three key challenges: 1) how to deal with the as

Ranran Haoran Zhang, Aysa Xuemo Fan, Rui Zhang

A universal classification model aims to generalize to diverse classification tasks in both zero and few shot settings. A promising way toward universal classification is to cast heterogeneous data formats into a dataset-agnostic "meta-task" (e.g., textual entailment, question answering) then pretrain a model on the combined meta dataset. The existing work i

Hyunjae Kim, Jaehyo Yoo, Seunghyun Yoon, Jaewoo Kang

Most weakly supervised named entity recognition (NER) models rely on domain-specific dictionaries provided by experts. This approach is infeasible in many domains where dictionaries do not exist. While a phrase retrieval model was used to construct pseudo-dictionaries with entities retrieved from Wikipedia automatically in a recent study, these dictionaries

Yuxin Wang, Tao Wu, Zheng Li, Kun Jiang

The structure of charge density wave states in AV$_3$Sb$_5$ (A = K, Rb, Cs) kagome superconductors remains elusive, with three possible $2a\times2a\times2c$ candidates: tri-hexagonal, star-of-David, and their mixture. In this study, we conducted a systematic first-principles investigation of the nuclear quadrupole resonance (NQR) and nuclear magnetic resonan

Krzysztof Maślanka

We present a new asymptotic formula for the Stieltjes constants which is both simpler and more accurate than several others published in the literature (see e.g. \cite{Fekih-Ahmed}, \cite{Knessl Coffey}, \cite{Paris}). More importantly, it is also a good starting point for a detailed analysis of some surprising regularities in these important constants.

Benbo Zha, Hong Shen

Burst-Buffering is a promising storage solution that introduces an intermediate highthroughput storage buffer layer to mitigate the I/O bottleneck problem that the current High-Performance Computing (HPC) platforms suffer. The existing Markov-Chain based probabilistic I/O scheduling utilizes the load state of Burst-Buffers and the periodical characteristics

Dmitry S. Bykov, Lorenzo Dania, Florian Goschin, Tracy E. Northup

Cooling the center-of-mass motion of levitated nanoparticles provides a route to quantum experiments at mesoscopic scales. Here we demonstrate three-dimensional sympathetic cooling and detection of the center-of-mass motion of a levitated silica nanoparticle. The nanoparticle is electrostatically coupled to a feedback-cooled particle while both particles are

Jae Yong Lee, Chuhang Zou, Derek Hoiem

Recent work in multi-view stereo (MVS) combines learnable photometric scores and regularization with PatchMatch-based optimization to achieve robust pixelwise estimates of depth, normals, and visibility. However, non-learning based methods still outperform for large scenes with sparse views, in part due to use of geometric consistency constraints and ability

A. Ritter, Q. A. Parker, L. Sabin, P. Le Dû

We present Grantecan 10 m telescope (GTC) spectroscopic confirmations of 55 faint Planetary Nebulae (PNe) candidates discovered largely in the INT Photometric H$_\alpha$ Survey of the Northern Galactic Plane (IPHAS) by our pro-am collaboration. We confirm 46 of them as 'True' (T), 4 as 'Likely' (L) and 5 as 'Possible' (P) PNe and including 5 new PNe central

Rahul Biswas, Somabha Mukherjee

The estimator of a causal directed acyclic graph (DAG) with the PC algorithm is known to be consistent based on independent and identically distributed samples. In this paper, we consider the scenario when the multivariate samples are identically distributed but not independent. A common example is a stationary multivariate time series. We show that under a

Xiaogang Huang, Tiefeng Ma, Conan Liu, Shuangzhe Liu

DBSCAN is a fundamental spatial clustering algorithm with numerous practical applications. However, a bottleneck of the algorithm is in the worst case, the run time complexity is $O(n^2)$. To address this limitation, we propose a new grid-based algorithm for exact DBSCAN in Euclidean space called GriT-DBSCAN, which is based on the following two techniques. F

Su Hu, Min-Soo Kim

Let $\{a_{1}, a_{2},\ldots, a_{n},\ldots\}$ be a sequence of complex numbers which has at most polynomial growth and satisfies an extra assumption. In this paper, inspired by a recent work of Sasane, we give an explanation of the sum $$a_{1}+2a_{2}+3a_{3}+\cdots+na_{n}+\cdots,$$ and more generally, for any $k\in\mathbb{N},$ the sum $$1^{k}a_{1}+2^{k}a_{2}+3^

Youssef Chaabouni, Andrea Araldo, André de Palma, Souhila Arib

In carpooling systems, a set of drivers owning a private car can accept a small detour to pick-up and drop-off other riders. However, carpooling is widely used for long-distance trips, where rider-driver matching can be done days ahead. Making carpooling a viable option for daily commute is more challenging, as trips are shorter and, proportionally, the deto

Andra Petrovai, Sergiu Nedevschi

Depth-aware video panoptic segmentation tackles the inverse projection problem of restoring panoptic 3D point clouds from video sequences, where the 3D points are augmented with semantic classes and temporally consistent instance identifiers. We propose a novel solution with a multi-task network that performs monocular depth estimation and video panoptic seg

Adnan A. E. Hajomer, Huy Q. Nguyen, Tobias Gehring

We report the first experiment of continuous-variable measurement-device-independent quantum key distribution that enables secret key generation at a symbol rate of 5 MBaud without frequency and optical phase locking. This is achieved by using a new relay structure based on a polarization-based 90-degree optical hybrid and a well-designed DSP pipeline.

M. Schmelling, Á. Pastor-Gutiérrez, H. Schorlemmer, R. D. Parsons

In the sub-TeV regime, the most widely used hadronic interaction models disagree significantly in their predictions of particle spectra from cosmic ray induced air showers. We investigate the nature and impact of model uncertainties, focussing on air shower primaries with energies around the transition between high and low energy hadronic interaction models,

Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue

Recent text-to-image generation models have shown promising results in generating high-fidelity photo-realistic images. Though the results are astonishing to human eyes, how applicable these generated images are for recognition tasks remains under-explored. In this work, we extensively study whether and how synthetic images generated from state-of-the-art te

Ashish Kumar Jayant, Shalabh Bhatnagar

During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents perform a significant number of random exploratory steps. In the real world, this can limit the practicality of these algorithms as it can lead to potentially dangerous behavior. Hence safe exploration is a critical issue in applying RL algorithms in the real world.

Hailong Yuan, Song Wang, Zhongrui Bai, Yue Wang

We report the discovery of one possible neutron star binary ($P_{\rm orb} =$ 0.8666 day) by using the LAMOST low-resolution spectroscopic data. The visible companion is a late A-type dwarf ($T_{\rm eff} = 7900 \pm 200$ K; log$g$ $=$ 4.3$\pm$0.2; $M =$ 1.7$\pm$0.1 M$_{\odot}$; $R\ =\ 1.7\pm0.2$ R$_{\odot}$), at a distance of 1.11$\pm0.03$ kpc. No double-lined

Xuetong Xue, Jiaying Shi, Xinxue He, Shenghui Xu

Deep hashing has been widely applied to large-scale image retrieval tasks owing to efficient computation and low storage cost by encoding high-dimensional image data into binary codes. Since binary codes do not contain as much information as float features, the essence of binary encoding is preserving the main context to guarantee retrieval quality. However,

Chaoqi Chen, Luyao Tang, Feng Liu, Gangming Zhao

Domain generalization (DG) enables generalizing a learning machine from multiple seen source domains to an unseen target one. The general objective of DG methods is to learn semantic representations that are independent of domain labels, which is theoretically sound but empirically challenged due to the complex mixture of common and domain-specific factors.

Ying Su, Zihao Wang, Tianqing Fang, Hongming Zhang

Commonsense reasoning tasks such as commonsense knowledge graph completion and commonsense question answering require powerful representation learning. In this paper, we propose to learn commonsense knowledge representation by MICO, a Multi-alternative contrastve learning framework on COmmonsense knowledge graphs (MICO). MICO generates the commonsense knowle

Priyanka Sinha, Subaveerapandiyan A

The author's productivity is assessed based on publications, which requires a lot of motivation and time. Manuscripts get through several steps before being accepted and published. The purpose of this paper is to understand the time gap between acceptance to the publication of manuscripts in reputed journals of Library and Information Science. This paper is

Hirokazu Tsunetsugu, Hiroaki Kusunose

We have developed a microscopic theory on phonon energy dispersion in chiral crystals within a harmonic approximation. One of the main issues is about the splitting of sound velocity of acoustic phonons with opposite ``crystal'' angular momentum. We have shown that the splitting must be zero even in chiral crystals and the difference starts from the order of

J. L. Lado, J. Fernández-Rossier

Systems that can be described with the same mathematical models that account for the properties of electrons in graphene are known as graphene-like systems. These include magnons, photons, polaritons, acoustic waves, and electrons in honeycomb lattices, either natural or artificial. All of them feature an outstanding property, the existence of states localiz

Shiyun Wang

We expand the chromatic symmetric functions for Dyck paths of bounce number three in the elementary symmetric function basis using a combinatorial interpretation of the inverse of the Kostka matrix studied in E\u{g}ecio\u{g}lu-Remmel (1990). We prove that certain coefficients in this expansion are positive. We establish the $e$-positivity of an extended clas

Swaroop Mishra, Anjana Arunkumar, Chris Bryan, Chitta Baral

Several benchmarks have been built with heavy investment in resources to track our progress in NLP. Thousands of papers published in response to those benchmarks have competed to top leaderboards, with models often surpassing human performance. However, recent studies have shown that models triumph over several popular benchmarks just by overfitting on spuri

Tianxiang Sun, Zhengfu He, Qin Zhu, Xipeng Qiu

Prompt tuning is a parameter-efficient approach to adapting pre-trained language models to downstream tasks. Although prompt tuning has been shown to match the performance of full model tuning when training data is sufficient, it tends to struggle in few-shot learning settings. In this paper, we present Multi-task Pre-trained Modular Prompt (MP2) to boost pr

Xin Tian, Yingzhan Lin, Mengfei Song, Siqi Bao

Existing pipelined task-oriented dialogue systems usually have difficulties adapting to unseen domains, whereas end-to-end systems are plagued by large-scale knowledge bases in practice. In this paper, we introduce a novel query-driven task-oriented dialogue system, namely Q-TOD. The essential information from the dialogue context is extracted into a query,

Naoto Komeno, Brendan Michael, Katharina Küchler, Edgar Anarossi

Soft robots are challenging to model and control as inherent non-linearities (e.g., elasticity and deformation), often requires complex explicit physics-based analytical modeling (e.g., a priori geometric definitions). While machine learning can be used to learn non-linear control models in a data-driven approach, these models often lack an intuitive interna

Hyeong Kyu Choi, Joonmyung Choi, Hyunwoo J. Kim

Mixup is a commonly adopted data augmentation technique for image classification. Recent advances in mixup methods primarily focus on mixing based on saliency. However, many saliency detectors require intense computation and are especially burdensome for parameter-heavy transformer models. To this end, we propose TokenMixup, an efficient attention-guided tok

Mogan Gim, Donghee Choi, Kana Maruyama, Jihun Choi

We propose a computational approach for recipe ideation, a downstream task that helps users select and gather ingredients for creating dishes. To perform this task, we developed RecipeMind, a food affinity score prediction model that quantifies the suitability of adding an ingredient to set of other ingredients. We constructed a large-scale dataset containin

Manu A., Debodirna Ghosh

In this short note, we analyse low energy electromagnetic radiation for spinning particles using the KMOC formalism and the quantum soft theorems. In particular, we study low energy electromagnetic radiation emitted by the so-called $\sqrt{\text{Kerr}}$ object. The $\sqrt{\text{Kerr}}$ is a solution of the free Maxwell's equations with infinite multipole mom

Ayan Mitra, Richard Kessler, Surhud More, Renee Hlozek

We perform a rigorous cosmology analysis on simulated type Ia supernovae (SN~Ia) and evaluate the improvement from including photometric host-galaxy redshifts compared to using only the "zspec" subset with spectroscopic redshifts from the host or SN. We use the Deep Drilling Fields (~50 deg^2) from the Photometric LSST Astronomical Time-Series Classification

Yuta Matsunaga, Takaaki Saeki, Shinnosuke Takamichi, Hiroshi Saruwatari

We present a comprehensive empirical study for personalized spontaneous speech synthesis on the basis of linguistic knowledge. With the advent of voice cloning for reading-style speech synthesis, a new voice cloning paradigm for human-like and spontaneous speech synthesis is required. We, therefore, focus on personalized spontaneous speech synthesis that can

Mojtaba Valipour, Mehdi Rezagholizadeh, Ivan Kobyzev, Ali Ghodsi

With the ever-growing size of pretrained models (PMs), fine-tuning them has become more expensive and resource-hungry. As a remedy, low-rank adapters (LoRA) keep the main pretrained weights of the model frozen and just introduce some learnable truncated SVD modules (so-called LoRA blocks) to the model. While LoRA blocks are parameter-efficient, they suffer f

Minh-Tâm Quang Trinh

Let $\mathcal{U}$ be the unipotent variety of a complex reductive group $G$. Fix opposed Borel subgroups $B_\pm \subseteq G$ with unipotent radicals $U_\pm$. The map that sends $x_+x_- \mapsto x_+x_-x_+^{-1}$ for all $x_\pm \in U_\pm$ restricts to a map from $U_+U_- \cap gB_+$ into $\mathcal{U} \cap gB_+$, for any $g$. We conjecture that the restricted map f

Ashwani Kr. Tripathi, Tsvi Tlusty

Nanoswimmers are ubiquitous in bio- and nano-technology but are extremely challenging to measure due to their minute size and driving forces. A simple method is proposed for detecting the elusive physical features of nanoswimmers by observing how they affect the motion of much larger, easily traceable particles. Modeling the swimmers as hydrodynamic force di

Guillermo Gallego, Danny Segev

In the adaptive ProbeMax problem, given a collection of mutually-independent random variables $X_1, \ldots, X_n$, our goal is to design an adaptive probing policy for sequentially sampling at most $k$ of these variables, with the objective of maximizing the expected maximum value sampled. In spite of its stylized formulation, this setting captures numerous t

Aref Hashemi, Edward T. Gilman, Aditya S. Khair

We develop a two-timing perturbation analysis to investigate the existence of temporal ratchets in an exemplary system of a particle moving in a tank of fluid in response to an external vibration of the tank. We consider two-mode vibrations with angular frequencies $\omega$ and $\alpha\omega$, where $\alpha$ is a rational number. It has been established, in

Quentin A. Parker, Pascal Le Dû, Andreas Ritter, Peter Goodhew

We present evidence that the nebular cocoon and bow-shock emission nebula putatively and recently reported as deriving from the 9th magnitude "runaway" star HD 185806 is the previously discovered but obscure planetary nebula WHTZ 1 (Ra 7). It has a Gaia DR3 G~16 blue ionizing star at its geometric centre. We present imagery, spectroscopy, other data and argu

Dongjie Yu, Wenjun Zou, Yujie Yang, Haitong Ma

Safe reinforcement learning (RL) that solves constraint-satisfactory policies provides a promising way to the broader safety-critical applications of RL in real-world problems such as robotics. Among all safe RL approaches, model-based methods reduce training time violations further due to their high sample efficiency. However, lacking safety robustness agai