May 2023 arXiv papers — page 190

Yiyuan She, Jianhui Shen, Adrian Barbu

Big-data applications often involve a vast number of observations and features, creating new challenges for variable selection and parameter estimation. This paper presents a novel technique called ``slow kill,'' which utilizes nonconvex constrained optimization, adaptive $\ell_2$-shrinkage, and increasing learning rates. The fact that the problem si

Kerven Durdymyradov, Mikhail Moshkov

Decision trees and systems of decision rules are widely used as classifiers, as a means for knowledge representation, and as algorithms. They are among the most interpretable models for data analysis. The study of the relationships between these two models can be seen as an important task of computer science. Methods for transforming decision trees into syst

Lior Shamir

The Dark Energy Survey is able to collect image data of an extremely large number of extragalactic objects, and it can be reasonably assumed that many unusual objects of high scientific interest are hidden inside these data. Due to the extreme size of DES data, identifying these objects among many millions of other celestial objects is a challenging task. Th

T. Paskett, J. P. Whitehead, R. A. Harris, C. Ashcroft

Using a Bayesian approach we compare anecdotal tsunami runup observations from the 29 December 1820 Flores Sea earthquake with close to 200,000 tsunami simulations to determine the most probable earthquake parameters causing the tsunami. Using a dual hypothesis of the source earthquake either originating from the Flores Thrust or the Walanae/Selayar Fault, w

C. Antel, M. Battaglieri, J. Beacham, C. Boehm

Particle physics today faces the challenge of explaining the mystery of dark matter, the origin of matter over anti-matter in the Universe, the origin of the neutrino masses, the apparent fine-tuning of the electro-weak scale, and many other aspects of fundamental physics. Perhaps the most striking frontier to emerge in the search for answers involves new ph

Soheil Behnezhad, Mohammad Saneian

Given a graph $G$, an edge-coloring is an assignment of colors to edges of $G$ such that any two edges sharing an endpoint receive different colors. By Vizing's celebrated theorem, any graph of maximum degree $Δ$ needs at least $Δ$ and at most $(Δ+ 1)$ colors to be properly edge colored. In this paper, we study edge colorings in the streaming setting. Th

Himarsha R. Jayanetti, Erika Frydenlund, Michele C. Weigle

This study explores xenophobic events related to refugees and migration using the GDELT 2.0 database and APIs through visualizations. We conducted two case studies -- the first being an analysis of refugee-related news following the death of a two-year-old Syrian boy, Alan Kurdi, and the second a surge in news articles in March 2021 based on the data obtaine

Leopoldo Sarra, Kevin Ellis, Florian Marquardt

Despite rapid progress in the field, it is still challenging to discover new ways to take advantage of quantum computation: all quantum algorithms need to be designed by hand, and quantum mechanics is notoriously counterintuitive. In this paper, we study how artificial intelligence, in the form of program synthesis, may help to overcome some of these difficu

Sangita Dutta, Abhijit Mondal, Prosenjit Kundu, Pitambar Khanra

The study of first order transition (explosive synchronization) in an ensemble (network) of coupled oscillators has been the topic of paramount interest among the researchers for more than onedecade. Several frameworks have been proposed to induce explosive synchronization in a network and it has been reported that phase frustration in a network usually supp

Masaki Sakuma

We prove the existence of infinitely many solutions to a fractional Choquard type equation \[ (-Δ)^s_p u+V(x)|u|^{p-2}u=(K\ast g(u))g'(u)+\varepsilon_W W(x)f'(u)\quad\text{in }\mathbb{R}^N \] involving fractional $p$-Laplacian and a general convolution term with critical growth. In order to obtain infinitely many solutions, we use a type of the symme

A. Claret, J. Southworth

Multiple parametric limb-darkening laws have been presented, and there are many available sources of theoretical limb-darkening coefficients (LDCs) calculated using stellar model atmospheres. The power-2 limb-darkening law allows a very good representation of theoretically predicted intensity profiles, but few LDCs are available for this law from spherically

Colton Mikes, Ismael R. de Farias, David Huckleberry Gutman, Victoria E. Howle

This paper introduces a quantum-classical hybrid algorithm for generalized pattern search (GPS) algorithms. We introduce a quantum search step algorithm using amplitude amplification, which reduces the number of oracle calls needed during the search step from O(N) classical calls to O(N^(1/2)) quantum calls. This work addresses three fundamental issues with

Yury Alkhimenkov, Lyudmila Khakimova, Ivan Utkin, Yury Podladchikov

Shear strain localization refers to the phenomenon of accumulation of material deformation in narrow slip zones. Many materials exhibit strain localization under different spatial and temporal scales, particularly rocks, metals, soils, and concrete. In the Earth's crust, irreversible deformation can occur in brittle as well as in ductile regimes. Modelin

Lee Milburn, Juan Gamba, Miguel Fernandes, Claudio Semini

The VINUM project seeks to address the shortage of skilled labor in modern vineyards by introducing a cutting-edge mobile robotic solution. Leveraging the capabilities of the quadruped robot, HyQReal, this system, equipped with arm and vision sensors, offers autonomous navigation and winter pruning of grapevines reducing the need for human intervention. At t

Len Bos

We discuss the growth of the Lebesgue constants for polynomial interpolation at Fekete points for fixed degree (one) and varying dimension, and underlying set $K\subset \R^d$ a simplex, ball or cube.

Gennesaret Tjusila, Mathieu Besançon, Mark Turner, Thorsten Koch

It has been shown that any 9 by 9 Sudoku puzzle must contain at least 17 clues to have a unique solution. This paper investigates the more specific question: given a particular completed Sudoku grid, what is the minimum number of clues in any puzzle whose unique solution is the given grid? We call this problem the Minimum Sudoku Clue Problem (MSCP). We formu

Nicola Franchini, Sebastian H. Völkel

The purpose of this chapter is to provide an overview of the exciting field of black hole quasi-normal modes and its capabilities to test general relativity in the 21st century. After motivating this line of research, we provide a qualitative introduction to the concept of quasi-normal modes and outline black hole perturbation theory. With the perturbation e

E. S. Rykoff, D. L. Tucker, D. L. Burke, S. S. Allam

This Technical Note presents a catalog of calibrated reference stars that was generated by the Forward Calibration Method (FGCM) pipeline (arXiv:1706.01542) as part of the FGCM photometric calibration of the full Dark Energy Survey (DES) 6-Year data set (Y6). This catalog provides DES grizY magnitudes for 17 million stars with i-band magnitudes mostly in the

Lydia Makrygianni, Benny Trakhtenbrot, Iair Arcavi, Claudio Ricci

AT 2021loi is an optical-ultraviolet transient located at the center of its host galaxy. Its spectral features identify it as a member of the ``Bowen Fluorescence Flare'' (BFF) class. The first member of this class was considered to be related to a tidal disruption event, but enhanced accretion onto an already active supermassive black hole was sugge

Murray Brightman, Jean-Marie Hameury, Jean-Pierre Lasota, Ranieri D. Baldi

Ultraluminous X-ray sources (ULXs) are our best laboratories for studying extreme super-Eddington accretion. Most studies of these objects are of relatively persistent sources, however there is growing evidence to suggest a large fraction of these sources are transient. Here we present a sample of five newly reported transient ULXs in the galaxies NGC 4945,

Matthew J. Colbrook, Alex Townsend

The first step when solving an infinite-dimensional eigenvalue problem is often to discretize it. We show that one must be extremely careful when discretizing nonlinear eigenvalue problems. Using examples, we show that discretization can: (1) introduce spurious eigenvalues, (2) entirely miss spectra, and (3) bring in severe ill-conditioning. While there are

I. El Mellah, B. Cerutti, B. Crinquand

Low-luminosity supermassive and stellar-mass black holes (BHs) may be embedded in a collisionless and highly magnetized plasma. They show non-thermal flares indicative of efficient dissipative processes in the vicinity of the BH. During NIR flares from the supermassive BH Sagittarius A* (Sgr A*), GRAVITY detected circular motion and polarization evolution wh

A. Chiesa, S. Roca, S. Chicco, M. C. de Ory

The implementation of a universal quantum processor still poses fundamental issues related to error mitigation and correction, which demand to investigate also platforms and computing schemes alternative to the main stream. A possibility is offered by employing multi-level logical units (qudits), naturally provided by molecular spins. Here we present the blu

A. Batra, H. B. Câmara, F. R. Joaquim

We propose a minimal model where a dark sector, odd under a $\mathcal{Z}_2$ discrete symmetry, is the seed of lepton number violation in the neutrino sector at the loop level, in the context of the linear seesaw mechanism. Neutrino mass suppression stems from a naturally small scalar potential coupling which breaks the lepton number symmetry softly. The fact

Federico Mogavero, Nam H. Hoang, Jacques Laskar

Numerical integrations of the Solar System reveal a remarkable stability of the orbits of the inner planets over billions of years, in spite of their chaotic variations characterized by a Lyapunov time of only 5 million years and the lack of integrals of motion able to constrain their dynamics. To open a window on such long-term behavior, we compute the enti

Chengshu Li, Ming-Gen He, Chang-Yan Wang, Hui Zhai

When the Fermi Hubbard model was first introduced sixty years ago, one of the original motivations was to understand correlation effects in itinerant ferromagnetism. In the past two decades, ultracold Fermi gas in an optical lattice has been used to study the Fermi Hubbard model. However, the metallic ferromagnetic correlation was observed only in a recent e

Eric R. Coughlin

A star destroyed by a supermassive black hole (SMBH) in a tidal disruption event (TDE) is transformed into a filamentary structure known as a tidally disrupted stellar debris stream. We show that when ideal gas pressure dominates the thermodynamics of the stream, there is an exact solution to the hydrodynamics equations that describes the stream evolution an

Mudit Jain, Mustafa A. Amin, Han Pu

We provide an algorithm for evolving general spin-$s$ Gross-Pitaevskii / non-linear Schrödinger systems carrying a variety of interactions, where the $2s+1$ components of the `spinor' field represent the different spin-multiplicity states. We consider many nonrelativistic interactions up to quartic order in the Schrödinger field (both short and long-rang

Jacob L. Bourjaily, Simon Caron-Huot

We derive novel recursion relations for all loop amplitude integrands of planar, maximally supersymmetric Yang-Mills theory in terms of unitarity-like `cuts' obtained via sequences of BCFW deformations in momentum-twistor space.

Zoe A. Purcell, Mengchen Dong, Anne-Marie Nussberger, Nils Köbis

The rapid development of AI-mediated communication technologies (AICTs), which are digital tools that use AI to augment interpersonal messages, has raised concerns about the future of interpersonal trust and prompted discussions about disclosure and uptake. This paper contributes to this discussion by assessing perceptions about the acceptability and use of

Xin Hong, Yanyan Lan, Liang Pang, Jiafeng Guo

Most existing visual reasoning tasks, such as CLEVR in VQA, ignore an important factor, i.e.~transformation. They are solely defined to test how well machines understand concepts and relations within static settings, like one image. Such \textbf{state driven} visual reasoning has limitations in reflecting the ability to infer the dynamics between different s

Ke Zhang

Accurately predicting the performance of architecture with small sample training is an important but not easy task. How to analysis and train dataset to overcome overfitting is the core problem we should deal with. Meanwhile if there is the mult-task problem, we should also think about if we can take advantage of their correlation and estimate as fast as we

Takuma Miyaguchi, Hideyoshi Yanagisawa

We formulated the sense of the presence of a remote participant in hybrid communication using a Bayesian framework. We also applied the knowledge gained from the simulation with the Bayesian model to the avatar robot's intervention behavior and encouraged the local participants to speak by intervening in the remote participant's behavior using an ava

Sebastian Stumper, Junichi Okamoto

We study a fermionic two-band model with the interband transition resonantly coupled to a cavity. This model was recently proposed to explain cavity-enhanced charge transport, but a thorough characterization of the closed system, in particular localization of various excitations, is lacking. In this work, using exact diagonalization, we characterize the syst

Manish Bhatia, Balram Meena, Vipin Kumar Rathi, Prayag Tiwari

The shape of erythrocytes or red blood cells is altered in several pathological conditions. Therefore, identifying and quantifying different erythrocyte shapes can help diagnose various diseases and assist in designing a treatment strategy. Machine Learning (ML) can be efficiently used to identify and quantify distorted erythrocyte morphologies. In this pape

He Liu, Xiao-Min Zhang, Peng-Cheng Chu

Using the constraints from astrophysical observations and heavy-ion experiments, we investigate the equation of state (EOS) of hybrid star matter and the properties of quark-matter cores in hybrid stars. The quark matter interactions in hybrid stars are described based on 3-flavor Nambu-Jona-Lasinio model with various vector and vector-isovector coupling con

Jie Liu, Peizheng Wang, Chao Wu

Data valuation using Shapley value has emerged as a prevalent research domain in machine learning applications. However, it is a challenge to address the role of order in data cooperation as most research lacks such discussion. To tackle this problem, this paper studies the definition of the partial ordinal Shapley value by group theory in abstract algebra.

Rahul Bhagat, S. A. Narawade, B. Mishra

In this paper, we have studied the dynamical aspects of the cosmological model of the Universe in the Weyl type $f(Q,T)$ gravity, which is an extension of symmetric teleparallel gravity. The non-metricity scalar $Q$ has been expressed in standard Weyl form and can be determined by a vector field $w_μ$ and the trace of energy momentum tensor denoted as $T$. T

Ruoshi Liu, Carl Vondrick

The relatively hot temperature of the human body causes people to turn into long-wave infrared light sources. Since this emitted light has a larger wavelength than visible light, many surfaces in typical scenes act as infrared mirrors with strong specular reflections. We exploit the thermal reflections of a person onto objects in order to locate their positi

Yasumasa Onoe, Michael J. Q. Zhang, Shankar Padmanabhan, Greg Durrett

Pre-trained language models (LMs) are used for knowledge intensive tasks like question answering, but their knowledge gets continuously outdated as the world changes. Prior work has studied targeted updates to LMs, injecting individual facts and evaluating whether the model learns these facts while not changing predictions on other contexts. We take a step f

Natalie Burns, Michael J. Daniels

Enriched Dirichlet process mixture (EDPM) models are Bayesian nonparametric models which can be used for nonparametric regression and conditional density estimation and which overcome a key disadvantage of jointly modeling the response and predictors as a Dirichlet process mixture (DPM) model: when there is a large number of predictors, the clusters induced

Ariel Gera, Roni Friedman, Ofir Arviv, Chulaka Gunasekara

Applying language models to natural language processing tasks typically relies on the representations in the final model layer, as intermediate hidden layer representations are presumed to be less informative. In this work, we argue that due to the gradual improvement across model layers, additional information can be gleaned from the contrast between higher

A. Claret

One of the most reliable means of studying the stellar interior is through the apsidal motion in double line eclipsing binary systems since these systems present errors in masses, radii, and effective temperatures of only a few per cent. On the other hand, the theoretical values of the apsidal motion to be compared with the observed values depend on the stel

Haryanto M. Siahaan

We investigate the pair production near a (near) extremal magnetized Reissner-Nordstrom black hole. The pair production is shown to exist in the extremal state, which can be interpreted as the Schwinger effect due to the strong field under consideration. To show a correspondence between the growth of the external magnetic field and the scalar absorption, som

Xiang Li, Xin Jiang, Xuying Meng, Aixin Sun

Pre-trained language models (PLMs) have achieved remarkable success in NLP tasks. Despite the great success, mainstream solutions largely follow the pre-training then finetuning paradigm, which brings in both high deployment costs and low training efficiency. Nevertheless, fine-tuning on a specific task is essential because PLMs are only pre-trained with lan

Quan Ze Chen, Amy X. Zhang

When groups of people are tasked with making a judgment, the issue of uncertainty often arises. Existing methods to reduce uncertainty typically focus on iteratively improving specificity in the overall task instruction. However, uncertainty can arise from multiple sources, such as ambiguity of the item being judged due to limited context, or disagreements a

Sumanta Ghosh, Subhajit Nath, Sarvesh Sortee, Lokesh Kumar

In this paper we address the multi-agent collaborative object transportation problem in a partially known environment with obstacles under a specified goal condition. We propose a leader follower approach for two mobile manipulators collaboratively transporting an object along specified desired trajectories. The proposed approach treats the mobile manipulati

Jason Gaddis

We survey several generalizations of the Weyl algebra including generalized Weyl algebras, twisted generalized Weyl algebras, quantized Weyl algebras, and Bell-Rogalski algebras. Attention is paid to ring-theoretic properties, representation theory, and invariant theory.

Rei Richter, Itsik Bergel, Yair Noam, Ephi Zehavi

Channel reciprocity can significantly reduce the overhead of obtaining channel-state information at the transmitter (CSIT). However, true reciprocity only exists in time division duplex (TDD). In this paper, we propose a novel tracking method that exploits implicit reciprocity in FDD line-of-sight (LOS) channels as in low-earth-orbit (LEO) satellite communic

Sergey V. Tikhonov

Let $G$ be an absolutely almost simple algebraic group over a field $K$. The genus ${\bf gen}_K(G)$ of $G$ is the set of $K$-isomorphism classes of $K$-forms $G'$ of $G$ that have the same $K$-isomorphism classes of maximal $K$-tori as $G$. We construct an example of outer forms of type $A_2$ with infinite genus.

M. Schweizer, N. Straumann, A. Wipf

We adapt the post-Newtonian gravitational-radiation methods developed within general relativity by Epstein and Wagoner to the gravitation theory with torsion, recently proposed by Hehl et al., and show that the two theories predict in this approximation the same gravitational radiation losses. Since they agree also on the first post-Newtonian level, they are

R. K. Singh, T. Sandev, Sadhana Singh

We study the escape behavior of a lamb to safe haven pursued by a hungry lion. Identifying the system with a pair of vicious Brownian walkers we evaluate the probability density function for the vicious pair and from there we estimate the distribution of first passage times. The process ends in two ways: either the lamb makes it to the safe haven (success) o

Lisa Hackett, Matthew Koppa, Brandon Smith, Michael Miller

We show that phononic frequency conversion can be enhanced by orders of magnitude in piezoelectric systems by heterogeneous integration of high-mobility semiconductor films. A lithium niobate and indium gallium arsenide heterostructure is utilized to demonstrate efficient three-wave mixing processes at microwave frequencies, including 16% phononic power conv

Xinyu Yi, Yuxiao Zhou, Marc Habermann, Vladislav Golyanik

Human and environment sensing are two important topics in Computer Vision and Graphics. Human motion is often captured by inertial sensors, while the environment is mostly reconstructed using cameras. We integrate the two techniques together in EgoLocate, a system that simultaneously performs human motion capture (mocap), localization, and mapping in real ti

Tong Lu, Yuan Zhang, Peter Kochunov, Elliot Hong

Brain connectome analysis commonly compresses high-resolution brain scans (typically composed of millions of voxels) down to only hundreds of regions of interest (ROIs) by averaging within-ROI signals. This huge dimension reduction improves computational speed and the morphological properties of anatomical structures; however, it also comes at the cost of su

Aki Barry, Lei Han, Gianluca Demartini

With the proliferation of algorithmic decision-making, increased scrutiny has been placed on these systems. This paper explores the relationship between the quality of the training data and the overall fairness of the models trained with such data in the context of supervised classification. We measure key fairness metrics across a range of algorithms over m

D. Yang, L. Gizon, H. Barucq, J. Hirzberger

Earth-side observations of solar p modes can be used to image and monitor magnetic activity on the Sun's far side. Here we use magnetograms of the far side obtained by the Polarimetric and Helioseismic Imager (PHI) onboard Solar Orbiter (SO) to directly assess -- for the first time -- the validity of far-side helioseismic holography. We wish to co-locate

Karl Bringmann, Alejandro Cassis

We revisit the classic 0-1-Knapsack problem, in which we are given $n$ items with their weights and profits as well as a weight budget $W$, and the goal is to find a subset of items of total weight at most $W$ that maximizes the total profit. We study pseudopolynomial-time algorithms parameterized by the largest profit of any item $p_{\max}$, and the largest

Anastasiia Sheveleva, Saïd Hamdi, Aurélien Coillet, Christophe Finot

We demonstrate that the Dynamic Mode Decomposition technique can effectively reduce the amount of noise in Dispersive Fourier Transform dataset; and allow for finer quantitative analysis of the experimental data. We therefore were able to demonstrate that the oscillation pattern of a soliton molecule actually results from the interplay of several elementary

D. Spence, M. Bonamente, J. Nevalainen, T. Tuominen

This paper presents an analysis of XMM X--ray spectra of the quasar 1ES 1553+113, in search for absorption lines from the intervening warm--hot intergalactic medium. A search for OVII, OVIII and NeIX resonance absorption lines was performed at eight fixed redshifts that feature OVI or HI broad Lyman--$α$ absorption lines that were previously detected from HS

Marvin Künnemann, Filip Mazowiecki, Lia Schütze, Henry Sinclair-Banks

Seminal results establish that the coverability problem for Vector Addition Systems with States (VASS) is in EXPSPACE (Rackoff, '78) and is EXPSPACE-hard already under unary encodings (Lipton, '76). More precisely, Rosier and Yen later utilise Rackoff's bounding technique to show that if coverability holds then there is a run of length at most $n

Arsenii Gorin, Cem Subakan, Sajjad Abdoli, Junhao Wang

In this paper, we explore self-supervised learning (SSL) for analyzing a first-of-its-kind database of cry recordings containing clinical indications of more than a thousand newborns. Specifically, we target cry-based detection of neurological injury as well as identification of cry triggers such as pain, hunger, and discomfort. Annotating a large database i

Dmitrii Taletskii

We show that the number of independent sets in every outerplanar graph is greater than the number of its 4-dominating sets.

T. J. J. M. van Overveld, H. J. H. Clercx, M. Duran-Matute

We study the self-organization of spherical particles in an oscillating flow through experiments inside an oscillating box. The interactions between the particles and the time-averaged (steady streaming) flow lead to the formation of either one-particle-thick chains or multiple-particle-wide bands, depending on the oscillatory conditions. Both the chains and

Florian Steininger, Piotr T. Chruściel

We analyze the Cauchy problem for the Proca equation in gravitating dielectric media.

Isak G. B. Wold, Sangeeta Malhotra, James E. Rhoads, Vithal Tilvi

The slitless grism on the Nancy Grace Roman Space Telescope will enable deep near-infrared spectroscopy over a wide field of view. We demonstrate Roman's capability to detect Ly$α$ galaxies at $z>7$ using a multi-position-angle (PA) observational strategy. We simulate Roman grism data using a realistic foreground scene from the COSMOS field. We also inpu

Zhishuo Zhang, Chengxiang Tan, Xueyan Zhao, Min Yang

Cross-lingual and cross-domain knowledge alignment without sufficient external resources is a fundamental and crucial task for fusing irregular data. As the element-wise fusion process aiming to discover equivalent objects from different knowledge graphs (KGs), entity alignment (EA) has been attracting great interest from industry and academic research recen

Zhishuo Zhang, Chengxiang Tan, Haihang Wang, Xueyan Zhao

Entity alignment(EA) is a crucial task for integrating cross-lingual and cross-domain knowledge graphs(KGs), which aims to discover entities referring to the same real-world object from different KGs. Most existing methods generate aligning entity representation by mining the relevance of triple elements via embedding-based methods, paying little attention t

Francesco Picciariello, Francesco Vedovato, Davide Orsucci, Pablo Nahuel Dominguez

Global Navigation Satellite Systems (GNSSs), such as GPS and Galileo, provide precise time and space coordinates globally and constitute part of the critical infrastructure of modern society. To reliably operate GNSS, a highly accurate and stable system time is required, such as the one provided by several independent clocks hosted in Precise Timing Faciliti

Aly M. Kassem

Large Language models (LLMs) are trained on large amounts of data, which can include sensitive information that may compromise personal privacy. LLMs showed to memorize parts of the training data and emit those data verbatim when an adversary prompts appropriately. Previous research has primarily focused on data preprocessing and differential privacy techniq

Maurizio M. Busso, Sara Palmerini

We outline a partial historical summary of the steps through which the nucleosynthesis phenomena induced by {\it slow} neutron captures (the {\it s-process}) were clarified, a scientific achievement in which Franz Käppeler played a major role. We start by recalling the early phenomenological approach, which yielded a basic understanding of the subject even b

Kazuki Irie, Jürgen Schmidhuber

Few-shot learning with sequence-processing neural networks (NNs) has recently attracted a new wave of attention in the context of large language models. In the standard N-way K-shot learning setting, an NN is explicitly optimised to learn to classify unlabelled inputs by observing a sequence of NK labelled examples. This pressures the NN to learn a learning

Ahmet R. Emirdagi, M. Serkan Kopuzlu, M. Okan Araz, Murat Kuscu

A key challenge in Molecular Communications (MC) is low data transmission rates, which can be addressed by channel multiplexing techniques. One way to achieve channel multiplexing in MC is to leverage the diversity of different molecule types with respect to their receptor binding characteristics, such as affinity and kinetic binding/unbinding rates. In this

Delin Hu, Zhou Chen, Paul Baisamy, Zhe Liu

Tactile sensing in soft robots remains particularly challenging because of the coupling between contact and deformation information which the sensor is subject to during actuation and interaction with the environment. This often results in severe interference and makes disentangling tactile sensing and geometric deformation difficult. To address this problem

M. H. Shachar, J. E. Garay

Scattering problems are important in describing light propagation in wide ranging media such as the atmosphere, colloidal solutions, metamaterials, glass ceramic composites, transparent polycrystalline ceramics, and surfaces. The Rayleigh Gans Debye (RGD) approximation has enjoyed great success in describing a wide range of scattering phenomena. We derive a

Alejandro Ortega

In this work we analyze the behavior of truncated functionals as \begin{equation*} \int_{\mathbb{R}^N}\int_{B(x,δ)} G\left(\frac{|u(x)-u(y)|}{|x-y|^{s}}\right)\frac{dydx}{|x-y|^N}\qquad\text{for }δ\to0^+. \end{equation*} Here the function $G$ is an Orlicz function that in addition is assumed to be a regularly varying function at $0$. A prototype of such func

Matthias Krinninger, Nicolas Bock, Sebastian Kaiser, Johanna Plansky

Carbon nitrides have recently come into focus for photo- and thermal catalysis, both as support materials for metal nanoparticles as well as photocatalysts themselves. While many approaches for the synthesis of three-dimensional carbon nitride materials are available, only top-down approaches by exfoliation of powders lead to thin film flakes of this inheren

Daniel J. Hicks

tmfast is an R package for fitting topic models using a fast algorithm based on partial PCA and the varimax rotation. After providing mathematical background to the method, we present two examples, using a simulated corpus and aggregated works of a selection of authors from the long nineteenth century, and compare the quality of the fitted models to a standa

Maria Axenovich, Domagoj Bradač, Lior Gishboliner, Dhruv Mubayi

The well-known Erdős-Hajnal conjecture states that for any graph $F$, there exists $ε>0$ such that every $n$-vertex graph $G$ that contains no induced copy of $F$ has a homogeneous set of size at least $n^ε$. We consider a variant of the Erdős-Hajnal problem for hypergraphs where we forbid a family of hypergraphs described by their orders and sizes. For grap

Jianquan Li, Xidong Wang, Xiangbo Wu, Zhiyi Zhang

In this paper, we release a largest ever medical Question Answering (QA) dataset with 26 million QA pairs. We benchmark many existing approaches in our dataset in terms of both retrieval and generation. Experimental results show that the existing models perform far lower than expected and the released dataset is still challenging in the pre-trained language

Guangshen Ma, Ravi Prakash, Brian Mann, Weston Ross

In robotic laser surgery, shape prediction of an one-shot ablation cavity is an important problem for minimizing errant overcutting of healthy tissue during the course of pathological tissue resection and precise tumor removal. Since it is difficult to physically model the laser-tissue interaction due to the variety of optical tissue properties, complicated

Alaa Saade, Steven Kapturowski, Daniele Calandriello, Charles Blundell

We introduce Robust Exploration via Clustering-based Online Density Estimation (RECODE), a non-parametric method for novelty-based exploration that estimates visitation counts for clusters of states based on their similarity in a chosen embedding space. By adapting classical clustering to the nonstationary setting of Deep RL, RECODE can efficiently track sta

Kyung Ho Park, Hyunhee Chung

Recent progress of deep learning has empowered various intelligent transportation applications, especially in car-sharing platforms. While the traditional operations of the car-sharing service highly relied on human engagements in fleet management, modern car-sharing platforms let users upload car images before and after their use to inspect the cars without

Christos P. Lamprakos, Sotirios Xydis, Francky Catthoor, Dimitrios Soudris

Recent work has shown that viewing allocators as black-box 2DBP solvers bears meaning. For instance, there exists a 2DBP-based fragmentation metric which often correlates monotonically with maximum resident set size (RSS). Given the field's indeterminacy with respect to fragmentation definitions, as well as the immense value of physical memory savings, w

Eleonora Zedda, Marco Manca, Fabio Paterno, Carmen Santoro

The monotonous nature of repetitive cognitive training may cause losing interest in it and dropping out by older adults. This study introduces an adaptive technique that enables a Socially Assistive Robot (SAR) to select the most appropriate actions to maintain the engagement level of older adults while they play the serious game in cognitive training. The g

J. Yu. Panteleeva, E. Epelbaum, J. Gegelia, U. -G. Meißner

The matrix elements of the electromagnetic current and the energy-momentum tensor for sharply localized states of spin-1 systems are considered. Their interpretation as local spatial densities of various characteristics of the considered system is discussed.

yaacov Kopeliovich

In this paper we formulate and solve an optimal problem for Stochastic process with a regime absorbing state. The solution for this problem is obtained through a system of partial differential equations. The method is applied to obtain an explicit solution for the Merton portfolio problem when an asset has a default probability in case of a log utility.

Zijian Zhao, Shan Deng, Swetaki Chatterjee, Zhouhang Jiang

Single-port ferroelectric FET (FeFET) that performs write and read operations on the same electrical gate prevents its wide application in tunable analog electronics and suffers from read disturb, especially to the high-threshold voltage (VTH) state as the retention energy barrier is reduced by the applied read bias. To address both issues, we propose to ado

Etienne Labbé, Julien Pinquier, Thomas Pellegrini

In this work, we propose to study the performance of a model trained with a sentence embedding regression loss component for the Automated Audio Captioning task. This task aims to build systems that can describe audio content with a single sentence written in natural language. Most systems are trained with the standard Cross-Entropy loss, which does not take

Ailin Deng, Miao Xiong, Bryan Hooi

Reliable application of machine learning is of primary importance to the practical deployment of deep learning methods. A fundamental challenge is that models are often unreliable due to overconfidence. In this paper, we estimate a model's reliability by measuring \emph{the agreement between its latent space, and the latent space of a foundation model}.

Naman Jain, M Girish Chandra

Portfolio optimization is one of the most studied problems for demonstrating the near-term applications of quantum computing. However, large-scale problems cannot be solved on today's quantum hardware. In this work, we extend upon a study to use the best of both quantum annealing and gate-based quantum computing systems to enable solving large-scale opti

Tatiana Daddario, Richard P. McLean, Andrew Postlewaite

In this paper, we take a mechanism design approach to optimal assignment problems with asymmetrically informed buyers. In addition, the surplus generated by an assignment of a buyer to a seller may be adversely affected by externalities generated by other assignments. The problem is complicated by several factors. Buyers know their own valuations and externa

O-joung Kwon, Xiaopan Lian

We introduce the vertex-arboricity of group-labelled graphs. For an abelian group $Γ$, a $Γ$-labelled graph is a graph whose edges are labelled by elements of $Γ$. For an abelian group $Γ$ and $A\subseteq Γ$, the $(Γ, A)$-vertex-arboricity of a $Γ$-labelled graph is the minimum integer $k$ such that its vertex set can be partitioned into $k$ parts where each

Rajni Dabas, Neelima Gupta, Tanmay Inamdar

Clustering problems such as $k$-Median, and $k$-Means, are motivated from applications such as location planning, unsupervised learning among others. In such applications, it is important to find the clustering of points that is not ``skewed'' in terms of the number of points, i.e., no cluster should contain too many points. This is modeled by capaci

Jittat Fakcharoenphol, Chayutpong Prompak

We naturally generalize the on-line graph prediction problem to a version of stochastic contextual bandit problems where contexts are vertices in a graph and the structure of the graph provides information on the similarity of contexts. More specifically, we are given a graph $G=(V,E)$, whose vertex set $V$ represents contexts with {\em unknown} vertex label

N. S. Kavya, V. Venkatesha, G. Mustafa, P. K. Sahoo

In this study, we explore the new wormhole solutions in the framework of new modified $f(R,L_m)$ gravity. To obtain a characteristic wormhole solution, we use anisotropic matter distribution and a specific form of energy density. As second adopt the isotropic case with a linear EoS relation as a general technique for the system and discuss several physical a

Sebastian Noe, Dominik Husmann, Nils Müller, Jacques Morel

We present a long-range fiber-optic environmental deformation sensor based on active phase noise cancellation (PNC) in metrological frequency dissemination. PNC sensing exploits recordings of a compensation frequency that is commonly discarded. Without the need for dedicated measurement devices, it operates synchronously with metrological services, suggestin

Nattawut Phetmak, Jittat Fakcharoenphol

We consider a problem in computational origami. Given a piece of paper as a convex polygon $P$ and a point $f$ located within, fold every point on a boundary of $P$ to $f$ and compute a region that is safe from folding, i.e., the region with no creases. This problem is an extended version of a problem by Akitaya, Ballinger, Demaine, Hull, and Schmidt~[CCCG&#

Yaacov Kopeliovich

We express the branch points cross ratio of Hyper-elliptic Mumford curves as quotients of p adic theta functions evaluated at the p adic period matrix

Nicolas Charpenay, Maël le Treust, Aline Roumy

In the zero-error Slepian-Wolf source coding problem, the optimal rate is given by the complementary graph entropy $\overline{H}$ of the characteristic graph. It has no single-letter formula, except for perfect graphs, for the pentagon graph with uniform distribution $G_5$, and for their disjoint union. We consider two particular instances, where the charact