October 2022 arXiv papers — page 58

Elmira Shahraki, Mahtab Mirmohseni, Hengameh Keshavarz

The performance of physical layer secrecy approach in non-orthogonal multiple access (NOMA)-enabled heterogeneous networks (HetNets) is analyzed in this paper. A $K$-tier multi-cell HetNet is considered, comprising NOMA adopted in all tiers. The base stations, legitimate users (in a two-user NOMA setup), and passive eavesdroppers, all with single-antenna, ar

Fergus Imrie, Bogdan Cebere, Eoin F. McKinney, Mihaela van der Schaar

Diagnostic and prognostic models are increasingly important in medicine and inform many clinical decisions. Recently, machine learning approaches have shown improvement over conventional modeling techniques by better capturing complex interactions between patient covariates in a data-driven manner. However, the use of machine learning introduces a number of

Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo, Fosca Giannotti

Graph Neural Networks (GNNs) perform well in community detection and molecule classification. Counterfactual Explanations (CE) provide counter-examples to overcome the transparency limitations of black-box models. Due to the growing attention in graph learning, we focus on the concepts of CE for GNNs. We analysed the SoA to provide a taxonomy, a uniform nota

Giuseppe Belgioioso, Dominic Liao-McPherson, Mathias Hudoba de Badyn, Saverio Bolognani

This paper proposes a unifying design framework for dynamic feedback controllers that track solution trajectories of time-varying generalized equations, such as local minimizers of nonlinear programs or competitive equilibria (e.g., Nash) of non-cooperative games. Inspired by the feedback optimization paradigm, the core idea of the proposed approach is to re

Dhiman Bhowmick, Hao Sun, Bo Yang, Pinaki Sengupta

Although theoretical modelling and inelastic neutron scattering measurements have indicated the presence of topological magnon bands in multiple quantum magnets, experiments remain unable to detect signal of magnon thermal Hall effect in the quantum magnets, which is a consequence of magnons condensation at the bottom of the bands following Bose Einstein sta

Yunus Inan, Reka Inovan, Emre Telatar

We study a discrete-time model where each packet has a cost of not being sent -- this cost might depend on the packet content. We study the tradeoff between the age and the cost where the sender is confined to packet-based strategies. The optimal tradeoff is found by an appropriate formulation of the problem as a Markov Decision Process (MDP). We show that t

Qiaofeng Liu, Ian Low, Thomas Mehen

We study low-energy scattering of spin-1/2 baryons from the perspective of quantum information science, focusing on the correlation between entanglement minimization and the appearance of accidental symmetries. The baryon transforms as an octet under the SU(3) flavor symmetry and its interactions below the pion threshold are described by contact operators in

Leonard Adolphs, Michelle Chen Huebscher, Christian Buck, Sertan Girgin

Neural retrieval models have superseded classic bag-of-words methods such as BM25 as the retrieval framework of choice. However, neural systems lack the interpretability of bag-of-words models; it is not trivial to connect a query change to a change in the latent space that ultimately determines the retrieval results. To shed light on this embedding space, w

Mohammed Alaqdhi, Abdulrahman Alabduljabbar, Kyle Thomas, Saeed Salem

This paper investigates the potential causes of the vulnerabilities of free content websites to address risks and maliciousness. Assembling more than 1,500 websites with free and premium content, we identify their content management system (CMS) and malicious attributes. We use frequency analysis at both the aggregate and per category of content (books, game

Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland

We prove a new generalization bound that shows for any class of linear predictors in Gaussian space, the Rademacher complexity of the class and the training error under any continuous loss $\ell$ can control the test error under all Moreau envelopes of the loss $\ell$. We use our finite-sample bound to directly recover the "optimistic rate" of Zhou et al. (2

Niall Rodgers, Peter Tino, Samuel Johnson

Knowing which nodes are influential in a complex network and whether the network can be influenced by a small subset of nodes is a key part of network analysis. However, many traditional measures of importance focus on node level information without considering the global network architecture. We use the method of Trophic Analysis to study directed networks

Gyunam Park, Wil. M. P. van der Aalst

Constraint monitoring aims to monitor the violation of constraints in business processes, e.g., an invoice should be cleared within 48 hours after the corresponding goods receipt, by analyzing event data. Existing techniques for constraint monitoring assume that a single case notion exists in a business process, e.g., a patient in a healthcare process, and e

Mitja Nikolaus, Emmanuelle Salin, Stephane Ayache, Abdellah Fourtassi

Recent advances in vision-and-language modeling have seen the development of Transformer architectures that achieve remarkable performance on multimodal reasoning tasks. Yet, the exact capabilities of these black-box models are still poorly understood. While much of previous work has focused on studying their ability to learn meaning at the word-level, their

Maximilian Wegge, Enrica Troiano, Laura Oberländer, Roman Klinger

Emotion classification in NLP assigns emotions to texts, such as sentences or paragraphs. With texts like "I felt guilty when he cried", focusing on the sentence level disregards the standpoint of each participant in the situation: the writer ("I") and the other entity ("he") could in fact have different affective states. The emotions of different entities h

Simon Fowler, Vashti Galpin, James Cheney

Modern applications often manage time-varying data. Despite decades of research on temporal databases, which culminated in the addition of temporal data operations into the SQL:2011 standard, temporal data query and manipulation operations are unavailable in most mainstream database management systems, leaving developers with the unenviable task of implement

Viviana Villafañe, Malte Kremser, Ruven Hübner, Marko M. Petrić

Optoelectronic properties of van der Waals homostructures can be selectively engineered by the relative twist angle between layers. Here, we study the twist-dependent moire coupling in MoSe2 homobilayers. For small angles, we find a pronounced redshift of the K-K and {\Gamma}-K excitons accompanied by a transition from K-K to {\Gamma}-K emission. Both effect

I. E. Alexeev, S. V. Bakhlanov, E. A. Chmel, A. V. Derbin

We present a description of the originally developed $\beta$-spectrometer consisting of two Si(Li)-detectors with sensitive area thickness above 8~mm and $4\pi$-geometry. The full absorption spectrometer allows for direct measurements of $\beta$-spectra, disregarding the corrections to the response function induced by the electron backscattering from the cry

Miłosz Rybak, Tomasz Woźniak, Magdalena Birowska, Filip Dybała

Optical measurements under externally applied stresses allow us to study the materials' electronic structure by comparing the pressure evolution of optical peaks obtained from experiments and theoretical calculations. We examine the stress-induced changes in electronic structure for the thermodynamically stable 1T polytype of selected MX2 compounds (M=Hf, Zr

Damir Becirevic, Florentin Jaffredo

Motivated by the first observation of $\Lambda_b\to\Lambda_c~\tau\bar{\nu}$ by LHCb, we discuss various observables that can be derived from angular distribution of this decay which, if measured, could be essential for explanation of the $b\to c\tau\bar{\nu}$ anomalies. Furthermore, we show that the measurement of $R_{\Lambda_c}=\mathcal{B}(\Lambda_b\to\Lamb

Shadan Ghassemi Tabrizi, Carlos A. Jiménez-Hoyos

Recent work on approximating ground states of Heisenberg spin clusters by projected Hartree-Fock theory (PHF) is extended to a cluster-based ansatz (cPHF). Whereas PHF variationally optimizes a site-spin product state for the restoration of spin- and point-group symmetry, cPHF groups sites into discrete clusters and uses a cluster-product state as the broken

Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus

Dataset distillation compresses large datasets into smaller synthetic coresets which retain performance with the aim of reducing the storage and computational burden of processing the entire dataset. Today's best-performing algorithm, \textit{Kernel Inducing Points} (KIP), which makes use of the correspondence between infinite-width neural networks and kerne

Alfredo González Lezcano, Maximilian Jerdee, Leopoldo A. Pando Zayas

We consider the superconformal index of three-dimensional ${\cal N}=2$ supersymmetric field theories computed via localization on $S^1\times S^2$. We systematically develop an expansion where the ratio of the radius of $S^1$ to the radius of $S^2$ is taken very small -- a Cardy-like expansion. We emphasize the sub-leading structures in this Cardy-like expans

David Reeb, Kanil Patel, Karim Barsim, Martin Schiegg

Assessing the validity of a real-world system with respect to given quality criteria is a common yet costly task in industrial applications due to the vast number of required real-world tests. Validating such systems by means of simulation offers a promising and less expensive alternative, but requires an assessment of the simulation accuracy and therefore e

Giorgio Cipolloni, László Endős, Dominik Schröder

We prove that the mesoscopic linear statistics $\sum_i f(n^a(\sigma_i-z_0))$ of the eigenvalues $\{\sigma_i\}_i$ of large $n\times n$ non-Hermitian random matrices with complex centred i.i.d. entries are asymptotically Gaussian for any $H^{2}_0$-functions $f$ around any point $z_0$ in the bulk of the spectrum on any mesoscopic scale $0<a<1/2$. This extends o

Jeremy Guillaume, Maxime Pelcat, Amor Nafkha, Rubén Salvador

Side-Channel Attacks (SCAs) exploit data correla-tion in signals leaked from devices to jeopardize confidentiality. Locating and synchronizing segments of interest in traces from Cryptographic Processes (CPs) is a key step of the attack. The most common method consists in generating a trigger signal to indicate to the attacker the start of a CP. This paper p

Artemiy S. Sherbakov, Oleg I. Utesov

Motivated by recent experimental data on dichloro-tetrakis thiourea-nickel (DTN) [T.A. Soldatov $\textit{et al}$, Phys. Rev. B ${\bf 101}$, 104410 (2020)], a model of antiferromagnet on a tetragonal lattice with single-ion easy-plane anisotropy in the tilted external magnetic field is considered. Using the smallness of the in-plane field component, we analyt

Gergely Neu, Nneka Okolo

We propose a new stochastic primal-dual optimization algorithm for planning in a large discounted Markov decision process with a generative model and linear function approximation. Assuming that the feature map approximately satisfies standard realizability and Bellman-closedness conditions and also that the feature vectors of all state-action pairs are repr

Hannah Elfner, Berndt Müller

This article summarizes our present knowledge about nuclear matter at the highest energy densities and its formation in relativistic heavy ion collisions. We review what is known about the structure and properties of the quark-gluon plasma and survey the observables that are used to glean information about it from experimental data.

Haoyan Guan, Michael Spratling

Few-shot segmentation (FSS) aims to segment unseen classes using a few annotated samples. Typically, a prototype representing the foreground class is extracted from annotated support image(s) and is matched to features representing each pixel in the query image. However, models learnt in this way are insufficiently discriminatory, and often produce false pos

Edoardo Manino, Iury Bessa, Lucas Cordeiro

Neural networks are a powerful class of non-linear functions. However, their black-box nature makes it difficult to explain their behaviour and certify their safety. Abstraction techniques address this challenge by transforming the neural network into a simpler, over-approximated function. Unfortunately, existing abstraction techniques are slack, which limit

Arielle K. Carr, Eric de Sturler, Mark Embree

In many applications, linear systems arise where the coefficient matrix takes the special form ${\bf I} + {\bf K} + {\bf E}$, where ${\bf I}$ is the identity matrix of dimension $n$, ${\rm rank}({\bf K}) = p \ll n$, and $\|{\bf E}\| \leq \epsilon < 1$. GMRES convergence rates for linear systems with coefficient matrices of the forms ${\bf I} + {\bf K}$ and $

John Fabricius, Markus Gahn

We study a Stokes system posed in a thin perforated layer with a Navier-slip condition on the internal oscillating boundary from two viewpoints: 1) dimensional reduction of the layer and 2) homogenization of the perforated structure. Assuming the perforations are periodic, both aspects can be described through a small parameter $\epsilon>0,$ which is related

Sofie Goethals, Kenneth Sörensen, David Martens

Black-box machine learning models are being used in more and more high-stakes domains, which creates a growing need for Explainable AI (XAI). Unfortunately, the use of XAI in machine learning introduces new privacy risks, which currently remain largely unnoticed. We introduce the explanation linkage attack, which can occur when deploying instance-based strat

Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian

Derivative-free prompt learning has emerged as a lightweight alternative to prompt tuning, which only requires model inference to optimize the prompts. However, existing work did not take full advantage of the over-parameterized characteristics of large pre-trained language models (PLMs). In this paper, we propose Clip-Tuning, a simple yet effective method t

Sujun Yun, Werner Dobrautz, Hongjun Luo, Vamshi Katukuri

Two-dimensional Hubbard lattices with two or three holes are investigated as a function of $U$ in the large-$U$ limit. In the so-called Nagaoka limit (one-hole system at infinite $U$), it is known that the Hubbard model exhibits a ferromagnetic ground-state. Here, by means of exact FCIQMC simulations applied to periodic lattices up to 24 sites, we compute sp

Corinna Coupette, Sebastian Dalleiger, Bastian Rieck

Bridging geometry and topology, curvature is a powerful and expressive invariant. While the utility of curvature has been theoretically and empirically confirmed in the context of manifolds and graphs, its generalization to the emerging domain of hypergraphs has remained largely unexplored. On graphs, the Ollivier-Ricci curvature measures differences between

Aleksander Doan, Semon Rezchikov

We outline a proposal for a $2$-category $\mathrm{Fuet}_M$ associated to a hyperk\"ahler manifold $M$, which categorifies the subcategory of the Fukaya category of $M$ generated by complex Lagrangians. Morphisms in this $2$-category are formally the Fukaya--Seidel categories of holomorphic symplectic action functionals. As such, $\mathrm{Fuet}_M$ is based on

É. Delaygue

$E$-functions were introduced by Siegel in 1929 to generalize Diophantine properties of the exponential function. After developments of Siegel's methods by Shidlovskii, Nesterenko and Andr\'e, Beukers proved in 2006 an optimal result on the algebraic independence of the values of $E$-functions which generalizes the Lindemann-Weierstrass theorem. Since then,

Han Wang, Zhi-Wei Sun

Let $A_1,\ldots,A_n$ be finite subsets of an additive abelian group $G$ with $|A_1|=\cdots=|A_n|\ge2$. Concerning the two new kinds of restricted sumsets $$L(A_1,\ldots,A_n)=\{a_1+\cdots+a_n:\ a_1\in A_1,\ldots,a_n\in A_n,\ \text{and}\ a_i\not=a_{i+1} \ \text{for}\ 1\le i<n\}$$ and $$C(A_1,\ldots,A_n)=\{a_1+\cdots+a_n:\ a_i\in A_i\ (1\le i\le n),\ \text{and}

Anthonny F. Canazas Garay, Diego H. Correa, Alberto Faraggi, Guillermo A. Silva

We consider two instances of boundary conditions for massless scalars on $AdS_2$ that interpolate between the Dirichlet and Neumann cases while preserving scale invariance. Assessing invariance under the full $SL(2;\mathds{R})$ conformal group is not immediate given their non-local nature. To further clarify this issue, we compute holographically 2- and 4-po

Stefan Feintuch, Haim H. Permuter, Igal Bilik, Joseph Tabrikian

This work addresses the problem of range-Doppler multiple target detection in a radar system in the presence of slow-time correlated and heavy-tailed distributed clutter. Conventional target detection algorithms assume Gaussian-distributed clutter, but their performance is significantly degraded in the presence of correlated heavy-tailed distributed clutter.

Emanuel A. Fronhofer, Dov Corenblit, Jhelam N. Deshpande, Lynn Govaert

Eco-evolutionary dynamics, or eco-evolution for short, are thought to involve rapid demography (ecology) and equally rapid phenotypic changes (evolution) leading to novel, emergent system behaviours. This focus on contemporary dynamics is likely due to accumulating evidence for rapid evolution, from classical laboratory microcosms and natural populations, in

Christo Kurisummoottil Thomas, Walid Saad

Semantic communication (SC) aims to communicate reliably with minimal data transfer while simultaneously providing seamless connectivity to heterogeneous services and users. In this paper, a novel emergent SC (ESC) system framework is proposed and is composed of a signaling game for emergent language design and a neuro-symbolic (NeSy) artificial intelligence

Ranchhaigiri Brahma, A. K. Sen

In this paper, we solved the Einstein's field equation and obtained a line element for static, ellipsoidal objects characterized by the linear eccentricity ($\eta$) instead of quadrupole parameter ($q$). This line element recovers the Schwarzschild line element when $\eta$ is zero. In addition to that it also reduces to the Schwarzschild line element, if we

Alexander Arbieto, Miguel Pineda, Elias Rego, Kendry J. Vivas

In this paper, we make several contributions to the theory of asymptotically sectional-hyperbolic (ASH) flows. First, we prove that every star ASH attractor for a $C^2$ vector field is, in fact, sectional-hyperbolic (SH). Second, we establish that all ASH attractors exhibit the property of entropy flexibility. Additionally, we show that any ASH attractor for

Anton Glushchenko, Konstantin Lastochkin

A novel method of exponentially stable adaptive control to compensate for matched parametric uncertainty under a mild condition of semi-persistent excitation (s-PE) of a regressor with piecewise-constant rank and nullspace is proposed. It is based on the generalized dynamic regressor extension and mixing procedure developed earlier by the authors, does not r

Guilherme D. da Fonseca, Yan Gerard, Bastien Rivier

A set of segments in the plane may form a Euclidean TSP tour or a matching, among others. Optimal TSP tours as well as minimum weight perfect matchings have no crossing segments, but several heuristics and approximation algorithms may produce solutions with crossings. To improve such solutions, we can successively apply a flip operation that replaces a pair

Brendan O'Donoghue

In this short note we derive a relationship between the Bregman divergence from the current policy to the optimal policy and the suboptimality of the current value function in a regularized Markov decision process. This result has implications for multi-task reinforcement learning, offline reinforcement learning, and regret analysis under function approximat

João Carmona, Tamás Karácsony, João Paulo Silva Cunha

Human motion analysis has seen drastic improvements recently, however, due to the lack of representative datasets, for clinical in-bed scenarios it is still lagging behind. To address this issue, we implemented BlanketGen, a pipeline that augments videos with synthetic blanket occlusions. With this pipeline, we generated an augmented version of the pose esti

Ryuichiro Higashinaka, Takashi Minato, Hiromitsu Nishizaki, Takayuki Nagai

The proceedings contain papers on the dialogue systems developed by the twelve teams participating in DRC2022, as well as an overview paper summarizing the competition.

Bruno Balthazar, Jinwei Chu, David Kutasov

We discuss the worldsheet sigma-model whose target space is the $d+1$ dimensional Euclidean Schwarzschild black hole. We argue that in the limit where the Hawking temperature of the black hole, $T$, approaches the Hagedorn temperature, $T_H$, it can be described in terms of a generalized version of the Horowitz-Polchinski effective theory. For $d\geq6$, wher

Zhuo Ye, Feng Zhang, Yong-Xin Yao, Cai-Zhuang Wang

Ground-state properties, such as energies and double occupancies, of a one-dimensional two-band Hubbard model are calculated using a first principles Gutzwiller conjugate gradient minimization theory. The favorable agreement with the results from the density matrix renormalization group theory demonstrates the accuracy of our method. A rotationally invariant

Tammi Chowdhury, Seyda Ipek

We calculate the Big Bang Nucleosynthesis abundances for helium-4 and deuterium for a range of neutron lifetimes, $\tau_n = 840 - 1050$ s, using the state-of-the-art Python package \textsc{PRyMordial}. We show the results for two different nuclear reaction rates, calculated by NACRE II [1] and the PRIMAT [2] collaborations.

Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus

Two key challenges facing modern deep learning are mitigating deep networks' vulnerability to adversarial attacks and understanding deep learning's generalization capabilities. Towards the first issue, many defense strategies have been developed, with the most common being Adversarial Training (AT). Towards the second challenge, one of the dominant theories

Zeyu Tang, Nan Yang, Simon Walsh, Guang Yang

Discontinuity in the delineation of peripheral bronchioles hinders the potential clinical application of automated airway segmentation models. Moreover, the deployment of such models is limited by the data heterogeneity across different centres, and pathological abnormalities also make achieving accurate robust segmentation in distal small airways difficult.

Dinesh S Thakur

We present an heuristic argument for the prediction of expected Mordell-Weil rank of elliptic curves over number fields, using Birch and Swinnerton-Dyer's original conjecture and Sato-Tate conjectures. We do calculations in some cases and raise questions about their relations, if any, with the predictions of various average rank models that have been conside

C. Maria Keet

Computing and Internet access are substantially growing markets in Southern Africa, which brings with it increasing demands for local content and tools in indigenous African languages. Since most of those languages are low-resourced, efforts have gone into the notion of bootstrapping tools for one African language from another. This paper provides an overvie

Fabian Neuhaus, Janna Hastings

Ontology development methodologies emphasise knowledge gathering from domain experts and documentary resources, and knowledge representation using an ontology language such as OWL or FOL. However, working ontologists are often surprised by how challenging and slow it can be to develop ontologies. Here, with a particular emphasis on the sorts of ontologies th

Georgy Kitavtsev, Roman M. Taranets

We analyze long-time behavior of solutions to a class of problems related to very fast and singular diffusion porous medium equations having nonhomogeneous in space and time source terms with zero mean. In dimensions two and three, we determine critical values of porous medium exponent for the asymptotic $H^1$-convergence of the solutions to a unique nonhomo

Jason P. Bell, Léon Burkhardt, Nicholas Priebe

We consider Ore extensions of the form $T:=R[x;\sigma,\delta]$ with $R$ a commutative integral domain that is finitely generated over a field $k$. We show that if $T$ has Gelfand-Kirillov dimension less than four then a prime ideal $P\in {\rm Spec}(T)$ is primitive if and only if $\{P\}$ is locally closed in ${\rm Spec}(T)$, if and only if the Goldie ring of

Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf

We have recently witnessed a number of impressive results on hard mathematical reasoning problems with language models. At the same time, the robustness of these models has also been called into question; recent works have shown that models can rely on shallow patterns in the problem description when generating a solution. Building on the idea of behavioral

Laura Aina, Nikos Voskarides, Roi Blanco

Pre-trained language models (LMs) obtain state-of-the-art performance when adapted to text classification tasks. However, when using such models in real-world applications, efficiency considerations are paramount. In this paper, we study how different training procedures that adapt LMs to text classification perform, as we vary model and train set size. More

Fernando Lucatelli Nunes, Rui Prezado, Lurdes Sousa

For any suitable base category $\mathcal{V} $, we find that $\mathcal{V} $-fully faithful lax epimorphisms in $\mathcal{V} $-$\mathsf{Cat} $ are precisely those $\mathcal{V}$-functors $F \colon \mathcal{A} \to \mathcal{B}$ whose induced $\mathcal{V} $-functors $\mathsf{Cauchy} F \colon \mathsf{Cauchy} \mathcal{A} \to \mathsf{Cauchy} \mathcal{B} $ between the

Jun Wang, Weixun Li, Changyu Hou, Xin Tang

Contrastive learning has emerged as a powerful tool for graph representation learning. However, most contrastive learning methods learn features of graphs with fixed coarse-grained scale, which might underestimate either local or global information. To capture more hierarchical and richer representation, we propose a novel Hierarchical Contrastive Learning (

John B. Biersteker, Benjamin P. Weiss, Corey J. Cochrane, Camilla D. K. Harris

Some icy moons and small bodies in the solar system are believed to host subsurface liquid water oceans. The interaction of these saline, electrically conductive oceans with time-varying external magnetic fields generates induced magnetic fields. Magnetometry observations of these induced fields in turn enable the detection and characterization of these ocea

Tom M. Ragonneau

This thesis studies derivative-free optimization (DFO), particularly model-based methods and software. These methods are motivated by optimization problems for which it is impossible or prohibitively expensive to access the first-order information of the objective function and possibly the constraint functions. In particular, this thesis presents PDFO, a pac

Francesco Rinaldo Talenti, Stefan Wabnitz, Inès Ghorbel, Sylvain Combrié

We introduce a numerical procedure which permits to drastically accelerate the design of multimode photonic crystal resonators. Specifically, we demonstrate that the optical response of an important class of such nanoscale structures is reproduced accurately by a simple, one-dimensional model, within the entire spectral range of interest. This model can desc

J. Lucassen, M. J. G. Peeters, C. F. Schippers, R. A. Duine

Spin waves are proposed as information carriers for next-generation computing devices because of their low power consumption. Moreover, their wave-like nature allows for novel computing paradigms. Conventional methods to detect spin waves are based either on electrical induction, limiting the downscaling and efficiency complicating eventual implementation, o

Oswin Aichholzer, Thomas Hackl, Maarten Löffler, Alexander Pilz

Given two distinct point sets $P$ and $Q$ in the plane, we say that $Q$ \emph{blocks} $P$ if no two points of $P$ are adjacent in any Delaunay triangulation of $P\cup Q$. Aichholzer et al. (2013) showed that any set $P$ of $n$ points in general position can be blocked by $\frac{3}{2}n$ points and that every set $P$ of $n$ points in convex position can be blo

Ignacio Borsa, Daniel de Florian, Iván Pedron

We present the second order contributions to the coefficient functions for the parity violating polarized structure functions $g_L$ and $g_4$, thus completing the $\mathcal{O}(\alpha_S^2)$ knowledge on DIS structure functions. We obtain the missing $\mathcal{O}(\alpha_S^2)$ pieces from the known parity conserving unpolarized coefficient functions. We also pr

Xiaozong Wang

Let $X$ be a smooth projective variety defined over a finite field. We show that any algebraic $1$-cycle on $X$ is rationally equivalent to a smooth $1$-cycle, which is a $\mathbb{Z}$-linear combination of smooth curves on $X$. We also prove a generalized version of Poonen's Bertini theorem over finite fields. Given a very ample line bundle $\mathcal{L}$ on

David Richter

This article studies a large, general class of orthogonal polytopes which we may call "generic orthotopes". These objects emerged from a desire to represent a Coxeter complex by an orthogonal polytope that is particularly nice with respect to traditional topological, structural, or combinatorial considerations. Generic orthotopes have a pleasant "homogeneity

Aleksandra Sierant, Marek Kopciuch, Szymon Pustelny

In this paper, we investigate the coherent control over a complex multi-level atomic system using the stimulated Raman adiabatic passage (STIRAP). Based on the example of rubidium-87 atoms, excited with circularly-polarized light at the D1 line, we demonstrate the ability to decompose the system into three- and four-level subsystems independently interacting

Guillaume Noetinger, Samuel Métais, Geoffroy Lerosey, Mathias Fink

A novel approach to improving the performances of confocal scanning imaging is proposed. We experimentally demonstrate its feasibility using acoustic waves. It relies on a new way to encode spatial information using the temporal dimension. By moving an emitter, used to insonify an object, along a circular path, we create a temporally modulated wavefield. Due

Shadan Ghassemi Tabrizi, R. Rodríguez-Guzmán, Carlos A. Jiménez-Hoyos

The variational inclusion of spin-orbit coupling in self-consistent field (SCF) calculations requires a generalised two-component framework, which permits the single-determinant wave function to completely break spin symmetry. The individual components of the molecular g-tensor are commonly obtained from separate SCF solutions that align the magnetic moment

Sudeep Pasricha

The dawn of the digital medicine era, ushered in by increasingly powerful embedded systems and Internet of Things (IoT) computing devices, is creating new therapies and biomedical solutions that promise to positively transform our quality of life. However, the digital medicine revolution also creates unforeseen and complex ethical, regulatory, and societal i

Rahul Goswami, Arabin Kumar Dey

Recently Goswami et al. \cite{goswami2022concordance} introduced two novel implementations of combined regression strategy to find the conditional survival function. The paper uses regression-based weak learners and provides an alternative version of the combined regression strategy (COBRA) ensemble using the Integrated Brier Score to predict conditional sur

Marc Habermann, Lingjie Liu, Weipeng Xu, Gerard Pons-Moll

Photo-real digital human avatars are of enormous importance in graphics, as they enable immersive communication over the globe, improve gaming and entertainment experiences, and can be particularly beneficial for AR and VR settings. However, current avatar generation approaches either fall short in high-fidelity novel view synthesis, generalization to novel

Gaoshuai Wang, Fabrice Lauri, Pu Wang, Hongyuan Luo

Feature selection is used to eliminate redundant features and keep relevant features, it can enhance machine learning algorithm's performance and accelerate computing speed. In various methods, mutual information has attracted increasingly more attention as it's an effective criterion to measure variable correlation. However, current works mainly focus on ma

Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun

Modern neural networks are often quite wide, causing large memory and computation costs. It is thus of great interest to train a narrower network. However, training narrow neural nets remains a challenging task. We ask two theoretical questions: Can narrow networks have as strong expressivity as wide ones? If so, does the loss function exhibit a benign optim

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The ratio of branching fractions of $B_c^+ \to B_s^0 \pi^+$ and $B_c^+ \to J/\psi \pi^+$ decays is measured with proton-proton collision data of a centre-of-mass energy of $13\text{TeV}$. The data were collected with the LHCb experiment during 2016--2018, corresponding to an integrated luminosity of $5.4 \text{fb}^{-1}$. The $B_s^0$ mesons are reconstructed

Phillip Czech, Markus Braun, Ulrich Kreßel, Bin Yang

This paper presents a novel approach to pedestrian trajectory prediction for on-board camera systems, which utilizes behavioral features of pedestrians that can be inferred from visual observations. Our proposed method, called Behavior-Aware Pedestrian Trajectory Prediction (BA-PTP), processes multiple input modalities, i.e. bounding boxes, body and head ori

Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang

To meet the practical requirements of low latency, low cost, and good privacy in online intelligent services, more and more deep learning models are offloaded from the cloud to mobile devices. To further deal with cross-device data heterogeneity, the offloaded models normally need to be fine-tuned with each individual user's local samples before being put in

Tuo Wu, Cunhua Pan, Yijin Pan, Hong Ren

Reconfigurable intelligent surface (RIS) is a promising technique for millimeter wave (mmWave) positioning systems. In this paper, we consider multiple mobile users (MUs) positioning problem in the multiple-input multiple-output (MIMO) time-division duplex (TDD) mmWave systems aided by the RIS. We derive the expression for the space-time channel response vec

Mikolaj Sitarz

This article explores the extension of well-known F1 score used for assessing the performance of binary classifiers. We propose the new metric using probabilistic interpretation of precision, recall, specificity, and negative predictive value. We describe its properties and compare it to common metrics. Then we demonstrate its behavior in edge cases of the c

Karl Bringmann, Nofar Carmeli

We study the enumeration of answers to Unions of Conjunctive Queries (UCQs) with optimal time guarantees. More precisely, we wish to identify the queries that can be solved with linear preprocessing time and constant delay. Despite the basic nature of this problem, it was shown only recently that UCQs can be solved within these time bounds if they admit free

Sébastien Descotes-Genon, Ioannis Plakias, Olcyr Sumensari

Decays based on the $b\to s\gamma$ transition are expected to yield left-handed photons in the Standard Model, but could be particularly sensitive to New Physics contributions modifying the short-distance Wilson coefficients $\mathcal{C}_7$ and $\mathcal{C}_{7'}$ defined in the low-energy Effective Field Theory. These coefficients can be determined by combin

Xiang Li, Yuzheng Chen, Xiaohang Tang

In this paper, we introduce GesPlayer, a gesture-based empowered video player that explores how users can experience their hands as an interface through gestures. We provide three semantic gestures based on the camera of a computer or other smart device to detect and adjust the progress of video playback, volume, and screen brightness, respectively. Our goal

Lingxiao Huang, Yuyi Wang, Chunxue Yang, Huanjian Zhou

The problem of monotone submodular maximization has been studied extensively due to its wide range of applications. However, there are cases where one can only access the objective function in a distorted or noisy form because of the uncertain nature or the errors involved in the evaluation. This paper considers the problem of constrained monotone submodular

Bram Vanherle, Jeroen Put, Nick Michiels, Frank Van Reeth

In this paper a deep learning architecture is presented that can, in real time, detect the 2D locations of certain landmarks of physical tools, such as a hammer or screwdriver. To avoid the labor of manual labeling, the network is trained on synthetically generated data. Training computer vision models on computer generated images, while still achieving good

Sören Dittmer, Michael Roberts, Julian Gilbey, Ander Biguri

In this perspective, we argue that despite the democratization of powerful tools for data science and machine learning over the last decade, developing the code for a trustworthy and effective data science system (DSS) is getting harder. Perverse incentives and a lack of widespread software engineering (SE) skills are among many root causes we identify that

Yilin Wang, Xiangping Chen, Yuan Huang, Hao-Nan Zhu

Smart contracts are pieces of code that reside inside the blockchains and can be triggered to execute any transaction when specifically predefined conditions are satisfied. Being commonly used for commercial transactions in blockchain makes the security of smart contracts particularly important. Over the last few years, we have seen a great deal of academic

Tanise Ceron, Nico Blokker, Sebastian Padó

Even though fine-tuned neural language models have been pivotal in enabling "deep" automatic text analysis, optimizing text representations for specific applications remains a crucial bottleneck. In this study, we look at this problem in the context of a task from computational social science, namely modeling pairwise similarities between political parties.

Qi Zhang, Zhongchang Sun, Luis C. Herrera, Shaofeng Zou

The paper investigates the problems of quickest change detection in Markov models and hidden Markov models (HMMs). Sequential observations are taken from a (hidden) Markov model. At some unknown time, an event occurs in the system and changes the transition kernel of the Markov model and/or the emission probability of the HMM. The objective is to detect the

Marco Gaido, Sara Papi, Matteo Negri, Marco Turchi

Modern automatic translation systems aim at place the human at the center by providing contextual support and knowledge. In this context, a critical task is enriching the output with information regarding the mentioned entities, which is currently achieved processing the generated translation with named entity recognition (NER) and entity linking systems. In

Elspeth K. H. Lee, Bibiana Prinoth, Daniel Kitzmann, Shang-Min Tsai

The atmospheres of ultra hot Jupiters (UHJs) are prime targets for the detection of molecules and atoms at both low and high spectral resolution. We study the atmospheres of the UHJs WASP-121b and WASP-189b by performing 3D general circulation models (GCMs) of these planets using high temperature correlated-k opacity schemes with ultra-violet (UV) absorbing

Jens Walter Fischer

Understanding the topology of the state space has proven to be extremely efficient for dynamical systems with a continuous state space. On the other hand, for particle systems on finite simple graphs, it has not yet been subject to deep investigation due to combinatorial hurdles and existing efficient spectral theoretic approaches to the analysis of classica

Daniel Fernández-González

Intelligent voice assistants, such as Apple Siri and Amazon Alexa, are widely used nowadays. These task-oriented dialogue systems require a semantic parsing module in order to process user utterances and understand the action to be performed. This semantic parsing component was initially implemented by rule-based or statistical slot-filling approaches for pr

Jonas Bundschuh, M. Greta Ruppert, Yvonne Späck-Leigsnering

Pyrit is a field simulation software based on the finite element method written in Python to solve coupled systems of partial differential equations. It is designed as a modular software that is easily modifiable and extendable. The framework can, therefore, be adapted to various activities, i.e. research, education and industry collaboration.

Juan Marshall-Maldonado

The present paper explores the spectral cocycle, defined by A. Bufetov and B. Solomyak, in the special case of bijective substitutions on two letters, the most prominent example being the Thue-Morse substitution. We derive an explicit subexponential behaviour of the deviations from the expected exponential behavior. Moreover, these sharp bounds will be explo