April 2023 arXiv papers — page 74

Songsong Tian, Lusi Li, Weijun Li, Hang Ran

Large deep learning models are impressive, but they struggle when real-time data is not available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for deep neural networks to learn new tasks from just a few labeled samples without forgetting the previously learned ones. This setup easily leads to catastrophic forgetting and overfitt

L. Cavallo, L. Greggio

Recently, the characterisation of binary systems of neutron stars has become central in various fields such as gravitational waves, gamma-ray bursts (GRBs), and the chemical evolution of galaxies. In this work, we explore possible observational proxies that can be used to infer some characteristics of the delay time distribution (DTD) of neutron star mergers

Qi Xiong, Nasrin Sohrabi, Hai Dong, Chenhao Xu

Blockchain has been used in several domains. However, this technology still has major limitations that are largely related to one of its core components, namely the consensus protocol/algorithm. Several solutions have been proposed in literature and some of them are based on the use of Machine Learning (ML) methods. The ML-based consensus algorithms usually

N. Le, A. Karska, M. Figueira, M. Sewiło

(abridged) Far-infrared (FIR) line emission provides key information about the gas cooling and heating due to shocks and UV radiation associated with the early stages of star formation. Gas cooling via FIR lines might, however, depend on metallicity. We aim to quantify the FIR line emission and determine the spatial distribution of the CO rotational temperat

Noël Hallemans, David Howey, Alberto Battistel, Nessa Fereshteh Saniee

Electrochemical impedance spectroscopy (EIS) is a widely used experimental technique for characterising materials and electrode reactions by observing their frequency-dependent impedance. Classical EIS measurements require the electrochemical process to behave as a linear time-invariant system. However, electrochemical processes do not naturally satisfy this

Roger Bielawski, Lorenzo Foscolo

We study transverse equivariant Hilbert schemes of affine hypertoric varieties equipped with a symplectic action of a Weyl group. In particular, we show that the Coulomb branches of Braverman, Finkelberg, and Nakajima can be obtained either as such Hilbert schemes or Hamiltonian reductions thereof. Furthermore, we propose that the Coulomb branches for repres

A. Shepherd, M. Bigi, R. Casagrande, M. Dan

SPIDER, the ion source prototype for ITER neutral beam injectors, has been in operation since 2018. The experiment includes a system of Ion Source and Extraction Power Supplies (ISEPS), whose design dates back to 2011. Since then the experience gained has led to substantial changes, the most dramatic modification being the complete replacement of the radiofr

Simone Blumer, Claudio Quadrelli, Thomas S. Weigel

For a prime number $\ell$ we introduce and study oriented right-angled Artin pro-$\ell$ groups $G_{\Gamma,\lambda}$(oriented pro-$\ell$ RAAGs for short) associated to a finite oriented graph $\Gamma$ and a continuous group homomorphism $\lambda\colon\mathbb Z_\ell\to\mathbb Z_\ell^\times$. We show that an oriented pro-$\ell$ RAAG $G_{\Gamma,\lambda}$ is a Bl

Heather Leitch, Kenza Hammam, Gabriele De Chiara

We investigate the thermodynamics of a hybrid quantum device consisting of two qubits collectively interacting with a quantum rotor and coupled dissipatively to two equilibrium reservoirs at different temperatures. By modelling the dynamics and the resulting steady state of the system using a collision model, we identify the functioning of the device as a th

Philippe Gimenez, Diego Ruano, Rodrigo San-José

We study the subfield subcodes of projective Reed-Solomon codes and their duals: we provide bases for these codes and estimate their parameters. With this knowledge, we can construct symmetric and asymmetric entanglement-assisted quantum error-correcting codes, which in many cases have new or better parameters than the ones available in the literature.

Sacha Lapins, Antony Butcher, J. -Michael Kendall, Thomas S. Hudson

This article presents a weakly supervised machine learning method, which we call DAS-N2N, for suppressing strong random noise in distributed acoustic sensing (DAS) recordings. DAS-N2N requires no manually produced labels (i.e., pre-determined examples of clean event signals or sections of noise) for training and aims to map random noise processes to a chosen

Sonali Sharma, K. Palpandi

A tensor ${\mathcal A}$ of order $m$ and dimension $n$ is called a ${\rm Q}$-tensor if the tensor complementarity problem has a solution for all ${\bf q} \in {\mathbb R}^{n}$. This means that for every vector ${\bf q}$, there exists a vector ${\bf u}$ such that ${\bf u} \geq {\bf 0},{\bf w} = {\mathcal A}{\bf u}^{m-1}+{\bf q} \geq {\bf 0},~\text{and}~ {\bf u

Spyros Argyropoulos, Clare Burrage, Christoph Englert

Dynamical theories of dark energy predict new degrees of freedom with particular environmental sensitivity to avoid constraints on fifth forces. We show that the similar, yet complementary multi-purpose detector setup of the ATLAS and CMS experiments provides a unique opportunity to place sensitivity on such scenarios in a narrow, yet relevant parameter rang

Sitan Lin

In this paper, we investigate Bernoulli type free boundary problem on collapsed RCD(K,N)-spaces. We prove the existence of minimizers and prove the local Lipschitz continuity of minimizers provided that the negative part is locally Lipschitz continuous. In particular, we prove the local Lipschitz continuity of minimizers for the one-phase problem (i.e. when

Alexander Söderberg Rousu

Replica twist defects are of codimension two and enter in quantum information when finding the R\'enyi entropy. In particular, they generate n replicas of the bulk conformal field theory. We study the monodromy of such defect and learn how a global O(N)-symmetry is broken. By applying the equation of motion to the bulk-defect operator-product expansion we ar

Mehrdad Farahani, Richard Johansson

Autoregressive models used to generate responses in open-domain dialogue systems often struggle to take long-term context into account and to maintain consistency over a dialogue. Previous research in open-domain dialogue generation has shown that the use of \emph{auxiliary tasks} can introduce inductive biases that encourage the model to improve these quali

Jeeseung Park, Jin-Woo Park, Jong-Seok Lee

Human-Object Interaction (HOI) detection, which localizes and infers relationships between human and objects, plays an important role in scene understanding. Although two-stage HOI detectors have advantages of high efficiency in training and inference, they suffer from lower performance than one-stage methods due to the old backbone networks and the lack of

Tomas McKelvey

A regression model with more parameters than data points in the training data is overparametrized and has the capability to interpolate the training data. Based on the classical bias-variance tradeoff expressions, it is commonly assumed that models which interpolate noisy training data are poor to generalize. In some cases, this is not true. The best models

Jędrzej Hodor, William T. Trotter

Over the past 10 years, there has been considerable interest in exploring questions connecting dimension for posets with graph theoretic properties of their cover graphs and order diagrams, especially with the concepts of planarity and treewidth. Joret and Micek conjectured that if $P$ is a poset with a planar cover graph, then the dimension of $P$ is bounde

Faranak Shamsafar, Sunil Jaiswal, Benjamin Kelkel, Kireeti Bodduna

Printed circuit boards (PCBs) are essential components of electronic devices, and ensuring their quality is crucial in their production. However, the vast variety of components and PCBs manufactured by different companies makes it challenging to adapt to production lines with speed demands. To address this challenge, we present a multi-view object detection

Xiao Sun, Bo Zhang, Chenrui Zhang, Han Ren

AUC is a common metric for evaluating the performance of a classifier. However, most classifiers are trained with cross entropy, and it does not optimize the AUC metric directly, which leaves a gap between the training and evaluation stage. In this paper, we propose the PDAOM loss, a Personalized and Differentiable AUC Optimization method with Maximum violat

Daichi Nakamura, Kazuya Inaka, Nobuyuki Okuma, Masatoshi Sato

Whereas point-gap topological phases are responsible for exceptional phenomena intrinsic to non-Hermitian systems, their realization in quantum materials is still elusive. Here we propose a simple and universal platform of point-gap topological phases constructed from Hermitian topological insulators and superconductors. We show that (d-1)-dimensional point-

Xianghui Sun, Yunjie Ji, Baochang Ma, Xiangang Li

Recently, the instruction-tuning of large language models is a crucial area of research in the field of natural language processing. Due to resource and cost limitations, several researchers have employed parameter-efficient tuning techniques, such as LoRA, for instruction tuning, and have obtained encouraging results In comparison to full-parameter fine-tun

Matias Koivurova, Charles W. Robson, Marco Ornigotti

We study the implications of time-varying wave mechanics, and show how the standard wave equation is modified if the speed of a wave is not constant in time. In particular, waves which experience longitudinal acceleration are shown to have clear relativistic properties when a constant reference speed exists. Moreover, the accelerating wave equation admits on

Hao Tian, Yu Cao, P. Y. Mok

Clothing segmentation and fine-grained attribute recognition are challenging tasks at the crossing of computer vision and fashion, which segment the entire ensemble clothing instances as well as recognize detailed attributes of the clothing products from any input human images. Many new models have been developed for the tasks in recent years, nevertheless t

Angel Victor Juanco Muller, Joao F. C. Mota, Keith A. Goatman, Corne Hoogendoorn

With nearly one million new cases diagnosed worldwide in 2020, head \& neck cancer is a deadly and common malignity. There are challenges to decision making and treatment of such cancer, due to lesions in multiple locations and outcome variability between patients. Therefore, automated segmentation and prognosis estimation approaches can help ensure each pat

D. Pross, S. Wuyckens, S. Deffet, E. Sterpin

Background: Dose calculation and optimization algorithms in proton therapy treatment planning often have high computational requirements regarding time and memory. This can hinder the implementation of efficient workflows in clinics and prevent the use of new, elaborate treatment techniques aiming to improve clinical outcomes like robust optimization, arc an

PLUS Science Team, Akio K. Inoue, Yuichi Harikane, Takashi Moriya

GREX-PLUS (Galaxy Reionization EXplorer and PLanetary Universe Spectrometer) is a mission candidate for a JAXA's strategic L-class mission to be launched in the 2030s. Its primary sciences are two-fold: galaxy formation and evolution and planetary system formation and evolution. The GREX-PLUS spacecraft will carry a 1.2 m primary mirror aperture telescope co

Yuzhe Cai, Shaoguang Mao, Wenshan Wu, Zehua Wang

Utilizing Large Language Models (LLMs) for complex tasks is challenging, often involving a time-consuming and uncontrollable prompt engineering process. This paper introduces a novel human-LLM interaction framework, Low-code LLM. It incorporates six types of simple low-code visual programming interactions to achieve more controllable and stable responses. Th

Shu-Ichiro Suzuki, Yasuhiro Asano, Alexander A. Golubov

We study theoretically the shape of the current-phase relation in a Josephson junction comprising the Zeeman-split superconductors (ZSs) and a normal metal (N). We show that at low temperatures the Josephson current in the ZS/N/ZS junctions exhibits an additional reversal in direction at a certain phase difference $\varphi_c \in (0, \pi)$. Calculating the sp

Jiawei Xu, Zongqing Lu, Qingmin Liao

Lack of texture often causes ambiguity in matching, and handling this issue is an important challenge in optical flow estimation. Some methods insert stacked transformer modules that allow the network to use global information of cost volume for estimation. But the global information aggregation often incurs serious memory and time costs during training and

Hyangdong Park

We prove the stability of three-dimensional axisymmetric solutions to the steady Euler system with transonic shocks in divergent nozzles under perturbations of the exit pressure and the supersonic solution in the upstream region. We first derive a free boundary problem with the newly introduced formulation of the Euler system for three-dimensional axisymmetr

Balint Rago

We give an algebraic characterization of half-factorial orders in algebraic number fields. This generalizes prior results for seminormal orders and for orders in quadratic number fields.

Federico Becattini, Federico Maria Teotini, Alberto Del Bimbo

Suggesting complementary clothing items to compose an outfit is a process of emerging interest, yet it involves a fine understanding of fashion trends and visual aesthetics. Previous works have mainly focused on recommendation by scoring visual appeal and representing garments as ordered sequences or as collections of pairwise-compatible items. This limits t

Arindam Chakraborty

A non-Hermitian version of Rashba Hamiltonian has been introduced motivated from the Levy-leblond type linearisation of Schrodinger equation in a Galilean invariant frame-work. The said Hamiltonian is found to be pseudo-Hermitian under fermionic time-reversal and its eigen-spinors show bi-orthogonality. The whole discussion has been cast in a Clifford algeb

Vladimir Onoochin

The integral expressions served to decompose vector field into irrotational and divergence-free components represent modern version of the Helmholtz decomposition theorem. These expressions are also widely used to decompose the electromagnetic fields. However, an appropriate analysis of application of these expressions to electrodynamics shows that the impro

Wenhan Yu, Jun Zhao

The increasing popularity of applications like the Metaverse has led to the exploration of new, more effective ways of communication. Semantic communication, which focuses on the meaning behind transmitted information, represents a departure from traditional communication paradigms. As mobile devices become increasingly prevalent, it is important to explore

Paul Ferrand, Maxime Guillaud, Christoph Studer, Olav Tirkkonen

Channel charting is a recently proposed framework that applies dimensionality reduction to channel state information (CSI) in wireless systems with the goal of associating a pseudo-position to each mobile user in a low-dimensional space: the channel chart. Channel charting summarizes the entire CSI dataset in a self-supervised manner, which opens up a range

Clara Siepmann, Mohamed Amine Chatti

Trust is long recognized to be an important factor in Recommender Systems (RS). However, there are different perspectives on trust and different ways to evaluate it. Moreover, a link between trust and transparency is often assumed but not always further investigated. In this paper we first go through different understandings and measurements of trust in the

Johannes Hirth, Viktoria Horn, Gerd Stumme, Tom Hanika

Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textua

Shao-Jun Zhang

In this work, we present a new type of scalar clouds supported by spherically symmetric horizonless compact objects in the scalar-Gauss-Bonnet theory. Unlike the previous spontaneous scalarization that is triggered by the tachyonic instability, our scalarization arises from a nonlinear instability that is non-spontaneous. We explore two types of boundary con

Maxime Brunet, Marine Pétriaux, Florent Di Meglio, Nicolas Petit

This paper exposes a control architecture enabling rehabilitation of walking impaired patients with the lower-limb exoskeleton Atalante. Atalante's control system is modified to allow the patient to contribute to the walking motion through their efforts. Only the swing leg degree of freedom along the nominal path is relaxed. An online trajectory optimization

Giacomo Elefante, Alvise Sommariva, Marco Vianello

We discuss a bottom-up algorithm for Tchakaloff like compression of Quasi-MonteCarlo (QMC) integration on surfaces that admit an analytic parametrization.

Wei Ji, Chao Liu, Bo Zhang

In this work, we present Stellar Spectra Factory (SSF), a tool to generate empirical-based stellar spectra from arbitrary stellar atmospheric parameters. The relative flux-calibrated empirical spectra can be predicted by SSF given arbitrary effective temperature, surface gravity, and metallicity. SSF constructs the interpolation approach based on the SLAM, u

Huiping Chen, Yong Chen, Yong Liu

For a series of univariate or multivariate complex multiple Wiener-It\^o integrals, we appreciably improve the previously known contractions condition of complex Fourth Moment Theorem (FMT) and present a fourth moment type Berry-Ess\'een bound under Wasserstein distance. Note that in some special cases of univariate complex multiple Wiener-It\^o integral, th

José L. Jiménez, Isobel Barrott, Francesca Gasperoni, Dominic Magirr

What can be considered an appropriate statistical method for the primary analysis of a randomized clinical trial (RCT) with a time-to-event endpoint when we anticipate non-proportional hazards owing to a delayed effect? This question has been the subject of much recent debate. The standard approach is a log-rank test and/or a Cox proportional hazards model.

Balder ten Cate, Jesse Comer

We show that the guarded-negation fragment (GNFO) is, in a precise sense, the smallest extension of the guarded fragment (GFO) with Craig interpolation. In contrast, %we show that the smallest extension of the two-variable fragment (FO2) with Craig interpolation is full first-order logic.

Xiao Wang, Weikang Zhou, Can Zu, Han Xia

Large language models have unlocked strong multi-task capabilities from reading instructive prompts. However, recent studies have shown that existing large models still have difficulty with information extraction tasks. For example, gpt-3.5-turbo achieved an F1 score of 18.22 on the Ontonotes dataset, which is significantly lower than the state-of-the-art pe

Igor Dolinka, Robert D. Gray

A prefix monoid is a finitely generated submonoid of a finitely presented group generated by the prefixes of its defining relators. Important results of Guba (1997), and of Ivanov, Margolis and Meakin (2001), show how the word problem for certain one-relator monoids, and inverse monoids, can be reduced to solving the membership problem in prefix monoids of c

Jonas F. Haderlein, Andre D. H. Peterson, Anthony N. Burkitt, Iven M. Y. Mareels

Autoregressive models are ubiquitous tools for the analysis of time series in many domains such as computational neuroscience and biomedical engineering. In these domains, data is, for example, collected from measurements of brain activity. Crucially, this data is subject to measurement errors as well as uncertainties in the underlying system model. As a res

Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu

Recommender systems are seen as an effective tool to address information overload, but it is widely known that the presence of various biases makes direct training on large-scale observational data result in sub-optimal prediction performance. In contrast, unbiased ratings obtained from randomized controlled trials or A/B tests are considered to be the golde

Yang Liu, Ying Tan, Jingzhou Luo, Weixing Chen

Existing visual question reasoning methods usually fail to explicitly discover the inherent causal mechanism and ignore jointly modeling cross-modal event temporality and causality. In this paper, we propose a visual question reasoning framework named Cross-Modal Question Reasoning (CMQR), to discover temporal causal structure and mitigate visual spurious co

Mu-Yao Li, Ying-Ting Zhang, Wei-Xing Zhou

The temporal rich club (TRC) phenomenon is widespread in real systems, forming a tight and continuous collection of the prominent nodes that control the system. However, there is still a lack of sufficient understanding of the mechanisms of TRC formation. Here we use the international N-nutrient trade network as an example of an in-depth identification, anal

Asif Sania, Basdouri Imed, Sadraoui Mohamed Amin

This study aims to generalize the notion of compatible Lie algebras to the compatible Lie Yamaguti algebras. Along with describing the representation of the compatible Lie Yamaguti algebra in detail, we also introduce the Maurer-Cartan characterization and cohomology of Lie Yamaguti algebras. As a result of the obtained cohomology, we studied its deformation

Suparna Sarkar, Santanu K. Maiti, David Laroze

We investigate, for the first time, the thermal signature of a single-stranded helical molecule that is described beyond usual nearest-neighbor electron hopping, by analyzing electronic specific heat. Depending on the hopping of electrons, two different kinds of helical systems are considered. In one case the hopping is confined within a few neighboring latt

Ivan Fotev, Stephan Winnerl, Saicharan Aswartham, Sabine Wurmehl

BaFe$_2$As$_2$ is the parent compound for a family of iron-based high-temperature superconductors as well as a prototypical example of the spin-density wave (SDW) system. In this study, we perform an optical pump-probe study of this compound to systematically investigate the SDW order across the pressure-temperature phase diagram. The suppression of the SDW

Joonhyung Kim, Ioannis D. Platis, Li-Jie Sun

Let $\mathfrak{H}$ be the Heisenberg group. From the standard CR structure $\mathcal{H}$ of $\mathfrak{H}$ we construct the complex hyperbolic structure of the Siegel domain. Additionally, using the same minimal data for $\mathfrak{H}$, that is, its Sasakian structure, we provide the Siegel domain with yet another K\"ahler structure: this structure is of unb

Weinan Guan, Wei Wang, Jing Dong, Bo Peng

Detecting maliciously falsified facial images and videos has attracted extensive attention from digital-forensics and computer-vision communities. An important topic in manipulation detection is the localization of the fake regions. Previous work related to forgery detection mostly focuses on the entire faces. However, recent forgery methods have developed t

Nan Li, Bo Kang, Tijl De Bie

We present SkillGPT, a tool for skill extraction and standardization (SES) from free-style job descriptions and user profiles with an open-source Large Language Model (LLM) as backbone. Most previous methods for similar tasks either need supervision or rely on heavy data-preprocessing and feature engineering. Directly prompting the latest conversational LLM

Doratossadat Dastgheib, Hadi Farahani

In this paper, we propose a doxastic extension $BL^+$ of Lukasiewicz logic which is sound and complete relative to the introduced corresponding semantics. Also, we equip our doxastic Lukasiewicz logic $BL^+$ with public announcement and propose the logic $DL$. As an application, we model a fuzzy version of muddy children puzzle with public announcement using

Byeongho Jo, Seungkwon Beack, Taejin Lee

Over the past decade, audio coding technology has seen standardization and the development of many frameworks incorporated with linear predictive coding (LPC). As LPC reduces information in the frequency domain, LP-based frequency-domain noise-shaping (FDNS) was previously proposed. To code transient signals effectively, FDNS with temporal noise shaping (TNS

S. Peszat, J. Zabczyk

We consider the Heath-Jarrow-Morton model of forward rates processes with linear volatility. The noise is either a Wiener or a pure jump Leevy process. We provide formulae for the forward rate processes, and discus the problem of their global in time existence.

Dulaji Hidellaarachchi, John Grundy, Rashina Hoda, Ingo Mueller

Context: Requirements Engineering (RE)-related activities are critical in developing quality software and one of the most human-dependent processes in software engineering (SE). Hence, identifying the impact of diverse human-related aspects on RE is crucial in the SE context. Objective: Our study explores the impact of one of the most influential human aspec

Bartłomiej Zawalski

Let $f\in W^{3,1}_{\mathrm{loc}}(\Omega)$ be a function defined on a connected open subset $\Omega\subseteq\mathbb R^2$. We will show that its graph is contained in a quadratic surface if and only if $f$ is a weak solution to a certain system of third-order partial differential equations unless the Hessian determinant of $f$ is non-positive everywhere on $\O

Li Zhu, Jiawei Jiang, Lin Lu, Jin Li

Multimodal magnetic resonance imaging (MRI) can reveal different patterns of human tissue and is crucial for clinical diagnosis. However, limited by cost, noise and manual labeling, obtaining diverse and reliable multimodal MR images remains a challenge. For the same lesion, different MRI manifestations have great differences in background information, coars

Yu Liu, Jin Lan

We show that spin wave acquires a polarization-dependent geometric phase along a cyclic trajectory of non-coplanar magnetizations in antiferromagnets. Specifically, we demonstrate that a cyclic set of 90 degree antiferromagnetic domain walls simultaneously introduce geometric and dynamic phases to spin wave, and thus leads to asymmetric magnitude of overall

Dominique Malicet, Emmanuel Militon

In 2000, Margulis proved that any group of homeomorphisms of the circle either preserves a probabilty measure on the circle or contains a free subgroup in two generators, which is reminiscent of the Tits alternatve for linear groups. In this article, we prove an analogous statement for groups of locally monotonic homeomorphisms of a compact subset of R.

Yian Zhao, Wenyu Lv, Shangliang Xu, Jinman Wei

The YOLO series has become the most popular framework for real-time object detection due to its reasonable trade-off between speed and accuracy. However, we observe that the speed and accuracy of YOLOs are negatively affected by the NMS. Recently, end-to-end Transformer-based detectors (DETRs) have provided an alternative to eliminating NMS. Nevertheless, th

Gilles Dowek

Instead of developing a customized typed lambda-calculus for each theory, we attempt to design a general parametric calculus that permits to express the proofs of any theory. This way, the problem of expressing proofs in the lambda-calculus is separated from that of choosing a theory.

Sania Asif, Lipeng Luo, Yanyong Hong, Zhixiang Wu

Let $\mathcal{R}$ be a finite Lie conformal algebra. In this paper, we first investigate the conformal derivation algebra $CDer(\mathcal{R})$, the conformal triple derivation algebra $CTDer(\mathcal{R})$ and the generalized conformal triple derivation algebra $GCTDer(\mathcal{R})$. Mainly, we focus on the connections among these derivation algebras. Next, we

Jonas F. Haderlein, Andre D. H. Peterson, Parvin Zarei Eskikand, Anthony N. Burkitt

The empirical success of machine learning models with many more parameters than measurements has generated an interest in the theory of overparameterisation, i.e., underdetermined models. This paradigm has recently been studied in domains such as deep learning, where one is interested in good (local) minima of complex, nonlinear loss functions. Optimisers, l

Giovanni Perona, Angelo Raffaele Meo, Marco Allegretti, Isabella Bordi

The purpose of the following proposal is to create a new class of antennas of low weight but with a large transmitting and receiving surface made of metallized fabric. This class of antennas will be stationed in low satellite orbits, at about 2000 km from sea level and will be easily steerable by exploiting the interaction between the earth's magnetic field

Pablo Arrighi, Gilles Dowek

The possibility to describe the laws of the Universe in a computational way seems to be correlated to a principle that the density of information is bounded. This principle, that is dual to that of a finite velocity of information, has already been investigated in Physics, and is correlated to the old idea that there is no way to know a magnitude with an inf

Cheikh Saliou Ndiaye

In this note, we study B{\'e}zout type inequalities for mixed volume and Minkowski sum of convex bodies in R n. We first give a new proof and we extend inequalities of Jian Xiao on mixed discriminants. Then, we use mass transport method to deduce some B{\'e}zout type inequalities for mixed volumes. Finally, we apply these inequalities to obtain B{\'e}zout ty

Guilhem Balvet, Jean-Pierre Minier, Christophe Henry, Yelva Roustan

The purpose of this paper is to propose a time-step-robust cell-to-cell integration of particle trajectories in 3-D unstructured meshes in particle/mesh Lagrangian stochastic methods. The main idea is to dynamically update the mean fields used in the time integration by splitting, for each particle, the time step into sub-steps such that each of these sub-st

Arthur Grundner, Tom Beucler, Pierre Gentine, Veronika Eyring

A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning-based parameterizations using output from global storm-resolving models. While neural networks can achieve state-of-the-art performance within their training distribution, they can make unreliable predictions outside

Qingyao Ai, Xuanhui Wang, Michael Bendersky

Ranking is at the core of Information Retrieval. Classic ranking optimization studies often treat ranking as a sorting problem with the assumption that the best performance of ranking would be achieved if we rank items according to their individual utility. Accordingly, considerable ranking metrics have been developed and learning-to-rank algorithms that hav

Sophie Jaffard, Samuel Vaiter, Alexandre Muzy, Patricia Reynaud-Bouret

We propose a simple network of Hawkes processes as a cognitive model capable of learning to classify objects. Our learning algorithm, named HAN for Hawkes Aggregation of Neurons, is based on a local synaptic learning rule based on spiking probabilities at each output node. We were able to use local regret bounds to prove mathematically that the network is ab

Thierry Huillet

Life is on the razor's edge as resulting from competitive birth and death random forces. We illustrate this aphorism in the context of three Markov chain population models where systematic random immigration events promoting growth are simultaneously balanced with random emigration ones provoking thinning. The origin of mass removals are either determined by

Christopher P. Chambers, Georgios Gerasimou

Diversification is the typical investment strategy of risk-averse agents. However, non-diversified positions that allocate all resources to a single asset, state of the world or revenue stream are common too. We show that whenever finitely many non-diversified demands under uncertainty are compatible with risk-averse subjective expected utility maximization

Nicolas Pinon, Robin Trombetta, Carole Lartizien

Anomaly detection remains a challenging task in neuroimaging when little to no supervision is available and when lesions can be very small or with subtle contrast. Patch-based representation learning has shown powerful representation capacities when applied to industrial or medical imaging and outlier detection methods have been applied successfully to these

Pierre Maréchal, Faouzi Triki, Walter C. Simo Tao Lee

In this paper we study the inverse Laplace transform. We first derive a new global logarithmic stability estimate that shows that the inversion is severely ill-posed. Then we propose a regularization method to compute the inverse Laplace transform using the concept of mollification. Taking into account the exponential instability we derive a criterion for se

Mohamed Ali Chebbi, Ewelina Rupnik, Marc Pierrot-Deseilligny, Paul Lopes

We present three multi-scale similarity learning architectures, or DeepSim networks. These models learn pixel-level matching with a contrastive loss and are agnostic to the geometry of the considered scene. We establish a middle ground between hybrid and end-to-end approaches by learning to densely allocate all corresponding pixels of an epipolar pair at onc

Laurent Manivel, Rosa Miro-Roig

We consider the problem of constructing matrices of linear forms of constant rank by focusing on the associated vector bundles on projective spaces. Important examples are given by the classical Steiner bundles, as well as some special (duals of) syzygy bundles that we call Dr{\'e}zet bundles. Using the classification of globally generated vector bundles wit

Irene Balelli, Aude Sportisse, Francesco Cremonesi, Pierre-Alexandre Mattei

Federated learning allows for the training of machine learning models on multiple decentralized local datasets without requiring explicit data exchange. However, data pre-processing, including strategies for handling missing data, remains a major bottleneck in real-world federated learning deployment, and is typically performed locally. This approach may be

Zhengyang Liu, Liang Shan, Zihe Wang

Time or money? That is a question! In this paper, we consider this dilemma in the pricing regime, in which we try to find the optimal pricing scheme for identical items with heterogenous time-sensitive buyers. We characterize the revenue-optimal solution and propose an efficient algorithm to find it in a Bayesian setting. Our results also demonstrate the tig

Yi Luo, Rongzhi Gu

Modern neural-network-based speech processing systems are typically required to be robust against reverberation, and the training of such systems thus needs a large amount of reverberant data. During the training of the systems, on-the-fly simulation pipeline is nowadays preferred as it allows the model to train on infinite number of data samples without pre

Jiaxu Liu, Song Chen, Shengze Cai, Chao Xu

In this paper, we investigate a distributed aggregative optimization problem in a network, where each agent has its own local cost function which depends not only on the local state variable but also on an aggregated function of state variables from all agents. To accelerate the optimization process, we combine heavy ball and Nesterov's accelerated methods w

Kévin Le Balc'H, Jérémy Martin

The goal of this article is to obtain observability estimates for Schr{\"o}dinger equations in the plane R 2. More precisely, considering a 2$\pi$Z 2-periodic potential V $\in$ L $\infty$ (R 2), we prove that the evolution equation i$\partial$tu = --$\Delta$u + V (x)u, is observable from any 2$\pi$Z 2-periodic measurable set, in any small time T > 0. We then

Jian Gao, Dashun Wang

The ongoing artificial intelligence (AI) revolution has the potential to change almost every line of work. As AI capabilities continue to improve in accuracy, robustness, and reach, AI may outperform and even replace human experts across many valuable tasks. Despite enormous effort devoted to understanding the impact of AI on labor and the economy and AI's r

Francisco Estrada, Richard S. J. Tol, Wouter Botzen

Damage functions in integrated assessment models (IAMs) map changes in climate to economic impacts and form the basis for most of estimates of the social cost of carbon. Implicit in these functions lies an unwarranted assumption that restricts the spatial variation (Svar) and temporal variability (Tvar) of changes in climate to be null. This could bias damag

Victor Boone

In this technical note, we establish an upper-bound on the threshold on the discount factor starting from which all discounted-optimal deterministic policies are gain-optimal, that we prove to be tight on an example. To address computability issues of that theoretical threshold, we provide a weaker bound which is tractable on ergodic MDPs in polynomial time.

Kévin Deturck, Parantapa Goswami, Damien Nouvel, Frédérique Segond

In this paper, we present our participation to CLEF MC2 2018 edition for the task 2 Mining opinion argumentation. It consists in detecting the most argumentative and diverse Tweets about some festivals in English and French from a massive multilingual collection. We measure argumentativity of a Tweet computing the amount of argumentation compounds it contain

Anarya Ray, Ignacio Magaña Hernandez, Siddharth Mohite, Jolien Creighton

The observation of gravitational waves from multiple compact binary coalescences by the LIGO-Virgo-KAGRA detector networks has enabled us to infer the underlying distribution of compact binaries across a wide range of masses, spins, and redshifts. In light of the new features found in the mass spectrum of binary black holes and the uncertainty regarding bina

O. Ogulcan Tuncer

We introduce pseudo-spherical non-null framed curves in the three-dimensional anti-de Sitter spacetime and establish the existence and uniqueness of these curves. We then give moving frames along pseudo-spherical framed curves, which are well-defined even at singular points of the curve. These moving frames enable us to define evolutes and focal surfaces of

Haoyang Zhang, Shenbang Yang, Benzhong Dai

The quasi-periodic oscillations (QPOs) found in active galactic nuclei (AGNs) are a very interesting observational phenomenon implying an unknown physical mechanism around supermassive black holes. Several AGNs have been found to have QPO phenomena in the X-ray energy band. Long-duration X-ray observations were collected and reduced for six AGNs with a suspe

Daisuke Kishimoto, Takahiro Matsushita

The van Kampen-Flores theorem states that the $d$-skeleton of a $(2d+2)$-simplex does not embed into $\mathbb{R}^{2d}$. We prove the van Kampen-Flores theorem for triangulations of manifolds satisfying a certain condition on their Stiefel-Whitney classes. In particular, we show that the $d$-skeleton of a triangulation of a $(2d+1)$-manifold with non-trivial

Luca Pacioselli, Orlando Panella, Matteo Presilla, She-Sheng Xue

We study the contribution of a heavy right-handed Majorana neutrino to neutrinoless double beta decay ($0\nu\beta\beta$) via four-fermion effective interactions of Nambu-Jona-Lasinio (NJL) type. In this physical scenario, the sterile neutrino contributes to the nuclear transition through gauge, contact, and mixed interactions. Using the lower limit on the ha

Jakob Nyberg, Pontus Johnson

We implemented and evaluated an automated cyber defense agent. The agent takes security alerts as input and uses reinforcement learning to learn a policy for executing predefined defensive measures. The defender policies were trained in an environment intended to simulate a cyber attack. In the simulation, an attacking agent attempts to capture targets in th

Sumita Sharma, Netta Iivari, Leena Ventä-Olkkonen, Heidi Hartikainen

Children increasingly use applications utilizing Artificial Intelligence / Machine Learning (AI/ML). Given the propensity of such applications to propagate existing social, gender, and racial biases, it becomes imperative to consider designing and developing child-centered AI applications for children. Furthermore, children should have opportunities and skil