November 2018 arXiv papers — page 121

Mayank Sharma, Jayadeva, Sumit Soman

Explaining the unreasonable effectiveness of deep learning has eluded researchers around the globe. Various authors have described multiple metrics to evaluate the capacity of deep architectures. In this paper, we allude to the radius margin bounds described for a support vector machine (SVM) with hinge loss, apply the same to the deep feed-forward architect

Ziyuan Zhao, Shoutao Zhang, Tong Yu, Haiyang Xu

Electrides are unique compounds where most of the electrons reside at interstitial regions of the crystal behaving as anions, which strongly determines its physical properties. Interestingly, the magnitude and distribution of interstitial electrons can be effectively modified either by modulating its chemical composition or external conditions (e.g. pressure

J. Dubreuil, J. S. Bobowski

The complex permeability of an iron-oxide nanosuspension has been measured as a function of magnetic field strength at RF and microwave frequencies using a loop-gap resonator. The particles were suspended in water and had an 8-nm diameter Fe$_3$O$_4$ core that was coated by Dextran. The real part of the permeability increased sharply beyond a frequency-depen

Robert Salazar, Camilo Bayona

We study the steady state motion of incompressible and viscous fluid flow in a rotating reference frame where vortices may take place. An approximated analytic solution of the Stokes flow problem is proposed for situations where the vorticity is highly concentrated along a given direction. The approximation disconnects the component of velocity along the axi

Shivani Choudhary, Amol R. Holkundkar

The propagation of the laser pulses in the underdense plasma is a very crucial aspect of laser-plasma interaction process. In this work, we explored the two regimes of laser propagation in plasma, one with $a_0 < 1$ and other with $a_0 \gtrsim 10$. For $a_0<1$ case, we used a cold relativistic fluid model, wherein apart from immobile ions no further approxim

Timm Faulwasser, Alexander Engelmann, Tillmann Mühlpfordt, Veit Hagenmeyer

The Energiewende is a paradigm change that can be witnessed at latest since the political decision to step out of nuclear energy. Moreover, despite common roots in Electrical Engineering, the control community and the power systems community face a lack of common vocabulary. In this context, this paper aims at providing a systems-and-control specific introdu

An Zhang, Yong Chen, Zhi-Zhong Chen, Guohui Lin

Given a simple graph $G = (V, E)$ and a constant integer $k \ge 2$, the $k$-path vertex cover problem ({\sc P$k$VC}) asks for a minimum subset $F \subseteq V$ of vertices such that the induced subgraph $G[V - F]$ does not contain any path of order $k$. When $k = 2$, this turns out to be the classic vertex cover ({\sc VC}) problem, which admits a $\left(2 - {

Engin Arslan, Ahmed Alhussen

The amount of data generated by scientific and commercial applications is growing at an ever-increasing pace. This data is often moved between geographically distributed sites for various purposes such as collaboration and backup which has led to significant increase in data transfer rates. Surge in data transfer rates when combined with proliferation of sci

Haitao Liu, Jianfei Cai, Yew-Soon Ong, Yi Wang

As a non-parametric Bayesian model which produces informative predictive distribution, Gaussian process (GP) has been widely used in various fields, like regression, classification and optimization. The cubic complexity of standard GP however leads to poor scalability, which poses challenges in the era of big data. Hence, various scalable GPs have been devel

Lifang He, Kun Chen, Wanwan Xu, Jiayu Zhou

We propose a sparse and low-rank tensor regression model to relate a univariate outcome to a feature tensor, in which each unit-rank tensor from the CP decomposition of the coefficient tensor is assumed to be sparse. This structure is both parsimonious and highly interpretable, as it implies that the outcome is related to the features through a few distinct

Anthony Bau, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani

Neural machine translation (NMT) models learn representations containing substantial linguistic information. However, it is not clear if such information is fully distributed or if some of it can be attributed to individual neurons. We develop unsupervised methods for discovering important neurons in NMT models. Our methods rely on the intuition that differe

Hong-Mei Zou, Mao-Fa Fang, Bai-Yuan Yang, You-Neng Guo

The quantum entropic uncertainty relation and entanglement witness in the two-atom system coupling with the non-Markovian environments are studied by the time-convolutionless master-equation approach. The influence of non-Markovian effect and detuning on the lower bound of the quantum entropic uncertainty relation and entanglement witness is discussed in det

Liu Yu, Zou Hong-Mei, Fang Mao-Fa

Quantum coherence and non-Markovianity of an atom in dissipative cavity under weak measurement are investigated in this work. We find that, the quantum coherence obviously depends on the atomic initial state, the strength of the weak measurement and its reversal, the atom-cavity coupling constant and the non-Markovian effecct. The more obvious the weak measu

Yufan Luo

We prove a Hodge-type decomposition for the de-Rham cohomology of $ p$-adically uniformized varieties by the product of Drinfeld&#39;s symmetric spaces. It is based on work of Schneider, Stuhler, Iovita and Spiess on the cohomology of Drinfeld&#39;s symmetric space.

Ramadan Abdul-Rashid, Ali Al-Shaikhi, Ahmad Masoud

This paper concerns with the synchronization of infrastructure impoverished sensor networks under harsh conditions. It suggests three novel asynchronous, decentralized, energyefficient time synchronization protocols. The protocols require only single hop, sparse communication with unlabeled neighboring nodes of the network to determine accurately the time of

Ryo Matsumoto, Masanori Nagao, Masayuki Ochi, Hiromi Tanaka

Transport properties of Ce$_{0.85}$F0.15SbS$_{2}$ and undoped CeOSbS$_{2}$ under high pressure were investigated experimentally and theoretically. Electrical resistivity measurements of the Ce$_{0.85}$F0.15SbS$_{2}$ single crystals were performed under various high pressures using a diamond anvil cell with boron-doped diamond electrodes. The samples showed t

Yogesh Kumar, Sukumar Srikant, Debasish Chatterjee

This article treats three problems of sparse and optimal multiplexing a finite ensemble of linear control systems. Given an ensemble of linear control systems, multiplexing of the controllers consists of an algorithm that selects, at each time \(t\), only one from the ensemble of linear systems is actively controlled whereas the other systems evolve in open-

Sharon Levy, Wenhan Xiong, Elizabeth Belding, William Yang Wang

Recent studies show that 85% of women have changed their traveled route to avoid harassment and assault. Despite this, current mapping tools do not empower users with information to take charge of their personal safety. We propose SafeRoute, a novel solution to the problem of navigating cities and avoiding street harassment and crime. Unlike other street nav

P. Ganesh, Frank Lechermann, Ilkka Kylanpaa, Jaron Krogel

Rutile ($R$) phase VO$_2$ is a quintessential example of a strongly correlated bad-metal, which undergoes a metal-insulator transition (MIT) concomitant with a structural transition to a V-V dimerized monoclinic phase below T$_{MIT} \sim 340K$. It has been experimentally shown that one can control this transition by doping VO$_2$. In particular, doping with

Robert E. Kent

The IFF approach for the notion of &#34;lattice of theories&#34; uses the idea of a concept lattice from Formal Concept Analysis (Ganter and Wille) and the idea of the truth classification from Information Flow (Barwise and Seligman). The IFF approach is concentrated in the joining of these two important ideas. The result is called the truth concept lattice,

Diasuke Miura, Akimasa Sakuma

We theoretically investigate the spin--wave spin current induced by the spin Seebeck effect in magnonic spin tunneling junctions (MSTJs) for arbitrary magnetization directions. We show that the MSTJ functions as a \textit{tunable} spin Seebeck diode in which the tunneling spin current can be turned on and off with high efficiency by controlling the magnetiza

F. B. A. Aghbolagh, V. Nampoothiri, B. Debord, F. Gerome

Emission at 4.6 um was observed from an N2O filled hollow core fiber laser. 8-ns pump pulses at 1.517 um excited a vibrational overtone resulting in lasing on an R and P branch fundamental transition from the upper pump state. At optimum gas pressure of 80 Torr a photon conversion efficiency of 9% and a slope efficiency of 3% was observed from a mirrorless l

Song Huang, Alexie Leauthaud, Andrew Hearin, Peter Behroozi

Using deep images from the Hyper Suprime-Cam (HSC) survey and taking advantage of its unprecedented weak lensing capabilities, we reveal a remarkably tight connection between the stellar mass distribution of massive central galaxies and their host dark matter halo mass. Massive galaxies with more extended stellar mass distributions tend to live in more massi

Irena Lasiecka, Michael Pokojovy, Xiang Wan

We consider an initial-boundary-value problem for a thermoelastic Kirchhoff & Love plate, thermally insulated and simply supported on the boundary, incorporating rotational inertia and a quasilinear hypoelastic response, while the heat effects are modeled using the hyperbolic Maxwell-Cattaneo-Vernotte law giving rise to a &#39;second sound&#39; effect. We st

Surafel M. Lakew, Aliia Erofeeva, Matteo Negri, Marcello Federico

We propose a method to transfer knowledge across neural machine translation (NMT) models by means of a shared dynamic vocabulary. Our approach allows to extend an initial model for a given language pair to cover new languages by adapting its vocabulary as long as new data become available (i.e., introducing new vocabulary items if they are not included in th

Lajanugen Logeswaran, Honglak Lee, Samy Bengio

In this work, we address the problem of modifying textual attributes of sentences. Given an input sentence and a set of attribute labels, we attempt to generate sentences that are compatible with the conditioning information. To ensure that the model generates content compatible sentences, we introduce a reconstruction loss which interpolates between auto-en

Nicolas Papernot

There is growing recognition that machine learning (ML) exposes new security and privacy vulnerabilities in software systems, yet the technical community&#39;s understanding of the nature and extent of these vulnerabilities remains limited but expanding. In this talk, we explore the threat model space of ML algorithms through the lens of Saltzer and Schroede

Leonardo de P. Carvalho, Jonathan M. Palma, Lucas P. Moreira, Alim P. C. Gonçalves

In this work, we present an analysis of the Burst failure effect in the $H_\infty$ norm. We present a procedure to perform an analysis between different Markov Chain models and a numerical example. In the numerical example the results obtained pointed out that the burst failure effect in the performance does not exceed 6.3%. However, this work is an introduc

Axel Sauer, Nikolay Savinov, Andreas Geiger

Most existing approaches to autonomous driving fall into one of two categories: modular pipelines, that build an extensive model of the environment, and imitation learning approaches, that map images directly to control outputs. A recently proposed third paradigm, direct perception, aims to combine the advantages of both by using a neural network to learn ap

Sebastian Neumayer, Johannes Persch, Gabriele Steidl

This paper addresses the solution of inverse problems in imaging given an additional reference image. We combine a modification of the discrete geodesic path model for image metamorphosis with a variational model,actually the $L^2$-$TV$ model, for image reconstruction. We prove that the space continuous model has a minimizer which depends in a stable way fro

Qian Feng, Sing Kiong Nguang, Alexandre Seuret

In this paper, we present a new method for the dissipativity and stability analysis of a linear coupled differential-difference system (CDDS) with general distributed delays at both state and output. More precisely, the distributed delay terms under consideration can contain any $\fL^{2}$ functions which are approximated via a class of elementary functions w

Hans Kersting, Philipp Hennig

There is resurging interest, in statistics and machine learning, in solvers for ordinary differential equations (ODEs) that return probability measures instead of point estimates. Recently, Conrad et al. introduced a sampling-based class of methods that are &#39;well-calibrated&#39; in a specific sense. But the computational cost of these methods is signific

Souvik Kundu, Tushar Khot, Ashish Sabharwal, Peter Clark

We propose a novel, path-based reasoning approach for the multi-hop reading comprehension task where a system needs to combine facts from multiple passages to answer a question. Although inspired by multi-hop reasoning over knowledge graphs, our proposed approach operates directly over unstructured text. It generates potential paths through passages and scor

Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin

We consider the problem of aligning continuous word representations, learned in multiple languages, to a common space. It was recently shown that, in the case of two languages, it is possible to learn such a mapping without supervision. This paper extends this line of work to the problem of aligning multiple languages to a common space. A solution is to inde

Ekaterina Brui, Aleksandr Y. Efimtcev, Vladimir A. Fokin, Remi Fernandez

The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensured optimal performance in the presence of a limited amount of training data. The CNN was trained and validate

Arun Ganesh, Qiuyi Zhang

We consider the phylogenetic tree reconstruction problem with insertions and deletions (indels). Phylogenetic algorithms proceed under a model where sequences evolve down the model tree, and given sequences at the leaves, the problem is to reconstruct the model tree with high probability. Traditionally, sequences mutate by substitution-only processes, althou

Yong Huang, Yi Bu, Ying Ding, Wei Lu

This paper defines and explores the direct citations between citing publications (DCCPs) of a publication. We construct an ego-centered citation network for each paper that contains all of its citing papers and itself, as well as the citation relationships among them. By utilizing a large-scale scholarly dataset from the computer science field in the Microso

Peter J. Haine

Let $P$ be a poset. We define a new homotopy theory of suitably nice $P$-stratified topological spaces with equivalences on strata and links inverted. We show that the exit-path construction of MacPherson, Treumann, and Lurie defines an equivalence from our homotopy theory of $P$-stratified topological spaces to the $\infty$-category of $\infty$-categories w

Xing Niu, Weijia Xu, Marine Carpuat

We aim to better exploit the limited amounts of parallel text available in low-resource settings by introducing a differentiable reconstruction loss for neural machine translation (NMT). This loss compares original inputs to reconstructed inputs, obtained by back-translating translation hypotheses into the input language. We leverage differentiable sampling

Ilona Ambartsumyan, Eldar Khattatov, Jan M. Nordbotten, Ivan Yotov

We develop a multipoint stress mixed finite element method for linear elasticity with weak stress symmetry on quadrilateral grids, which can be reduced to a symmetric and positive definite cell centered system. The method is developed on simplicial grids in [4]. The method utilizes the lowest order Brezzi-Douglas-Marini finite element spaces for the stress a

Elena S. Dimitrova, Qijun He, Brandilyn Stigler, Anyu Zhang

Model selection based on experimental data is an important challenge in biological data science. Particularly when collecting data is expensive or time consuming, as it is often the case with clinical trial and biomolecular experiments, the problem of selecting information-rich data becomes crucial for creating relevant models. We identify geometric properti

T. Koide, T. Kodama

The interplay between quantum fluctuation and spacetime curvature is shown to induce an additional quantum-curvature (QC) term in the energy-momentum tensor of fluid using the generalized framework of the stochastic variational method (SVM). The QC term is necessary to satisfy the momentum conservation but the corresponding quantum hydrodynamics is not neces

Matt Wala, Andreas Klöckner

We develop an algorithm for the asymptotically fast evaluation of layer potentials close to and on the source geometry, combining Geometric Global Accelerated QBX (`GIGAQBX&#39;) and target-specific expansions. GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX&#39;) using local expansions formed via

N. Fraija, M. Araya, A. Galvan-Gamez, J. A. de Diego

Centaurus B (Cen B) is one of the closest and brightest radio-loud galaxy in the southern sky. This radio galaxy, proposed as a plausible candidate for accelerating ultra-high-energy cosmic rays (UHECRs), is near the highest-energy neutrino event reported (IC35) in the High-Energy Starting Events catalog. Pierre Auger observatory reported the highest energy

Michael Kemeny

We explore the concept of projections of syzygies and prove two new technical results; we firstly give a precise characterization of syzygy schemes in terms of their projections, secondly, we prove a converse to Aprodu&#39;s Projection Theorem. Applying these results, we prove that extremal syzygies of general curves of non-maximal gonality embedded by a lin

Athanasios G. Tzikas

In the present paper we try to connect the Bardeen black hole with the concept of the recently proposed black hole chemistry. We study thermodynamic properties of the regular black hole with an anti-deSitter background. The negative cosmological constant $\Lambda$ plays the role of the positive thermodynamic pressure of the system. After studying the thermod

Laura Classen, Neil J. Robinson, Alexei M. Tsvelik

In the nested limit of the spin-fermion model for the cuprates, one-dimensional physics in the form of half-filled two-leg ladders emerges. We show that the renormalization group flow of the corresponding ladder is towards the d-Mott phase, a gapped spin-liquid with short-ranged d-wave pairing correlations, and reveals an intermediate SO(5)$\times$SO(3) symm

Cole Franks

A $k$-permutation family on $n$ vertices is a set system consisting of the intervals of $k$ permutations of the integers $1$ through $n$. The discrepancy of a set system is the minimum over all red-blue vertex colorings of the maximum difference between the number of red and blue vertices in any set in the system. In 2011, Newman and Nikolov disproved a conj

Dominic Joyce, Yuuji Tanaka, Markus Upmeier

Let $X$ be a compact manifold, $D$ a real elliptic operator on $X$, $G$ a Lie group, $P\to X$ a principal $G$-bundle, and ${\mathcal B}_P$ the infinite-dimensional moduli space of all connections $\nabla_P$ on $P$ modulo gauge, as a topological stack. For each $[\nabla_P]\in{\mathcal B}_P$, we can consider the twisted elliptic operator $D^{\nabla_{Ad(P)}}$ o

Huy Phan, Oliver Y. Chén, Philipp Koch, Lam Pham

Due to the variability in characteristics of audio scenes, some scenes can naturally be recognized earlier than others. In this work, rather than using equal-length snippets for all scene categories, as is common in the literature, we study to which temporal extent an audio scene can be reliably recognized given state-of-the-art models. Moreover, as model fu

V. Marín, H. Pinedo

In this article, we introduce the concept of partial groupoid actions on R- semicategories as well as we give criteria for existence of a globalization of it. This point of view is a generalization of the notions of partial groupoid actions on rings and partial group action on an R-semicategory. We also define the notions of partial skew groupoid category, s

Huy Phan, Oliver Y. Chén, Philipp Koch, Lam Pham

We propose a multi-label multi-task framework based on a convolutional recurrent neural network to unify detection of isolated and overlapping audio events. The framework leverages the power of convolutional recurrent neural network architectures; convolutional layers learn effective features over which higher recurrent layers perform sequential modelling. F

Dor Muhlgay, Jonathan Herzig, Jonathan Berant

Training models to map natural language instructions to programs given target world supervision only requires searching for good programs at training time. Search is commonly done using beam search in the space of partial programs or program trees, but as the length of the instructions grows finding a good program becomes difficult. In this work, we propose

Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez

Traditional hyperspectral unmixing methods neglect the underlying variability of spectral signatures often observed in typical hyperspectral images (HI), propagating these missmodeling errors throughout the whole unmixing process. Attempts to model material spectra as members of sets or as random variables tend to lead to severely ill-posed unmixing problems

Li Li, Yan Yan Li, Xukai Yan

$(-1)$-homogeneous axisymmetric no-swirl solutions of three dimensional incompressible stationary Navier-Stokes equations which are smooth on the unit sphere minus the north and south poles have been classified, %as a four parameter family for each viscosity. In this paper we study the vanishing viscosity limit of sequences of these solutions. As the viscosi

Jason Phang, Thibault Févry, Samuel R. Bowman

Pretraining sentence encoders with language modeling and related unsupervised tasks has recently been shown to be very effective for language understanding tasks. By supplementing language model-style pretraining with further training on data-rich supervised tasks, such as natural language inference, we obtain additional performance improvements on the GLUE

Bai Xue, Martin Fränzle, Naijun Zhan

In this paper we propose a convex programming based method to address a long-standing problem of inner-approximating backward reachable sets of state-constrained polynomial systems subject to time-varying uncertainties. The backward reachable set is a set of states, from which all trajectories starting will surely enter a target region at the end of a given

Scott C. Merrill, Christopher J. Koliba, Susan M. Moegenburg, Asim Zia

Livestock industries are vulnerable to disease threats, which can cost billions of dollars and have substantial negative social ramifications. Losses are mitigated through increased use of disease-related biosecurity practices, making increased biosecurity an industry goal. Currently, there is no industry-wide standard for sharing information about disease i

Siddhartha Santra, Liang Jiang, Vladimir Malinovsky

We propose a quantum repeater protocol and architecture that mitigates decoherence of the entangled states by optimizing the quantum memory buffer time. The protocol maximizes the rate of distillable entanglement in the average accessed state at all nesting levels. The achievable rate is higher by orders of magnitude in comparison to a canonical protocol tha

Will Ma, David Simchi-Levi, Jinglong Zhao

This work is motivated by our collaboration with a large consumer packaged goods (CPG) company. We have found that while the company appreciates the advantages of dynamic pricing, they deem it operationally much easier to plan out a static price calendar in advance. We investigate the efficacy of static control policies for revenue management problems whose

Rajen D. Shah, Benjamin Frot, Gian-Andrea Thanei, Nicolai Meinshausen

In this work we consider the problem of estimating a high-dimensional $p \times p$ covariance matrix $Σ$, given $n$ observations of confounded data with covariance $Σ+ ΓΓ^T$, where $Γ$ is an unknown $p \times q$ matrix of latent factor loadings. We propose a simple and scalable estimator based on the projection on to the right singular vectors of the observe

Kenneth A. Watanabe

The Goldbach conjecture states that every even integer greater than 2 can be expressed as the sum of two prime numbers. This conjecture was first proposed by German mathematician Christian Goldbach in 1742 and, despite being obviously true, has remained unproven. In this paper, it is shown that the set of all even integers n that are not divisible by a prime

Vincent Kurtz, Hai Lin

Next generation Unmanned Aerial Vehicles (UAVs) must reliably avoid moving obstacles. Existing dynamic collision avoidance methods are effective where obstacle trajectories are linear or known, but such restrictions are not accurate to many real-world UAV applications. We propose an efficient method of predicting an obstacle&#39;s motion based only on recent

K. Y. Oyulmaz, A. Senol, H. Denizli, A. Yilmaz

We study the anomalous FCNC $tqγ$ and $tqg$ couplings via $pp\to Wbγ+X$ signal process including realistic detector effects for both leptonic and hadronic decay channels of the W boson at 100 TeV FCC-hh. The relevant background are considered in the cut based analysis to obtain not only limits on the anomalous $λ$ and $ζ$ couplings but also branching ratios

Leonard W. T. Ng, Xiaoxi Zhu, Guohua Hu, Nasiruddin Macadam

Printing has drawn a lot of attention as a means of low per-unit cost and high throughput patterning of graphene inks for scaled-up thin-form factor device manufacturing. However, traditional printing processes require a flat surface and are incapable of achieving patterning on to 3D objects. Here, we present a conformal printing method to achieve functional

Thomas Krämer

We show that the only summands of theta divisors on Jacobians of curves and on intermediate Jacobians of cubic threefolds are the obvious powers of the curve and the Fano surface of lines on the threefold. The proof uses the decomposition theorem for perverse sheaves, a bit of representation theory and a computation of characteristic cycles for Brill-Noether

Yong Wang

Truly concurrent process algebras are generalizations to the traditional process algebras for true concurrency, CTC to CCS, APTC to ACP, $\pi_{tc}$ to $\pi$ calculus, APPTC to probabilistic process algebra. Now, it is the time to utilize truly concurrent process algebras APTC and APPTC to model quantum computing and unify quantum and classical computing. In

Kathryn L. Nicolich, Clinton Cahall, Nurul T. Islam, Gregory P. Lafyatis

We describe an electrothermal model for the turn-on dynamics of superconducting nanowire single-photon detectors (SNSPDs). By extracting a scaling law from a well-known electrothermal model of SNSPDs, we show that the rise-time of the readout signal encodes the photon number as well as the length of the nanowire with scaling $t_\text{rise}\propto \sqrt{\ell/

Aaron J. Goodman, Der-Hsien Lien, Geun Ho Ahn, Leo L. Spiegel

Atomically thin semiconductors such as monolayer MoS2 and WS2 exhibit nonlinear exciton-exciton annihilation at notably low excitation densities (below ~10 excitons/um2 in MoS2). Here, we show that the density threshold at which annihilation occurs can be tuned by changing the underlying substrate. When the supporting substrate is changed from SiO2 to Al2O3

Nouha Dziri, Ehsan Kamalloo, Kory W. Mathewson, Osmar Zaiane

Sequence-to-Sequence (Seq2Seq) models have witnessed a notable success in generating natural conversational exchanges. Notwithstanding the syntactically well-formed responses generated by these neural network models, they are prone to be acontextual, short and generic. In this work, we introduce a Topical Hierarchical Recurrent Encoder Decoder (THRED), a nov

Matthias Lalisse, Paul Smolensky

Neural models of Knowledge Base data have typically employed compositional representations of graph objects: entity and relation embeddings are systematically combined to evaluate the truth of a candidate Knowedge Base entry. Using a model inspired by Harmonic Grammar, we propose to tokenize triplet embeddings by subjecting them to a process of optimization

Stephen Page, Steffen Grünewälder

We study an adaptive estimation procedure called the Goldenshluger-Lepski method in the context of reproducing kernel Hilbert space (RKHS) regression. Adaptive estimation provides a way of selecting tuning parameters for statistical estimators using only the available data. This allows us to perform estimation without making strong assumptions about the esti

Bin Wang, Xinyuan Wu, Yonglei Fang

The study of the long time conservation for numerical methods poses interesting and challenging questions from the point of view of geometric integration. In this paper, we analyze the long time energy and magnetic moment conservations of two-step symmetric methods for charged-particle dynamics. A two-step symmetric method is proposed and its long time behav

Giovanni Gaiffi, Viola Siconolfi

For any triple given by a positive integer n, a finite group G, and a faithful representation V of G, one can describe a subspace arrangement whose intersection lattice is a generalized Dowling lattice in the sense of Hanlon. In this paper we construct the minimal De Concini-Procesi wonderful model associated to this subspace arrangement and give a descripti

Mikhail Hayhoe, Francisco Barreras, Hamed Hassani, Victor M. Preciado

Network alignment consists of finding a structure-preserving correspondence between the nodes of two correlated, but not necessarily identical, networks. This problem finds applications in a wide variety of fields, from the alignment of proteins in computational biology, to the de-anonymization of social networks, as well as recognition tasks in computer vis

Cédric Pilatte

Let $S$ be a set of $n\geq 7$ points in the plane, no three of which are collinear. Suppose that $S$ determines $n+1$ directions. That is to say, the segments whose endpoints are in $S$ form $n+1$ distinct slopes. We prove that $S$ is, up to an affine transformation, equal to $n$ of the vertices of a regular $(n+1)$-gon. This result was conjectured in 1986 b

C. Spiniello, A. Agnello, A. V. Sergeyev, T. Anguita

Gravitationally lensed quasars are valuable, but extremely rare, probes of observational cosmology and extragalactic astrophysics. Progress in these fields has been limited just by the paucity of systems with good ancillary data. Here we present a first spectroscopic confirmation of lenses discovered in the Southern Sky from the DES and KiDS-DR3 footprints.

Xiaoxiao Li, Junyan Wu, Eric Z. Chen, Hongda Jiang

Melanoma is a type of skin cancer with the most rapidly increasing incidence. Early detection of melanoma using dermoscopy images significantly increases patients&#39; survival rate. However, accurately classifying skin lesions by eye, especially in the early stage of melanoma, is extremely challenging for the dermatologists. Hence, the discovery of reliable

Sylvie Corteel, Olya Mandelshtam, Lauren Williams

The asymmetric simple exclusion exclusion process (ASEP) is a model of particles hopping on a one-dimensional lattice of n sites. It was introduced around 1970, and since then has been extensively studied by researchers in statistical mechanics, probability, and combinatorics. Recently the ASEP on a lattice with open boundaries has been linked to Koornwinder

Giovanna Guidoboni, Lorenzo Sala, Moein Enayati, Riccardo Sacco

Objective: to develop quantitative methods for the clinical interpretation of the ballistocardiogram (BCG). Methods: a closed-loop mathematical model of the cardiovascular system is proposed to theoretically simulate the mechanisms generating the BCG signal, which is then compared with the signal acquired via accelerometry on a suspended bed. Results: simula

Gabriel Khan

The purpose of this note is to study the complex structures orthogonal to a given Riemannian metric. For another paper on this topic, we highly recommend the work of Salamon. His work describes in great detail the role that curvature plays in this question. We instead focus on torsion, which lends itself to somewhat different analysis of the problem. In term

Tiago Pestana, Stefan Hickel

Transition from a split to a forward kinetic energy cascade system is explored in the context of rotating turbulence using direct numerical simulations with a three-dimensional isotropic random force uncorrelated with the velocity field. Our parametric study covers confinement effects in large aspect ratio domains and a broad range of rotation rates. Results

A. Di Canto, J. Garra Ticó, T. Gershon, N. Jurik

We propose a novel method to measure flavor-oscillations and charge-parity (CP) violation in charm mixing. The approach uses multibody charm decays, such as $D^0\to K_S^0π^+π^-$, and avoids the need for a fit of the decay amplitudes while suppressing biases due to nonuniform signal-reconstruction efficiencies as functions of phase space and decay time. Data

Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Rehan Ahmed

Most of the data manipulation attacks on deep neural networks (DNNs) during the training stage introduce a perceptible noise that can be catered by preprocessing during inference or can be identified during the validation phase. Therefore, data poisoning attacks during inference (e.g., adversarial attacks) are becoming more popular. However, many of them do

Oreste Pezzi, Francesco Valentini, Sergio Servidio, Enrico Camporeale

Turbulence at kinetic scales is an unresolved and ubiquitous phenomenon that characterizes both space and laboratory plasmas. Recently, new theories, {\it in-situ} spacecraft observations and numerical simulations suggest a novel scenario for turbulence, characterized by a so-called phase space cascade -- the formation of fine structures, both in physical an

Chengcheng Fang, Jinxing Li, Minghao Zhang, Yihui Zhang

Inactive lithium (Li) formation is the immediate cause of capacity loss and catastrophic failure of Li metal batteries. However, the chemical component and the atomic level structure of inactive Li have rarely been studied due to the lack of effective diagnosis tools to accurately differentiate and quantify Li+ in solid electrolyte interphase (SEI) component

Yanfang Ye, Shifu Hou, Lingwei Chen, Jingwei Lei

The explosive growth and increasing sophistication of Android malware call for new defensive techniques that are capable of protecting mobile users against novel threats. In this paper, we first extract the runtime Application Programming Interface (API) call sequences from Android apps, and then analyze higher-level semantic relations within the ecosystem t

C. C. Homes, S. Khim, A. P. Mackenzie

The temperature dependence of the optical properties of the delafossite PdCoO$_2$ has been measured in the a-b planes over a wide frequency range. The optical conductivity due to the free-carrier (intraband) response falls well below the interband transitions, allowing the plasma frequency to be determined from the $f$-sum rule. Drude-Lorentz fits to the com

Sachin J. Valera

We give an exposition of how the Kauffman bracket arises for certain systems of anyons, and do so outside the usual arena of Temperley-Lieb-Jones categories. This is further elucidated through the discussion of the Iwahori-Hecke algebra and its relation to modular tensor categories. We then proceed to classify the framed link-invariants associated to a syste

Sylvie Corteel, Olya Mandelshtam, Lauren Williams

Recently James Martin introduced multiline queues, and used them to give a combinatorial formula for the stationary distribution of the multispecies asymmetric simple exclusion exclusion process (ASEP) on a circle. The ASEP is a model of particles hopping on a one-dimensional lattice, which was introduced around 1970, and has been extensively studied in stat

Shahar Hadar

Black holes display universal behavior near extremality. One such feature is the late-time blowup of derivatives of linearized perturbations across the horizon. For generic initial data, this instability is regulated by backreaction, and the final state is a near-extremal black hole. The aim of this paper is to study the late time behavior of such black hole

Duff Neill, Wouter J. Waalewijn

Scattering processes often inevitably include the production of infrared states, which are highly correlated with the hard scattering event, and decohere the hard states. This can be described using the entropy of the hard reduced density matrix, which is obtained from tracing over infrared states. We determine this entropy for an asymptotically-free gauge t

Niclas Westerberg, Angus Prain, Daniele Faccio, Patrik Öhberg

Recent progress in photonics has led to a renewed interest in time-varying media that change on timescales comparable to the optical wave oscillation time. However, these studies typically overlook the role of material dispersion that will necessarily imply a delayed temporal response or, stated alternatively, a memory effect. We investigate the influence of

Peng Shi, Jinfeng Rao, Jimmy Lin

This paper explores the problem of ranking short social media posts with respect to user queries using neural networks. Instead of starting with a complex architecture, we proceed from the bottom up and examine the effectiveness of a simple, word-level Siamese architecture augmented with attention-based mechanisms for capturing semantic &#34;soft&#34; matche

Andrei Neguţ

We prove a conjecture of Kuznetsov stating that the equivariant K-theory of affine Laumon spaces is the universal Verma module for the quantum affine algebra U_q(gl_n^). We do so by reinterpreting the action of the quantum toroidal algebra U_q(gl_n^^) on the K-theory from [14] in terms of the shuffle algebra studied in [12], which constructs an embedding of

Daniel Elander, Maurizio Piai, John Roughley

We reconsider a one-parameter class of known solutions of the circle compactification of Romans six-dimensional half-maximal supergravity. The gauge-theory duals of these solutions are confining four-dimensional field theories. Their UV completions consist of the compactification on a circle of a higher-dimensional field theory that is flowing between two fi

Yoshitaka Saiki, Hiroki Takahasi, James A. Yorke

Chaotic dynamics can be quite heterogeneous in the sense that in some regions the dynamics are unstable in more directions than in other regions. When trajectories wander between these regions, the dynamics is complicated. We say a chaotic invariant set is heterogeneous when arbitrarily close to each point of the set there are different periodic points with

A. Yu. Okulov

Square vortex lattices predicted theoretically and experimentally observed in diode-pumped solid state microchip lasers are shown to have a remarkable symmetry. These lattices are formed by counter-rotating vortices. The interaction of vortices with nonlinear gain medium leads to precession of vortices and collective excitations with dynamics identical to ac

Gary Kennedy, Lee McEwan

We give a recursive formula, expressed in terms of the characteristic tuples, for the Betti numbers of the boundary of the Milnor fiber of an irreducible quasi-ordinary surface. The singular locus of the surface consists of two components, and for each component we introduce a sequence of increasingly simpler surfaces. Our recursion depends on a detailed com

Lewis A. Clark, Adam Stokes, Almut Beige

Quantum metrology exploits quantum correlations in specially prepared entangled or other non-classical states to perform measurements that exceed the standard quantum limit. Typically though, such states are hard to engineer, particularly when larger numbers of resources are desired. As an alternative, this paper aims to establish quantum jump metrology whic