April 2019 arXiv papers — page 110

Cecile Monthus

In various disordered systems or non-equilibrium dynamical models, the large deviations of some observables have been found to display different scalings for rare values bigger or smaller than the typical value. In the present paper, we revisit the simpler observables based on independent random variables, namely the empirical maximum, the empirical average,

Z. J. Ajaltouni, E. Di Salvo

We consider two-body and quasi-two-body decays of the type $f_1 \to f_2 B$, where $f_1$ and $f_2$ are spin-1/2 fermions and $B$ a spin-0 or spin-1 boson. After recalling the non-covariant formalism for decay amplitudes, we derive the expression of the differential decay width and of the polarizations of the final spinning particles, both on- and off-shell. W

Belle Collaboration, S. Wehle, I. Adachi, K. Adamczyk

We present a measurement of $R_{K^{\ast}}$, the branching fraction ratio ${{\cal B}(B\to K^\ast μ^+ μ^-)}$/ ${{\cal B}(B\to K^\ast e^+ e^-)}$, for both charged and neutral $B$ mesons. The ratio for the charged case, $R_{K{^{\ast +}}}$, is the first measurement ever performed. In addition, we report absolute branching fractions for the individual modes in bin

Assaf Rabinowicz, Saharon Rosset

K-fold cross-validation (CV) with squared error loss is widely used for evaluating predictive models, especially when strong distributional assumptions cannot be taken. However, CV with squared error loss is not free from distributional assumptions, in particular in cases involving non-i.i.d. data. This paper analyzes CV for correlated data. We present a cri

S. Franca, D. V. Efremov, I. C. Fulga

Two-dimensional second-order topological superconductors (SOTSCs) have gapped bulk and edge states, with zero-energy Majorana bound states localized at corners. Motivated by recent advances in Majorana nanowire experiments, we propose to realize a tunable SOTSC as a two-dimensional nanowire array. We show that the coupling between the Majorana modes of adjac

Kai Olav Ellefsen, Jim Torresen

A long-standing challenge in Reinforcement Learning is enabling agents to learn a model of their environment which can be transferred to solve other problems in a world with the same underlying rules. One reason this is difficult is the challenge of learning accurate models of an environment. If such a model is inaccurate, the agent's plans and actions w

Alexander J. Silenko, Pengming Zhang, Liping Zou

The analysis of twisted (vortex) paraxial photons and electrons is fulfilled in the framework of relativistic quantum mechanics. The use of the Foldy-Wouthuysen representation radically simplifies a description of relativistic electrons and clarifies fundamental properties of twisted particles. It is demonstrated that the twisted photon defined by the Laguer

Maxim Olshanii, Yuri Styrkas, Dmitry Yampolsky, Vanja Dunjko

We present a new class of electrostatics problems that are exactly solvable by adding finitely many image charges. Given a charge at some location inside a cavity bounded by up to four conducting grounded segments of spheres: if the spheres have a symmetry derived via a stereographic projection from a 4D finite reflection group, then this is a solvable gener

Kirill Melnikov, Robbert Rietkerk, Lorenzo Tancredi, Christopher Wever

We compute the three-loop master integrals required for the calculation of the triple-real contribution to the N$^3$LO quark beam function due to the splitting of a quark into a virtual quark and three collinear gluons, $q \to q^*+ggg$. This provides an important ingredient for the calculation of the leading-color contribution to the quark beam function at N

Mohammad Reza Ahmadpour Monazam, Ursula Ludacka, Hannu-Pekka Komsa, Jani Kotakoski

We report the first observation of substitutional silicon atoms in single-layer hexagonal boron nitride (h-BN) using aberration corrected scanning transmission electron microscopy (STEM). The medium angle annular dark field (MAADF) images reveal silicon atoms exclusively filling boron vacancies. This structure is stable enough under electron beam for repeate

Elsa Desmaele, Nicolas Sator, Rodolphe Vuilleumier, Bertrand Guillot

Atomistic simulations provide a meaningful way to determine the physico-chemical properties of liquids in a consistent theoretical framework. This approach takes on particular usefulness for the study of molten carbonates, in a context where thermodynamic and transport data are crucially needed over a large domain of temperatures and pressures (to ascertain

James Avery, Mark Runciman, Ara Darzi, George P. Mylonas

Soft robotic systems offer benefits over traditional rigid systems through reduced contact trauma with soft tissues and by enabling access through tortuous paths in minimally invasive surgery. However, the inherent deformability of soft robots places both a greater onus on accurate modelling of their shape, and greater challenges in realising intraoperative

Hongyu Chen, Li Jiang

Ubiquitous anomalies endanger the security of our system constantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However,

Okan Köpüklü, Neslihan Kose, Ahmet Gunduz, Gerhard Rigoll

Recently, convolutional neural networks with 3D kernels (3D CNNs) have been very popular in computer vision community as a result of their superior ability of extracting spatio-temporal features within video frames compared to 2D CNNs. Although there has been great advances recently to build resource efficient 2D CNN architectures considering memory and powe

Quentin Jodelet, Vincent Gripon, Masafumi Hagiwara

In this paper, we introduce a novel layer designed to be used as the output of pre-trained neural networks in the context of classification. Based on Associative Memories, this layer can help design Deep Neural Networks which support incremental learning and that can be (partially) trained in real time on embedded devices. Experiments on the ImageNet dataset

Hidefumi Matsuda, Teiji Kunihiro, Akira Ohnishi, Toru T. Takahashi

We investigate the shear viscosity of massless classical scalar fields in the $ϕ^4$ theory on a lattice by using the Green-Kubo formula. Based on the scaling property of the classical field, the shear viscosity is represented using a scaling function. Equilibrium expectation value of the time-correlation function of the energy-momentum tensor is evaluated as

Luai Al-Labadi, Forough Fazeli Asl, Zahra Saberi

In this paper, a novel Bayesian nonparametric test for assessing multivariate normal models is presented. While there are extensive frequentist and graphical methods for testing multivariate normality, it is challenging to find Bayesian counterparts. The proposed approach is based on the use of the Dirichlet process and Mahalanobis distance. More precisely,

Andrea Di Sorbo, Gerardo Canfora, Sebastiano Panichella

Context: Addressing user requests in the form of bug reports and Github issues represents a crucial task of any successful software project. However, user-submitted issue reports tend to widely differ in their quality, and developers spend a considerable amount of time handling them. Objective: By collecting a dataset of around 6,000 issues of 279 GitHub pro

Pietro Milici

In La Géométrie, Descartes proposed a balance between geometric constructions and symbolic manipulation with the introduction of suitable ideal machines. In modern terms, that is a balance between analog and symbolic computation. Descartes' geometric foundational approach (analysis without infinitary objects and synthesis with diagrammatic constructions)

Kazuyoshi Yoshimi, Makoto Naka, Hitoshi Seo

We theoretically study finite temperature properties of interacting fermion systems under geometrical frustration in the charge degree of freedom. Physical quantities such as charge structure factors, the specific heat, and the entropy, of the two-dimensional model of interacting spinless fermions on an anisotropic triangular lattice are numerically calculat

Pavel Paták, Martin Tancer

We improve the bound on Kühnel's problem to determine the smallest $n$ such that the $k$-skeleton of an $n$-simplex $Δ_n^{(k)}$ does not embed into a compact PL $2k$-manifold $M$ by showing that if $Δ_n^{(k)}$ embeds into $M$, then $n\leq (2k+1)+(k+1)β_k(M;\mathbb Z_2)$. As a consequence we obtain improved Radon and Helly type results for set systems in

J. Mathiaud, Luc Mieussens

We propose two models of the Boltzmann equation (BGK and Fokker-Planck models) for rarefied flows of diatomic gases in vibrational non-equilibrium. These models take into account the discrete repartition of vibration energy modes, which is required for high temperature flows, like for atmospheric re-entry problems. We prove that these models satisfy conserva

Prince Zizhuang Wang, William Yang Wang

Recurrent Variational Autoencoder has been widely used for language modeling and text generation tasks. These models often face a difficult optimization problem, also known as the Kullback-Leibler (KL) term vanishing issue, where the posterior easily collapses to the prior, and the model will ignore latent codes in generative tasks. To address this problem,

Zu-Cheng Chen, Qing-Guo Huang

We investigate how the next generation gravitational-wave (GW) detectors, such as Einstein Telescope (ET) and Cosmic Explorer (CE), can be used to distinguish primordial black holes (PBHs) from astrophysical black holes (ABHs). Since a direct detection of sub-solar mass black holes can be taken as the smoking gun for PBHs, we figure out the detectable limits

Jaume Haro

The gravitational production of superheavy dark matter, in the Peebles-Vilenkin quintessential inflation model, is studied in two different scenarios: When the particles, whose decay products reheat the universe after the end of the inflationary period, are created gravitationally, and when are produced via instant preheating. We show that the viability of b

Xiaoli Han, Hikaru Yamamoto

In this paper, we study the line bundle mean curvature flow defined by Jacob and Yau. The line bundle mean curvature flow is a kind of parabolic flows to obtain deformed Hermitian Yang-Mills metrics on a given Kähler manifold. The goal of this paper is to give an $\varepsilon$-regularity theorem for the line bundle mean curvature flow. To establish the theor

Linyu Peng, Zhenning Zhang

This paper mainly contributes to a classification of statistical Einstein manifolds, namely statistical manifolds at the same time are Einstein manifolds. A statistical manifold is a Riemannian manifold, each of whose points is a probability distribution. With the Fisher information metric as a Riemannian metric, information geometry was developed to underst

Jean Ginibre, Martine Le Berre, Yves Pomeau

It is well-known that the circulation of the velocity field of a fluid along a closed material curve is conserved for any solution of the Euler equation. We offer a slightly more explicit proof of that fact than that generally found in the literature. We then rewrite that property in terms of the rescaled variables and functions leading to the Euler-Leray eq

Duo Wang, Yu Cheng, Mo Yu, Xiaoxiao Guo

Few-shot learning aims to learn classifiers for new classes with only a few training examples per class. Most existing few-shot learning approaches belong to either metric-based meta-learning or optimization-based meta-learning category, both of which have achieved successes in the simplified "$k$-shot $N$-way" image classification settings. Specific

Sannyuya Liu, Zhonghua Yan, Xiufeng Cheng, Liang Zhao

As one of the classic models that describe the belief dynamics over social networks, a non-Bayesian social learning model assumes that members in the network possess accurate signal knowledge through the process of Bayesian inference. In order to make the non-Bayesian social learning model more applicable to human and animal societies, this paper extended th

Kousuke Ihara, Kenichi Kasamatsu

We study transverse instability and disintegration dynamics of a domain wall of a relative phase in two-component Bose-Einstein condensates with a coherent Rabi coupling. We obtain analytically the stability phase diagram of the stationary solution of the domain wall for the one-dimensional coupled Gross-Pitaevskii equations in the plane of the Rabi frequenc

Jiyoung Han

The celebrated result of Eskin, Margulis and Mozes (1998) and Dani and Margulis (1993) on quantitative Oppenheim conjecture says that for irrational quadratic forms $q$ of rank at least 5, the number of integral vectors $\mathbf v$ such that $q(\mathbf v)$ is in a given bounded interval is asymptotically equal to the volume of the set of real vectors $\mathb

Alexandre Boulch

Point clouds are unstructured and unordered data, as opposed to images. Thus, most machine learning approach developed for image cannot be directly transferred to point clouds. In this paper, we propose a generalization of discrete convolutional neural networks (CNNs) in order to deal with point clouds by replacing discrete kernels by continuous ones. This f

Najmuddin Fakhruddin, Chandrashekhar Khare, Stefan Patrikis

We study irreducible odd mod $p$ Galois representations $\barρ \colon \mathrm{Gal}(\overline{F}/F) \to G(\overline{\mathbb{F}}_p)$, for $F$ a totally real number field and $G$ a general reductive group. For $p \gg_{G, F} 0$, we show that any $\barρ$ that lifts locally, and at places above $p$ to de Rham and Hodge-Tate regular representations, has a geometric

N. K. Sahu

To improve the numerical efficiency of iterative algorithms for inverting the frame operator, the controlled frame was introduced by Balazs et al. \cite{Balazs}, and has since been given more importance. In this paper, we introduce the concept of controlled g-frames in Hilbert $C^{*}$-modules. We establish the equivalent condition for controlled $g$-frame us

Fatemeh Rajabi-Alni, Alireza Bagheri, Behrouz Minaei-Bidgoli

Given two sets S and T, a limited-capacity many-to-many matching (LCMM) between S and T matches each element p in S (resp. T) to at least 1 and at most Cap(p) elements in T (resp. S), where the function Cap:S\cup T-> Z>0 denotes the capacity of p. In this paper, we present the first linear time algorithm for finding a minimum-cost one-dimensional LCMM (OLCMM

Sergii Grytsiuk, Jan-Philipp Hanke, Markus Hoffmann, Juba Bouaziz

Two hundred years ago, André-Marie Ampère discovered that electric loops in which currents of electrons are generated by a penetrating magnetic field can interact with each other. Here we show that Ampère's observation can be transferred to the quantum realm of interactions between triangular plaquettes of spins on a lattice, where the electrical current

Nikos Leonardos, Stefanos Leonardos, Georgios Piliouras

To participate in the distributed consensus of permissionless blockchains, prospective nodes -- or miners -- provide proof of designated, costly resources. However, in contrast to the intended decentralization, current data on blockchain mining unveils increased concentration of these resources in a few major entities, typically mining pools. To study strate

Vladimir Nekrasov, Chunhua Shen, Ian Reid

Automatic search of neural architectures for various vision and natural language tasks is becoming a prominent tool as it allows to discover high-performing structures on any dataset of interest. Nevertheless, on more difficult domains, such as dense per-pixel classification, current automatic approaches are limited in their scope - due to their strong relia

Jin-Yi Cai, Zhiguo Fu, Shuai Shao

We define and explore a notion of unique prime factorization for constraint functions, and use this as a new tool to prove a complexity classification for counting weighted Eulerian orientation problems with arrow reversal symmetry (ARS). We prove that all such problems are either polynomial-time computable or #P-hard. We show that the class of weighted Eule

Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, William G. Macready

Domain shift is unavoidable in real-world applications of object detection. For example, in self-driving cars, the target domain consists of unconstrained road environments which cannot all possibly be observed in training data. Similarly, in surveillance applications sufficiently representative training data may be lacking due to privacy regulations. In thi

Isamu Iwanari

In this paper, we provide a conceptual new construction of the algebraic structure on the pair of the Hochschild cohomology spectrum (cochain complex) and Hochschild homology spectrum, which is analogous to the structure of calculus on a manifold. This algebraic structure is encoded by a two-colored operad introduced by Kontsevich and Soibelman. We prove tha

Seraphina Goldfarb-Tarrant, Haining Feng, Nanyun Peng

Story composition is a challenging problem for machines and even for humans. We present a neural narrative generation system that interacts with humans to generate stories. Our system has different levels of human interaction, which enables us to understand at what stage of story-writing human collaboration is most productive, both to improving story quality

Pin Wai Koh, Tiem Leong Yoon, Thong Leng Lim, Yee Hui Robin Chang

The structural and electronic properties of ternary AlxTiyNiz clusters, where x, y, and z are integers and x + y + z = 6 are investigated. Both SVWN and B3LYP exchange-correlation functionals are employed in a two-stage density functional theory (DFT) calculations to generate these clusters. In the first stage, a minimum energy cluster structure is generated

Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-resolution output. However, this approach does not fully address the mutual dependencies of low- and high-resolution images. We propose Deep Back-Projection Networks (DBPN), the wi

Zhengyao Wu

Let $ K $ be a global function field of characteristic $ 2 $. For each non-trivial place $ v $ of $ K $, let $ K_{v} $ be the completion of $ K $ at $ v $. We show that if two non-degenerate quadratic forms are similar over every $ K_{v} $, then they are similar over $ K $. This provides an analogue of the version for characteristic not $ 2 $ previously obta

Zhenguo Yang, Zehang Lin, Min Cheng, Qing Li

In this work, we construct and release a multi-domain and multi-modality event dataset (MMED), containing 25,165 textual news articles collected from hundreds of news media sites (e.g., Yahoo News, Google News, CNN News.) and 76,516 image posts shared on Flickr social media, which are annotated according to 412 real-world events. The dataset is collected to

N. N. Achasov, G. N. Shestakov

The isospin-breaking decay $X(3872)\to(D^*\bar D+ \bar D^*D) \toπ^0D\bar D\toπ^0π^+π^-$ is discussed. In its amplitude there is a triangle logarithmic singularity, due to which the dominant contribution to $BR(X(3872)\toπ^0π^+π^-)$ comes from the production of the $π^+π^-$ system in a narrow interval of the invariant mass $m_{π^+π^-}$ near the value of $2m_{

Andrea Coladangelo

We describe a two-player non-local game, with a fixed small number of questions and answers, such that an $ε$-close to optimal strategy requires an entangled state of dimension $2^{Ω(ε^{-1/8})}$. Our non-local game is inspired by the three-player non-local game of Ji, Leung and Vidick [arXiv:1802.04926]. It reduces the number of players from three to two, as

Yasemin Kara, Ekin Ozman

Recent work of Freitas and Siksek showed that an asymptotic version of Fermat's Last Theorem holds for many totally real fields. Later this result was extended by Deconinck to generalized Fermat equations of the form $Ax^p +By^p +Cz^p = 0$, where A;B;C are odd integers belonging to a totally real field. Another extension was given by Sengun and Siksek.

Robin Jia, Cliff Wong, Hoifung Poon

Most information extraction methods focus on binary relations expressed within single sentences. In high-value domains, however, $n$-ary relations are of great demand (e.g., drug-gene-mutation interactions in precision oncology). Such relations often involve entity mentions that are far apart in the document, yet existing work on cross-sentence relation extr

Primitivo B. Acosta-Humánez, Kazuyuki Yagasaki

Codimension-two bifurcations are fundamental and interesting phenomena in dynamical systems. Fold-Hopf and double-Hopf bifurcations are the most important among them. We study the unfoldings of these two codimension-two bifurcations, and obtain sufficient conditions for their nonintegrability in the meaning of Bogoyavlenskij. We reduce the problems of the un

Weijia Xu, Xing Niu, Marine Carpuat

Despite some empirical success at correcting exposure bias in machine translation, scheduled sampling algorithms suffer from a major drawback: they incorrectly assume that words in the reference translations and in sampled sequences are aligned at each time step. Our new differentiable sampling algorithm addresses this issue by optimizing the probability tha

Ayman Elgharabawy, Mukesh Prasad, Chin-Teng Lin

This paper proposes a preference neural network (PNN) to address the problem of indifference preferences orders with new activation function. PNN also solves the Multi-label ranking problem, where labels may have indifference preference orders or subgroups are equally ranked. PNN follows a multi-layer feedforward architecture with fully connected neurons. Ea

Qianrui Zhang, Haoci Zhang, Thibault Sellam, Eugene Wu

Interactive tools make data analysis more efficient and more accessible to end-users by hiding the underlying query complexity and exposing interactive widgets for the parts of the query that matter to the analysis. However, creating custom tailored (i.e., precise) interfaces is very costly, and automated approaches are desirable. We propose a syntactic appr

Chunting Zhou, Xuezhe Ma, Di Wang, Graham Neubig

Recent approaches to cross-lingual word embedding have generally been based on linear transformations between the sets of embedding vectors in the two languages. In this paper, we propose an approach that instead expresses the two monolingual embedding spaces as probability densities defined by a Gaussian mixture model, and matches the two densities using a

Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata

Generating texts which express complex ideas spanning multiple sentences requires a structured representation of their content (document plan), but these representations are prohibitively expensive to manually produce. In this work, we address the problem of generating coherent multi-sentence texts from the output of an information extraction system, and in

Juan-Juan Niu, Lei Guo, Hong-Hao Ma, Xing-Gang Wu

We systematically analyzed the production of semi-inclusive doubly heavy baryons ($Ξ_{cc}$, $Ξ_{bc}$ and $Ξ_{bb}$) for the process $H^0 \rightarrow Ξ_{QQ'}+ \bar {Q'} + \bar {Q}$ through four main Higgs decay channels within the framework of non-relativistic QCD. The contributions from the intermediate diquark states, $\langle cc\rangle[^{1}S_{0}]_{\

Marco Bortolomasi, Arturo Ortiz-Tapia

Starting from the first Hardy-Littlewood conjecture some topics will be covered: an empirical approach to the distribution of the twin primes in classes mod(10) and a simplified proof of the Bruns theorem . Finally, it will be explored an approach based on numerical analysis: Monte Carlo Method and Low discrepancy Sequences will be used to prove the converge

Maruan Al-Shedivat, Ankur P. Parikh

Generalization and reliability of multilingual translation often highly depend on the amount of available parallel data for each language pair of interest. In this paper, we focus on zero-shot generalization---a challenging setup that tests models on translation directions they have not been optimized for at training time. To solve the problem, we (i) reform

Snehajit Misra, Nabanita Ray

In this article, we give a description of the closed cone of curves of the projective bundle $\mathbb{P}(E)$ over a smooth projective variety $X$. Using duality, we then calculate the nef cone of divisors in $\mathbb{P}(E)$ over some special surfaces $X$ and for some special bundles on $X$. As an application, we also calculate the Seshadri constants of semis

Zhaowei Zhang, Kohta Murase, Peter Mészáros

We calculate spectra of escaping cosmic rays (CRs) accelerated at shocks produced by expanding Galactic superbubbles powered by multiple supernovae producing a continuous energy outflow in star-forming galaxies. We solve the generalized Kompaneets equations adapted to expansion in various external density profiles, including exponential and power-law shapes,

Takao Komatsu

We give continued fraction expansions of the generating functions of Bernoulli numbers, Cauchy numbers, Euler numbers, harmonic numbers, and their generalized or related numbers. In particular, we focus on explicit forms of the convergents of these continued fraction expansions. Linear fractional transformations of such continued fractions are also discussed

Arnab Saha, Rahul Marathe

From synthetic active devices such as self-propelling Janus colloids to micro-organisms like bacteria, micro-algae, living cells in tissues, active fluctuations are ubiquitous. Thermodynamics of small systems involving thermal as well as active fluctuations are of immense importance. They can be employed to extract thermodynamic work. Here we propose a simpl

S. James Gates,, Yangrui Hu, Hanzhi Jiang, S. -N. Hazel Mak

We present aspects of the component description of linearized Nordstr\" om Supergravity in eleven and ten dimensions. The presentation includes low order component fields in the supermultiplet, the supersymmetry variations of the scalar graviton and gravitino trace, their supercovariantized field strengths, and the supersymmetry commutator algebra of the

Jin-Jun Geng, Bing Zhang, Anders Kölligan, Rolf Kuiper

We perform a series of relativistic magnetohydrodynamics simulations to investigate how a hot magnetic jet propagates within the dynamical ejecta of a binary neutron star merger, with the focus on how the jet structure depends on the delay time of jet launching with respect to the merger time, $Δt_{\rm jet}$. We find that regardless of the jet launching dela

Hiroki Kato

For a family of varieties, we prove that the alternating sum of the traces of "local" monodromy acting on the $\ell$-adic étale cohomology groups of the generic fiber is an integer which is independent of $\ell$.

Fred Hohman, Haekyu Park, Caleb Robinson, Duen Horng Chau

Deep learning is increasingly used in decision-making tasks. However, understanding how neural networks produce final predictions remains a fundamental challenge. Existing work on interpreting neural network predictions for images often focuses on explaining predictions for single images or neurons. As predictions are often computed from millions of weights

Youshan Zhang, Brian D. Davison

Deep neural networks have been widely used in computer vision. There are several well trained deep neural networks for the ImageNet classification challenge, which has played a significant role in image recognition. However, little work has explored pre-trained neural networks for image recognition in domain adaption. In this paper, we are the first to extra

Rogerio Bonatti, Cherie Ho, Wenshan Wang, Sanjiban Choudhury

The use of drones for aerial cinematography has revolutionized several applications and industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. However, safely controlling a drone while filming a moving target usually requires multiple expert human operators; hence the need for an autonomous cinematographer. Cu

Tengfei Zhang, Yue Zhang, Xian Sun, Hao Sun

The current advances in object detection depend on large-scale datasets to get good performance. However, there may not always be sufficient samples in many scenarios, which leads to the research on few-shot detection as well as its extreme variation one-shot detection. In this paper, the one-shot detection has been formulated as a conditional probability pr

Jonathan W. Siegel, Jinchao Xu

We introduce a new algorithm, extended regularized dual averaging (XRDA), for solving regularized stochastic optimization problems, which generalizes the regularized dual averaging (RDA) method. The main novelty of the method is that it allows a flexible control of the backward step size. For instance, the backward step size used in RDA grows without bound,

Chris Gartland

The differentiation theory of Lipschitz functions taking values in a Banach space with the Radon-Nikodým property (RNP), originally developed by Cheeger-Kleiner, has proven to be a powerful tool to prove non-biLipschitz embeddability of metric spaces into these Banach spaces. Important examples of metric spaces to which this theory applies include nonabelian

Jonathan W. Siegel, Jinchao Xu

We prove some new results concerning the approximation rate of neural networks with general activation functions. Our first result concerns the rate of approximation of a two layer neural network with a polynomially-decaying non-sigmoidal activation function. We extend the dimension independent approximation rates previously obtained to this new class of act

Qi Wang

In [C. Ding, An infinite family of Steiner systems $S(2,4,2^m)$ from cyclic codes, {\em J. Combin. Des.} 26 (2018), no.3, 126--144], Ding constructed a family of Steiner systems $S(2,4,2^m)$ for all $m \equiv 2 \pmod{4}$ from a family of extended cyclic codes. The objective of this paper is to present a family of Steiner systems $S(2,4,2^m)$ for all $m \equi

Roozbeh Farhoodi, Khashayar Filom, Ilenna Simone Jones, Konrad Paul Kording

Any function can be constructed using a hierarchy of simpler functions through compositions. Such a hierarchy can be characterized by a binary rooted tree. Each node of this tree is associated with a function which takes as inputs two numbers from its children and produces one output. Since thinking about functions in terms of computation graphs is getting p

Guillaume Basse, Peng Ding, Avi Feller, Panos Toulis

Measuring the effect of peers on individuals' outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and unobservable ways. Group formation experiments avoid this problem by randomly assigning individuals to groups and observing their responses; for example, do first-year students have better grad

Saied Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh

Although numerous improvements have been made in the field of image segmentation using convolutional neural networks, the majority of these improvements rely on training with larger datasets, model architecture modifications, novel loss functions, and better optimizers. In this paper, we propose a new segmentation performance boosting paradigm that relies on

Chaitanya Malaviya, Shijie Wu, Ryan Cotterell

English verbs have multiple forms. For instance, talk may also appear as talks, talked or talking, depending on the context. The NLP task of lemmatization seeks to map these diverse forms back to a canonical one, known as the lemma. We present a simple joint neural model for lemmatization and morphological tagging that achieves state-of-the-art results on 20

R. Horsley, Z. Koumi, Y. Nakamura, H. Perlt

We report a new analysis of the isospin splittings within the decuplet baryon spectrum. Our numerical results are based upon five ensembles of dynamical QCD+QED lattices. The analysis is carried out within a flavour-breaking expansion which encodes the effects of breaking the quark masses and electromagnetic charges away from an approximate SU(3) symmetric p

Jeremias Knoblauch

This report provides an in-depth overview over the implications and novelty Generalized Variational Inference (GVI) (Knoblauch et al., 2019) brings to Deep Gaussian Processes (DGPs) (Damianou & Lawrence, 2013). Specifically, robustness to model misspecification as well as principled alternatives for uncertainty quantification are motivated with an informatio

Yen-Kheng Lim

A solution to an Einstein--Maxwell--dilaton-type theory with $M$ Liouville potentials and $N$ gauge fields is presented, where $M$ and $N$ are arbitrary integers. This exact solution interpolates between the Lifshitz black hole and the topological dilaton black hole. The thermodynamic behaviour of the solution is found to be similar to that of the Lifshitz b

Brian M. Kilpatrick, Tiffany Kataria, Nikole K. Lewis, Robert T. Zellem

Here we present the analysis of multi-epoch secondary eclipse observations of HD 189733b and HD 209458b as a probe of temporal variability in the planetary climate using both Spitzer channels 1 and 2 (3.6 and 4.5 um). Constraining temporal variability will inform models and identify physical processes occurring at either length scales too small to directly o

Bunyo Hatsukade, Tetsuya Hashimoto, Kotaro Kohno, Kouichiro Nakanishi

We present the results of CO(1-0) and CO(4-3) observations of the host galaxy of a long-duration gamma-ray burst GRB080207 at z = 2.0858 by using the Karl G. Jansky Very Large Array and the Atacama Large Millimeter/submillimeter Array. The host is detected in CO(1-0) and CO(4-3), becoming the first case for a GRB host with more than two CO transitions detect

Rohit Agrawal

We show that the moment generating function of the Kullback-Leibler divergence (relative entropy) between the empirical distribution of $n$ independent samples from a distribution $P$ over a finite alphabet of size $k$ (i.e. a multinomial distribution) and $P$ itself is no more than that of a gamma distribution with shape $k - 1$ and rate $n$. The resulting

Wenrui Xu, Daniel Fabrycky

We study the excitation of mutual inclination between planetary orbits by a novel secular-orbital resonance in multiplanet systems perturbed by binary companions which we call "ivection". The ivection resonance happens when the nodal precession rate of the planet matches a multiple of the orbital frequency of the binary, and its physical nature is si

Jianliang Gao, Noureddin Sadawi, Ibrahim Karaman, Jake T M Pearce

Background: Metabolomics datasets are becoming increasingly large and complex, with multiple types of algorithms and workflows needed to process and analyse the data. A cloud infrastructure with portable software tools can provide much needed resources enabling faster processing of much larger datasets than would be possible at any individual lab. The PhenoM

Hongxi Xing, Shinsuke Yoshida

The single-transverse spin asymmetry(SSA) for hadron production in the transversely polarized proton scattering receives major contribution from Sivers effect, which can be systematically described within the collinear twist-3 factorization framework in various processes. Conventional method in the evaluation of the Sivers effect known as pole calculation is

Natalie M. Gosnell, Emily M. Leiner, Robert D. Mathieu, Aaron M. Geller

Recent studies show that the majority of blue straggler stars (BSSs) in old open clusters are formed through mass transfer from an evolved star onto a main-sequence companion, resulting in a BSS and white dwarf (WD) in a binary system. We present constraints on the mass transfer histories of two BSS-WD binaries in the open cluster NGC 188, using WD temperatu

Taiki Hasegawa, Nobuchika Okada, Osamu Seto

An additional $U(1)$ gauge interaction is one of promising extensions of the standard model of particle physics. Among others, the $U(1)_{B-L}$ gauge symmetry is particularly interesting because it addresses the origin of Majorana masses of right-handed neutrinos, which naturally leads to tiny light neutrino masses through the seesaw mechanism. We show that,

Shinsuke Iwao

We show a new neutral-fermionic presentation of Ikeda-Naruse's $K$-theoretic $Q$-functions, which represent a Schubert class in the $K$-theory of coherent sheaves on the Lagrangian Grassmannian. Our presentation provides a simple description and yields straightforward proof of two types of Pfaffian formulas for them. We present a dual space of $GΓ$, the

Nam Le

The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolvi

Abdulelah Abuabat, Steven Johnston, Mohammed Aldosari, Taylor Neal

Regional Intergovernmental Organizations (RIGOs) are constituted by the local governments within their respective regions and are supported by the active engagement of the regions community and citizens. Metropolitan Statistical Areas (MSAs), on the other hand, are classified by the federal government based on commuting and commerce patterns. They do not adh

Junxi Feng, Xiaohai He, Qizhi Teng, Chao Ren

Porous media are ubiquitous in both nature and engineering applications, thus their modelling and understanding is of vital importance. In contrast to direct acquisition of three-dimensional (3D) images of such medium, obtaining its sub-region (s) like two-dimensional (2D) images or several small areas could be much feasible. Therefore, reconstructing whole

Noreddine Gherabi, Bahaj Mohamed

We propose a new method for shape recognition and retrieval based on dynamic programming. Our approach uses the dynamic programming algorithm to compute the optimal score and to find the optimal alignment between two strings. First, each contour of shape is represented by a set of points. After alignment and matching between two shapes, the contours are tran

Thomas Köllmer, Jens Hasselbach, Patrick Aichroth

We apply text analysis approaches for a specialized search engine for 3D CAD models and associated products. The main goals are to distinguish between actual product descriptions and other text on a website, as well as to decide whether a given text is or contains a product name. For this we use paragraph vectors for text classification, a character-level lo

Guilherme Gomes, Vinayak Rao, Jennifer Neville

Clustering and community detection with multiple graphs have typically focused on aligned graphs, where there is a mapping between nodes across the graphs (e.g., multi-view, multi-layer, temporal graphs). However, there are numerous application areas with multiple graphs that are only partially aligned, or even unaligned. These graphs are often drawn from th

Amin Azari

Bitcoin is considered the most valuable currency in the world. Besides being highly valuable, its value has also experienced a steep increase, from around 1 dollar in 2010 to around 18000 in 2017. Then, in recent years, it has attracted considerable attention in a diverse set of fields, including economics and computer science. The former mainly focuses on s

Yihao Yang, Yuichiro Yamagami, Xiongbin Yu, Prakash Pitchappa

The computing speeds in modern multi-core processors and big data servers are no longer limited by the on-chip transistor density that doubles every two years following the Moores law, but are limited by the on-chip data communication between memories and microprocessor cores. Realization of integrated, low-cost, and efficient solutions for high speed, on-ch

Monalisa Pal, Sanghamitra Bandyopadhyay, Saugat Bhattacharyya

In Brain-Computer Interfacing (BCI), due to inter-subject non-stationarities of electroencephalogram (EEG), classifiers are trained and tested using EEG from the same subject. When physical disabilities bottleneck the natural modality of performing a task, acquisition of ample training data is difficult which practically obstructs classifier training. Previo