November 2018 arXiv papers — page 20

Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, Alexei A. Efros

Model distillation aims to distill the knowledge of a complex model into a simpler one. In this paper, we consider an alternative formulation called dataset distillation: we keep the model fixed and instead attempt to distill the knowledge from a large training dataset into a small one. The idea is to synthesize a small number of data points that do not need

Ivan Kojadinovic, Kristina Stemikovskaya

A key tool to carry out inference on the unknown copula when modeling a continuous multivariate distribution is a nonparametric estimator known as the empirical copula. One popular way of approximating its sampling distribution consists of using the multiplier bootstrap. The latter is however characterized by a high implementation cost. Given the rank-based

R. J. Shannon, B. Hornung, D. P. Tew, D. R. Glowacki

Methodologies for creating reactive potential energy surfaces from molecular mechanics force-fields are becoming increasingly popular. To date, molecular mechanics force-fields use harmonic expressions to treat bonding stretches, which is a poor approximation in reactive molecular dynamics simulations since bonds are displaced significantly from their equili

Oren Kalinsky, Oren Mishali, Aidan Hogan, Yoav Etsion

We propose a visual query language for interactively exploring large-scale knowledge graphs. Starting from an overview, the user explores bar charts through three interactions: class expansion, property expansion, and subject/object expansion. A major challenge faced is performance: a state-of-the-art SPARQL engine may require tens of minutes to compute the

Xiuming Liu, Dave Zachariah, Johan Wågberg, Thomas B. Schön

Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed to improve classification performance and has in fact been reported to impair the performance in certain cases. A fundamental source of error arises from restrictive assumptions a

Valentin Zieglmeier, Severin Kacianka, Thomas Hutzelmann, Alexander Pretschner

Connected vehicles are becoming commonplace. A constant connection between vehicles and a central server enables new features and services. This added connectivity raises the likelihood of exposure to attackers and risks unauthorized access. A possible countermeasure to this issue are intrusion detection systems (IDS), which aim at detecting these intrusions

Shuang Liang, Deping Zhang, Wei Chen

We study the one-dimensional Fermionic Hubbard model with SU(N) spin symmetry in the incommensurate filling case. The basic properties of Green's function, momentum distribution and tunneling density of states of the system at low temperature are studied in the frame work of Luttinger liquid theory combined with Bethe Ansatz solutions for arbitrary inter

Francis Williams, Teseo Schneider, Claudio Silva, Denis Zorin

The reconstruction of a discrete surface from a point cloud is a fundamental geometry processing problem that has been studied for decades, with many methods developed. We propose the use of a deep neural network as a geometric prior for surface reconstruction. Specifically, we overfit a neural network representing a local chart parameterization to part of a

Georgios Fragkoulidis, Volkmar Wirth

This study investigates the synoptic circulation patterns associated with temperature extremes in southeastern (SE) Europe. Using ERA-Interim reanalysis data we report on the typical patterns that characterize the middle and upper tropospheric flow a few days before and during hot and cold extremes. The analysis is done separately for each season, while a fu

Roland Steinbauer

Recently the 'memory effect' has been studied in plane gravitational waves and, in particular, in impulsive plane waves. Based on an analysis of the particle motion (mainly in Baldwin-Jeffery-Rosen coordinates) a 'velocity memory effect' is claimed to be found in [P.-M. Zhang, C. Duval, and P. A. Horvathy. Memory effect for impulsive gravitat

Xiaojie Wang, Sebastian Cammerer, Stephan ten Brink

This paper considers the forward error correction (FEC) code design for approaching the capacity of a dynamic multiple access channel (MAC) where both the number of users and their respective signal powers keep constantly changing, resembling the scenario of an actual wireless cellular system. To obtain a low-complexity non-orthogonal multiple access (NOMA)

Paul Gassiat

We consider a class of fractional stochastic volatility models (including the so-called rough Bergomi model), where the volatility is a superlinear function of a fractional Gaussian process. We show that the stock price is a true martingale if and only if the correlation $ρ$ between the driving Brownian motions of the stock and the volatility is nonpositive.

Grigoris Maravelias, Andreas Zezas, Vallia Antoniou, Despina Hatzidimitriou

Almost all confirmed optical counterparts of HMXBs in the SMC are OB stars with equatorial decretion disks (OBe). These sources emit strongly in Balmer lines and standout when imaged through narrow-band Hα imaging. The lack of secure counterparts for a significant fraction of the HMXBs motivated us to search for more. Using the catalogs for OB/OBe stars (Mar

Ilkka Helenius

In this talk we apply the photoproduction framework recently implemented into the Pythia 8 Monte Carlo event generator to study the potential of photo-nuclear dijets in ultra-peripheral Pb+Pb collisions at the LHC to further constrain the nuclear PDFs. These events can be described as $γ$A collisions where the relevant part of the flux of quasi-real photons

Gloria Montana, Laura Tolos, Matthias Hanauske, Luciano Rezzolla

If a phase transition is allowed to take place in the core of a compact star, a new stable branch of equilibrium configurations can appear, providing solutions with the same mass as the purely hadronic branch and hence giving rise to twin-star configurations. We perform an extensive analysis of the features of the phase transition leading twin-star configura

Laurent Orseau, Levi H. S. Lelis, Tor Lattimore, Théophane Weber

We introduce two novel tree search algorithms that use a policy to guide search. The first algorithm is a best-first enumeration that uses a cost function that allows us to prove an upper bound on the number of nodes to be expanded before reaching a goal state. We show that this best-first algorithm is particularly well suited for `needle-in-a-haystack'

Stephen Coughlan, Tom Ducat

Cluster algebras give rise to a class of Gorenstein rings which enjoy a large amount of symmetry. Concentrating on the rank 2 cases, we show how cluster varieties can be used to construct many interesting projective algebraic varieties. Our main application is then to construct hundreds of families of Fano 3-folds in codimensions 4 and 5. In particular, for

Ze Li

In this paper and the companion work \cite{LIZE2}, we prove that the Schrödinger map flows from $\Bbb R^d$ with $d\ge 2$ to compact Kähler manifolds with small initial data in critical Sobolev spaces are global. The main difficulty compared with the constant sectional curvature case is that the gauged equation now is not self-contained due to the curvature p

Utkarsh Bhardwaj, Andrea E. Sand, Manoj Warrier

The structure of defect clusters formed in a displacement cascade plays a significant role in the micro-structural evolution during irradiation. Molecular dynamics simulations have been widely used to study collision cascades and subsequent clustering of defects. We present a novel method to pattern match and classify defect clusters. A cluster is characteri

Aritz Arrate, José González Cabañas, Ángel Cuevas, María Calderón

Online advertising is the major source of income for a large portion of Internet Services. There exists a body of literature aiming at optimizing ads engagement, understanding the privacy and ethical implications of online advertising, etc. However, to the best of our knowledge, no previous work analyses at large scale the exposure of real users to online ad

Pratik Mullick, Parongama Sen

We consider a single species reaction diffusion system on a two dimensional lattice where the particles $A$ are biased to move towards their nearest neighbours and annihilate as they meet; $A + A \to \emptyset$. Allowing the bias to take both negative and positive values parametrically, any nonzero bias is seen to drastically affect the behaviour of the syst

Nezihe Uzun

In the paraxial regime of Newtonian optics, propagation of an ensemble of rays is represented by a symplectic ABCD transfer matrix defined on a reduced phase space. Here, we present its analogue for general relativity. Starting from simultaneously applied null geodesic actions for two curves, we obtain a geodesic deviation action up to quadratic order. We ac

Wei Wang, Kaicheng Yu, Joachim Hugonot, Pascal Fua

As mixed reality is gaining increased momentum, the development of effective and efficient solutions to egocentric hand segmentation is becoming critical. Traditional segmentation techniques typically follow a one-shot approach, where the image is passed forward only once through a model that produces a segmentation mask. This strategy, however, does not ref

Tomasz Brzeziński, James Gaunt, Alexander Schenkel

The $θ$-deformed Hopf fibration $\mathbb{S}^3_θ\to \mathbb{S}^2$ over the commutative $2$-sphere is compared with its classical counterpart. It is shown that there exists a natural isomorphism between the corresponding associated module functors and that the affine spaces of classical and deformed connections are isomorphic. The latter isomorphism is equivar

Woosung Park, Sungtae Cho, Su Houng Lee

We systematically analyze the flavor color spin structure of the pentaquark $q^4\bar{Q}$ system in a constituent quark model based on the chromomagnetic interaction in both the SU(3) flavor symmetric and SU(3) flavor broken case with and without charm quarks. We show that the originally proposed pentaquark state $\bar{Q}s qqq$ by Gignoux et al and by Lipkin

Fan Yang, Ryota Hinami, Yusuke Matsui, Steven Ly

Diffusion is commonly used as a ranking or re-ranking method in retrieval tasks to achieve higher retrieval performance, and has attracted lots of attention in recent years. A downside to diffusion is that it performs slowly in comparison to the naive k-NN search, which causes a non-trivial online computational cost on large datasets. To overcome this weakne

Enric Pardo, Francesco Grilli, Yingzhen Liu, Simon Wolftaedler

Many superconducting power applications contain REBCO coils. Superconducting motors are very interesting for mobile applications like aviation, thanks to their high power per unit weight. In order to reduce the inductance, multi-tape conductors are often used in windings but parallel tapes present coupling AC loss. In this article, we analyze the AC loss of

Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen

Cellular network configuration plays a critical role in network performance. In current practice, network configuration depends heavily on field experience of engineers and often remains static for a long period of time. This practice is far from optimal. To address this limitation, online-learning-based approaches have great potentials to automate and optim

Benoît Bonnet, Jean-Paul Gauthier, Francesco Rossi

In this paper, we extend and complete the classification of the generic singularities of the 3D-contact sub-Riemmanian conjugate locus in a neighbourhood of the origin.

Tomonari Mizoguchi, Tohru Koma

We propose an approach to detect the peculiarity of Majorana fermions at the edges of Kitaev magnets. As is well known, a pair of Majorana edge modes is realized when a single complex fermion splits into real and imaginary parts which are, respectively, localized at the left and right edges of a sample magnet. Reflecting both of this peculiarity of the Major

Hideki Ishihara, Tatsuya Ogawa

We construct, numerically, stationary and spherically symmetric nontopological soliton solutions in the system composed of a complex scalar field, a U(1) gauge field, and a complex Higgs scalar field that causes spontaneous symmetry braking. It is shown that the charge of the soliton is screened by counter charge everywhere.

Renqiang Li, Hong Liu, Xiangdong Wan, Yueliang Qian

Braille is an effective way for the visually impaired to learn knowledge and obtain information. Braille image recognition aims to automatically detect Braille dots in the whole Braille image. There is no available public datasets for Braille image recognition to push relevant research and evaluate algorithms. This paper constructs a large-scale Double-Sided

Claudio Gallicchio

Reservoir Computing (RC) provides an efficient way for designing dynamical recurrent neural models. While training is restricted to a simple output component, the recurrent connections are left untrained after initialization, subject to stability constraints specified by the Echo State Property (ESP). Literature conditions for the ESP typically fail to prope

BESIII Collaboration, M. Ablikim, M. N. Achasov, S. Ahmed

Using a $3.19~\mathrm{fb}^{-1}$ data sample collected at an $e^+e^-$ center-of-mass energy of $E_{\rm cm}=4.178$ GeV with the BESIII detector, we measure the branching fraction of the leptonic decay $D_s^+\toμ^+ν_μ$ to be $\mathcal{B}_{D_s^+\toμ^+ν_μ}=(5.49\pm0.16_{\rm stat.}\pm0.15_{\rm syst.})\times10^{-3}$. Combining our branching fraction with the masses

Carlos Galindo, Francisco Monserrat, Carlos-Jesús Moreno-Ávila

We consider rational surfaces $Z$ defined by divisorial valuations $ν$ of Hirzebruch surfaces. We introduce the concepts of non-positivity and negativity at infinity for these valuations and prove that these concepts admit nice local and global equivalent conditions. In particular we prove that, when $ν$ is non-positive at infinity, the extremal rays of the

Marco Fuhrman, Marie-Amélie Morlais

We address a general optimal switching problem over finite horizon for a stochastic system described by a differential equation driven by Brownian motion. The main novelty is the fact that we allow for infinitely many modes (or regimes, i.e. the possible values of the piecewise-constant control process). We allow all the given coefficients in the model to be

Francesco Giacomello, Antonio De Felice, Stefano Ansoldi

Several modified cosmological models exist, which also try to address the tensions between data and predictions of the $Λ$-CDM model. Galileon models are particular scalar tensor theories that represent one such possibilities. While it is commonly understood that there may be inconsistencies between predictions of some Galileon models and observations, in pa

Xiangxia Ren, Jun Zhang, Weiguo Song, Shuchao Cao

The worldwide population is aging and countries are facing ongoing challenges in meeting the transportation demand of the elderly. In this study, we investigate the movement characteristics of elders in the straight corridor and compare them with that of young adults. The free speeds of the elderly (about 1.28m/s) are obviously slower than that of the young

Alastair Gregory, Din-Houn Lau, Mark Girolami, Liam Butler

A recent development which is poised to disrupt current structural engineering practice is the use of data obtained from physical structures such as bridges, viaducts and buildings. These data can represent how the structure responds to various stimuli over time when in operation, providing engineers with a unique insight into how their designs are performin

Jingran Qiu, Weixi Huang, Chunxiao Xu, Lihao Zhao

Particular types of plankton in aquatic ecosystems can coordinate their motion depending on the local flow environment to reach regions conducive to their growth or reproduction. Investigating their swimming strategies with regard to the local environment is important to obtain in-depth understanding of their behavior in the aquatic environment. In the prese

Arjun Bagchi, Aritra Banerjee, Shankhadeep Chakrabortty, Pulastya Parekh

A new type of tensionless superstring theory, called the Inhomogeneous tensionless superstring, has been recently introduced. This is characterised by a residual symmetry algebra on the worldsheet richer in structure than the previously known symmetry algebra related to Homogeneous tensionless superstring. In this paper, we investigate theories of tensile su

O. Gargiulo, S. Oleschko, J. Prat-Camps, M. Zanner

Fast magnetic flux control is a crucial ingredient for circuit quantum electrodynamics (cQED) systems. So far it has been a challenge to implement this technology with the high coherence 3D cQED architecture. In this paper we control the magnetic field inside a superconducting waveguide cavity using a magnetic hose, which allows fast flux control of 3D trans

Hao Zhang, Wenxiu Li, Xiaoyang Chang, Peng Han

A whispering gallery mode resonator with a cavity-made slot filled atomic vapor is demonstrated, in which the chiral symmetry is broken induced by asymmetric backscattering of counter-propagating optical waves in the WGM microcavity. The chirality of resonator modes is steered via tuning dispersion relation in the cavity-made slot. The system exhibiting a hi

Yusuke Niitani, Takuya Akiba, Tommi Kerola, Toru Ogawa

Efficient and reliable methods for training of object detectors are in higher demand than ever, and more and more data relevant to the field is becoming available. However, large datasets like Open Images Dataset v4 (OID) are sparsely annotated, and some measure must be taken in order to ensure the training of a reliable detector. In order to take the incomp

Dagnachew Jenber Negash

A recurrence relations for sums of powers of complex functions can be written as a system of linear equation AX=B. Using properties of determinant and Cramer's rule for solving systems of linear equation, this paper presents an absolutely explicit identity for solving sums of powers of complex functions without one sum depends on the others.

Chiara Ricca, Iurii Timrov, Matteo Cococcioni, Nicola Marzari

We propose a self-consistent site-dependent Hubbard $U$ approach for DFT+$U$ calculations of defects in complex transition-metal oxides, using Hubbard parameters computed via linear-response theory. The formation of a defect locally perturbs the chemical environment of Hubbard sites in its vicinity, resulting in different Hubbard $U$ parameters for different

Matthieu Dussaule, Ilya Gekhtman

We are interested in the Guivarc'h inequality for admissible random walks on finitely generated relatively hyperbolic groups, endowed with a word metric. We show that for random walks with finite super-exponential moment, if this inequality is an equality, then the Green distance is roughly similar to the word distance, generalizing results of Blach{è}re

Can Shao, Takami Tohyama, Hong-Gang Luo, Hantao Lu

The charge carrier dynamics of doped electronic correlated systems on ladders and chains, subject to ultrafast photoirradiation, is investigated using the time-dependent Lanczos method. The time-resolved optical conductivity and the temporal profiles of other relevant quantities, including the doublon number, the kinetic energy, and the interaction energy, a

Carlos A. R. Herdeiro, Eugen Radu, Kunihito Uzawa

Recently, two simple criteria were proposed to assess if vacua emerging from an effective scalar field theory are part of the string "landscape" or "swampland". The former are the vacua that emerge from string compactifications; the latter are not obtained by any such compactification and hence may not survive in a UV completed theory of grav

Frederic Latremoliere

We define a metric on the class of metric spectral triples, which is null exactly between spectral triples with unitary equivalent Dirac operators and *-isomorphic underlying C*-algebras. This metric dominates the propinquity, and thus implies metric convergence of the compact quantum metric spaces induced by metric spectral triples. In the process of our co

Junsong Fan, Zhaoxiang Zhang, Tieniu Tan, Chunfeng Song

Weakly supervised semantic segmentation with only image-level labels saves large human effort to annotate pixel-level labels. Cutting-edge approaches rely on various innovative constraints and heuristic rules to generate the masks for every single image. Although great progress has been achieved by these methods, they treat each image independently and do no

Toru Sasahara

First, we classify proper biharmonic Hopf real hypersurfaces in $\mathbb{C}P^2$. Next, we classify proper biharmonic real hypersurfaces with two distinct principal curvatures in $\mathbb{C}P^n$, where $n\geq 2$. Finally, we prove that biharmonic ruled real hypersurfaces in $\mathbb{C}P^n$ are minimal, where $n\geq 2$.

C. L. Ahmed Rizwan, A. Naveena Kumara, K. V. Rajani, Deepak Vaid.

We investigate thermodynamics and geometrothermodynamics of regular Bardeen AdS black hole with quintessence. The thermodynamics of the black hole is studied using temperature-entropy ($T-S$) , Pressure-Volume ($P-v$), and Gibbs energy plots, which indicate a critical behaviour.This is also confirmed from the divergence of specific heat against entropy, whic

S. H. Fatemi, S. Azami

For a complete Riemannian manifold $M$ with an (1,1)-elliptic Codazzi self-adjoint tensor field $A$ on it, we use the divergence type operator ${L_A}(u): = div(A\nabla u)$ and an extension of the Ricci tensor to extend some major comparison theorems in Riemannian geometry. In fact we extend theorems like mean curvature comparison theorem, Bishop-Gromov volum

Qichuan Geng, Hong Zhang, Xinyu Huang, Sen Wang

Part information has been shown to be resistant to occlusions and viewpoint changes, which is beneficial for various vision-related tasks. However, we found very limited work in car pose estimation and reconstruction from street views leveraging the part information. There are two major contributions in this paper. Firstly, we make the first attempt to build

Carlo Danieli, Thudiyangal Mithun, Yagmur Kati, David K. Campbell

Integrable many-body systems are characterized by a complete set of preserved actions. Close to an integrable limit, a {\it nonintegrable} perturbation creates a coupling network in action space which can be short- or long-ranged. We analyze the dynamics of observables which turn into the conserved actions in the integrable limit. We compute distributions of

Rowan Zellers, Yonatan Bisk, Ali Farhadi, Yejin Choi

Visual understanding goes well beyond object recognition. With one glance at an image, we can effortlessly imagine the world beyond the pixels: for instance, we can infer people's actions, goals, and mental states. While this task is easy for humans, it is tremendously difficult for today's vision systems, requiring higher-order cognition and commons

Hidenori Fukaya

Gravity is difficult to quantize. This is a well-known fact but its reason is given simply by non-renormalizability of the Newton constant and little is discussed why among many quantum gauge theories, gravity is special. In this essay we try to treat the gravity as one of many gauge theories, and discuss how it is special and why it is difficult to quantize

Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu

Depending on how much information an adversary can access to, adversarial attacks can be classified as white-box attack and black-box attack. For white-box attack, optimization-based attack algorithms such as projected gradient descent (PGD) can achieve relatively high attack success rates within moderate iterates. However, they tend to generate adversarial

Suwon Shon, Younggun Lee, Taesu Kim

This paper describes a fast speaker search system to retrieve segments of the same voice identity in the large-scale data. A recent study shows that Locality Sensitive Hashing (LSH) enables quick retrieval of a relevant voice in the large-scale data in conjunction with i-vector while maintaining accuracy. In this paper, we proposed Random Speaker-variability

Mahesh Subedar, Ranganath Krishnan, Paulo Lopez Meyer, Omesh Tickoo

Deep neural networks (DNNs) provide state-of-the-art results for a multitude of applications, but the approaches using DNNs for multimodal audiovisual applications do not consider predictive uncertainty associated with individual modalities. Bayesian deep learning methods provide principled confidence and quantify predictive uncertainty. Our contribution in

Honglu Fan, Hsian-Hua Tseng, Fenglong You

Given a smooth projective variety $X$ with a smooth nef divisor $D$ and a positive integer $r$, we construct an $I$-function, an explicit slice of Givental's Lagrangian cone, for Gromov--Witten theory of the root stack $X_{D,r}$. As an application, we also obtain an $I$-function for relative Gromov--Witten theory following the relation between relative a

Yoritaka Iwata

The rotation group is formulated based on the abstract $B(X)$-module framework. Although the infinitesimal generators of rotation group include differential operators, the rotation group is formulated utilizing the framework of bounded operator algebra. In this article, unbounded formulation of rotation group is established.

Josefa M. Garcia, Pascual Jara

In fuzzy theory of sets and groups, the use of $α$--levels is a standard to translate problems from the fuzzy to the crisp framework. Using strong $α$--levels, it is possible to establish a one to one correspondence which makes possible doubly, a gradual and a functorial treatment of the fuzzy theory. The main result of this paper is to identify the class of

David Hall, Feras Dayoub, John Skinner, Haoyang Zhang

We introduce Probabilistic Object Detection, the task of detecting objects in images and accurately quantifying the spatial and semantic uncertainties of the detections. Given the lack of methods capable of assessing such probabilistic object detections, we present the new Probability-based Detection Quality measure (PDQ).Unlike AP-based measures, PDQ has no

Owen Lahav, Nicholas Mastronarde, Mihaela van der Schaar

Recent efforts in Machine Learning (ML) interpretability have focused on creating methods for explaining black-box ML models. However, these methods rely on the assumption that simple approximations, such as linear models or decision-trees, are inherently human-interpretable, which has not been empirically tested. Additionally, past efforts have focused excl

Yiwen Huang, Rihui Wu, Pinglai Ou, Ziyong Feng

Modern deep networks generally implement a certain form of shortcut connections to alleviate optimization difficulties. However, we observe that such network topology alters the nature of deep networks. In many ways, these networks behave similarly to aggregated wide networks. We thus exploit the aggregation nature of shortcut connections at a finer architec

Dimitris Berberidis, Georgios B. Giannakis

Node embedding is the task of extracting informative and descriptive features over the nodes of a graph. The importance of node embeddings for graph analytics, as well as learning tasks such as node classification, link prediction and community detection, has led to increased interest on the problem leading to a number of recent advances. Much like PCA in th

D. R. de Matos Pimentel, E. Moura-Santos

In this work, we investigate the role of emission by dust at infrared wavelengths in the absorption of gamma radiation from distant extragalactic sources. We use an existing EBL model based on direct starlight emission at UV/visible and secondary radiation due to dust (PAHs (polycyclic aromatic hydrocarbons), small and large grains) at IR due to partial abso

Bernat Capdevila, Ursula Laa, German Valencia

Discrepancies between measurements of decay modes with an underlying quark level transition $b\to s \ell^+\ell^-$ and standard model (SM) predictions have persisted for several years, particularly for the muon channels. The inadequacy of the SM becomes more compelling in a global fit. For example, Ref. [1] described 175 observables by six parameters encoding

Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael Rabbat

Distributed data-parallel algorithms aim to accelerate the training of deep neural networks by parallelizing the computation of large mini-batch gradient updates across multiple nodes. Approaches that synchronize nodes using exact distributed averaging (e.g., via AllReduce) are sensitive to stragglers and communication delays. The PushSum gossip algorithm is

Sen Na, Mladen Kolar

We study the estimation of the parametric components of single and multiple index volatility models. Using the first- and second-order Stein's identities, we develop methods that are applicable for the estimation of the variance index in the high-dimensional setting requiring finite moment condition, which allows for heavy-tailed data. Our approach compl

Yang Feng, Lin Ma, Wei Liu, Jiebo Luo

Deep neural networks have achieved great successes on the image captioning task. However, most of the existing models depend heavily on paired image-sentence datasets, which are very expensive to acquire. In this paper, we make the first attempt to train an image captioning model in an unsupervised manner. Instead of relying on manually labeled image-sentenc

Zengjian Chen, Jiayi Liu, Yihe Deng, Kun He

In this paper we make progress on the unsupervised task of mining arbitrarily shaped clusters in highly noisy datasets, which is a task present in many real-world applications. Based on the fundamental work that first applies a wavelet transform to data clustering, we propose an adaptive clustering algorithm, denoted as AdaWave, which exhibits favorable char

William Donnelly, Gabriel Wong

Entanglement entropy is an important quantity in field theory, but its definition poses some challenges. The naive definition involves an extension of quantum field theory in which one assigns Hilbert spaces to spatial sub-regions. For two-dimensional topological quantum field theory we show that the appropriate extension is the open-closed topological quant

Zhi-Hong Sun

Let $\Bbb Z$ and $\Bbb Z^+$ be the set of integers and the set of positive integers, respectively. For $a,b,c,d,n\in\Bbb Z^+$ let $t(a,b,c,d;n)$ be the number of representations of $n$ by $ax(x+1)/2+by(y+1)/2+cz(z+1)/2+dw(w+1)/2$ $(x,y,z,w\in\Bbb Z)$. In this paper, by using Ramanujan's theta functions $φ(q)$ and $ψ(q)$ we present many formulas and conje

Toshinori Suzuki, Masahiro Kaminaga

To increase the number of wireless devices, e.g., mobile or IoT terminals, cryptosystems are essential for secure communications. In this regard, random number generation is crucial because the appropriate function of cryptosystems relies on it to work properly. This paper proposes a true random number generator (TRNG) method capable of working in wireless c

Claire Miller, Edmund Crampin, James Osborne

The maintenance of the proliferative cell niche is critical to epithelial tissue morphology and function. In this paper we investigate how current modelling methods can result in the erroneous loss of proliferative cells from the proliferative cell niche. Using an established model of the inter-follicular epidermis we find there is a limit to the proliferati

Maxim Lyutikov

We reconsider the structure of thermally driven rotating Parker wind. Rotation, without \Bf, changes qualitatively the structure of the subsonic region: solutions become non-monotonic and do not extend to the origin. For small angular velocities solutions have two critical points - X-point and O-points, which merge at the critical angular velocity of the cen

Kevin K. Yang, Zachary Wu, Frances H. Arnold

Machine learning (ML)-guided directed evolution is a new paradigm for biological design that enables optimization of complex functions. ML methods use data to predict how sequence maps to function without requiring a detailed model of the underlying physics or biological pathways. To demonstrate ML-guided directed evolution, we introduce the steps required t

Teng Huang

Let $E$ be a Hermitian vector bundle over a complete Kähler manifold $(X,ω)$, $\dim_{\mathbb{C}}X=n$, with a $d$(bounded) Kähler form $ω$, $d_{A}$ be a Hermitian connection on $E$. The goal of this article is to study the $L^{2}$-Hodge theory on the vector bundle $E$. We extend the results of Gromov's \cite{Gro} to the Hermitian vector bundle. At last, a

Jacques Kaiser, Hesham Mostafa, Emre Neftci

A growing body of work underlines striking similarities between biological neural networks and recurrent, binary neural networks. A relatively smaller body of work, however, discusses similarities between learning dynamics employed in deep artificial neural networks and synaptic plasticity in spiking neural networks. The challenge preventing this is largely

Boris Pittel

Bollobás-Riordan random pairing model of a preferential attachment graph $G_m^n$ is studied. Let $\{W_j\}_{j\le mn+1}$ be the process of sums of independent exponentials with mean $1$. We prove that the degrees of the first $ν_m^n:=n^{\frac{m}{m+2}-ε}$ vertices are jointly, and uniformly, asymptotic to $\{2(mn)^{1/2}\bigl(W^{1/2}_{mj}-W^{1/2}_{m(j-1)}\bigr)\

Chengjiang Long, Arslan Basharat, Anthony Hoogs

Videos can be manipulated by duplicating a sequence of consecutive frames with the goal of concealing or imitating a specific content in the same video. In this paper, we propose a novel coarse-to-fine framework based on deep Convolutional Neural Networks to automatically detect and localize such frame duplication. First, an I3D network finds coarse-level ma

Tae Jin Park, Kyu Han, Ian Lane, Panayiotis Georgiou

This work presents a novel approach to leverage lexical information for speaker diarization. We introduce a speaker diarization system that can directly integrate lexical as well as acoustic information into a speaker clustering process. Thus, we propose an adjacency matrix integration technique to integrate word level speaker turn probabilities with speaker

Shijun Yoshida

We construct the stably stratified magnetized stars within the framework of general relativity. The effects of magnetic fields on the structure of the star and spacetime are treated as perturbations of non-magnetized stars. By assuming ideal magnetohydrodynamics and employing one-parameter equations of state, we derive basic equations for describing stationa

J. I. Katz

Repeating and apparently non-repeating fast radio bursts (FRB) differ by orders of magnitude in duty factors, energy and rotation measure. Extensive monitoring of apparently non-repeating FRB has failed to find any repetitions. This suggests the two types differ qualitatively, rather than in repetition rate, and are produced by distinct kinds of sources. The

Weidong Sun, Gao Tang, Kris Hauser

We present an efficient optimization framework that solves trajectory optimization problems by decoupling state variables from timing variables, thereby decomposing a challenging nonlinear programming (NLP) problem into two easier subproblems. With timing fixed, the state variables can be optimized efficiently using convex optimization, and the timing variab

Gumaro Rendon, Luka Leskovec, Stefan Meinel, John Negele

In this project, we will compute the form factors relevant for $B \to K^*(\to K π)\ell^+\ell^-$ decays. To map the finite-volume matrix elements computed on the lattice to the infinite-volume $B \to K π$ matrix elements, the $K π$ scattering amplitude needs to be determined using Lüscher's method. Here we present preliminary results from our calculations

Silvia de Juan, Judi Hewitt, Maria Dulce Subida, Simon Thrush

It is crucial that societies are informed on the risks of impoverished ecosystem health for their well-being. For this purpose, Ecological Integrity (EI) is a useful concept that seeks to capture the complex nature of ecosystems and their interaction with social welfare. But the challenge remains to measure EI and translate scientific terminology into operat

Alev Kelleci

In this paper, we give the definition of the natural mate of a non-null Frenet curve in Minkowski 3-spaces. The main purpose of this paper is to prove some relationships between a non-null Frenet curve and its natural mate. In particular, we obtain some necessary and suffcient conditions for the natural mate of a non-null Frenet curve to be a slant helix, a

Yusuke Kaino, Shogo H. Nakakita, Masayuki Uchida

We consider parametric estimation for ergodic diffusion processes with noisy sampled data based on the hybrid method, that is, the multi-step estimation with the initial Bayes type estimators. In order to select proper initial values for optimisation of the quasi likelihood function of ergodic diffusion processes with noisy observations, we construct the ini

Francesco Fraternali, Bharathan Balaji, Yuvraj Agarwal, Luca Benini

Smart building applications require a large-scale deployment of sensors distributed across the environment. Recent innovations in smart environments are driven by wireless networked sensors as they are easy to deploy. However, replacing these batteries at scale is a non-trivial, labor-intensive task. Energy harvesting has emerged as a potential solution to a

Xiaowei Liu

The so-called \textit{China crisis}, well documented in \textit{History of the IAU} by Adriaan Blaauw and in \textit{Under the Same Starry Sky: History of the IAU} by Chengqi Fu and Shuhua Ye, refers to the withdrawal in 1960 of the People's Republic of China (PRC) from the Union. The crisis stemmed from the admission by the IAU, amidst strong protest fr

Mikhail B. Salin, Dmitrii A. Kosteev

The paper is devoted to the usage of nearfield acoustic holography methods for estimating far field of the object. An experiment was carried out in anechoic chamber. First, acoustic filed was recorded in a plane that was close to source. This signals records were used to reconstruct the far field by computation routines. Second, the signal in the far field i

Cedric Bellis

This study addresses the question of the quantitative reconstruction of heterogeneous distributions of isotropic elastic moduli from full strain field data. This parameter identification problem exposes the need for a local reconstruction procedure that is investigated here in the case of materials with small contrast. To begin with the integral formulation

Cedric Bellis, Pierre Suquet

The homogenization of periodic elastic composites is addressed through the reformulation of the local equations of the mechanical problem in a geometric functional setting. This relies on the definition of Hilbert spaces of kinematically and statically admissible tensor fields, whose orthogonality and duality properties are recalled. These are endowed with s

Trevor P. Searight

A five-dimensional theory of relativity is presented which suggests that gravitation and electromagnetism may be unified using a degenerate metric. There are four fields (in the four-dimensional sense): a tensor field, two vector fields and a scalar field, and they are unified with a combination of a gauge-like invariance and a reflection symmetry which mean

Randall L. Rathbun

By examining the 3 surface angles which exist at any of the 8 vertices of a Diophantine parallelepiped, and classifying them by the appearance of a right angle, it is discovered that 5 unique classes of Diophantine parallelepipeds exist. It is proposed to name these classes: acute (triclinic), obtuse (triclinic), 1-ortho (biclinic), 2-ortho (monoclinic), and

Wei Wei, Lingjie Xu, Lingling Jin, Wei Zhang

Deep neural network (DNN) architectures, such as convolutional neural networks (CNN), involve heavy computation and require hardware, such as CPU, GPU, and AI accelerators, to provide the massive computing power. With the many varieties of AI hardware prevailing on the market, it is often hard to decide which one is the best to use. Thus, benchmarking AI har