November 2018 arXiv papers — page 23

Semih Cayci, Atilla Eryilmaz

We study the problem of serving randomly arriving and delay-sensitive traffic over a multi-channel communication system with time-varying channel states and unknown statistics. This problem deviates from the classical exploration-exploitation setting in that the design and analysis must accommodate the dynamics of packet availability and urgency as well as t

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

Abhishek Thakur, Arnav Dhamija, Tejeshwar Reddy G

Crowd-sourced video distribution is frequently of interest in the local vicinity. In this paper, we propose a novel design to transfer such content over opportunistic networks with adaptive quality encoding to achieve reasonable delay bounds. The video segments are transmitted between source and destination in a delay tolerant manner using the Nearby Connect

Hongbin Fang, Suyi Li, Manoj Thota, Kon-Well Wang

Lattices and their underlying symmetries play a central role in determining the physical properties and applications of many natural and engineered materials. By bridging the lattice geometry and rigid-folding kinematics, this study elucidates that origami offers a comprehensive solution to a long-standing challenge regarding the lattice-based materials: how

Hideaki Ooshima, Katsumi Ooshima

We define two new unstable n-fold Toda brackets for every composable sequence (f_n, ... ,f_1) of pointed maps f_i : X_i \to X_{i+1} between well-pointed spaces with n > 2. The brackets agree with the classical Toda bracket when n = 3, and they are subsets of both the unstable n-fold Toda brackets of Gershenson and Cohen for every n > 2.

O. M. Sotnikov, V. V. Mazurenko, J. Colbois, F. Mila

Skyrmions in condensed matter physics appear as classical topological spin structures. This nontrivial state can be obtained solving the corresponding micromagnetic model, where the magnetization is treated as a continuous classical vector field. Here, we introduce a new concept of quantum skyrmions of a nanoscale size. This distinct magnetic state can be fo

Hao Jeng, Spyros Tserkis, Jing Yan Haw, Helen M. Chrzanowski

Measures of entanglement can be employed for the analysis of numerous quantum information protocols. Due to computational convenience, logarithmic negativity is often the choice in the case of continuous variable systems. In this work, we analyse a continuous variable measurement-based entanglement distillation experiment using a collection of entanglement m

Nathaniel Watson, Steve Reeves, Paolo Masci

Creating formal models of interactive systems has wide reaching benefits, not only for verifying low-level correctness, but also as a tool for ensuring user interfaces behave logically and consistently. Despite this, tools for designing user experiences and tools for creating and working with formal models are typically distinctly separate systems. This work

Spencer Park, Emil Sekerinski

This paper proposes the use of notebooks for the design documentation and tool interaction in the rigorous design of embedded systems. Conventionally, a notebook is a sequence of cells alternating between (textual) code and prose to form a document that is meant to be read from top to bottom, in the spirit of literate programming. We extend the use of notebo

Makarius Wenzel

Isabelle/jEdit is the main application of the Prover IDE (PIDE) framework and the default user-interface of Isabelle, but it is not limited to theorem proving. This paper explores possibilities to use it as a general IDE for formal languages that are defined in user-space, and embedded into informal text documents. It covers overall document structure with a

Alexander Knüppel, Thomas Thüm, Carsten Pardylla, Ina Schaefer

Deductive verification of software has not yet found its way into industry, as complexity and scalability issues require highly specialized experts. The long-term perspective is, however, to develop verification tools aiding industrial software developers to find bugs or bottlenecks in software systems faster and more easily. The KeY project constitutes a fr

Rui Couto, José C. Campos, Nuno Macedo, Alcino Cunha

Alloy is a lightweight formal specification language, supported by an IDE, which has proven well-suited for reasoning about software design in early development stages. The IDE provides a visualizer that produces graphical representations of analysis results, which is essential for the proper validation of the model. Alloy is a rich language but inherently s

Paolo Arcaini, Riccardo Melioli, Elvinia Riccobene

Abstract State Machines (ASMs) have shown to be a suitable high-level specification method for complex, even industrial, systems; the ASMETA framework, supporting several validation and verification activities on ASM models, is an example of a formal integrated development environment. Although ASMs allow modeling complex systems in a rather concise way -and

Jan Bessai, Anna Vasileva

Usability is crucial for the adoption of software development technologies. This is especially true in development stages, where build processes fail, because software is not yet complete or was incompletely modified. We present early work that aims to improve usability of the Combinatory Logic Synthesizer (CL)S framework, especially in these stages. (CL)S i

Sylvain Dailler, Claude Marché, Yannick Moy

Among formal methods, the deductive verification approach allows establishing the strongest possible formal guarantees on critical software. The downside is the cost in terms of human effort required to design adequate formal specifications and to successfully discharge the required proof obligations. To popularize deductive verification in an industrial sof

Suwon Shon, Tae-Hyun Oh, James Glass

In this paper, we present a multi-modal online person verification system using both speech and visual signals. Inspired by neuroscientific findings on the association of voice and face, we propose an attention-based end-to-end neural network that learns multi-sensory associations for the task of person verification. The attention mechanism in our proposed n

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

Xiaoshuang Shi, Fuyong Xing, Zizhao Zhang, Manish Sapkota

Maintaining the pair similarity relationship among originally high-dimensional data into a low-dimensional binary space is a popular strategy to learn binary codes. One simiple and intutive method is to utilize two identical code matrices produced by hash functions to approximate a pairwise real label matrix. However, the resulting quartic problem is difficu

Nina Hernitschek, Judith G. Cohen, Hans-Walter Rix, Eugene Magnier

We present new spatial models and distance estimates for globular clusters (GC) and dwarf spheroidals (dSphs) orbiting our Galaxy based on RR Lyrae (RRab) stars in the Pan-STARRS1 (PS1) 3$\pi$ survey. Using the PS1 sample of RRab stars from Sesar et al. (2017) in 16 globular clusters and 5 dwarf galaxies, we fit structural models in $(l,b,D)$ space; for 13 g

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 and o

Kohta Hatakeyama, Asato Tsuchiya, Kazushi Yamashiro

We study renormalization on the fuzzy sphere, which is a typical example of non-commutative spaces. We numerically simulate a scalar field theory on the fuzzy sphere, which is described by a Hermitian matrix model. We define correlation functions by using the Berezin symbol and show that they are made independent of the matrix size, which plays a role of a U

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.

Sudhanshu Kumar, Shirsendu Sukanta Halder, Kanjar De, Partha Pratim Roy

Recommendation systems are important intelligent systems that play a vital role in providing selective information to users. Traditional approaches in recommendation systems include collaborative filtering and content-based filtering. However, these approaches have certain limitations like the necessity of prior user history and habits for performing the tas

Josefa M. Garcia, Pascual Jara

In fuzzy theory of sets and groups, the use of $\alpha$--levels is a standard to translate problems from the fuzzy to the crisp framework. Using strong $\alpha$--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 th

Michael Szmuk, Taylor P. Reynolds, Behcet Acikmese

In this paper, we present a real-time successive convexification algorithm for a generalized free-final-time 6-degree-of-freedom powered descent guidance problem. We build on our previous work by introducing the following contributions: (i) a free-ignition-time modification that allows the algorithm to determine the optimal engine ignition time, (ii) a tract

Nianpeng Lu, Yujia Wang, Shuang Qiao, Hao-Bo Li

Design novel solid oxide electrolyte with enhanced ionic conductivity forms one of the Holy Grails in the field of materials science due to its great potential for wide range of energy applications. Conventional solid oxide electrolyte typically requires elevated temperature to activate the ionic transportation, while it has been increasing research interest

Shirsendu Sukanta Halder, Kanjar De, Partha Pratim Roy

Colours are everywhere. They embody a significant part of human visual perception. In this paper, we explore the paradigm of hallucinating colours from a given gray-scale image. The problem of colourization has been dealt in previous literature but mostly in a supervised manner involving user-interference. With the emergence of Deep Learning methods numerous

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

Yongyong Wei, Cristian Frincu, Rong Zheng

Fingerprint-based indoor localization methods are promising due to the high availability of deployed access points and compatibility with commercial-off-the-shelf user devices. However, to train regression models for localization, an extensive site survey is required to collect fingerprint data from the target areas. In this paper, we consider the problem of

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

Zhuolu Li, Shengchun Shen, Zijun Tian, Kyle Hwangbo

Ionic substitution forms an essential pathway to manipulate the carrier density and crystalline symmetry of materials via ion-lattice-electron coupling, leading to a rich spectrum of electronic states in strongly correlated systems. Using the ferromagnetic metal SrRuO3 as a model system, we demonstrate an efficient and reversible control of both carrier dens

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

W. Ronny Huang, Miguel A. Perez

Inherent risk scoring is an important function in anti-money laundering, used for determining the riskiness of an individual during onboarding $\textit{before}$ fraudulent transactions occur. It is, however, often fraught with two challenges: (1) inconsistent notions of what constitutes as high or low risk by experts and (2) the lack of labeled data. This pa

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 complemen

Enya Shen, Zhidong Cao, Changqing Zou, Jianmin Wang

Network embedding aims to find a way to encode network by learning an embedding vector for each node in the network. The network often has property information which is highly informative with respect to the node's position and role in the network. Most network embedding methods fail to utilize this information during network representation learning. In this

Shirsendu Sukanta Halder, Sanchayan Santra, Bhabatosh Chanda

Haze and fog reduce the visibility of outdoor scenes as a veil like semi-transparent layer appears over the objects. As a result, images captured under such conditions lack contrast. Image dehazing methods try to alleviate this problem by recovering a clear version of the image. In this paper, we propose a Fully Convolutional Neural Network based model to re

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

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

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

Bryan W. Lynn, Glenn D. Starkman

The Standard Model of particle physics, augmented with neutrino mixing, is at least very nearly the complete theory of interactions of known particles at energies accessible to Nature on Earth. Candidate effective theories of nuclear structure must therefore reflect SM symmetries, especially the chiral global $SU(2)_L \times SU(2)_R$ symmetry of two-massless

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 $\varphi(q)$ and $\psi(q)$ we present many formulas and

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

Kosuke Namekata, Hiroyuki Maehara, Yuta Notsu, Shin Toriumi

Active solar-type stars show large quasi-periodic brightness variations caused by stellar rotations with star spots, and the amplitude changes as the spots emerge and decay. The Kepler data are suitable for investigations on the emergence and decay processes of star spots, which are important to understand underlying stellar dynamo and stellar flares. In thi

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

J. Socorro, Omar E. Núñez, Rafael Hernández-Jiménez

A flat Fiedmann-Robertson-Walker (FRW) multi-scalar field cosmology is studied with a particular potential of the form $ \rm V(\phi,\sigma)=V_0 e^{-\lambda_1 \phi-\lambda_2 \sigma}$, which emerges as a relation between the time derivatives of the scalars field momenta. Classically, by employing the Hamiltonian formalism of two scalar fields $\rm(\phi,\sigma)

Naser Ahmadiniaz, Christian Schubert

The Bern-Kosower formalism, developed around 1990 as a novel way of obtaining QCD amplitudes as the limit of infinite string tension of the corresponding string amplitudes, was originally designed as an on-shell formalism. Building on early work by Strassler, the authors have recently shown that this `string-inspired formalism' is extremely efficient also as

Wei Shen, Rujie Liu

Softmax activation is commonly used to output the probability distribution over categories based on certain distance metric. In scenarios like one-shot learning, the distance metric is often chosen to be squared Euclidean distance between the query sample and the category prototype. This practice works well in most time. However, we find that choosing square

Yue Hu, Xiaohan Liu, Mathews Jacob

Recent theory of mapping an image into a structured low-rank Toeplitz or Hankel matrix has become an effective method to restore images. In this paper, we introduce a generalized structured low-rank algorithm to recover images from their undersampled Fourier coefficients using infimal convolution regularizations. The image is modeled as the superposition of

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

Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu

Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings. In this paper, we propose a novel method for joint representation learning of cross-lingual words and entities. It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and text

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

Alban de Vaucorbeil, Chad W. Sinclair, Warren J. Poole

In certain naturally aged aluminum alloys, significant strengthening can be obtained due to the decomposition of a super-saturated solid solution into clusters. The origins of such strengthening remain unclear due to the challenge of differentiating solute cluster strengthening from solid solution or precipitate strengthening. To shed light on the origin of

Katharina Kann, Alex Warstadt, Adina Williams, Samuel R. Bowman

Verbs occur in different syntactic environments, or frames. We investigate whether artificial neural networks encode grammatical distinctions necessary for inferring the idiosyncratic frame-selectional properties of verbs. We introduce five datasets, collectively called FAVA, containing in aggregate nearly 10k sentences labeled for grammatical acceptability,

Teng Huang

Let $E$ be a Hermitian vector bundle over a complete K\"{a}hler manifold $(X,\omega)$, $\dim_{\mathbb{C}}X=n$, with a $d$(bounded) K\"{a}hler form $\omega$, $d_{A}$ 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 bund

Majid Soleimani nia, Peter Oshkai, Ned Djilali

Fundamental insight into the physics of buoyant gas dispersion from realistic flow geometries is necessary to accurately predict flow structures associated with hydrogen outflow from accidental leaks and the associated flammability envelope. Using helium as an experimental proxy, turbulent buoyant jets issuing from high-aspect-ratio slots on the side wall of

T. Leroux, S. -H. Ieng, R. Benosman

This paper presents a new method for 3D depth estimation using the output of an asynchronous time driven image sensor. In association with a high speed Digital Light Processing projection system, our method achieves real-time reconstruction of 3D points cloud, up to several hundreds of hertz. Unlike state of the art methodology, we introduce a method that re

Wei Shen, Rujie Liu

Recent advances in fine-grained recognition utilize attention maps to localize objects of interest. Although there are many ways to generate attention maps, most of them rely on sophisticated loss functions or complex training processes. In this work, we propose a simple and straightforward attention generation model based on the output activations of classi

Yin Huang, Cheng-jian Xiao, Li-Sheng Geng, Jun He

We study the strong decays of the newly observed $\Xi_b(6227)$ assuming that it is a pure $\Sigma_b\bar{K}$ molecular state. Considering four possible spin-parity assingments $J^P=1/2^{\pm}$ and $3/2^{\pm}$, the partial decay widths of the $\Sigma_b\bar{K}$ molecular state into $\Lambda_b\bar{K}$, $\Xi_b\pi$, and $\Xi_b^{'}\pi$ final states through hadronic

Junqiang Zhang, Zongguang Liu

In this article, the authors consider the Schr\"{o}dinger type operator $L:=-{\rm div}(A\nabla)+V$ on $\mathbb{R}^n$ with $n\geq 3$, where the matrix $A$ satisfies uniformly elliptic condition and the nonnegative potential $V$ belongs to the reverse H\"{o}lder class $RH_q(\mathbb{R}^n)$ with $q\in(n/2,\,\infty)$. Let $p(\cdot):\ \mathbb{R}^n\to(0,\,\infty)$

Juan C. Martínez Mori, Samitha Samaranayake

We introduce the batched set cover problem, which is a generalization of the online set cover problem. In this problem, the elements of the ground set that need to be covered arrive in batches. Our main technical contribution is a tight $\Omega(H_{m - 2^z + 1})$ lower bound on the competitive ratio of any fractional batched algorithm given an adversary that

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

Vikas Nandal, Pradeep R. Nair

Demonstration of high-efficiency large area cells with excellent stability is an important requirement towards commercialization of perovskite solar cells (PSC). With reports of high-quality perovskite grains, it is evident that the performance of such large area cells will be strongly influenced by phenomena like carrier recombination and ion migration at g

Boris Pittel

Bollob\'as-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 $\nu_m^n:=n^{\frac{m}{m+2}-\epsilon}$ vertices are jointly, and uniformly, asymptotic to $\{2(mn)^{1/2}\bigl(W^{1/2}_{mj}-W^{1/2}_{m(j

Xiao Wang, Tao Sun, Rui Yang, Chenglong Li

Incorporating various modes of information into the machine learning procedure is becoming a new trend. And data from various source can provide more information than single one no matter they are heterogeneous or homogeneous. Existing deep learning based algorithms usually directly concatenate features from each domain to represent the input data. Seldom of

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 from P

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

Ben F. M. Intoy, J. Woods Halley

We apply previously introduced measures of chemical disequilibrium to Cassini mass spectroscopy data on the atmosphere of Titan. In the analysis presented here, we use an improved description, avoiding the meanfield approximation in previous work. The results of the analysis are nearly exactly the same as those found earlier and confirm that, with respect to

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

Thomas Fauchez, Giada Arney, Ravi Kumar Kopparapu, Shawn Domagal Goldman

1D climate models are less sophisticated than 3D global circulation models (GCMs), however their computational time is much less expensive, allowing a large number of runs in a short period of time to explore a wide parameter space. Exploring parameter space is particularly important for predicting the observable properties of exoplanets, for which few param

Matías Pavez, Javier Ruiz del Solar, Victoria Amo, Felix Meyer zu Driehausen

Long-term memory is essential to feel like a continuous being, and to be able to interact/communicate coherently. Social robots need long-term memories in order to establish long-term relationships with humans and other robots, and do not act just for the moment. In this paper this challenge is highlighted, open questions are identified, the need of addressi

Wenceslao Shaw Cortez, Denny Oetomo, Chris Manzie, Peter Choong

For successful object manipulation with robotic hands, it is important to ensure that the object remains in the grasp at all times. In addition to grasp constraints associated with slipping and singular hand configurations, excessive rolling is an important grasp concern where the contact points roll off of the fingertip surface. Related literature focus onl

Linhai Xie, Yishu Miao, Sen Wang, Phil Blunsom

Due to the sparse rewards and high degree of environment variation, reinforcement learning approaches such as Deep Deterministic Policy Gradient (DDPG) are plagued by issues of high variance when applied in complex real world environments. We present a new framework for overcoming these issues by incorporating a stochastic switch, allowing an agent to choose

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

Naota Furutachi, Futoshi Minato, Osamu Iwamoto

A phenomenological level density model that has different level density parameter sets for the state densities of the deformed and the spherical states, and the optimization of the parameters using experimental data of the average s-wave neutron resonance spacing are presented. The transition to the spherical state from the deformed one is described using th

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

Dmitry Gavinsky, Troy Lee, Miklos Santha, Swagato Sanyal

Let $R_\epsilon(\cdot)$ stand for the bounded-error randomized query complexity with error $\epsilon > 0$. For any relation $f \subseteq \{0,1\}^n \times S$ and partial Boolean function $g \subseteq \{0,1\}^m \times \{0,1\}$, we show that $R_{1/3}(f \circ g^n) \in \Omega(R_{4/9}(f) \cdot \sqrt{R_{1/3}(g)})$, where $f \circ g^n \subseteq (\{0,1\}^m)^n \times

Sanghamitra Dutta, Ziqian Bai, Haewon Jeong, Tze Meng Low

This paper has two contributions. First, we propose a novel coded matrix multiplication technique called Generalized PolyDot codes that advances on existing methods for coded matrix multiplication under storage and communication constraints. This technique uses "garbage alignment," i.e., aligning computations in coded computing that are not a part of the des

Gumaro Rendon, Luka Leskovec, Stefan Meinel, John Negele

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

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

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

Ye Zhao, Luis Sentis

Robotic systems are increasingly relying on distributed feedback controllers to tackle complex and latency-prone sensing and decision problems. These demands come at the cost of a growing computational burden and, as a result, larger controller latencies. To maximize robustness to mechanical disturbances and achieve high control performance, we emphasize the

Xiang Xu, Yanxiang Zhao

In this paper, we propose a first order energy stable linear semi-implicit method for solving the Allen-Cahn-Ohta-Kawasaki equation. By introducing a new nonlinear term in the Ohta-Kawasaki free energy functional, all the system forces in the dynamics are localized near the interfaces which results in the desire hyperbolic tangent profile. In our numerical m

Shai Biton, Guy Gilboa

A fundamental concept in solving inverse problems is the use of regularizers, which yield more physical and less-oscillatory solutions. Total variation (TV) has been widely used as an edge-preserving regularizer. However, objects are often over-regularized by TV, becoming blob-like convex structures of low curvature. This phenomenon was explained mathematica

Francesco Fraternali, Bharathan Balaji, Rajesh Gupta

With the advent of the Internet of Things (IoT), an increasing number of energy harvesting methods are being used to supplement or supplant battery based sensors. Energy harvesting sensors need to be configured according to the application, hardware, and environmental conditions to maximize their usefulness. As of today, the configuration of sensors is eithe

Maxim Rakhuba, Alexander Novikov, Ivan Oseledets

Such problems as computation of spectra of spin chains and vibrational spectra of molecules can be written as high-dimensional eigenvalue problems, i.e., when the eigenvector can be naturally represented as a multidimensional tensor. Tensor methods have proven to be an efficient tool for the approximation of solutions of high-dimensional eigenvalue problems,

James Rynn, Simon Cotter, Catherine E Powell, Louise Wright

Determination of the thermal properties of a material is an important task in many scientific and engineering applications. How a material behaves when subjected to high or fluctuating temperatures can be critical to the safety and longevity of a system's essential components. The laser flash experiment is a well-established technique for indirectly meas

Iasson Karafyllis, Maria Kontorinaki, Miroslav Krstic

The paper extends a recently proposed indirect, certainty-equivalence, event-triggered adaptive control scheme to the case of non-observable parameters. The extension is achieved by using a novel Batch Least-Squares Identifier (BaLSI), which is activated at the times of the events. The BaLSI guarantees the finite-time asymptotic constancy of the parameter es

Andrew J. Kurdila, Parag Bobade

Koopman theory studies dynamical systems in terms of operator theoretic properties of the Perron-Frobenius operator $\mathcal{P}$ and Koopman operator $\mathcal{U}$ respectively. In this paper, we derive the rates of convergence of approximations of $\mathcal{P}$ or $\mathcal{U}$ that are generated by finite dimensional bases like wavelets, multiwavelets, an

Wei Xiao, Christos G. Cassandras

This paper addresses the optimal control of Connected and Automated Vehicles (CAVs) arriving from two roads at a merging point where the objective is to jointly minimize the travel time and energy consumption of each CAV. The solution guarantees that a speed-dependent safety constraint is always satisfied, both at the merging point and everywhere within a co

Tuğba Akman Yıldız, Murat Uzunca, Bülent Karasözen

Minimization of energy in gradient systems leads to formation of oscillatory and Turing patterns in reaction-diffusion systems. These patterns should be accurately computed using fine space and time meshes over long time horizons to reach the spatially inhomogeneous steady state. In this paper, a reduced order model (ROM) is developed which preserves the gra

Tony Shardlow

The Feynman-Kac formula for the exterior-value problem for the fractional Laplacian leads to a walk-outside-spheres algorithm via sampling alpha-stable Levy processes on their exit from maximally inscribed balls and sampling their occupation distribution. Kyprianou, Osojnik, and Shardlow (2017) developed this algorithm, providing a complexity analysis and an

Michael A. Bennett, Greg Martin, Kevin O'Bryant, Andrew Rechnitzer

We derive explicit upper bounds for various functions counting primes in arithmetic progressions. By way of example, if $q$ and $a$ are integers with $\gcd(a,q)=1$ and $3 \leq q \leq 10^5$, and $θ(x;q,a)$ denotes the sum of the logarithms of the primes $p \equiv a \pmod{q}$ with $p \leq x$, we show that $$ \bigg| θ(x; q, a) - \frac{x}{ϕ(q)} \bigg| < \frac1{1