July 2019 arXiv papers — page 41

Nicolas Berkouk, Grégory Ginot, Steve Oudot

In this paper we provide an explicit connection between level-sets persistence and derived sheaf theory over the real line. In particular we construct a functor from 2-parameter persistence modules to sheaves over $\mathbb{R}$, as well as a functor in the other direction. We also observe that the 2-parameter persistence modules arising from the level sets of

Ayelet Zalic, Shahar Simon, Sergei Remennik, Atzmon Vakahi

We report on fabrication of devices integrating FeTe$_{0.55}$Se$_{0.45}$ with other van-der-Waals materials, measuring transport properties as well as tunneling spectra at variable magnetic fields and temperatures down to 35 mK. Transport measurements are reliable and repeatable, revealing temperature and magnetic field dependence in agreement with prior res

Karolina Kalbarczyk, Krzysztof Dybko, Katarzyna Gas, Dariusz Sztenkiel

Schottky barrier height and the ideality factor $η$ are established for the first time in the single phase (Ga,Mn)N using a vertical geometry device. The material has been heteroepitaxially grown on commercially available low threading dislocation density GaN:Si template. The observed above 10M$Ω$ resistances already at room temperature are indicative that a

Giuseppe Bove, Pier Luigi Conti, Daniela Marella

A measure of interrater absolute agreement for ordinal scales is proposed capitalizing on the dispersion index for ordinal variables proposed by Giuseppe Leti. The procedure allows to avoid the problem of restriction of variance that sometimes affect traditional measures of interrater agreement in different fields of application. An unbiased estimator of the

Yaxing Wang, Abel Gonzalez-Garcia, Joost van de Weijer, Luis Herranz

The task of unpaired image-to-image translation is highly challenging due to the lack of explicit cross-domain pairs of instances. We consider here diverse image translation (DIT), an even more challenging setting in which an image can have multiple plausible translations. This is normally achieved by explicitly disentangling content and style in the latent

Manisha Chowdhury, B. V. Rathish Kumar

In this paper subgrid multiscale stabilized finite element method for Advection-Diffusion-Reaction (ADR) equation coupled with Stokes-Darcy flow problem has been studied. Here the advection velocity involved in ADR equation obeys Stokes-Darcy flow equation. In this study the approach of algebraic approximation of stabilization parameter has been considered.

Yaxiong Wang, Hao Yang, Xueming Qian, Lin Ma

Image-text matching tasks have recently attracted a lot of attention in the computer vision field. The key point of this cross-domain problem is how to accurately measure the similarity between the visual and the textual contents, which demands a fine understanding of both modalities. In this paper, we propose a novel position focused attention network (PFAN

Ming Yin, Weitian Huang, Junbin Gao

Clustering multi-view data has been a fundamental research topic in the computer vision community. It has been shown that a better accuracy can be achieved by integrating information of all the views than just using one view individually. However, the existing methods often struggle with the issues of dealing with the large-scale datasets and the poor perfor

Lothar Nannen, Markus Wess

The technique of complex scaling for time harmonic wave type equations relies on a complex coordinate stretching to generate exponentially decaying solutions. In this work, we use a Galerkin method with ansatz functions with infinite support to discretize complex scaled Helmholtz resonance problems. We show that the approximation error of the method decays s

Junjie Huang, Tiejian Luo

A typical social research topic is to figure out the influential people's relationship and its weights. It is very tedious for social scientists to solve those problems by studying massive literature. Digital humanities bring a new way to a social subject. In this paper, we propose a framework for social scientists to find out ancient figures' power

Félix Cabello Sánchez, Antonio Avilés, Piotr Borodulin-Nadzieja, David Chodounský

We study splitting chains in $\mathscr{P}(ω)$, that is, families of subsets of $ω$ which are linearly ordered by $\subseteq^*$ and which are splitting. We prove that their existence is independent of axioms of $\mathsf{ZFC}$. We show that they can be used to construct certain peculiar Banach spaces: twisted sums of $C(ω^*)=\ell_\infty/c_0$ and $c_0(\mathfrak

Kai Brehmer, Benjamin Wacker, Jan Modersitzki

Quantification of image similarity is a common problem in image processing. For pairs of two images, a variety of options is available and well-understood. However, some applications such as dynamic imaging or serial sectioning involve the analysis of image sequences and thus require a simultaneous and unbiased comparison of many images. This paper proposes

E. Constable, A. D. Squires, J. Horvat, R. A. Lewis

The low energy lattice dynamics of the quasi-periodic spin-ladder cuprate Sr$_{14-x}$Ca$_x$Cu$_{24}$O$_{41}$ are investigated using terahertz frequency synchrotron radiation. A high density of low-lying optical excitations are present in the 1-3 THz energy range, while at least two highly absorbing excitations stemming from rigid acoustic oscillations of the

Bryan Liu, Zhiqiang Wei, Jinhong Yuan, Milutin Pajovic

In this paper, we propose a deep learning aided list approximate message passing (AMP) algorithm to further improve the user identification performance in massive machine type communications. A neural network is employed to identify a suspicious device which is most likely to be falsely alarmed during the first round of the AMP algorithm. The neural network

Kai Brehmer, Hari Om Aggrawal, Stefan Heldmann, Jan Modersitzki

Image registration, especially the quantification of image similarity, is an important task in image processing. Various approaches for the comparison of two images are discussed in the literature. However, although most of these approaches perform very well in a two image scenario, an extension to a multiple images scenario deserves attention. In this artic

J. Kudrnovský, V. Drchal, F. Máca, I. Turek

The high-entropy alloys Al$_{x}$CrFeCoNi exist over a broad range of Al concentrations ($0 < x < 2$). With increasing Al content their structure is changed from the fcc to bcc phase. We investigate the effect of such structural changes on transport properties including the residual resistivity and the anomalous Hall resistivity. We have performed a detailed

Emilie Forel, Benjamin Dollet, Dominique Langevin, Emmanuelle Rio

While coalescence is ultimately the most drastic destabilization process in foams, its underlying processes are still unclear. To better understand them, we track individual coalescence events in two-dimensional foams at controlled capillary pressure. We obtain statistical information revealing the influence of the different parameters which have been previo

Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola

Determining biomarkers for autism spectrum disorder (ASD) is crucial to understanding its mechanisms. Recently deep learning methods have achieved success in the classification task of ASD using fMRI data. However, due to the black-box nature of most deep learning models, it&#39;s hard to perform biomarker selection and interpret model decisions. The recentl

Yao Ming, Panpan Xu, Huamin Qu, Liu Ren

One of the major challenges in machine learning nowadays is to provide predictions with not only high accuracy but also user-friendly explanations. Although in recent years we have witnessed increasingly popular use of deep neural networks for sequence modeling, it is still challenging to explain the rationales behind the model outputs, which is essential fo

Satoshi Murai

Let $S_n$ be a polynomial ring with $n$ variables over a field and $\{I_n\}_{n \geq 1}$ a chain of ideals such that each $I_n$ is a monomial ideal of $S_n$ fixed by permutations of the variables. In this paper, we present a way to determine all nonzero positions of Betti tables of $I_n$ for all large intergers $n$ from the $\mathbb Z^m$-graded Betti table of

Oleksandr Teplytskyi, Illia Teplytskyi, Serhiy Semerikov, Vladimir Soloviev

The monograph defines the conditions of training of future teachers in natural sciences and mathematics by means of computer simulation, developed a structural-functional model of training, selected socio-constructivist forms of organization, methods and learning tools of computer modeling for future teachers of natural and mathematical disciplines.

Takeshi Ise, Yurika Oba

Analyzing and utilizing spatiotemporal big data are essential for studies concerning climate change. However, such data are not fully integrated into climate models owing to limitations in statistical frameworks. Herein, we employ VARENN (visually augmented representation of environment for neural networks) to efficiently summarize monthly observations of cl

Satoru Katsumata, Mamoru Komachi

We introduce unsupervised techniques based on phrase-based statistical machine translation for grammatical error correction (GEC) trained on a pseudo learner corpus created by Google Translation. We verified our GEC system through experiments on various GEC dataset, includi ng a low resource track of the shared task at Building Educational Applications 2019

Soojin Cho, JiSun Huh, Sun-Young Nam

We investigate chromatic symmetric functions in the relation to the algebra $Γ$ of symmetric functions generated by Schur $Q$-functions. We construct natural bases of $Γ$ in terms of chromatic symmetric functions. We also consider the $p$-positivity of skew Schur $Q$-functions and find a class of $p$-positive ribbon Schur $Q$-functions, making a conjecture t

Anshu Kumari, R. Ramesh, C. Kathiravan, T. J. Wang

We report a solar coronal split-band type II radio burst that was observed on 2016 March 16 with the Gauribidanur Radio Spectro-Polarimeter (GRASP) in the frequency range $\approx$\,90\,-\,50 MHz, and the Gauribidanur RadioheliograPH (GRAPH) at two discrete frequencies, viz. 80 MHz and 53.3 MHz. Observations around the same epoch in extreme-ultraviolet (EUV)

Jawdat Alshaer

A few years ago, Automotive area in the IoT was seen as theoretical concept and today we are already seeing the possibilities of not only driverless cars, but applications of IoT in the intelligent vehicles including parking, maintaining environment, protecting lives and smoothing the flow vehicle movements. We have realized the urgent need of using simple a

Mithilesh Singh

The propagation of nonlinear waves in one dimensional space, unsteady and compressible flow in Darcy-type porous media is analyzed. It is assumed that the weak discontinuity propagate long the characteristic path using the characteristics of the governing quasilinear system as the reference coordinate system. Evolution equation in the characteristic plane is

Yuming Chen, Wai Shun Cheung, Tuen Wai Ng

The voting rules of the European Council (EU) under the Treaty of Lisbon became effective on 1 November 2014. Kurz \& Napel (2015) showed that the dimension of this voting system is between $7$ and $13,368$. The lower bound $7$ actually sets a new world record for the dimension of the real-world voting bodies. In this article, by finding a new way to represe

Greta Faccio, Alice Cont, Erik Mailand, Elaheh Zare-Eelanjegh

By applying a slow curing process, we show that biomolecules can be incorporated via a simple process as liquid stable phases inside a polydimethylsiloxane (PDMS) matrix. The process is carried out under mild conditions with regards to temperature, pH and relative humidity, and is thus suitable for application to biological entities. Fluorescence and enzymat

Xu Chen, Siheng Chen, Huangjie Zheng, Jiangchao Yao

Graph structured data provide two-fold information: graph structures and node attributes. Numerous graph-based algorithms rely on both information to achieve success in supervised tasks, such as node classification and link prediction. However, node attributes could be missing or incomplete, which significantly deteriorates the performance. The task of node

Zhaoyi Wan, Fengming Xie, Yibo Liu, Xiang Bai

Scene text recognition has been an important, active research topic in computer vision for years. Previous approaches mainly consider text as 1D signals and cast scene text recognition as a sequence prediction problem, by feat of CTC or attention based encoder-decoder framework, which is originally designed for speech recognition. However, different from spe

Changkun Wei, Jiaqing Yang, Bo Zhang

This paper is concerned with the time-dependent acoustic-elastic interaction problem associated with a bounded elastic body immersed in a homogeneous air or fluid above an unbounded rough surface. The well-posedness and stability of the problem are first established by using the Laplace transform and the energy method. A perfectly matched layer (PML) is then

Tianwei Lin, Xiao Liu, Xin Li, Errui Ding

Temporal action proposal generation is an challenging and promising task which aims to locate temporal regions in real-world videos where action or event may occur. Current bottom-up proposal generation methods can generate proposals with precise boundary, but cannot efficiently generate adequately reliable confidence scores for retrieving proposals. To addr

Sooyoung Cha, Seongjoon Hong, Jingyoung Kim, Junhee Lee

We present a technique to automatically generate search heuristics for dynamic symbolic execution. A key challenge in dynamic symbolic execution is how to effectively explore the program&#39;s execution paths to achieve high code coverage in a limited time budget. Dynamic symbolic execution employs a search heuristic to address this challenge, which favors e

Jesús A. De Loera, Thomas A. Hogan

We present new stochastic geometry theorems that give bounds on the probability that $m$ random data classes all contain a point in common in their convex hulls. We apply these stochastic separation theorems to obtain bounds on the probability of existence of maximum likelihood estimators in multinomial logistic regression. We also discuss connections to con

Tao Sun, Dongsheng Li, Zhe Quan, Hao Jiang

Nonconvex optimization algorithms with random initialization have attracted increasing attention recently. It has been showed that many first-order methods always avoid saddle points with random starting points. In this paper, we answer a question: can the nonconvex heavy-ball algorithms with random initialization avoid saddle points? The answer is yes! Dire

Shivangi Srivastava, Maxim Berman, Matthew B. Blaschko, Devis Tuia

The problem of a deep learning model losing performance on a previously learned task when fine-tuned to a new one is a phenomenon known as Catastrophic forgetting. There are two major ways to mitigate this problem: either preserving activations of the initial network during training with a new task; or restricting the new network activations to remain close

Jaehyun Hong, Minhyuk Kwon

We classify smooth Schubert varieties S_0 in a rational homogeneous manifold S associated to a short root, and show that they are rigid in the sense that any subvariety of S having the same homology class as S_0 is induced by the action of Aut_0(S), unless S_0 is linear.

Boyuan Pan, Yazheng Yang, Zhou Zhao, Yueting Zhuang

Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), is one of the most important problems in natural language processing. It requires to infer the logical relationship between two given sentences. While current approaches mostly focus on the interaction architectures of the sentences, in this paper, we propose to transfer kn

Yeon Joo Lee, Kandis-Lea Jessup, Santiago Perez-Hoyos, Dmitrij V. Titov

An unknown absorber near the cloud top level of Venus generates a broad absorption feature from the ultraviolet (UV) to visible, peaking around 360 nm, and therefore plays a critical role in the solar energy absorption. We present a quantitative study on the variability of the cloud albedo at 365 nm and its impact on Venus&#39; solar heating rates based on a

Mansour Kalantar

We prove that the set of points where a subharmonic function fails to be continuous is polar.

Howard H. Yang, Ahmed Arafa, Tony Q. S. Quek, H. Vincent Poor

Optimization of information freshness in wireless networks has usually been performed based on queueing analysis that captures only the temporal traffic dynamics associated with the transmitters and receivers. However, the effect of interference, which is mainly dominated by the interferers&#39; geographic locations, is not well understood. In this paper, we

Marcus Hoerger, Hanna Kurniawati, Alberto Elfes

Planning under partial obervability is essential for autonomous robots. A principled way to address such planning problems is the Partially Observable Markov Decision Process (POMDP). Although solving POMDPs is computationally intractable, substantial advancements have been achieved in developing approximate POMDP solvers in the past two decades. However, co

David Gaddy, Dan Klein

We consider the problem of learning to map from natural language instructions to state transitions (actions) in a data-efficient manner. Our method takes inspiration from the idea that it should be easier to ground language to concepts that have already been formed through pre-linguistic observation. We augment a baseline instruction-following learner with a

Yongpei Zhu, Zicong Zhou, Guojun Liao, Kehong Yuan

Accurate registration of medical images is vital for doctor&#39;s diagnosis and quantitative analysis. In this paper, we propose a new deformable medical image registration method based on average geometric transformations and VoxelMorph CNN architecture. We compute the differential geometric information including Jacobian determinant(JD) and the curl vector

Linkai Luo, Yue Wang

This paper describes our approach to the EmotionX-2019, the shared task of SocialNLP 2019. To detect emotion for each utterance of two datasets from the TV show Friends and Facebook chat log EmotionPush, we propose two-step deep learning based methodology: (i) encode each of the utterance into a sequence of vectors that represent its meaning; and (ii) use a

Jing Tang, Keke Huang, Xiaokui Xiao, Laks V. S. Lakshmanan

As a dual problem of influence maximization, the seed minimization problem asks for the minimum number of seed nodes to influence a required number $η$ of users in a given social network $G$. Existing algorithms for seed minimization mostly consider the non-adaptive setting, where all seed nodes are selected in one batch without observing how they may influe

Liang Ze Wong

The smash product construction (or the Grothendieck construction) takes a functor (or prestack) $F \colon B^{op} \to \mathbf{Cat}$ and returns a fibration $p \colon A \to B$. In this paper, we develop an analogue of the smash product for prestacks internal to a non-cartesian monoidal category. Our construction simultaneously generalizes the Grothendieck cons

Jianwei Lee, Lijiong Shen, Alessandro Cerè, James Troupe

We demonstrate an attack on a clock synchronization protocol that attempts to detect tampering of the synchronization channel using polarization-entangled photon pairs. The protocol relies on a symmetrical channel, where propagation delays do not depend on propagation direction, for correctly deducing the offset between clocks -- a condition that could be ma

Haijun Liu, Jian Cheng

Existing person re-identification has achieved great progress in the visible domain, capturing all the person images with visible cameras. However, in a 24-hour intelligent surveillance system, the visible cameras may be noneffective at night. In this situation, thermal cameras are the best supplemental components, which capture images without depending on v

Junyang Gao, Xian Li, Yifan Ethan Xu, Bunyamin Sisman

Estimation of the accuracy of a large-scale knowledge graph (KG) often requires humans to annotate samples from the graph. How to obtain statistically meaningful estimates for accuracy evaluation while keeping human annotation costs low is a problem critical to the development cycle of a KG and its practical applications. Surprisingly, this challenging probl

Masoud Baghbahari, Aman Behal

Tactile perception is an essential ability of intelligent robots in interaction with their surrounding environments. This perception as an intermediate level acts between sensation and action and has to be defined properly to generate suitable action in response to sensed data. In this paper, we propose a feedback approach to address robot grasping task usin

Xuan Xue, Yongchao Wang, Long Yang, Jia Shi

This paper investigates the hybrid precoding design in millimeter-wave (mmWave) systems with a fully-adaptive-connected precoding structure, where a switch-controlled connection is deployed between every antenna and every radio frequency (RF) chain. To maximally enhance the energy efficiency (EE) of hybrid precoding under this structure, the joint optimizati

John A. Baldwin, Tye Lidman, C. -M. Michael Wong

We prove that the LOSS and GRID invariants of Legendrian links in knot Floer homology behave in certain functorial ways with respect to decomposable Lagrangian cobordisms in the symplectization of the standard contact structure on $\mathbb{R}^3$. Our results give new, computable, and effective obstructions to the existence of such cobordisms.

Fangneng Zhan, Chuhui Xue, Shijian Lu

Recent adversarial learning research has achieved very impressive progress for modelling cross-domain data shifts in appearance space but its counterpart in modelling cross-domain shifts in geometry space lags far behind. This paper presents an innovative Geometry-Aware Domain Adaptation Network (GA-DAN) that is capable of modelling cross-domain shifts concu

Ali Najmi, David Rey, Taha H. Rashidi, S. Travis Waller

In this paper, a novel transport planning model system (TPMS) is formulated which is built on the concepts of supernetworks, multi-modality, integrity and calibration. In the proposed formulation, activity travel pattern (ATP) choice facets including the choices of activity, activity sequence, mode, departure time, and parking location, are all unified into

Huabin Ge, Wenshuai Jiang, Hui-Chun Zhang

In this paper, we prove the Lipschitz regularity of continuous harmonic maps from an finite dimensional Alexandrov space to a compact smooth Riemannian manifold. This solves a conjecture of F. H. Lin in \cite{lin97}. The proof extends the argument of Huang-Wang \cite {hua-w10}.

M. Bzowski, A. Czechowski, P. C. Frisch, S. A. Fuselier

Interstellar neutral gas atoms penetrate the heliopause and reach 1~au, where they are detected by IBEX. The flow of neutral interstellar helium through the perturbed interstellar plasma in the outer heliosheath (OHS) results in creation of the secondary population of interstellar He atoms, the so-called Warm Breeze, due to charge exchange with perturbed ion

Jose Martinez-Bernal, Miguel A. Valencia-Bucio, Rafael H. Villarreal

Following Britz, Johnsen, Mayhew and Shiromoto, we consider demi\-ma\-troids as a(nother) natural generalization of matroids. As they have shown, demi\-ma\-troids are the appropriate combinatorial objects for studying Wei&#39;s duality. Our results here apport further evidence about the trueness of that observation. We define the Hamming polynomial of a demi

Rico Krueger, Taha H. Rashidi, Akshay Vij

In this paper, we contrast parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian multinomial logit models and leverage these methods to infer distributions of willingness to pay for features of shared automated vehicle (SAV) services. Specifically, we compare the multivariate normal (MVN), finite mixture of norma

Aidan Zellner, Alice M. Richardson, Brett A. Lidbury, Peter Hobson

Background: Reference intervals are essential to interpret diagnostic tests, but their determination has become controversial. Methods: In this paper parametric, non-parametric and robust reference intervals with Tukey and block elimination are calculated from a dataset of over 32,000 serum immunoglobulin A (IgA) measurements. Results: The outlier eliminatio

Nuno M. G. Paulino, Mathias Foo, Jongmin Kim, Declan G. Bates

Recent work has shown how chemical reaction network theory may be used to design dynamical systems that can be implemented biologically in nucleic acid-based chemistry. While this has allowed the construction of advanced open-loop circuitry based on cascaded DNA strand displacement (DSD) reactions, little progress has so far been made in developing the requi

Miguel Picallo, Adolfo Anta, Bart De Schutter

The small amount of measurements in distribution grids makes their monitoring more difficult. Topological observability may not be possible, and thus, pseudo-measurements are needed to perform state estimation, which is required to control elements such as distributed generation or transformers at distribution grids. Therefore, we consider the problem of opt

Dena Firoozi, Peter E. Caines, Sebastian Jaimungal

In many stochastic games stemming from financial models, the environment evolves with latent factors and there may be common noise across agents&#39; states. Two classic examples are: (i) multi-agent trading on electronic exchanges, and (ii) systemic risk induced through inter-bank lending/borrowing. Moreover, agents&#39; actions often affect the environment

Woojay Jeon, Maxwell Jordan, Mahesh Krishnamoorthy

We present a new method for computing ASR word confidences that effectively mitigates the effect of ASR errors for diverse downstream applications, improves the word error rate of the 1-best result, and allows better comparison of scores across different models. We propose 1) a new method for modeling word confidence using a Heterogeneous Word Confusion Netw

Zachary Cramer

Building on MacDonald's formula for the distance from a rank-one projection to the set of nilpotents in $\mathbb{M}_n(\mathbb{C})$, we prove that the distance from a rank $n-1$ projection to the set of nilpotents in $\mathbb{M}_n(\mathbb{C})$ is $\frac{1}{2}\sec\left(\frac{\pi}{\frac{n}{n-1}+2}\right)$. For each $n\geq 2$, we construct examples of pairs $(Q,

Daniel Z. Huang, Man Long Wong, Sanjiva K. Lele, Charbel Farhat

A homogenization approach is proposed for the treatment of porous wall boundary conditions in the computation of compressible viscous flows. Like any other homogenization approach, it eliminates the need for pore-resolved fluid meshes and therefore enables practical flow simulations in computational fluid domains with porous wall boundaries. Unlike alternati

Hyungmok Son, Juliana J. Park, Wolfgang Ketterle, Alan O. Jamison

Since the original work on Bose-Einstein condensation, quantum degenerate gases of atoms have allowed the quantum emulation of important systems from condensed matter and nuclear physics, as well as the study of novel many-body states with no analog in other fields of physics. Ultracold molecules in the micro- and nano-Kelvin regimes promise to bring powerfu

Po-Yu Kao, Jefferson W. Chen, B. S. Manjunath

The volume of stroke lesion is the gold standard for predicting the clinical outcome of stroke patients. However, the presence of stroke lesion may cause neural disruptions to other brain regions, and these potentially damaged regions may affect the clinical outcome of stroke patients. In this paper, we introduce the tractographic feature to capture these po

Ivan Corwin, Shalin Parekh

This is an expository note answering a question posed to us by Richard Stanley, in which we prove a limit shape theorem for partitions of $n$ which maximize the number of subpartitions. The limit shape and the growth rate of the number of subpartitions are explicit. The key ideas are to use large deviations estimates for random walks, together with convex an

Benjamin R. Ryan, Joshua C. Dolence

We present a conservative numerical method for radiation magnetohydrodynamics with frequency-dependent full transport in stationary spacetimes. This method is stable and accurate for both large and small optical depths and radiation pressures. The radiation stress-energy tensor is evolved in flux-conservative form, and closed with a swarm of samples that eac

Sarkhan Badirli, Zeynep Akata, Murat Dundar

Object classes that surround us have a natural tendency to emerge at varying levels of abstraction. We propose a Bayesian approach to zero-shot learning (ZSL) that introduces the notion of meta-classes and implements a Bayesian hierarchy around these classes to effectively blend data likelihood with local and global priors. Local priors driven by data from s

Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudík

We propose a new framework for designing estimators for off-policy evaluation in contextual bandits. Our approach is based on the asymptotically optimal doubly robust estimator, but we shrink the importance weights to minimize a bound on the mean squared error, which results in a better bias-variance tradeoff in finite samples. We use this optimization-based

N. Huang, L. E. Bleem, B. Stalder, P. A. R. Ade

We present a catalog of galaxy cluster candidates detected in 100 square degrees surveyed with the SPTpol receiver on the South Pole Telescope. The catalog contains 89 candidates detected with a signal-to-noise ratio greater than 4.6. The candidates are selected using the Sunyaev-Zel'dovich effect at 95 and 150 GHz. Using both space- and ground-based optical

Kelsey R. Allen, Kevin A. Smith, Joshua B. Tenenbaum

Many animals, and an increasing number of artificial agents, display sophisticated capabilities to perceive and manipulate objects. But human beings remain distinctive in their capacity for flexible, creative tool use -- using objects in new ways to act on the world, achieve a goal, or solve a problem. To study this type of general physical problem solving,

G. Oliveira-Neto, L. G. Rezende Rodrigues

In the present letter, we consider homogeneous and isotropic noncommutative cosmological models induced by a symplectic formalism coupled to phantom perfect fluids and a cosmological constant. After computing the field equations, we solve them to find the scalar factor dynamics. We restrict our attention to expansive solutions, that may represent the present

Hoang-Van Do, Cosimo Lovecchio, Ivana Mastroserio, Nicole Fabbri

In the ideal quantum Zeno effect, repeated quantum projective measurements can freeze the coherent dynamics of a quantum system. However, in the weak quantum Zeno regime, measurement back-actions can allow the sensing of semi-classical field fluctuations. In this regard, we theoretically show how to combine the controlled manipulation of a quantum two-level

Likun Zhang, Benjamin A. Shaby, Jennifer L. Wadsworth

Flexible spatial models that allow transitions between tail dependence classes have recently appeared in the literature. However, inference for these models is computationally prohibitive, even in moderate dimensions, due to the necessity of repeatedly evaluating the multivariate Gaussian distribution function. In this work, we attempt to achieve truly high-

Alexandre Reeberg de Mello, Marcelo Ricardo Stemmer, Alessandro Lameiras Koerich

In this paper we present an incremental variant of the Twin Support Vector Machine (TWSVM) called Fuzzy Bounded Twin Support Vector Machine (FBTWSVM) to deal with large datasets and learning from data streams. We combine the TWSVM with a fuzzy membership function, so that each input has a different contribution to each hyperplane in a binary classifier. To s

Jeffrey W. Miller

Generalized likelihoods are commonly used to obtain consistent estimators with attractive computational and robustness properties. Formally, any generalized likelihood can be used to define a generalized posterior distribution, but an arbitrarily defined "posterior" cannot be expected to appropriately quantify uncertainty in any meaningful sense. In this art

Nuno F. Loureiro, Stanislav Boldyrev

Recent analytical works on strong magnetized plasma turbulence have hypothesized the existence of a range of scales where the tearing instability may govern the energy cascade. In this paper, we estimate the conditions under which such tearing may give rise to full nonlinear magnetic reconnection in the turbulent eddies, thereby enabling significant energy c

Harbir Antil, Zichao Di, Ratna Khatri

In this work we consider a generalized bilevel optimization framework for solving inverse problems. We introduce fractional Laplacian as a regularizer to improve the reconstruction quality, and compare it with the total variation regularization. We emphasize that the key advantage of using fractional Laplacian as a regularizer is that it leads to a linear op

Francisco Eiras, Morteza Lahijanian, Marta Kwiatkowska

Research into safety in autonomous and semi-autonomous vehicles has, so far, largely been focused on testing and validation through simulation. Due to the fact that failure of these autonomous systems is potentially life-endangering, formal methods arise as a complementary approach. This paper studies the application of formal methods to the verification of

Luis Lozano, Hugo Garcia-Compean

The emergence of a Kalb-Ramond field and string charge in the lattice is discussed. The local bosonic model with rotor variables placed on the faces of a cubic lattice is considered. The coupling model consisting of the Maxwell fields and the Kalb-Ramond field is given. This construction naturally incorporates the emerging coupling between both gauge and str

Lorenzo A. Rossi, Chad Shawber, Janet Munu, Finly Zachariah

Laboratory test results are an important and generally high dimensional component of a patient&#39;s Electronic Health Record (EHR). We train embedding representations (via Word2Vec and GloVe) for LOINC codes of laboratory tests from the EHRs of about 80,000 patients at a cancer center. To include information about lab test outcomes, we also train embeddings

Przemyslaw Swatek, Yun Wu, Lin-Lin Wang, Kyungchan Lee

We use high-resolution, tunable angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT) calculations to study the electronic properties of single crystals of MnBi2Te4, a material that was predicted to be the first intrinsic antiferromagnetic (AFM) topological insulator. We observe both bulk and surface bands in the electronic sp

Mingxing Tan, Quoc V. Le

Depthwise convolution is becoming increasingly popular in modern efficient ConvNets, but its kernel size is often overlooked. In this paper, we systematically study the impact of different kernel sizes, and observe that combining the benefits of multiple kernel sizes can lead to better accuracy and efficiency. Based on this observation, we propose a new mixe

Mohak Bhardwaj, Byron Boots, Mustafa Mukadam

Modern trajectory optimization based approaches to motion planning are fast, easy to implement, and effective on a wide range of robotics tasks. However, trajectory optimization algorithms have parameters that are typically set in advance (and rarely discussed in detail). Setting these parameters properly can have a significant impact on the practical perfor

Michael T. Jury, Robert T. W. Martin

A classical theorem of Fatou asserts that the Radon-Nikodym derivative of any finite positive Borel measure, $\mu$, with respect to Lebesgue measure on the complex unit circle, is recovered as the non-tangential limits of its Poisson transform in the complex unit disk. This positive harmonic Poisson transform is the real part of an analytic function whose Ta

Joseph Najnudel, Jim Pitman

Feller (1945) provided a coupling between the counts of cycles of various sizes in a uniform random permutation of $[n]$ and the spacings between successes in a sequence of $n$ independent Bernoulli trials with success probability $1/n$ at the $n$th trial. Arratia, Barbour and Tavar\'e (1992) extended Feller's coupling, to associate cycles of random permutat

Gunnar Taraldsen

In 1933 Kolmogorov constructed a general theory that defines the modern concept of conditional probability. In 1955 Renyi fomulated a new axiomatic theory for probability motivated by the need to include unbounded measures. This note introduces a general concept of conditional probability in Renyi spaces. Keywords: Measure theory; conditional probability spa

Huajia Wang, Tianci Zhou

It is believed that thermalization drives the reduced density matrix of a subsystem to approach a short-range entangled operator. If the initial state is also short-range entangled, it is possible that the reduced density matrix remains low-entangled throughout thermalization; or there could exist a barrier with high operator entanglement between the initial

Andrey Zhmoginov, Ian Fischer, Mark Sandler

We propose a new method for learning image attention masks in a semi-supervised setting based on the Information Bottleneck principle. Provided with a set of labeled images, the mask generation model is minimizing mutual information between the input and the masked image while maximizing the mutual information between the same masked image and the image labe

Adam Krawczyk, Alex Kruckman, Wiesław Kubiś, Aristotelis Panagiotopoulos

We present several examples of hereditary classes of finite structures satisfying the joint embedding property and the weak amalgamation property, but failing the cofinal amalgamation property. These include a continuum-sized family of classes of finite undirected graphs, as well as an example due to Pouzet with countably categorical generic limit.

Mathew D. E. Denys, Murray K. Olsen, Luke S. Trainor, Harald G. L. Schwefel

Triplet down conversion, the process of converting one high-energy photon into three low-energy photons, may soon be experimentally feasible due to advances in optical resonator technology. We use quantum phase-space techniques to analyse the process of degenerate intracavity triplet down conversion by solving stochastic differential equations within the tru

Matteo A. Cardella

The Sachdev-Ye-Kitaev model spectral form factor exhibits absence of information loss in the form of a ramp and a plateau, that are typical of random matrix theory. In a large $N$ collective fields description, the ramp was reproduced by Saad, Shenker and Stanford \cite{Saad:2018bqo}, by replica symmetry breaking saddles for a connected component of the anal

Peiye Liu, Bo Wu, Huadong Ma, Mingoo Seok

Recent studies on automatic neural architectures search have demonstrated significant performance, competitive to or even better than hand-crafted neural architectures. However, most of the existing network architecture tend to use residual, parallel structures and concatenation block between shallow and deep features to construct a large network. This requi

Marianna Torelli, Giacinto Iannicola, Peter B. Stetson, Ivan Ferraro

Theory and observations indicate that the distribution of stars along the horizontal branch of Galactic globular clusters mainly depends on the metal content. However, the existence of globular clusters with similar metal content and absolute age but different horizontal branch morphologies, suggests the presence of another parameter affecting the star distr

Naftali Cohen, Tucker Balch, Manuela Veloso

Financial companies continuously analyze the state of the markets to rethink and adjust their investment strategies. While the analysis is done on the digital form of data, decisions are often made based on graphical representations in white papers or presentation slides. In this study, we examine whether binary decisions are better to be decided based on th

Batu Güneysu, Max von Renesse

Set $\Psi:=-\log(\tilde{\Psi})$, with $\tilde{\Psi}>0$ the ground state of an arbitrary molecule with $n$ electrons in the infinite mass limit (neglecting spin/statistics). Let $\Sigma\subset \IR^{3n}$ be the set of singularities of the underlying Coulomb potential. We show that the metric measure space $\IMM$ given by $\IR^{3n}$ with its Euclidean distance