February 2019 arXiv papers — page 65

A. A. Kolpakov, A. G. Kolpakov

A paper by Ye, Berdichevsky and Yu features a set of formulas for effective stiffnesses of corrugated plates. Without elaborating on said authors' actual approach leading to such formulas, we shall focus on the fact that they can be brought to a simpler form.

Shoujin Wang, Longbing Cao, Yan Wang, Quan Z. Sheng

Recommender systems (RSs) have been playing an increasingly important role for informed consumption, services, and decision-making in the overloaded information era and digitized economy. In recent years, session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs. Different from other RSs such as content-based RSs and collaborative filte

Antonio Cicone, Enza Pellegrino

In this work, we present a new technique for the decomposition of multivariate data, which we call Multivariate Fast Iterative Filtering (MvFIF) algorithm. We study its properties, proving rigorously that it converges in finite time when applied to the decomposition of any kind of multivariate signal. We test MvFIF performance using a wide variety of artific

Masahiko Ito, Masatoshi Noumi

The evaluation formula for an elliptic beta integral of type $G_2$ is proved. The integral is expressed by a product of Ruijsenaars' elliptic gamma functions, and the formula includes that of Gustafson's $q$-beta integral of type $G_2$ as a special limiting case as $p\to 0$. The elliptic beta integral of type $BC_1$ by van Diejen and Spiridonov is effectivel

Naoto Shiraishi, Keiji Saito

We establish that entropy production, which is crucial to the characterization of thermodynamic irreversibility, is obtained through a variational principle involving the Kulback-Leibler divergence. A simple application of this representation leads to an information-theoretical bound on entropy production in thermal relaxation processes; this is a stronger i

Giuseppe Alberti, Pierre-Henri Chavanis

The Thomas-Fermi model is extended at finite temperature, to describe the gravitational phase transition occurring in massive fermionic systems in a general-relativistic framework. It is shown that, when a nondegenerate fermionic gas (for $N < N_{OV}$, where $N_{OV}$ is the Oppenheimer-Volkoff limit) is cooled down below a critical temperature, a condensed p

Martin Meere, Giuseppe Pontrelli, Sean McGinty

Much work has been devoted to analysing thermodynamic models for solid dispersions with a view to identifying regions in the phase diagram where amorphous phase separation or drug recrystallization can occur. However, detailed partial differential equation non-equilibrium models that track the evolution of solid dispersions in time and space are lacking. Hen

Jan Blechta, Josef Málek, K. R. Rajagopal

In the first part of the paper we provide a new classification of incompressible fluids characterized by a continuous monotone relation between the velocity gradient and the Cauchy stress. The considered class includes Euler fluids, Navier-Stokes fluids, classical power-law fluids as well as stress power-law fluids, and their various generalizations includin

Giuseppe Alberti

We study the dynamical stability of self-gravitating systems in presence of anisotropy. In particular, we introduce a stability criterion, in terms of the adiabatic local index, that generalizes the stability condition $<\gamma> \geq 4/3$ of the isotropic regime. Also, we discuss some applications of the criterion.

Hilary Hunt, Agne Tilunaite, Greg Bass, Christian Soeller

Calcium (Ca2+) plays a central role in mediating both contractile function and hypertrophic signalling in ventricular cardiomyocytes. L-type Ca2+ channels trigger release of Ca2+ from ryanodine receptors (RyRs) for cellular contraction, while signalling downstream of Gq coupled receptors stimulates Ca2+ release via inositol 1,4,5-trisphosphate receptors (IP3

J. Alaminos, M. Brešar, J. Extremera, A. R. Villena

A Banach algebra $A$ is said to be a zero Jordan product determined Banach algebra if every continuous bilinear map $\varphi\colon A\times A\to X$, where $X$ is an arbitrary Banach space, which satisfies $\varphi(a,b)=0$ whenever $a$, $b\in A$ are such that $ab+ba=0$, is of the form $\varphi(a,b)=\sigma(ab+ba)$ for some continuous linear map $\sigma$. We sho

Amey Agrawal, Abhishek Dixit, Namrata Shettar, Darshil Kapadia

In many software applications, logs serve as the only interface between the application and the developer. However, navigating through the logs of long-running applications is often challenging. Logs from previously successful application runs can be leveraged to automatically identify errors and provide users with only the logs that are relevant to the debu

William A McIntyre, Hilary Weller, Christopher E Holloway

Convection schemes are a large source of error in global weather and climate models, and modern resolutions are often too fine to parameterise convection but are still too coarse to fully resolve it. Recently, numerical solutions of multi-fluid equations have been proposed for a more flexible and consistent treatment of sub-grid scale convection, including n

Moritz Doll, André Froehly, René Schulz

We discuss the determination of the Lam\'e parameters of an elastic material by the means of boundary measurements. We will combine previous results of Eskin-Ralston and Isakov to prove inverse results in the case of bounded domains with partial data. Moreover, we generalise these results to infinite cylinders.

Samyadeb Bhattacharya, Bihalan Bhattacharya, A. S. Majumdar

We establish a connection between non-Markovianity and negative entropy production rate for various classes of quantum operations. We analyse several aspects of unital and thermal operations in connection with resource theories of purity and thermodynamics. We fully characterize Lindblad operators corresponding to unital operations. We also characterize the

D. Bresch, David Lannes, Guy Metivier

This paper is devoted to the derivation and mathematical analysis of a wave-structure interaction problem which can be reduced to a transmission problem for a Boussinesq system. Initial boundary value problems and transmission problems in dimension d= 1 for $2\times2$ hyperbolic systems are well understood. However, for many applications, and especially for

Thomas Ehrhard

In probabilistic coherence spaces, a denotational model of probabilistic functional languages, mor-phisms are analytic and therefore smooth. We explore two related applications of the corresponding derivatives. First we show how derivatives allow to compute the expectation of execution time in the weak head reduction of probabilistic PCF (pPCF). Next we appl

Emilio Said, Ahmed Bel Hadj Ayed, Damien Thillou, Jean-Jacques Rabeyrin

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders-large orders that are split into smaller pieces before being sent to the market on one of the main Asian markets. In line with our previous work on the equity ma

Duc-Manh Nguyen

Given $d\in \mathbb{N}$, $g\in \mathbb{N} \cup\{0\}$, and an integral vector $\kappa=(k_1,\dots,k_n)$ such that $k_i>-d$ and $k_1+\dots+k_n=d(2g-2)$, let $\Omega^d\mathcal{M}_{g,n}(\kappa)$ denote the moduli space of meromorphic $d$-differentials on Riemann surfaces of genus $g$ whose zeros and poles have orders prescribed by $\kappa$. We show that $\Omega^d

David T. Frazier, David J. Nott, Christopher Drovandi, Robert Kohn

Implementing Bayesian inference is often computationally challenging in applications involving complex models, and sometimes calculating the likelihood itself is difficult. Synthetic likelihood is one approach for carrying out inference when the likelihood is intractable, but it is straightforward to simulate from the model. The method constructs an approxim

Revaz Beradze, Merab Gogberashvili

We want to explain non-observation of electromagnetic counterpart of currently confirmed ten gravitational wave signals from the black hole mergers assuming their existence in the hidden mirror universe. Mirror matter, which interacts with our world only through gravity, is a candidate of dark matter and its density can exceed ordinary matter density five ti

Giuseppe Facchetti, Benjamin Knapp, Fred Chang, Martin Howard

Fundamental mechanisms governing cell size control and homeostasis are still poorly understood. The relationship between sizes at division and birth in single cells is used as a metric to categorize the basis of size homeostasis [1-3]. Cells dividing at a fixed size regardless of birth size (sizer) are expected to show a division-birth slope of 0, whereas ce

Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang

Graph convolutional networks (GCNs) have been successfully applied in node classification tasks of network mining. However, most of these models based on neighborhood aggregation are usually shallow and lack the &#34;graph pooling&#34; mechanism, which prevents the model from obtaining adequate global information. In order to increase the receptive field, we

Cihan Unal, Ismail Aydin

In this study, we define double weighted variable exponent Sobolev spaces $W^{1,q(.),p(.)}\left( \Omega ,\vartheta _{0},\vartheta \right) $ with respect to two different weight functions. Also, we investigate the basic properties of this spaces. Moreover, we discuss the existence of weak solutions for weighted Dirichlet problem of $p(.)$-Laplacian equation \

Vuk Milisic

In the context of cell motility modelling and more particularly related to the Filament Based Lamelipodium Model [Manhart et al 2015 & 2017], this work deals with a rigorous mathematical proof of convergence between solutions of two problems : we start from a microscopic description of adhesions using a delayed and constrained vector valued equation with spa

Nicolas S. Holliman, Manu Antony, James Charlton, Stephen Dowsland

Background: Photo-realistic terapixel visualization is computationally intensive and to date there have been no such visualizations of urban digital twins, the few terapixel visualizations that exist have looked towards space rather than earth. Objective: our aims are: creating a scalable cloud supercomputer software architecture for visualization; a photo-r

Kevin Roth, Yannic Kilcher, Thomas Hofmann

We investigate conditions under which test statistics exist that can reliably detect examples, which have been adversarially manipulated in a white-box attack. These statistics can be easily computed and calibrated by randomly corrupting inputs. They exploit certain anomalies that adversarial attacks introduce, in particular if they follow the paradigm of ch

Andreas Venzke, Spyros Chatzivasileiadis, Daniel K. Molzahn

Convex relaxations of AC optimal power flow (AC-OPF) problems have attracted significant interest as in several instances they provably yield the global optimum to the original non-convex problem. If, however, the relaxation is inexact, the obtained solution is not AC-feasible. The quality of the obtained solution is essential for several practical applicati

Ismail Aydin, Cihan Unal

In this study, we consider weighted stochastic field exponent function spaces $L_{\vartheta }^{p(.,.)}\left( D\times \Omega \right) $ and $W_{\vartheta }^{k,p(.,.)}\left( D\times \Omega \right) $. Also, we investigate some basic properties and embeddings of these spaces. Finally, we present an application of these spaces to the stochastic partial differentia

Chi Jin, Praneeth Netrapalli, Rong Ge, Sham M. Kakade

Gradient descent (GD) and stochastic gradient descent (SGD) are the workhorses of large-scale machine learning. While classical theory focused on analyzing the performance of these methods in convex optimization problems, the most notable successes in machine learning have involved nonconvex optimization, and a gap has arisen between theory and practice. Ind

Yuri Ozhigov

Experimental attempts to implement quantum speedup of computations over the past 30 years have yielded a negative result, despite the absence of physical laws prohibiting such speedup. The article formulates the limitation of quantum formalism in the form of uncertainty &#34;the complexity of the system - the accuracy of its description at the quantum level&

Antonio Alvaro Ranha Neves, Carlos Lenz Cesar

Arthur Ashkin was awarded the 2018 Nobel prize in physics for the invention of optical tweezers. Since the first publication in 1986 Optical Tweezers have been used as a tool to measure forces and rheological properties of microscopic systems. For the calibration of these measurements, the knowledge of the forces is fundamental. However, it is still common t

N. Milazzo, D. Braun, O. Giraud

With the advance of quantum information technology, the question of how to most efficiently test quantum circuits is becoming of increasing relevance. Here we introduce the statistics of lengths of measurement sequences that allows one to certify entanglement across a given bi-partition of a multi-qubit system over the possible sequence of measurements of ra

Jérôme Burelbach

We present a complete reciprocal description of particle motion inside multi-component fluids that extends the conventional Onsager formulation of non-equilibrium transport to systems where the thermodynamic forces are non-uniform on the colloidal scale. Based on the dynamic length and time scale separation in suspensions, the particle flux is shown to be re

Michel Planat, Raymond Aschheim, Marcelo M. Amaral, Klee Irwin

The fundamental group $\pi_1(L)$ of a knot or link $L$ may be used to generate magic states appropriate for performing universal quantum computation and simultaneously for retrieving complete information about the processed quantum states. In this paper, one defines braids whose closure is the $L$ of such a quantum computer model and computes their Seifert s

Shi-Zeng Lin, Duk Y. Kim, Eric D. Bauer, Filip Ronning

The $d$-wave superconductor $\mathrm{CeCoIn_5}$ has been proposed as a strong candidate for supporting the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state near the low-temperature boundary of its upper critical field. Neutron diffraction, however, finds spin-density-wave (SDW) order in this part of the phase diagram for field in the $a$-$b$ plane, and evidence

Lin Lin, Michael Lindsey

We prove that for various impurity models, in both classical and quantum settings, the self-energy matrix is a sparse matrix with a sparsity pattern determined by the impurity sites. In the quantum setting, such a sparsity pattern has been known since Feynman. Indeed, it underlies several numerical methods for solving impurity problems, as well as many appro

Simon Rabanser, Lukas Neumann, Markus Haltmeier

Block coordinate descent (BCD) methods approach optimization problems by performing gradient steps along alternating subgroups of coordinates. This is in contrast to full gradient descent, where a gradient step updates all coordinates simultaneously. BCD has been demonstrated to accelerate the gradient method in many practical large-scale applications. Despi

Victor Dominguez, Mahadevan Ganesh, Francisco-Javier Sayas

A natural medium for wave propagation comprises a coupled bounded heterogeneous region and an unbounded homogeneous free-space. Frequency-domain wave propagation models in the medium, such as the variable coefficient Helmholtz equation, include a faraway decay radiation condition (RC). It is desirable to develop algorithms that incorporate the full physics o

Hironori Shimazu

Magnetic flux ropes in space are generally connected to some regions electromagnetically. We consider the whole closed current system of the expanding flux ropes including the electric current associated with them. By combining the theories regarding the self-similar expansion of cylindrical flux ropes and the Alfven wave current system, we examine condition

Gabriele Di Bona, Andrea Giacobbe

We write a nonlinear model that predicts the climate (temperature and humidity) on the surface of a small region on Earth, perform numerical investigations using the model, and compare the results to real climate on a variety of regions on Earth. It the parameters are chosen keeping into consideration the climatic Köppen zone to which the region belongs, the

Michele Rossi

The present paper is devoted to developing relations between Galois \'etale coverings in codimension 1 and \'etale fundamental groups in codimension 1 of algebraic varieties, aimed to studying the topology of Mori dream spaces. In particular, the universal \'etale covering in codimension 1 of a non-degenerate toric variety and a canonical Galois \'etale cove

Megha Srivastava, Hoda Heidari, Andreas Krause

Fairness for Machine Learning has received considerable attention, recently. Various mathematical formulations of fairness have been proposed, and it has been shown that it is impossible to satisfy all of them simultaneously. The literature so far has dealt with these impossibility results by quantifying the tradeoffs between different formulations of fairne

Lin F. Yang, Mengdi Wang

Consider a Markov decision process (MDP) that admits a set of state-action features, which can linearly express the process&#39;s probabilistic transition model. We propose a parametric Q-learning algorithm that finds an approximate-optimal policy using a sample size proportional to the feature dimension $K$ and invariant with respect to the size of the stat

Cihan Unal, Ismail Aydin

In this paper, we define weighted relative $p(.)$-capacity and discuss properties of capacity in the space $W_{\vartheta }^{1,p(.)}(\mathbb{R}^{n}).$ Also, we investigate some properties of weighted variable Sobolev capacity. It is shown that there is a relation between these two capacities. Moreover, we introduce a thinness in sense to this new defined rela

Vineeta Kumari, Aijaz Ahmed, Gyanendra Sheoran, Tirupathiraju Kanumuri

The development of compact indirect microwave holographic set-up by the implementation of low cost, specifically designed directive antennae as transmitter and receiver is proposed. Microwave holograms are recorded by 2D scanning over a plane using motorized translation stage. The recorded interference pattern i.e. holograms are then processed numerically to

Zhanyu Ma, Jalil Taghia, Jun Guo

Variational inference (VI) is a widely used framework in Bayesian estimation. For most of the non-Gaussian statistical models, it is infeasible to find an analytically tractable solution to estimate the posterior distributions of the parameters. Recently, an improved framework, namely the extended variational inference (EVI), has been introduced and applied

Q. Zhao, S. M. Weng, M. Chen, M. Zeng

It is shown that electron injection into a laser-driven plasma bubble can be manipulated by applying an external magnetic field in the presence of a plasma density gradient. The down-ramp of the density-tailored plasma locally reduces the plasma wave phase velocity, which triggers injection. The longitudinal magnetic field dynamically induces an expanding ho

Lei Pan, Shu Chen, Xiaoling Cui

We study interacting ultracold atoms in a three-dimensional (3D) harmonic trap with spin-selective dissipations, which can be effectively described by non-Hermitian parity-time ($\mathcal{PT}$) symmetric Hamiltonians. By solving the non-Hermitian two-body problem of spin-1/2 (spin-1) bosons in a 3D harmonic trap exactly, we find that the system can exhibit t

Yue Xie, Oscar Harper, Hirad Assimi, Aneta Neumann

Evolutionary algorithms have been applied to a wide range of stochastic problems. Motivated by real-world problems where constraint violations have disruptive effects, this paper considers the chance-constrained knapsack problem (CCKP) which is a variance of the binary knapsack problem. The problem aims to maximize the profit of selected items under a constr

Cupjin Huang, Michael Newman, Mario Szegedy

We investigate Clifford+$T$ quantum circuits with a small number of $T$-gates. Using the sparsification lemma, we identify time complexity lower bounds in terms of $T$-gate count below which a strong simulator would improve on the state-of-the-art $3$-SAT solving.

Greg Yang

Several recent trends in machine learning theory and practice, from the design of state-of-the-art Gaussian Process to the convergence analysis of deep neural nets (DNNs) under stochastic gradient descent (SGD), have found it fruitful to study wide random neural networks. Central to these approaches are certain scaling limits of such networks. We unify these

Daisuke Ishima, Hisao Hayakawa

Herein, we numerically study the rheology of a two-dimensional frictional granular system confined by constant pressure under oscillatory shear. Several scaling laws for the storage and loss moduli against the scaled strain amplitude have been found. The scaling laws in plastic regime for large strain amplitude can be understood by the angular distributions

Hua-Rong He, Xia Wan, You-Kai Wang

We calculate the spinor helicity amplitudes of anomalous $H\to ZZ \to 4\ell$ decay. After embedding these analytic formulas into the $\texttt{MCFM}$ package, we study the interference effects between the anomalous $gg\to H\to ZZ \to 4\ell$ process and the SM processes, which are indispensable in the Higgs off-shell region. Subsequently, the constraints on th

Duggirala Meher Krishna, Duggirala Ravi

An integer adder for integers in the binary representation is one of the basic operations of any digital processor. For adding two integers of N bits each, the serial adder takes as many clock ticks. For achieving higher speeds, parallel circuits are discussed in the literature, and these circuits usually operate in two levels. At the lower level, integers r

Jian Zhao, Jianshu Li, Xiaoguang Tu, Fang Zhao

In this paper, we study the challenging unconstrained set-based face recognition problem where each subject face is instantiated by a set of media (images and videos) instead of a single image. Naively aggregating information from all the media within a set would suffer from the large intra-set variance caused by heterogeneous factors (e.g., varying media mo

Hirotaka Hayashi, Sung-Soo Kim, Kimyeong Lee, Futoshi Yagi

We discuss Type IIB 5-brane configurations for 5d $\mathcal{N}=1$ gauge theories with hypermultiplets in the rank-3 antisymmetric representation and with various other hypermultiplets, which flow to a UV fixed point at the infinite coupling. We propose 5-brane web diagrams for the theories of $SU(6)$ and $Sp(3)$ gauge groups with rank-3 antisymmetric matter

Xinpeng Xu, Xingkun Man, Masao Doi, Zhong-can Ou-Yang

Solvent vapor annealing (SVA) is known to be a simple, low-cost and highly efficient technique to produce defect-free diblock copolymer (BCP) thin films. Not only can the solvent weaken the BCP segmental interactions, but it can vary the characteristic spacing of the BCP microstructures. We carry out systematic theoretical studies on the effect of adding sol

Teiko Heinosaari, Maria Anastasia Jivulescu, Ion Nechita

We introduce several notions of random positive operator valued measures (POVMs), and we prove that some of them are equivalent. We then study statistical properties of the effect operators for the canonical examples, obtaining limiting eigenvalue distributions with the help of free probability theory. Similarly, we obtain the large system limit for several

X. Feng, A. D. Liu, C. Zhou, Z. X. Liu

By analyzing large quantities of discharges in the unfavorable ion $ \vec B\times \nabla B $ drift direction, the I-mode operation has been confirmed in EAST tokamak. During the L-mode to I-mode transition, the energy confinement has a prominent improvement by the formation of a high-temperature edge pedestal, while the particle confinement remains almost id

Sanghamitro Das, David J. Sawyer, Nectaria Diamanti, A. Peter Annan

A novel miniaturized printed folded dipole antenna has been designed for narrowband sensing applications. It is shown that the antenna may be systematically engineered to achieve matching to a practical source impedance at frequencies well below its half-wavelength resonance using series-LC loading and asymmetrical arm widths. This approach is used to design

Peixin Wang, Hongfei Fu, Krishnendu Chatterjee, Yuxin Deng

The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the program input result in proportional changes to the program output. For probabilistic programs the notion is naturally extended to expected sensitivity. A previous approach develops a relational program logic framework for proving expected sensitivity of probabilistic

Vaishnavh Nagarajan, J. Zico Kolter

Aimed at explaining the surprisingly good generalization behavior of overparameterized deep networks, recent works have developed a variety of generalization bounds for deep learning, all based on the fundamental learning-theoretic technique of uniform convergence. While it is well-known that many of these existing bounds are numerically large, through numer

Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour

Imagine a large firm with multiple departments that plans a large recruitment. Candidates arrive one-by-one, and for each candidate the firm decides, based on her data (CV, skills, experience, etc), whether to summon her for an interview. The firm wants to recruit the best candidates while minimizing the number of interviews. We model such scenarios as an as

Bobby Powers, David Tench, Emery D. Berger, Andrew McGregor

Programs written in C/C++ can suffer from serious memory fragmentation, leading to low utilization of memory, degraded performance, and application failure due to memory exhaustion. This paper introduces Mesh, a plug-in replacement for malloc that, for the first time, eliminates fragmentation in unmodified C/C++ applications. Mesh combines novel randomized a

F. Ebrahimi, E. G. Blackman

We show that non-axisymmetric, non-helical perturbations in an unstratified shear flow produce a shear-plane averaged electromotive force (EMF) proportional to a spatially dependent kinetic helicity. This new &#34;shear-driven $α$-effect&#34; can amplify shear-plane averaged magnetic fields, but is undiscoverable when invoking the homogeneity assumption for

Xinyuan You, J. A. Sauls, Jens Koch

Circuit quantization links a physical circuit to its corresponding quantum Hamiltonian. The standard quantization procedure generally assumes any external magnetic flux to be static. Time dependence naturally arises, however, when flux is modulated or when flux noise is considered. In this case, application of the existing quantization procedure can lead to

Weijia Zhang, Jiuyong Li, Lin Liu

Multi-instance learning (MIL) deals with tasks where data is represented by a set of bags and each bag is described by a set of instances. Unlike standard supervised learning, only the bag labels are observed whereas the label for each instance is not available to the learner. Previous MIL studies typically follow the i.i.d. assumption, that the training and

John Lagergren, John T. Nardini, G. Michael Lavigne, Erica M. Rutter

We investigate methods for learning partial differential equation (PDE) models from spatiotemporal data under biologically realistic levels and forms of noise. Recent progress in learning PDEs from data have used sparse regression to select candidate terms from a denoised set of data, including approximated partial derivatives. We analyze the performance in

Simon Foucart, Rémi Gribonval, Laurent Jacques, Holger Rauhut

We investigate the problem of recovering jointly $r$-rank and $s$-bisparse matrices from as few linear measurements as possible, considering arbitrary measurements as well as rank-one measurements. In both cases, we show that $m \asymp r s \ln(en/s)$ measurements make the recovery possible in theory, meaning via a nonpractical algorithm. In case of arbitrary

Michaela Cully-Hugill, Adrian W. Dudek

We furnish an explicit bound for the prime number theorem in short intervals on the assumption of the Riemann hypothesis.

Daniel B. Wilson, Ruth E. Baker, Francis G. Woodhouse

Consider a particle whose position evolves along the edges of a network. One definition for the displacement of a particle is the length of the shortest path on the network between the current and initial positions of the particle. Such a definition fails to incorporate information of the actual path the particle traversed. In this work we consider another d

Edward W. Schwieterman, Christopher T. Reinhard, Stephanie L. Olson, Chester E. Harman

The habitable zone (HZ) is commonly defined as the range of distances from a host star within which liquid water, a key requirement for life, may exist on a planet&#39;s surface. Substantially more CO2 than present in Earth&#39;s modern atmosphere is required to maintain clement temperatures for most of the HZ, with several bars required at the outer edge. H

Lixin Zou, Long Xia, Zhuoye Ding, Jiaxing Song

Recommender systems play a crucial role in our daily lives. Feed streaming mechanism has been widely used in the recommender system, especially on the mobile Apps. The feed streaming setting provides users the interactive manner of recommendation in never-ending feeds. In such an interactive manner, a good recommender system should pay more attention to user

Fadhel Ayed, Juho Lee, François Caron

Bayesian nonparametric approaches, in particular the Pitman-Yor process and the associated two-parameter Chinese Restaurant process, have been successfully used in applications where the data exhibit a power-law behavior. Examples include natural language processing, natural images or networks. There is also growing empirical evidence that some datasets exhi

Swetava Ganguli, Jared Dunnmon, Darren Hau

Obtaining reliable data describing local Food Security Metrics (FSM) at a granularity that is informative to policy-makers requires expensive and logistically difficult surveys, particularly in the developing world. We train a CNN on publicly available satellite data describing land cover classification and use both transfer learning and direct training to b

Kaisa Matomäki, Xuancheng Shao

Let $H = N^θ, θ> 2/3$ and $k \geq 1$. We obtain estimates for the following exponential sum over primes in short intervals: \[ \sum_{N < n \leq N+H} Λ(n) e(g(n)), \] where $g$ is a polynomial of degree $k$. As a consequence of this in the special case $g(n) = αn^k$, we deduce a short interval version of the Waring-Goldbach problem.

Yohsuke Murase, Hang-Hyun Jo, János Török, János Kertész

In a social network individuals or nodes connect to other nodes by choosing one of the channels of communication at a time to re-establish the existing social links. Since available data sets are usually restricted to a limited number of channels or layers, these autonomous decision making processes by the nodes constitute the sampling of a multiplex network

Devin Schwab, Tobias Springenberg, Murilo F. Martins, Thomas Lampe

We present a method for fast training of vision based control policies on real robots. The key idea behind our method is to perform multi-task Reinforcement Learning with auxiliary tasks that differ not only in the reward to be optimized but also in the state-space in which they operate. In particular, we allow auxiliary task policies to utilize task feature

Thomas Lidbetter

We consider a search problem in which one or more targets must be rescued by a search party, or Searcher. The targets may be survivors of some natural disaster, or prisoners held by an adversary. The targets are hidden among a finite set of locations, but when a location is searched, there is a known probability that the search will come to an end, perhaps b

Nikolaus Kriegeskorte, Tal Golan

Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence, where they are used to approximate functions and dynamics by learning from examples. Here we give a brief introduction to neural network models and deep learning for biologists. We introduce feedforward and recurrent ne

Mojtaba Abolfazli, Anders Host-Madsen, June Zhang

This paper introduces a new method for model selection and more generally hyperparameter selection in machine learning. Minimum description length (MDL) is an established method for model selection, which is however not directly aimed at minimizing generalization error, which is often the primary goal in machine learning. The paper demonstrates a relationshi

Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer

We study the interplay between memorization and generalization of overparameterized networks in the extreme case of a single training example and an identity-mapping task. We examine fully-connected and convolutional networks (FCN and CNN), both linear and nonlinear, initialized randomly and then trained to minimize the reconstruction error. The trained netw

Peilin Zhong, Yuchen Mo, Chang Xiao, Pengyu Chen

Many generative models have to combat $\textit{missing modes}$. The conventional wisdom to this end is by reducing through training a statistical distance (such as $f$-divergence) between the generated distribution and provided data distribution. But this is more of a heuristic than a guarantee. The statistical distance measures a $\textit{global}$, but not

Vahid Roostapour, Mojgan Pourhassan, Frank Neumann

The performance of base-line Evolutionary Algorithms (EAs) on combinatorial problems has been studied rigorously. From the theoretical viewpoint, the literature extensively investigates the linear problems, while the theoretical analysis of the non-linear problems is still far behind. In this paper, variations of the Packing While Travelling (PWT) -- also kn

John H. Ring, Colin M. Van Oort, David R. Dewhurst, Tyler J. Gray

Using the most comprehensive, commercially-available dataset of trading activity in U.S. equity markets, we catalog and analyze quote dislocations between the SIP National Best Bid and Offer (NBBO) and a synthetic BBO constructed from direct feeds. We observe a total of over 3.1 billion dislocation segments in the Russell 3000 during trading in 2016, roughly

Brian F. Tivnan, David Rushing Dewhurst, Colin M. Van Oort, John H. Ring

Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in 2016 from the vantage point of a single and fixed frame of reference. We find that inefficiencies created in part by the fragmentation of the equity marketplace are relatively common and persis

Shi Dai, Marcus E. Lower, Matthew Bailes, Fernando Camilo

The anomalous X-ray pulsar XTE J1810$-$197 was the first magnetar found to emit pulsed radio emission. After spending almost a decade in a quiescent, radio-silent state, the magnetar was reported to have undergone a radio outburst in December, 2018. We observed radio pulsations from XTE J1810$-$197 during this early phase of its radio revival using the Ultra

Peter M. Lavrov, Ilya L. Shapiro

Using the Batalin-Vilkovisky technique and the background field method the proof of gauge invariant renormalizability is elaborated for a generic model of quantum gravity which is diffeomorphism invariant and has no other, potentially anomalous, symmetries. The gauge invariant renormalizability means that in all orders of loop expansion of the quantum effect

Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro

We give nearly matching upper and lower bounds on the oracle complexity of finding $ε$-stationary points ($\| \nabla F(x) \| \leqε$) in stochastic convex optimization. We jointly analyze the oracle complexity in both the local stochastic oracle model and the global oracle (or, statistical learning) model. This allows us to decompose the complexity of finding

Elena Celledoni, Charalambos Evripidou, David McLaren, Brynjulf Owren

In this paper we use the method of discrete Darboux polynomials to calculate preserved measures and integrals of rational maps. The approach is based on the use of cofactors and Darboux polynomials and relies on the use of symbolic algebra tools. Given sufficient computing power, most, if not all, rational preserved integrals can be found (and even some non-

Owen Mayer, Matthew C. Stamm

In this paper we introduce a new digital image forensics approach called forensic similarity, which determines whether two image patches contain the same forensic trace or different forensic traces. One benefit of this approach is that prior knowledge, e.g. training samples, of a forensic trace are not required to make a forensic similarity decision on it in

Chen Sun, Ye Tian, Liang Gao, Yishuai Niu

Calibration models have been developed for determination of trace elements, silver for instance, in soil using laser-induced breakdown spectroscopy (LIBS). The major concern is the matrix effect. Although it affects the accuracy of LIBS measurements in a general way, the effect appears accentuated for soil because of large variation of chemical and physical

James E. Barrett, Aylin Cakiroglu, Catey Bunce, Anoop Shah

Large scale electronic health records (EHRs) present an opportunity to quickly identify suitable individuals in order to directly invite them to participate in an observational study. EHRs can contain data from millions of individuals, raising the question of how to optimally select a cohort of size n from a larger pool of size N. In this paper we propose a

Fazlul MKK, Shah Samiur Rashid, Nazmul MHM, Zaidul I. S. M

Antibiotics are the wonder discoveries to combat microbes. For decades, multiple varieties of antibiotics have been used for therapeutic purposes in hospital settings and communities throughout the world. Unfortunately, bacteria have become resistant to commonly prescribed antibiotics. This review aims to explore the development, challenges, and the current

Navjot Kukreja, Alena Shilova, Olivier Beaumont, Jan Huckelheim

Edge computing is the natural progression from Cloud computing, where, instead of collecting all data and processing it centrally, like in a cloud computing environment, we distribute the computing power and try to do as much processing as possible, close to the source of the data. There are various reasons this model is being adopted quickly, including priv

Abdullah B. Nasser, Kamal Z. Zamli, Bestoun S. Ahmed

Flower Pollination Algorithm (FPA) is the new breed of metaheuristic for the general optimization problem. In this paper, an improved algorithm based on Flower Pollination Algorithm (FPA), called imFPA, has been proposed. In imFPA, the static selection probability is replaced by the dynamic solution selection probability in order to enhance the diversificati

Kamal Z. Zamli, Fakhrud Din, Nazirah Ramli, Bestoun S. Ahmed

Although showing competitive performances in many real-world optimization problems, Teaching Learning based Optimization Algorithm (TLBO) has been criticized for having poor control on exploration and exploitation. Addressing these issues, a new variant of TLBO called Adaptive Fuzzy Teaching Learning based Optimization (ATLBO) has been developed in the liter

Chul Min Yeum, Ali Lenjani, Shirley J. Dyke, Ilias Bilionis

After a disaster, teams of structural engineers collect vast amounts of images from damaged buildings to obtain lessons and gain knowledge from the event. Images of damaged buildings and components provide valuable evidence to understand the consequences on our structures. However, in many cases, images of damaged buildings are often captured without suffici

Marko Poženel, Dejan Lavbič

Stock prediction has always been attractive area for researchers and investors since the financial gains can be substantial. However, stock prediction can be a challenging task since stocks are influenced by a multitude of factors whose influence vary rapidly through time. This paper proposes a novel approach (Word2Vec) for stock trend prediction combining N