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Fooling Sets and the Spanning Tree Polytope
In the study of extensions of polytopes of combinatorial optimization problems, a notorious open question is that for the size of the smallest extended formulation of the Minimum Spanning Tree problem on a complete graph with $n$ nodes. The best known lower bound is $\Omega(n^2)$, the best known upper bound is $O(n^3...
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From Azéma supermartingales of finite honest times to optional semimartingales of class-($Σ$)
Given a finite honest time, we derive representations for the additive and multiplicative decomposition of it's Azéma supermartingale in terms of optional supermartingales and its running supremum. We then extend the notion of semimartingales of class-$(\Sigma)$ to optional semimartingales with jumps in its finite va...
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Single versus Double Blind Reviewing at WSDM 2017
In this paper we study the implications for conference program committees of using single-blind reviewing, in which committee members are aware of the names and affiliations of paper authors, versus double-blind reviewing, in which this information is not visible to committee members. WSDM 2017, the 10th ACM Internat...
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Scale-variant Topological Information for Characterizing Complex Networks
Real-world networks are difficult to characterize because of the variation of topological scales, the non-dyadic complex interactions, and the fluctuations. Here, we propose a general framework to address these problems via a methodology grounded on topology data analysis. By observing the diffusion process in a netw...
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Topological orbital superfluid with chiral d-wave order in a rotating optical lattice
Topological superfluid is an exotic state of quantum matter that possesses a nodeless superfluid gap in the bulk and Andreev edge modes at the boundary of a finite system. Here, we study a multi-orbital superfluid driven by attractive s-wave interaction in a rotating optical lattice. Interestingly, we find that the r...
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Optimal client recommendation for market makers in illiquid financial products
The process of liquidity provision in financial markets can result in prolonged exposure to illiquid instruments for market makers. In this case, where a proprietary position is not desired, pro-actively targeting the right client who is likely to be interested can be an effective means to offset this position, rathe...
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Design of an Audio Interface for Patmos
This paper describes the design and implementation of an audio interface for the Patmos processor, which runs on an Altera DE2-115 FPGA board. This board has an audio codec included, the WM8731. The interface described in this work allows to receive and send audio from and to the WM8731, and to synthesize, store or m...
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A Classifying Variational Autoencoder with Application to Polyphonic Music Generation
The variational autoencoder (VAE) is a popular probabilistic generative model. However, one shortcoming of VAEs is that the latent variables cannot be discrete, which makes it difficult to generate data from different modes of a distribution. Here, we propose an extension of the VAE framework that incorporates a clas...
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On Estimation of Isotonic Piecewise Constant Signals
Consider a sequence of real data points $X_1,\ldots, X_n$ with underlying means $\theta^*_1,\dots,\theta^*_n$. This paper starts from studying the setting that $\theta^*_i$ is both piecewise constant and monotone as a function of the index $i$. For this, we establish the exact minimax rate of estimating such monotone...
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Deep Stacked Stochastic Configuration Networks for Non-Stationary Data Streams
The concept of stochastic configuration networks (SCNs) others a solid framework for fast implementation of feedforward neural networks through randomized learning. Unlike conventional randomized approaches, SCNs provide an avenue to select appropriate scope of random parameters to ensure the universal approximation ...
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Extracting Syntactic Patterns from Databases
Many database columns contain string or numerical data that conforms to a pattern, such as phone numbers, dates, addresses, product identifiers, and employee ids. These patterns are useful in a number of data processing applications, including understanding what a specific field represents when field names are ambigu...
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Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
We address the problem of multi-class classification in the case where the number of classes is very large. We propose a double sampling strategy on top of a multi-class to binary reduction strategy, which transforms the original multi-class problem into a binary classification problem over pairs of examples. The aim...
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Understanding and predicting travel time with spatio-temporal features of network traffic flow, weather and incidents
Travel time on a route varies substantially by time of day and from day to day. It is critical to understand to what extent this variation is correlated with various factors, such as weather, incidents, events or travel demand level in the context of dynamic networks. This helps a better decision making for infrastru...
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The power of sum-of-squares for detecting hidden structures
We study planted problems---finding hidden structures in random noisy inputs---through the lens of the sum-of-squares semidefinite programming hierarchy (SoS). This family of powerful semidefinite programs has recently yielded many new algorithms for planted problems, often achieving the best known polynomial-time gu...
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An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis
Polynomial chaos expansions (PCE) have seen widespread use in the context of uncertainty quantification. However, their application to structural reliability problems has been hindered by the limited performance of PCE in the tails of the model response and due to the lack of local metamodel error estimates. We propo...
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Experimental Tests of Spirituality
We currently harness technologies that could shed new light on old philosophical questions, such as whether our mind entails anything beyond our body or whether our moral values reflect universal truth.
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Chern classes and Gromov--Witten theory of projective bundles
We prove that the Gromov--Witten theory (GWT) of a projective bundle can be determined by the Chern classes and the GWT of the base. It completely answers a question raised in a previous paper (arXiv:1607.00740). Its consequences include that the GWT of the blow-up of X at a smooth subvariety Z is uniquely determined...
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Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
We introduce the concept of numerical Gaussian processes, which we define as Gaussian processes with covariance functions resulting from temporal discretization of time-dependent partial differential equations. Numerical Gaussian processes, by construction, are designed to deal with cases where: (1) all we observe ar...
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Learning from Experience: A Dynamic Closed-Loop QoE Optimization for Video Adaptation and Delivery
The quality of experience (QoE) is known to be subjective and context-dependent. Identifying and calculating the factors that affect QoE is indeed a difficult task. Recently, a lot of effort has been devoted to estimate the users QoE in order to improve video delivery. In the literature, most of the QoE-driven optimi...
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Deep CNN based feature extractor for text-prompted speaker recognition
Deep learning is still not a very common tool in speaker verification field. We study deep convolutional neural network performance in the text-prompted speaker verification task. The prompted passphrase is segmented into word states - i.e. digits -to test each digit utterance separately. We train a single high-level...
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Data-Injection Attacks in Stochastic Control Systems: Detectability and Performance Tradeoffs
Consider a stochastic process being controlled across a communication channel. The control signal that is transmitted across the control channel can be replaced by a malicious attacker. The controller is allowed to implement any arbitrary detection algorithm to detect if an attacker is present. This work characterize...
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Efficient Version-Space Reduction for Visual Tracking
Discrminative trackers, employ a classification approach to separate the target from its background. To cope with variations of the target shape and appearance, the classifier is updated online with different samples of the target and the background. Sample selection, labeling and updating the classifier is prone to ...
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Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts
Most of the JavaScript code deployed in the wild has been minified, a process in which identifier names are replaced with short, arbitrary and meaningless names. Minified code occupies less space, but also makes the code extremely difficult to manually inspect and understand. This paper presents Context2Name, a deep ...
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Reconstructing fluid dynamics with micro-finite element
In the theory of the Navier-Stokes equations, the viscous fluid in incompressible flow is modelled as a homogeneous and dense assemblage of constituent "fluid particles" with viscous stress proportional to rate of strain. The crucial concept of fluid flow is the velocity of the particle that is accelerated by the pre...
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Towards Black-box Iterative Machine Teaching
In this paper, we make an important step towards the black-box machine teaching by considering the cross-space machine teaching, where the teacher and the learner use different feature representations and the teacher can not fully observe the learner's model. In such scenario, we study how the teacher is still able t...
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On Generalization and Regularization in Deep Learning
Why do large neural network generalize so well on complex tasks such as image classification or speech recognition? What exactly is the role regularization for them? These are arguably among the most important open questions in machine learning today. In a recent and thought provoking paper [C. Zhang et al.] several ...
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Nonparametric Inference for Auto-Encoding Variational Bayes
We would like to learn latent representations that are low-dimensional and highly interpretable. A model that has these characteristics is the Gaussian Process Latent Variable Model. The benefits and negative of the GP-LVM are complementary to the Variational Autoencoder, the former provides interpretable low-dimensi...
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Imbalanced Malware Images Classification: a CNN based Approach
Deep convolutional neural networks (CNNs) can be applied to malware binary detection through images classification. The performance, however, is degraded due to the imbalance of malware families (classes). To mitigate this issue, we propose a simple yet effective weighted softmax loss which can be employed as the fin...
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Integrated optical force sensors using focusing photonic crystal arrays
Mechanical oscillators are at the heart of many sensor applications. Recently several groups have developed oscillators that are probed optically, fabricated from high-stress silicon nitride films. They exhibit outstanding force sensitivities of a few aN/Hz$^{1/2}$ and can also be made highly reflective, for efficien...
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Comparison of Signaling and Media Approaches to Detect VoIP SPIT Attack
IP networks became the most dominant type of information networks nowadays. It provides a number of services and makes it easy for users to be connected. IP networks provide an efficient way with a large number of services compared to other ways of voice communication. This leads to the migration to make voice calls ...
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Coupling functions: Universal insights into dynamical interaction mechanisms
The dynamical systems found in Nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. Here, we ai...
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Uncertainty quantification for radio interferometric imaging: II. MAP estimation
Uncertainty quantification is a critical missing component in radio interferometric imaging that will only become increasingly important as the big-data era of radio interferometry emerges. Statistical sampling approaches to perform Bayesian inference, like Markov Chain Monte Carlo (MCMC) sampling, can in principle r...
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Semialgebraic Invariant Synthesis for the Kannan-Lipton Orbit Problem
The \emph{Orbit Problem} consists of determining, given a linear transformation $A$ on $\mathbb{Q}^d$, together with vectors $x$ and $y$, whether the orbit of $x$ under repeated applications of $A$ can ever reach $y$. This problem was famously shown to be decidable by Kannan and Lipton in the 1980s. In this paper, we...
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Design and characterization of the Large-Aperture Experiment to Detect the Dark Age (LEDA) radiometer systems
The Large-Aperture Experiment to Detect the Dark Age (LEDA) was designed to detect the predicted O(100)mK sky-averaged absorption of the Cosmic Microwave Background by Hydrogen in the neutral pre- and intergalactic medium just after the cosmological Dark Age. The spectral signature would be associated with emergence ...
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Automatic Bayesian Density Analysis
Making sense of a dataset in an automatic and unsupervised fashion is a challenging problem in statistics and AI. Classical approaches for density estimation are usually not flexible enough to deal with the uncertainty inherent to real-world data: they are often restricted to fixed latent interaction models and homog...
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MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
With the widespread use of machine learning (ML) techniques, ML as a service has become increasingly popular. In this setting, an ML model resides on a server and users can query the model with their data via an API. However, if the user's input is sensitive, sending it to the server is not an option. Equally, the se...
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Brownian forgery of statistical dependences
The balance held by Brownian motion between temporal regularity and randomness is embodied in a remarkable way by Levy's forgery of continuous functions. Here we describe how this property can be extended to forge arbitrary dependences between two statistical systems, and then establish a new Brownian independence te...
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Internal sizes in $μ$-abstract elementary classes
Working in the context of $\mu$-abstract elementary classes ($\mu$-AECs) - or, equivalently, accessible categories with all morphisms monomorphisms - we examine the two natural notions of size that occur, namely cardinality of underlying sets and internal size. The latter, purely category-theoretic, notion generalize...
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Seasonal forecasts of the summer 2016 Yangtze River basin rainfall
The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-i...
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Modeling Interference Via Symmetric Treatment Decomposition
Classical causal inference assumes a treatment meant for a given unit does not have an effect on other units. When this "no interference" assumption is violated, new types of spillover causal effects arise, and causal inference becomes much more difficult. In addition, interference introduces a unique complication wh...
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A Bayesian algorithm for distributed network localization using distance and direction data
A reliable, accurate, and affordable positioning service is highly required in wireless networks. In this paper, the novel Message Passing Hybrid Localization (MPHL) algorithm is proposed to solve the problem of cooperative distributed localization using distance and direction estimates. This hybrid approach combines...
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Bounds for multivariate residues and for the polynomials in the elimination theorem
We present several upper bounds for the height of global residues of rational forms on an affine variety. As a consequence, we deduce upper bounds for the height of the coefficients in the Bergman-Weil trace formula. We also present upper bounds for the degree and the height of the polynomials in the elimination theo...
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An adsorbed gas estimation model for shale gas reservoirs via statistical learning
Shale gas plays an important role in reducing pollution and adjusting the structure of world energy. Gas content estimation is particularly significant in shale gas resource evaluation. There exist various estimation methods, such as first principle methods and empirical models. However, resource evaluation presents ...
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A Semantic Loss Function for Deep Learning with Symbolic Knowledge
This paper develops a novel methodology for using symbolic knowledge in deep learning. From first principles, we derive a semantic loss function that bridges between neural output vectors and logical constraints. This loss function captures how close the neural network is to satisfying the constraints on its output. ...
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Chaotic properties of a turbulent isotropic fluid
By tracking the divergence of two initially close trajectories in phase space in an Eulerian approach to forced turbulence, the relation between the maximal Lyapunov exponent $\lambda$, and the Reynolds number $Re$ is measured using direct numerical simulations, performed on up to $2048^3$ collocation points. The Lya...
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White light emission from silicon nanoparticles
As one of the most important semiconductors, silicon (Si) has been used to fabricate electronic devices, waveguides, detectors, and solar cells etc. However, its indirect bandgap hinders the use of Si for making good emitters1. For integrated photonic circuits, Si-based emitters with sizes in the range of 100-300 nm ...
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The collapse of ecosystem engineer populations
Humans are the ultimate ecosystem engineers who have profoundly transformed the world's landscapes in order to enhance their survival. Somewhat paradoxically, however, sometimes the unforeseen effect of this ecosystem engineering is the very collapse of the population it intended to protect. Here we use a spatial ver...
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Highly Viscous Microjet Generator
This paper describes a simple yet novel system for generating a highly viscous microjet. The jet is produced inside a wettable thin tube partially submerged in a liquid. The gas-liquid interface inside the tube, which is initially concave, is kept much deeper than that outside the tube. An impulsive force applied at ...
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Section problems for configuration spaces of surfaces
In this paper we give a close-to-sharp answer to the basic questions: When is there a continuous way to add a point to a configuration of $n$ ordered points on a surface $S$ of finite type so that all the points are still distinct? When this is possible, what are all the ways to do it? More precisely, let PConf$_n(S)...
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Odd-triplet superconductivity in single-level quantum dots
We study the interplay of spin and charge coherence in a single-level quantum dot. A tunnel coupling to a superconducting lead induces superconducting correlations in the dot. With full spin symmetry retained, only even-singlet superconducting correlations are generated. An applied magnetic field or attached ferromag...
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From Neuronal Models to Neuronal Dynamics and Image Processing
This paper is an introduction to the membrane potential equation for neurons. Its properties are described, as well as sample applications. Networks of these equations can be used for modeling neuronal systems, which also process images and video sequences, respectively. Specifically, (i) a dynamic retina is proposed...
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A compilation of LEGO Technic parts to support learning experiments on linkages
We present a compilation of LEGO Technic parts to provide easy-to-build constructions of basic planar linkages. Some technical issues and their possible solutions are discussed. To solve questions on fine details---like deciding whether the motion is an exactly straight line or not---we refer to the dynamic mathemati...
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On the Casas-Alvero conjecture
The conjecture is formulated in an affine structure and linked with dimension=1 of the defined CA sets. Then some known results are proved in this context. The short intended proof relies on a direct yet unclear statement about homogeneous dependence of algebraic equations. This might not be a complete proof or even ...
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Effect of compressibility and aspect ratio on performance of long elastic seals
Recent experiments show no statistical impact of seal length on the performance of long elastomeric seals in relatively smooth test fixtures. Motivated by these results, we analytically and computationally investigate the combined effects of seal length and compressibility on the maximum differential pressure a seal ...
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Integral models of reductive groups and integral Mumford-Tate groups
Let $G$ be a reductive algebraic group over a $p$-adic field or number field $K$, and let $V$ be a $K$-linear faithful representation of $G$. A lattice $\Lambda$ in the vector space $V$ defines a model $\hat{G}_{\Lambda}$ of $G$ over $\mathscr{O}_K$. One may wonder to what extent $\Lambda$ is determined by the group ...
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A proof of Boca's Theorem
We give a general method of extending unital completely positive maps to amalgamated free products of C*-algebras. As an application we give a dilation theoretic proof of Boca's Theorem.
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Vico-Greengard-Ferrando quadratures in the tensor solver for integral equations
Convolution with Green's function of a differential operator appears in a lot of applications e.g. Lippmann-Schwinger integral equation. Algorithms for computing such are usually non-trivial and require non-uniform mesh. However, recently Vico, Greengard and Ferrando developed method for computing convolution with sm...
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Mott insulators of hardcore bosons in 1D: many-body orders, entanglement, edge modes
Many-body phenomena were always an integral part of physics comprising of collective behaviors through self-organization, in systems consisting of many components and degrees of freedom. We investigate the collective behaviors of strongly interacting particles confined in one dimension. We show that many-body orders ...
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Fast Monte Carlo Markov chains for Bayesian shrinkage models with random effects
When performing Bayesian data analysis using a general linear mixed model, the resulting posterior density is almost always analytically intractable. However, if proper conditionally conjugate priors are used, there is a simple two-block Gibbs sampler that is geometrically ergodic in nearly all practical settings, in...
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Distributed Optimal Vehicle Grid Integration Strategy with User Behavior Prediction
With the increasing of electric vehicle (EV) adoption in recent years, the impact of EV charging activities to the power grid becomes more and more significant. In this article, an optimal scheduling algorithm which combines smart EV charging and V2G gird service is developed to integrate EVs into power grid as distr...
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Horcrux: A Password Manager for Paranoids
Vulnerabilities in password managers are unremitting because current designs provide large attack surfaces, both at the client and server. We describe and evaluate Horcrux, a password manager that is designed holistically to minimize and decentralize trust, while retaining the usability of a traditional password mana...
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Cross-validation
This text is a survey on cross-validation. We define all classical cross-validation procedures, and we study their properties for two different goals: estimating the risk of a given estimator, and selecting the best estimator among a given family. For the risk estimation problem, we compute the bias (which can also b...
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Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees
Objective: Using traditional approaches, a Brain-Computer Interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g.~by transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratc...
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Generalized Index Coding Problem and Discrete Polymatroids
The index coding problem has been generalized recently to accommodate receivers which demand functions of messages and which possess functions of messages. The connections between index coding and matroid theory have been well studied in the recent past. Index coding solutions were first connected to multi linear rep...
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Reconstruction via the intrinsic geometric structures of interior transmission eigenfunctions
We are concerned with the inverse scattering problem of extracting the geometric structures of an unknown/inaccessible inhomogeneous medium by using the corresponding acoustic far-field measurement. Using the intrinsic geometric properties of the so-called interior transmission eigenfunctions, we develop a novel inve...
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Thermoelectric phase diagram of the SrTiO3-SrNbO3 solid solution system
Thermoelectric energy conversion - the exploitation of the Seebeck effect to convert waste heat into electricity - has attracted an increasing amount of research attention for energy harvesting technology. Niobium-doped strontium titanate (SrTi1-xNbxO3) is one of the most promising thermoelectric material candidates,...
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AMPA, NMDA and GABAA receptor mediated network burst dynamics in cortical cultures in vitro
In this work we study the excitatory AMPA, and NMDA, and inhibitory GABAA receptor mediated dynamical changes in neuronal networks of neonatal rat cortex in vitro. Extracellular network-wide activity was recorded with 59 planar electrodes simultaneously under different pharmacological conditions. We analyzed the chan...
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Coarse fundamental groups and box spaces
We use a coarse version of the fundamental group first introduced by Barcelo, Kramer, Laubenbacher and Weaver to show that box spaces of finitely presented groups detect the normal subgroups used to construct the box space, up to isomorphism. As a consequence we have that two finitely presented groups admit coarsely ...
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Algebraic entropy of (integrable) lattice equations and their reductions
We study the growth of degrees in many autonomous and non-autonomous lattice equations defined by quad rules with corner boundary values, some of which are known to be integrable by other characterisations. Subject to an enabling conjecture, we prove polynomial growth for a large class of equations which includes the...
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Measurement of mirror birefringence with laser heterodyne polarimetry
A laser heterodyne polarimeter (LHP) designed for the measurement of the birefringence of dielectric super-mirrors is described and initial results are reported. The LHP does not require an optical resonator and so promises unprecedented accuracy in the measurement of the birefringence of individual mirrors. The work...
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Individual position diversity in dependence socioeconomic networks increases economic output
The availability of big data recorded from massively multiplayer online role-playing games (MMORPGs) allows us to gain a deeper understanding of the potential connection between individuals' network positions and their economic outputs. We use a statistical filtering method to construct dependence networks from weigh...
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A formula for the nonsymmetric Opdam's hypergeometric function of type $A_2$
The aim of this paper is to give an explicit formula for the nonsymmetric Heckman-Opdam's hypergeometric function of type $A_2$. This is obtained by differentiating the corresponding symmetric hypergeometric function.
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A new algorithm for irreducible decomposition of representations of finite groups
An algorithm for irreducible decomposition of representations of finite groups over fields of characteristic zero is described. The algorithm uses the fact that the decomposition induces a partition of the invariant inner product into a complete set of mutually orthogonal projectors. By expressing the projectors thro...
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Stability and Grothendieck
This note is a commentary on the model-theoretic interpretation of Grothendieck's double limit characterization of weak relative compactness.
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Visual Analogies between Atari Games for Studying Transfer Learning in RL
In this work, we ask the following question: Can visual analogies, learned in an unsupervised way, be used in order to transfer knowledge between pairs of games and even play one game using an agent trained for another game? We attempt to answer this research question by creating visual analogies between a pair of ga...
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Learning in the Repeated Secretary Problem
In the classical secretary problem, one attempts to find the maximum of an unknown and unlearnable distribution through sequential search. In many real-world searches, however, distributions are not entirely unknown and can be learned through experience. To investigate learning in such a repeated secretary problem we...
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Flexible Mixture Modeling on Constrained Spaces
This paper addresses challenges in flexibly modeling multimodal data that lie on constrained spaces. Applications include climate or crime measurements in a geographical area, or flow-cytometry experiments, where unsuitable recordings are discarded. A simple approach to modeling such data is through the use of mixtur...
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Universal equilibrium scaling functions at short times after a quench
By analyzing spin-spin correlation functions at relatively short distances, we show that equilibrium near-critical properties can be extracted at short times after quenches into the vicinity of a quantum critical point. The time scales after which equilibrium properties can be extracted are sufficiently short so that...
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First Results from CUORE: A Search for Lepton Number Violation via $0νββ$ Decay of $^{130}$Te
The CUORE experiment, a ton-scale cryogenic bolometer array, recently began operation at the Laboratori Nazionali del Gran Sasso in Italy. The array represents a significant advancement in this technology, and in this work we apply it for the first time to a high-sensitivity search for a lepton-number--violating proc...
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Bernoulli-Carlitz and Cauchy-Carlitz numbers with Stirling-Carlitz numbers
Recently, the Cauchy-Carlitz number was defined as the counterpart of the Bernoulli-Carlitz number. Both numbers can be expressed explicitly in terms of so-called Stirling-Carlitz numbers. In this paper, we study the second analogue of Stirling-Carlitz numbers and give some general formulae, including Bernoulli and C...
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Irreducible network backbones: unbiased graph filtering via maximum entropy
Networks provide an informative, yet non-redundant description of complex systems only if links represent truly dyadic relationships that cannot be directly traced back to node-specific properties such as size, importance, or coordinates in some embedding space. In any real-world network, some links may be reducible,...
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Synkhronos: a Multi-GPU Theano Extension for Data Parallelism
We present Synkhronos, an extension to Theano for multi-GPU computations leveraging data parallelism. Our framework provides automated execution and synchronization across devices, allowing users to continue to write serial programs without risk of race conditions. The NVIDIA Collective Communication Library is used ...
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The PomXYZ Proteins Self-Organize on the Bacterial Nucleoid to Stimulate Cell Division
Cell division site positioning is precisely regulated to generate correctly sized and shaped daughters. We uncover a novel strategy to position the FtsZ cytokinetic ring at midcell in the social bacterium Myxococcus xanthus. PomX, PomY and the nucleoid-binding ParA/MinD ATPase PomZ self-assemble forming a large nucle...
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Quantitative Results on Diophantine Equations in Many Variables
We consider a system of polynomials $f_1,\ldots, f_R\in \mathbb{Z}[x_1,\ldots, x_n]$ of the same degree with non-singular local zeros and in many variables. Generalising the work of Birch (1962) we find quantitative asymptotics (in terms of the maximum of the absolute value of the coefficients of these polynomials) f...
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Generalized Springer correspondence for symmetric spaces associated to orthogonal groups
Let $G = GL_N$ over an algebraically closed field of odd characteristic, and $\theta$ an involutive automorphism on $G$ such that $H = (G^{\theta})^0$ is isomorphic to $SO_N$. Then $G^{\iota\theta} = \{ g \in G \mid \theta(g) = g^{-1} \}$ is regarded as a symmetric space $G/G^{\theta}$. Let $G^{\iota\theta}_{uni}$ be...
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An Ensemble Boosting Model for Predicting Transfer to the Pediatric Intensive Care Unit
Our work focuses on the problem of predicting the transfer of pediatric patients from the general ward of a hospital to the pediatric intensive care unit. Using data collected over 5.5 years from the electronic health records of two medical facilities, we develop classifiers based on adaptive boosting and gradient tr...
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Effects of Network Structure on the Performance of a Modeled Traffic Network under Drivers' Bounded Rationality
We propose a minority route choice game to investigate the effect of the network structure on traffic network performance under the assumption of drivers' bounded rationality. We investigate ring-and-hub topologies to capture the nature of traffic networks in cities, and employ a minority game-based inductive learnin...
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Sneak into Devil's Colony- A study of Fake Profiles in Online Social Networks and the Cyber Law
Massive content about user's social, personal and professional life stored on Online Social Networks (OSNs) has attracted not only the attention of researchers and social analysts but also the cyber criminals. These cyber criminals penetrate illegally into an OSN by establishing fake profiles or by designing bots and...
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Preserving Data-Privacy with Added Noises: Optimal Estimation and Privacy Analysis
Networked system often relies on distributed algorithms to achieve a global computation goal with iterative local information exchanges between neighbor nodes. To preserve data privacy, a node may add a random noise to its original data for information exchange at each iteration. Nevertheless, a neighbor node can est...
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Geometric tuning of self-propulsion for Janus catalytic particles
Catalytic swimmers have attracted much attention as alternatives to biological systems for examining collective microscopic dynamics and the response to physico-chemical signals. Yet, understanding and predicting even the most fundamental characteristics of their individual propulsion still raises important challenge...
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On the Bogolubov-de Gennes Equations
We consider the Bogolubov-de Gennes equations giving an equivalent formulation of the BCS theory of superconductivity. We are interested in the case when the magnetic field is present. We (a) discuss their general features, (b) isolate key physical classes of solutions (normal, vortex and vortex lattice states) and (...
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High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
Penalized likelihood methods are widely used for high-dimensional regression. Although many methods have been proposed and the associated theory is now well-developed, the relative efficacy of different methods in finite-sample settings, as encountered in practice, remains incompletely understood. There is therefore ...
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Using Human Brain Activity to Guide Machine Learning
Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, ...
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Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning
We use a deep learning model trained only on a patient's blood oxygenation data (measurable with an inexpensive fingertip sensor) to predict impending hypoxemia (low blood oxygen) more accurately than trained anesthesiologists with access to all the data recorded in a modern operating room. We also provide a simple w...
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Merging fragments of classical logic
We investigate the possibility of extending the non-functionally complete logic of a collection of Boolean connectives by the addition of further Boolean connectives that make the resulting set of connectives functionally complete. More precisely, we will be interested in checking whether an axiomatization for Classi...
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Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series
We propose a new variational Bayes estimator for high-dimensional copulas with discrete, or a combination of discrete and continuous, margins. The method is based on a variational approximation to a tractable augmented posterior, and is faster than previous likelihood-based approaches. We use it to estimate drawable ...
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COSMO: Contextualized Scene Modeling with Boltzmann Machines
Scene modeling is very crucial for robots that need to perceive, reason about and manipulate the objects in their environments. In this paper, we adapt and extend Boltzmann Machines (BMs) for contextualized scene modeling. Although there are many models on the subject, ours is the first to bring together objects, rel...
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Learning Large-Scale Topological Maps Using Sum-Product Networks
In order to perform complex actions in human environments, an autonomous robot needs the ability to understand the environment, that is, to gather and maintain spatial knowledge. Topological map is commonly used for representing large scale, global maps such as floor plans. Although much work has been done in topolog...
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Entanglement scaling and spatial correlations of the transverse field Ising model with perturbations
We study numerically the entanglement entropy and spatial correlations of the one dimensional transverse field Ising model with three different perturbations. First, we focus on the out of equilibrium, steady state with an energy current passing through the system. By employing a variety of matrix-product state based...
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Anyonic excitations of hardcore anyons
Strongly interacting many-body systems consisting of fermions or bosons can host exotic quasiparticles with anyonic statistics. Here, we demonstrate that many-body systems of anyons can also form anyonic quasi-particles. The charge and statistics of the emergent anyons can be different from those of the original anyo...
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