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An upper bound on the distinguishing index of graphs with minimum degree at least two
The distinguishing index of a simple graph $G$, denoted by $D'(G)$, is the least number of labels in an edge labeling of $G$ not preserved by any non-trivial automorphism. It was conjectured by Pilśniak (2015) that for any 2-connected graph $D'(G) \leq \lceil \sqrt{\Delta (G)}\rceil +1$. We prove a more general resul...
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Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization
Pseudo healthy synthesis, i.e. the creation of a subject-specific `healthy' image from a pathological one, could be helpful in tasks such as anomaly detection, understanding changes induced by pathology and disease or even as data augmentation. We treat this task as a factor decomposition problem: we aim to separate ...
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Closure operators, frames, and neatest representations
Given a poset $P$ and a standard closure operator $\Gamma:\wp(P)\to\wp(P)$ we give a necessary and sufficient condition for the lattice of $\Gamma$-closed sets of $\wp(P)$ to be a frame in terms of the recursive construction of the $\Gamma$-closure of sets. We use this condition to show that given a set $\mathcal{U}$...
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The structure of rationally factorized Lax type flows and their analytical integrability
The work is devoted to constructing a wide class of differential-functional dynamical systems, whose rich algebraic structure makes their integrability analytically effective. In particular, there is analyzed in detail the operator Lax type equations for factorized seed elements, there is proved an important theorem ...
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Learning Policy Representations in Multiagent Systems
Modeling agent behavior is central to understanding the emergence of complex phenomena in multiagent systems. Prior work in agent modeling has largely been task-specific and driven by hand-engineering domain-specific prior knowledge. We propose a general learning framework for modeling agent behavior in any multiagen...
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Jamming-Resistant Receivers for the Massive MIMO Uplink
We design a jamming-resistant receiver scheme to enhance the robustness of a massive MIMO uplink system against jamming. We assume that a jammer attacks the system both in the pilot and data transmission phases. The key feature of the proposed scheme is that, in the pilot phase, we estimate not only the legitimate ch...
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Multiplex core-periphery organization of the human connectome
The behavior of many complex systems is determined by a core of densely interconnected units. While many methods are available to identify the core of a network when connections between nodes are all of the same type, a principled approach to define the core when multiple types of connectivity are allowed is still la...
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Towards Learned Clauses Database Reduction Strategies Based on Dominance Relationship
Clause Learning is one of the most important components of a conflict driven clause learning (CDCL) SAT solver that is effective on industrial instances. Since the number of learned clauses is proved to be exponential in the worse case, it is necessary to identify the most relevant clauses to maintain and delete the ...
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Integrable structure of products of finite complex Ginibre random matrices
We consider the squared singular values of the product of $M$ standard complex Gaussian matrices. Since the squared singular values form a determinantal point process with a particular Meijer G-function kernel, the gap probabilities are given by a Fredholm determinant based on this kernel. It was shown by Strahov \ci...
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Global well-posedness of the 3D primitive equations with horizontal viscosity and vertical diffusivity
In this paper, we consider the 3D primitive equations of oceanic and atmospheric dynamics with only horizontal eddy viscosities in the horizontal momentum equations and only vertical diffusivity in the temperature equation. Global well-posedness of strong solutions is established for any initial data such that the in...
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Superintegrable systems on 3-dimensional curved spaces: Eisenhart formalism and separability
The Eisenhart geometric formalism, which transforms an Euclidean natural Hamiltonian $H=T+V$ into a geodesic Hamiltonian ${\cal T}$ with one additional degree of freedom, is applied to the four families of quadratically superintegrable systems with multiple separability in the Euclidean plane. Firstly, the separabili...
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An Incentive-Based Online Optimization Framework for Distribution Grids
This paper formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic ob...
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Ricci solitons on Ricci pseudosymmetric $(LCS)_n$-manifolds
The object of the present paper is to study some types of Ricci pseudosymmetric $(LCS)_n$-manifolds whose metric is Ricci soliton. We found the conditions when Ricci soliton on concircular Ricci pseudosymmetric, projective Ricci pseudosymmetric, $W_{3}$-Ricci pseudosymmetric, conharmonic Ricci pseudosymmetric, confor...
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Optimal Gossip Algorithms for Exact and Approximate Quantile Computations
This paper gives drastically faster gossip algorithms to compute exact and approximate quantiles. Gossip algorithms, which allow each node to contact a uniformly random other node in each round, have been intensely studied and been adopted in many applications due to their fast convergence and their robustness to fai...
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Influence of Heat Treatment on the Corrosion Behavior of Purified Magnesium and AZ31 Alloy
Magnesium and its alloys are ideal for biodegradable implants due to their biocompatibility and their low-stress shielding. However, they can corrode too rapidly in the biological environment. The objective of this research was to develop heat treatments to slow the corrosion of high purified magnesium and AZ31 alloy...
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Towards a scientific blockchain framework for reproducible data analysis
Publishing reproducible analyses is a long-standing and widespread challenge for the scientific community, funding bodies and publishers. Although a definitive solution is still elusive, the problem is recognized to affect all disciplines and lead to a critical system inefficiency. Here, we propose a blockchain-based...
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Time Series Anomaly Detection; Detection of anomalous drops with limited features and sparse examples in noisy highly periodic data
Google uses continuous streams of data from industry partners in order to deliver accurate results to users. Unexpected drops in traffic can be an indication of an underlying issue and may be an early warning that remedial action may be necessary. Detecting such drops is non-trivial because streams are variable and n...
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A parallel approach to bi-objective integer programming
To obtain a better understanding of the trade-offs between various objectives, Bi-Objective Integer Programming (BOIP) algorithms calculate the set of all non-dominated vectors and present these as the solution to a BOIP problem. Historically, these algorithms have been compared in terms of the number of single-objec...
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The adaptive zero-error capacity for a class of channels with noisy feedback
The adaptive zero-error capacity of discrete memoryless channels (DMC) with noiseless feedback has been shown to be positive whenever there exists at least one channel output "disprover", i.e. a channel output that cannot be reached from at least one of the inputs. Furthermore, whenever there exists a disprover, the ...
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Comparison of Self-Aware and Organic Computing Systems
With increasing complexity and heterogeneity of computing devices, it has become crucial for system to be autonomous, adaptive to dynamic environment, robust, flexible, and having so called self-*properties. These autonomous systems are called organic computing(OC) systems. OC system was proposed as a solution to tac...
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First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems
We focus on nonconvex and nonsmooth minimization problems with a composite objective, where the differentiable part of the objective is freed from the usual and restrictive global Lipschitz gradient continuity assumption. This longstanding smoothness restriction is pervasive in first order methods (FOM), and was rece...
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An Army of Me: Sockpuppets in Online Discussion Communities
In online discussion communities, users can interact and share information and opinions on a wide variety of topics. However, some users may create multiple identities, or sockpuppets, and engage in undesired behavior by deceiving others or manipulating discussions. In this work, we study sockpuppetry across nine dis...
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Robust Bayesian Optimization with Student-t Likelihood
Bayesian optimization has recently attracted the attention of the automatic machine learning community for its excellent results in hyperparameter tuning. BO is characterized by the sample efficiency with which it can optimize expensive black-box functions. The efficiency is achieved in a similar fashion to the learn...
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Vehicle Localization and Control on Roads with Prior Grade Map
We propose a map-aided vehicle localization method for GPS-denied environments. This approach exploits prior knowledge of the road grade map and vehicle on-board sensor measurements to accurately estimate the longitudinal position of the vehicle. Real-time localization is crucial to systems that utilize position-depe...
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Estimating Tactile Data for Adaptive Grasping of Novel Objects
We present an adaptive grasping method that finds stable grasps on novel objects. The main contributions of this paper is in the computation of the probability of success of grasps in the vicinity of an already applied grasp. Our method performs grasp adaptions by simulating tactile data for grasps in the vicinity of...
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Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
Algorithm-dependent generalization error bounds are central to statistical learning theory. A learning algorithm may use a large hypothesis space, but the limited number of iterations controls its model capacity and generalization error. The impacts of stochastic gradient methods on generalization error for non-conve...
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Near-UV OH Prompt Emission in the Innermost Coma of 103P/Hartley 2
The Deep Impact spacecraft fly-by of comet 103P/Hartley 2 occurred on 2010 November 4, one week after perihelion with a closest approach (CA) distance of about 700 km. We used narrowband images obtained by the Medium Resolution Imager (MRI) onboard the spacecraft to study the gas and dust in the innermost coma. We de...
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Effective gravity and effective quantum equations in a system inspired by walking droplets experiments
In this paper we suggest a macroscopic toy system in which a potential-like energy is generated by a non-uniform pulsation of the medium (i.e. pulsation of transverse standing oscillations that the elastic medium of the system tends to support at each point). This system is inspired by walking droplets experiments wi...
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A gradient estimate for nonlocal minimal graphs
We consider the class of measurable functions defined in all of $\mathbb{R}^n$ that give rise to a nonlocal minimal graph over a ball of $\mathbb{R}^n$. We establish that the gradient of any such function is bounded in the interior of the ball by a power of its oscillation. This estimate, together with previously kno...
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The GAPS Programme with HARPS-N@TNG XIV. Investigating giant planet migration history via improved eccentricity and mass determination for 231 transiting planets
We carried out a Bayesian homogeneous determination of the orbital parameters of 231 transiting giant planets (TGPs) that are alone or have distant companions; we employed DE-MCMC methods to analyse radial-velocity (RV) data from the literature and 782 new high-accuracy RVs obtained with the HARPS-N spectrograph for ...
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Injective stabilization of additive functors. I. Preliminaries
This paper is the first one in a series of three dealing with the concept of injective stabilization of the tensor product and its applications. Its primary goal is to collect known facts and establish a basic operational calculus that will be used in the subsequent parts. This is done in greater generality than is n...
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Three hypergraph eigenvector centralities
Eigenvector centrality is a standard network analysis tool for determining the importance of (or ranking of) entities in a connected system that is represented by a graph. However, many complex systems and datasets have natural multi-way interactions that are more faithfully modeled by a hypergraph. Here we extend th...
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Reinforcement Learning using Augmented Neural Networks
Neural networks allow Q-learning reinforcement learning agents such as deep Q-networks (DQN) to approximate complex mappings from state spaces to value functions. However, this also brings drawbacks when compared to other function approximators such as tile coding or their generalisations, radial basis functions (RBF...
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Instantons and Fluctuations in a Lagrangian Model of Turbulence
We perform a detailed analytical study of the Recent Fluid Deformation (RFD) model for the onset of Lagrangian intermittency, within the context of the Martin-Siggia-Rose-Janssen-de Dominicis (MSRJD) path integral formalism. The model is based, as a key point, upon local closures for the pressure Hessian and the visc...
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The heavy path approach to Galton-Watson trees with an application to Apollonian networks
We study the heavy path decomposition of conditional Galton-Watson trees. In a standard Galton-Watson tree conditional on its size $n$, we order all children by their subtree sizes, from large (heavy) to small. A node is marked if it is among the $k$ heaviest nodes among its siblings. Unmarked nodes and their subtree...
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Perishability of Data: Dynamic Pricing under Varying-Coefficient Models
We consider a firm that sells a large number of products to its customers in an online fashion. Each product is described by a high dimensional feature vector, and the market value of a product is assumed to be linear in the values of its features. Parameters of the valuation model are unknown and can change over tim...
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A fast algorithm for maximal propensity score matching
We present a new algorithm which detects the maximal possible number of matched disjoint pairs satisfying a given caliper when a bipartite matching is done with respect to a scalar index (e.g., propensity score), and constructs a corresponding matching. Variable width calipers are compatible with the technique, provi...
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Fractional quantum Hall systems near nematicity: bimetric theory, composite fermions, and Dirac brackets
We perform a detailed comparison of the Dirac composite fermion and the recently proposed bimetric theory for a quantum Hall Jain states near half filling. By tuning the composite Fermi liquid to the vicinity of a nematic phase transition, we find that the two theories are equivalent to each other. We verify that the...
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Recognizing Objects In-the-wild: Where Do We Stand?
The ability to recognize objects is an essential skill for a robotic system acting in human-populated environments. Despite decades of effort from the robotic and vision research communities, robots are still missing good visual perceptual systems, preventing the use of autonomous agents for real-world applications. ...
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Generalizing Geometric Brownian Motion
To convert standard Brownian motion $Z$ into a positive process, Geometric Brownian motion (GBM) $e^{\beta Z_t}, \beta >0$ is widely used. We generalize this positive process by introducing an asymmetry parameter $ \alpha \geq 0$ which describes the instantaneous volatility whenever the process reaches a new low. For...
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Challenges testing the no-hair theorem with gravitational waves
General relativity's no-hair theorem states that isolated astrophysical black holes are described by only two numbers: mass and spin. As a consequence, there are strict relationships between the frequency and damping time of the different modes of a perturbed Kerr black hole. Testing the no-hair theorem has been a lo...
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Speculation On a Source of Dark Matter
By drawing an analogy with superfluid 4He vortices we suggest that dark matter may consist of irreducibly small remnants of cosmic strings.
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Analyzing Cloud Optical Properties Using Sky Cameras
Clouds play a significant role in the fluctuation of solar radiation received by the earth's surface. It is important to study the various cloud properties, as it impacts the total solar irradiance falling on the earth's surface. One of such important optical properties of the cloud is the Cloud Optical Thickness (CO...
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Response Formulae for $n$-point Correlations in Statistical Mechanical Systems and Application to a Problem of Coarse Graining
Predicting the response of a system to perturbations is a key challenge in mathematical and natural sciences. Under suitable conditions on the nature of the system, of the perturbation, and of the observables of interest, response theories allow to construct operators describing the smooth change of the invariant mea...
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The Australian PCEHR system: Ensuring Privacy and Security through an Improved Access Control Mechanism
An Electronic Health Record (EHR) is designed to store diverse data accurately from a range of health care providers and to capture the status of a patient by a range of health care providers across time. Realising the numerous benefits of the system, EHR adoption is growing globally and many countries invest heavily...
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Randomized Kernel Methods for Least-Squares Support Vector Machines
The least-squares support vector machine is a frequently used kernel method for non-linear regression and classification tasks. Here we discuss several approximation algorithms for the least-squares support vector machine classifier. The proposed methods are based on randomized block kernel matrices, and we show that...
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Optimal Transport: Fast Probabilistic Approximation with Exact Solvers
We propose a simple subsampling scheme for fast randomized approximate computation of optimal transport distances. This scheme operates on a random subset of the full data and can use any exact algorithm as a black-box back-end, including state-of-the-art solvers and entropically penalized versions. It is based on av...
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Reliable Clustering of Bernoulli Mixture Models
A Bernoulli Mixture Model (BMM) is a finite mixture of random binary vectors with independent Bernoulli dimensions. The problem of clustering BMM data arises in a variety of real-world applications, ranging from population genetics to activity analysis in social networks. In this paper, we have analyzed the informati...
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Short-time behavior of the heat kernel and Weyl's law on $RCD^*(K, N)$-spaces
In this paper, we prove pointwise convergence of heat kernels for mGH-convergent sequences of $RCD^*(K,N)$-spaces. We obtain as a corollary results on the short-time behavior of the heat kernel in $RCD^*(K,N)$-spaces. We use then these results to initiate the study of Weyl's law in the $RCD$ setting
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Football and Beer - a Social Media Analysis on Twitter in Context of the FIFA Football World Cup 2018
In many societies alcohol is a legal and common recreational substance and socially accepted. Alcohol consumption often comes along with social events as it helps people to increase their sociability and to overcome their inhibitions. On the other hand we know that increased alcohol consumption can lead to serious he...
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Cross-stream migration of a surfactant-laden deformable droplet in a Poiseuille flow
The motion of a viscous deformable droplet suspended in an unbounded Poiseuille flow in the presence of bulk-insoluble surfactants is studied analytically. Assuming the convective transport of fluid and heat to be negligible, we perform a small-deformation perturbation analysis to obtain the droplet migration velocit...
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PCA in Data-Dependent Noise (Correlated-PCA): Nearly Optimal Finite Sample Guarantees
We study Principal Component Analysis (PCA) in a setting where a part of the corrupting noise is data-dependent and, as a result, the noise and the true data are correlated. Under a bounded-ness assumption on the true data and the noise, and a simple assumption on data-noise correlation, we obtain a nearly optimal sa...
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Using a Predator-Prey Model to Explain Variations of Cloud Spot Price
The spot pricing scheme has been considered to be resource-efficient for providers and cost-effective for consumers in the Cloud market. Nevertheless, unlike the static and straightforward strategies of trading on-demand and reserved Cloud services, the market-driven mechanism for trading spot service would be compli...
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Separatrix crossing in rotation of a body with changing geometry of masses
We consider free rotation of a body whose parts move slowly with respect to each other under the action of internal forces. This problem can be considered as a perturbation of the Euler-Poinsot problem. The dynamics has an approximate conservation law - an adiabatic invariant. This allows to describe the evolution of...
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SING: Symbol-to-Instrument Neural Generator
Recent progress in deep learning for audio synthesis opens the way to models that directly produce the waveform, shifting away from the traditional paradigm of relying on vocoders or MIDI synthesizers for speech or music generation. Despite their successes, current state-of-the-art neural audio synthesizers such as W...
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Path-by-path regularization by noise for scalar conservation laws
We prove a path-by-path regularization by noise result for scalar conservation laws. In particular, this proves regularizing properties for scalar conservation laws driven by fractional Brownian motion and generalizes the respective results obtained in [Gess, Souganidis; Comm. Pure Appl. Math. (2017)]. In addition, w...
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An End-to-End Trainable Neural Network Model with Belief Tracking for Task-Oriented Dialog
We present a novel end-to-end trainable neural network model for task-oriented dialog systems. The model is able to track dialog state, issue API calls to knowledge base (KB), and incorporate structured KB query results into system responses to successfully complete task-oriented dialogs. The proposed model produces ...
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Neural IR Meets Graph Embedding: A Ranking Model for Product Search
Recently, neural models for information retrieval are becoming increasingly popular. They provide effective approaches for product search due to their competitive advantages in semantic matching. However, it is challenging to use graph-based features, though proved very useful in IR literature, in these neural approa...
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Scaling up the software development process, a case study highlighting the complexities of large team software development
Diamond Light Source is the UK's National Synchrotron Facility and as such provides access to world class experimental services for UK and international researchers. As a user facility, that is one that focuses on providing a good user experience to our varied visitors, Diamond invests heavily in software infrastruct...
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Lyapunov exponents for products of matrices
Let ${\bf M}=(M_1,\ldots, M_k)$ be a tuple of real $d\times d$ matrices. Under certain irreducibility assumptions, we give checkable criteria for deciding whether ${\bf M}$ possesses the following property: there exist two constants $\lambda\in {\Bbb R}$ and $C>0$ such that for any $n\in {\Bbb N}$ and any $i_1, \ldot...
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A definitive improvement of a game-theoretic bound and the long tightness game
The main goal of the paper is the full proof of a cardinal inequality for a space with points $G_\delta $, obtained with the help of a long version of the Menger game. This result, which improves a similar one of Scheepers and Tall, was already established by the authors under the Continuum Hypothesis. The paper is c...
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Group-Server Queues
By analyzing energy-efficient management of data centers, this paper proposes and develops a class of interesting {\it Group-Server Queues}, and establishes two representative group-server queues through loss networks and impatient customers, respectively. Furthermore, such two group-server queues are given model des...
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MC$^2$: Multi-wavelength and dynamical analysis of the merging galaxy cluster ZwCl 0008.8+5215: An older and less massive Bullet Cluster
We analyze a rich dataset including Subaru/SuprimeCam, HST/ACS and WFC3, Keck/DEIMOS, Chandra/ACIS-I, and JVLA/C and D array for the merging galaxy cluster ZwCl 0008.8+5215. With a joint Subaru/HST weak gravitational lensing analysis, we identify two dominant subclusters and estimate the masses to be M$_{200}=\text{5...
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Bayesian adaptive bandit-based designs using the Gittins index for multi-armed trials with normally distributed endpoints
Adaptive designs for multi-armed clinical trials have become increasingly popular recently in many areas of medical research because of their potential to shorten development times and to increase patient response. However, developing response-adaptive trial designs that offer patient benefit while ensuring the resul...
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Convexification of Queueing Formulas by Mixed-Integer Second-Order Cone Programming: An Application to a Discrete Location Problem with Congestion
Mixed-Integer Second-Order Cone Programs (MISOCPs) form a nice class of mixed-inter convex programs, which can be solved very efficiently due to the recent advances in optimization solvers. Our paper bridges the gap between modeling a class of optimization problems and using MISOCP solvers. It is shown how various pe...
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Discriminative Metric Learning with Deep Forest
A Discriminative Deep Forest (DisDF) as a metric learning algorithm is proposed in the paper. It is based on the Deep Forest or gcForest proposed by Zhou and Feng and can be viewed as a gcForest modification. The case of the fully supervised learning is studied when the class labels of individual training examples ar...
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An accurate and robust genuinely multidimensional Riemann solver for Euler equations based on TV flux splitting
A simple robust genuinely multidimensional convective pressure split (CPS) , contact preserving, shock stable Riemann solver (GM-K-CUSP-X) for Euler equations of gas dynamics is developed. The convective and pressure components of the Euler system are separated following the Toro-Vazquez type PDE flux splitting [Toro...
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Strong Convergence Rate of Splitting Schemes for Stochastic Nonlinear Schrödinger Equations
We prove the optimal strong convergence rate of a fully discrete scheme, based on a splitting approach, for a stochastic nonlinear Schrödinger (NLS) equation. The main novelty of our method lies on the uniform a priori estimate and exponential integrability of a sequence of splitting processes which are used to appro...
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Controllability of Conjunctive Boolean Networks with Application to Gene Regulation
A Boolean network is a finite state discrete time dynamical system. At each step, each variable takes a value from a binary set. The value update rule for each variable is a local function which depends only on a selected subset of variables. Boolean networks have been used in modeling gene regulatory networks. We fo...
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Fast-neutron and gamma-ray imaging with a capillary liquid xenon converter coupled to a gaseous photomultiplier
Gamma-ray and fast-neutron imaging was performed with a novel liquid xenon (LXe) scintillation detector read out by a Gaseous Photomultiplier (GPM). The 100 mm diameter detector prototype comprised a capillary-filled LXe converter/scintillator, coupled to a triple-THGEM imaging-GPM, with its first electrode coated by...
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Is Task Board Customization Beneficial? - An Eye Tracking Study
The task board is an essential artifact in many agile development approaches. It provides a good overview of the project status. Teams often customize their task boards according to the team members' needs. They modify the structure of boards, define colored codings for different purposes, and introduce different car...
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Characterizing the impact of model error in hydrogeologic time series recovery inverse problems
Hydrogeologic models are commonly over-smoothed relative to reality, owing to the difficulty of obtaining accurate high-resolution information about the subsurface. When used in an inversion context, such models may introduce systematic biases which cannot be encapsulated by an unbiased "observation noise" term of th...
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Suszko's Problem: Mixed Consequence and Compositionality
Suszko's problem is the problem of finding the minimal number of truth values needed to semantically characterize a syntactic consequence relation. Suszko proved that every Tarskian consequence relation can be characterized using only two truth values. Malinowski showed that this number can equal three if some of Tar...
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Optimization of distributions differences for classification
In this paper we introduce a new classification algorithm called Optimization of Distributions Differences (ODD). The algorithm aims to find a transformation from the feature space to a new space where the instances in the same class are as close as possible to one another while the gravity centers of these classes a...
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Galois descent of semi-affinoid spaces
We study the Galois descent of semi-affinoid non-archimedean analytic spaces. These are the non-archimedean analytic spaces which admit an affine special formal scheme as model over a complete discrete valuation ring, such as for example open or closed polydiscs or polyannuli. Using Weil restrictions and Galois fixed...
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Synthesis, Crystal Structure, and Physical Properties of New Layered Oxychalcogenide La2O2Bi3AgS6
We have synthesized a new layered oxychalcogenide La2O2Bi3AgS6. From synchrotron X-ray diffraction and Rietveld refinement, the crystal structure of La2O2Bi3AgS6 was refined using a model of the P4/nmm space group with a = 4.0644(1) {\AA} and c = 19.412(1) {\AA}, which is similar to the related compound LaOBiPbS3, wh...
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Planar Graph Perfect Matching is in NC
Is perfect matching in NC? That is, is there a deterministic fast parallel algorithm for it? This has been an outstanding open question in theoretical computer science for over three decades, ever since the discovery of RNC matching algorithms. Within this question, the case of planar graphs has remained an enigma: O...
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Recommendation under Capacity Constraints
In this paper, we investigate the common scenario where every candidate item for recommendation is characterized by a maximum capacity, i.e., number of seats in a Point-of-Interest (POI) or size of an item's inventory. Despite the prevalence of the task of recommending items under capacity constraints in a variety of...
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Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles
Using deep reinforcement learning, we train control policies for autonomous vehicles leading a platoon of vehicles onto a roundabout. Using Flow, a library for deep reinforcement learning in micro-simulators, we train two policies, one policy with noise injected into the state and action space and one without any inj...
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Relative Singularity Categories
We study the following generalization of singularity categories. Let X be a quasi-projective Gorenstein scheme with isolated singularities and A a non-commutative resolution of singularities of X in the sense of Van den Bergh. We introduce the relative singularity category as the Verdier quotient of the bounded deriv...
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Challenges to Keeping the Computer Industry Centered in the US
It is undeniable that the worldwide computer industry's center is the US, specifically in Silicon Valley. Much of the reason for the success of Silicon Valley had to do with Moore's Law: the observation by Intel co-founder Gordon Moore that the number of transistors on a microchip doubled at a rate of approximately e...
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Contiguous Relations, Laplace's Methods and Continued Fractions for 3F2(1)
Using contiguous relations we construct an infinite number of continued fraction expansions for ratios of generalized hypergeometric series 3F2(1). We establish exact error term estimates for their approximants and prove their rapid convergences. To do so we develop a discrete version of Laplace's method for hypergeo...
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Arimoto-Rényi Conditional Entropy and Bayesian $M$-ary Hypothesis Testing
This paper gives upper and lower bounds on the minimum error probability of Bayesian $M$-ary hypothesis testing in terms of the Arimoto-Rényi conditional entropy of an arbitrary order $\alpha$. The improved tightness of these bounds over their specialized versions with the Shannon conditional entropy ($\alpha=1$) is ...
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A note on the violation of Bell's inequality
With Bell's inequalities one has a formal expression to show how essentially all local theories of natural phenomena that are formulated within the framework of realism may be tested using a simple experimental arrangement. For the case of entangled pairs of spin-1/2 particles we propose an alternative measurement se...
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Real-Time Model Predictive Control for Energy Management in Autonomous Underwater Vehicle
Improving endurance is crucial for extending the spatial and temporal operation range of autonomous underwater vehicles (AUVs). Considering the hardware constraints and the performance requirements, an intelligent energy management system is required to extend the operation range of AUVs. This paper presents a novel ...
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Surjective H-Colouring over Reflexive Digraphs
The Surjective H-Colouring problem is to test if a given graph allows a vertex-surjective homomorphism to a fixed graph H. The complexity of this problem has been well studied for undirected (partially) reflexive graphs. We introduce endo-triviality, the property of a structure that all of its endomorphisms that do n...
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A modal typing system for self-referential programs and specifications
This paper proposes a modal typing system that enables us to handle self-referential formulae, including ones with negative self-references, which on one hand, would introduce a logical contradiction, namely Russell's paradox, in the conventional setting, while on the other hand, are necessary to capture a certain cl...
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Scalable Realistic Recommendation Datasets through Fractal Expansions
Recommender System research suffers currently from a disconnect between the size of academic data sets and the scale of industrial production systems. In order to bridge that gap we propose to generate more massive user/item interaction data sets by expanding pre-existing public data sets. User/item incidence matrice...
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Implementation of a Distributed Coherent Quantum Observer
This paper considers the problem of implementing a previously proposed distributed direct coupling quantum observer for a closed linear quantum system. By modifying the form of the previously proposed observer, the paper proposes a possible experimental implementation of the observer plant system using a non-degenera...
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Stacking and stability
Stacking is a general approach for combining multiple models toward greater predictive accuracy. It has found various application across different domains, ensuing from its meta-learning nature. Our understanding, nevertheless, on how and why stacking works remains intuitive and lacking in theoretical insight. In thi...
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Accelerating Discrete Wavelet Transforms on GPUs
The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques. Until now, several papers compared the performance of such transform on graphics processing units (GPUs). However, all of them only dealt with lifting and convolution computation schemes. In this paper, we...
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Accelerated Consensus via Min-Sum Splitting
We apply the Min-Sum message-passing protocol to solve the consensus problem in distributed optimization. We show that while the ordinary Min-Sum algorithm does not converge, a modified version of it known as Splitting yields convergence to the problem solution. We prove that a proper choice of the tuning parameters ...
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Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models
In the last few years, we have seen the transformative impact of deep learning in many applications, particularly in speech recognition and computer vision. Inspired by Google's Inception-ResNet deep convolutional neural network (CNN) for image classification, we have developed "Chemception", a deep CNN for the predi...
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Constraining the Milky Way assembly history with Galactic Archaeology. Ludwig Biermann Award Lecture 2015
The aim of Galactic Archaeology is to recover the evolutionary history of the Milky Way from its present day kinematical and chemical state. Because stars move away from their birth sites, the current dynamical information alone is not sufficient for this task. The chemical composition of stellar atmospheres, on the ...
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A unified view of entropy-regularized Markov decision processes
We propose a general framework for entropy-regularized average-reward reinforcement learning in Markov decision processes (MDPs). Our approach is based on extending the linear-programming formulation of policy optimization in MDPs to accommodate convex regularization functions. Our key result is showing that using th...
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Arithmetic Circuits for Multilevel Qudits Based on Quantum Fourier Transform
We present some basic integer arithmetic quantum circuits, such as adders and multipliers-accumulators of various forms, as well as diagonal operators, which operate on multilevel qudits. The integers to be processed are represented in an alternative basis after they have been Fourier transformed. Several arithmetic ...
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Quantifying the distribution of editorial power and manuscript decision bias at the mega-journal PLOS ONE
We analyzed the longitudinal activity of nearly 7,000 editors at the mega-journal PLOS ONE over the 10-year period 2006-2015. Using the article-editor associations, we develop editor-specific measures of power, activity, article acceptance time, citation impact, and editorial renumeration (an analogue to self-citatio...
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Threshold Constraints with Guarantees for Parity Objectives in Markov Decision Processes
The beyond worst-case synthesis problem was introduced recently by Bruyère et al. [BFRR14]: it aims at building system controllers that provide strict worst-case performance guarantees against an antagonistic environment while ensuring higher expected performance against a stochastic model of the environment. Our wor...
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GLSR-VAE: Geodesic Latent Space Regularization for Variational AutoEncoder Architectures
VAEs (Variational AutoEncoders) have proved to be powerful in the context of density modeling and have been used in a variety of contexts for creative purposes. In many settings, the data we model possesses continuous attributes that we would like to take into account at generation time. We propose in this paper GLSR...
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Timing Solution and Single-pulse Properties for Eight Rotating Radio Transients
Rotating radio transients (RRATs), loosely defined as objects that are discovered through only their single pulses, are sporadic pulsars that have a wide range of emission properties. For many of them, we must measure their periods and determine timing solutions relying on the timing of their individual pulses, while...
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