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Optimization and Testing in Linear Non-Gaussian Component Analysis
Independent component analysis (ICA) decomposes multivariate data into mutually independent components (ICs). The ICA model is subject to a constraint that at most one of these components is Gaussian, which is required for model identifiability. Linear non-Gaussian component analysis (LNGCA) generalizes the ICA model...
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New Horizons Ring Collision Hazard: Constraints from Earth-based Observations
The New Horizons spacecraft's nominal trajectory crosses the planet's satellite plane at $\sim 10,000\ \rm{km}$ from the barycenter, between the orbits of Pluto and Charon. I have investigated the risk to the spacecraft based on observational limits of rings and dust within this region, assuming various particle size...
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Dependability of Sensor Networks for Industrial Prognostics and Health Management
Maintenance is an important activity in industry. It is performed either to revive a machine/component or to prevent it from breaking down. Different strategies have evolved through time, bringing maintenance to its current state: condition-based and predictive maintenances. This evolution was due to the increasing d...
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On Markov Chain Gradient Descent
Stochastic gradient methods are the workhorse (algorithms) of large-scale optimization problems in machine learning, signal processing, and other computational sciences and engineering. This paper studies Markov chain gradient descent, a variant of stochastic gradient descent where the random samples are taken on the...
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Reduction of Second-Order Network Systems with Structure Preservation
This paper proposes a general framework for structure-preserving model reduction of a secondorder network system based on graph clustering. In this approach, vertex dynamics are captured by the transfer functions from inputs to individual states, and the dissimilarities of vertices are quantified by the H2-norms of t...
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Higher-rank graph algebras are iterated Cuntz-Pimsner algebras
Given a finitely aligned $k$-graph $\Lambda$, we let $\Lambda^i$ denote the $(k-1)$-graph formed by removing all edges of degree $e_i$ from $\Lambda$. We show that the Toeplitz-Cuntz-Krieger algebra of $\Lambda$, denoted by $\mathcal{T}C^*(\Lambda)$, may be realised as the Toeplitz algebra of a Hilbert $\mathcal{T}C^...
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Ultracold Atomic Gases in Artificial Magnetic Fields (PhD thesis)
A phenomenon can hardly be found that accompanied physical paradigms and theoretical concepts in a more reflecting way than magnetism. From the beginnings of metaphysics and the first classical approaches to magnetic poles and streamlines of the field, it has inspired modern physics on its way to the classical field ...
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Stream VByte: Faster Byte-Oriented Integer Compression
Arrays of integers are often compressed in search engines. Though there are many ways to compress integers, we are interested in the popular byte-oriented integer compression techniques (e.g., VByte or Google's Varint-GB). They are appealing due to their simplicity and engineering convenience. Amazon's varint-G8IU is...
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Kondo Signatures of a Quantum Magnetic Impurity in Topological Superconductors
We study the Kondo physics of a quantum magnetic impurity in two-dimensional topological superconductors (TSCs), either intrinsic or induced on the surface of a bulk topological insulator, using a numerical renormalization group technique. We show that, despite sharing the p + ip pairing symmetry, intrinsic and extri...
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Waldschmidt constants for Stanley-Reisner ideals of a class of graphs
In the present note we study Waldschmidt constants of Stanley-Reisner ideals of a hypergraph and a graph with vertices forming a bipyramid over a planar n-gon. The case of the hypergraph has been studied by Bocci and Franci. We reprove their main result. The case of the graph is new. Interestingly, both cases provide...
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FO model checking of geometric graphs
Over the past two decades the main focus of research into first-order (FO) model checking algorithms has been on sparse relational structures - culminating in the FPT algorithm by Grohe, Kreutzer and Siebertz for FO model checking of nowhere dense classes of graphs. On contrary to that, except the case of locally bou...
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Pseudo-linear regression identification based on generalized orthonormal transfer functions: Convergence conditions and bias distribution
In this paper we generalize three identification recursive algorithms belonging to the pseudo-linear class, by introducing a predictor established on a generalized orthonormal function basis. Contrary to the existing identification schemes that use such functions, no constraint on the model poles is imposed. Not only...
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Lower bounds for weak approximation errors for spatial spectral Galerkin approximations of stochastic wave equations
Although for a number of semilinear stochastic wave equations existence and uniqueness results for corresponding solution processes are known from the literature, these solution processes are typically not explicitly known and numerical approximation methods are needed in order for mathematical modelling with stochas...
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Structured low-rank matrix learning: algorithms and applications
We consider the problem of learning a low-rank matrix, constrained to lie in a linear subspace, and introduce a novel factorization for modeling such matrices. A salient feature of the proposed factorization scheme is it decouples the low-rank and the structural constraints onto separate factors. We formulate the opt...
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Greed Works - Online Algorithms For Unrelated Machine Stochastic Scheduling
This paper establishes the first performance guarantees for a combinatorial online algorithm that schedules stochastic, nonpreemptive jobs on unrelated machines to minimize the expected total weighted completion time. Prior work on unrelated machine scheduling with stochastic jobs was restricted to the offline case, ...
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On a combinatorial curvature for surfaces with inversive distance circle packing metrics
In this paper, we introduce a new combinatorial curvature on triangulated surfaces with inversive distance circle packing metrics. Then we prove that this combinatorial curvature has global rigidity. To study the Yamabe problem of the new curvature, we introduce a combinatorial Ricci flow, along which the curvature e...
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Improving End-to-End Speech Recognition with Policy Learning
Connectionist temporal classification (CTC) is widely used for maximum likelihood learning in end-to-end speech recognition models. However, there is usually a disparity between the negative maximum likelihood and the performance metric used in speech recognition, e.g., word error rate (WER). This results in a mismat...
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Better Protocol for XOR Game using Communication Protocol and Nonlocal Boxes
Buhrman showed that an efficient communication protocol implies a reliable XOR game protocol. This idea rederives Linial and Shraibman's lower bounds of communication complexity, which was derived by using factorization norms, with worse constant factor in much more intuitive way. In this work, we improve and general...
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DTN: A Learning Rate Scheme with Convergence Rate of $\mathcal{O}(1/t)$ for SGD
We propose a novel diminishing learning rate scheme, coined Decreasing-Trend-Nature (DTN), which allows us to prove fast convergence of the Stochastic Gradient Descent (SGD) algorithm to a first-order stationary point for smooth general convex and some class of nonconvex including neural network applications for clas...
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Minimax Distribution Estimation in Wasserstein Distance
The Wasserstein metric is an important measure of distance between probability distributions, with applications in machine learning, statistics, probability theory, and data analysis. This paper provides upper and lower bounds on statistical minimax rates for the problem of estimating a probability distribution under...
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Uniformization and Steinness
It is shown that the unit ball in ${\mathbb C}^n$ is the only complex manifold that can universally cover both Stein and non-Stein strictly pseudoconvex domains.
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Recent progress on conditional randomness
In this article, recent progress on ML-randomness with respect to conditional probabilities is reviewed. In particular a new result of conditional randomness with respect to mutually singular probabilities are shown, which is a generalization of Hanssen's result (2010) for Bernoulli processes.
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The evolution of red supergiants to supernovae
With red supergiants (RSGs) predicted to end their lives as Type IIP core collapse supernova (CCSN), their behaviour before explosion needs to be fully understood. Mass loss rates govern RSG evolution towards SN and have strong implications on the appearance of the resulting explosion. To study how the mass-loss rate...
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Conformally invariant elliptic Liouville equation and its symmetry preserving discretization
The symmetry algebra of the real elliptic Liouville equation is an infinite-dimensional loop algebra with the simple Lie algebra $o(3,1)$ as its maximal finite-dimensional subalgebra. The entire algebra generates the conformal group of the Euclidean plane $E_2$. This infinite-dimensional algebra distinguishes the ell...
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Discrete diffusion Lyman-alpha radiative transfer
Due to its accuracy and generality, Monte Carlo radiative transfer (MCRT) has emerged as the prevalent method for Ly$\alpha$ radiative transfer in arbitrary geometries. The standard MCRT encounters a significant efficiency barrier in the high optical depth, diffusion regime. Multiple acceleration schemes have been de...
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Kosterlitz-Thouless transition and vortex-antivortex lattice melting in two-dimensional Fermi gases with $p$- or $d$-wave pairing
We present a theoretical study of the finite-temperature Kosterlitz-Thouless (KT) and vortex-antivortex lattice (VAL) melting transitions in two-dimensional Fermi gases with $p$- or $d$-wave pairing. For both pairings, when the interaction is tuned from weak to strong attractions, we observe a quantum phase transitio...
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Chiral Optical Tamm States: Temporal Coupled-Mode Theory
The chiral optical Tamm state (COTS) is a special localized state at the interface of a handedness-preserving mirror and a structurally chiral medium such as a cholesteric liquid crystal or a chiral sculptured thin film. The spectral behavior of COTS, observed as reflection resonances, is described by the temporal co...
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Functional inequalities for Fox-Wright functions
In this paper, our aim is to show some mean value inequalities for the Fox-Wright functions, such as Turán--type inequalities, Lazarević and Wilker--type inequalities. As applications we derive some new type inequalities for hypergeometric functions and the four--parametric Mittag--Leffler functions. Furthermore, we ...
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Collaboration Spheres: a Visual Metaphor to Share and Reuse Research Objects
Research Objects (ROs) are semantically enhanced aggregations of resources associated to scientific experiments, such as data, provenance of these data, the scientific workflow used to run the experiment, intermediate results, logs and the interpretation of the results. As the number of ROs increases, it is becoming ...
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Intelligent flat-and-textureless object manipulation in Service Robots
This work introduces our approach to the flat and textureless object grasping problem. In particular, we address the tableware and cutlery manipulation problem where a service robot has to clean up a table. Our solution integrates colour and 2D and 3D geometry information to describe objects, and this information is ...
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Constraints on the Intergalactic Magnetic Field from Bow Ties in the Gamma-ray Sky
Pair creation on the cosmic infrared background and subsequent inverse-Compton scattering on the CMB potentially reprocesses the TeV emission of blazars into faint GeV halos with structures sensitive to intergalactic magnetic fields (IGMF). We attempt to detect such halos exploiting their highly anisotropic shape. Th...
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Learning Deep Representations with Probabilistic Knowledge Transfer
Knowledge Transfer (KT) techniques tackle the problem of transferring the knowledge from a large and complex neural network into a smaller and faster one. However, existing KT methods are tailored towards classification tasks and they cannot be used efficiently for other representation learning tasks. In this paper a...
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Pluricanonical Periods over Compact Riemann Surfaces of Genus at least 2
This article is an attempt to generalize Riemann's bilinear relations on compact Riemann surface of genus at least 2, which may lead to new structures in the theory of hyperbolic Riemann surfaces. No significant result is obtained, the article serves to bring the readers' attention to the observation made by [Bol-194...
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Stochastic Gradient Descent: Going As Fast As Possible But Not Faster
When applied to training deep neural networks, stochastic gradient descent (SGD) often incurs steady progression phases, interrupted by catastrophic episodes in which loss and gradient norm explode. A possible mitigation of such events is to slow down the learning process. This paper presents a novel approach to cont...
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Stacked Convolutional and Recurrent Neural Networks for Bird Audio Detection
This paper studies the detection of bird calls in audio segments using stacked convolutional and recurrent neural networks. Data augmentation by blocks mixing and domain adaptation using a novel method of test mixing are proposed and evaluated in regard to making the method robust to unseen data. The contributions of...
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Gibbs posterior convergence and the thermodynamic formalism
In this paper we consider a Bayesian framework for making inferences about dynamical systems from ergodic observations. The proposed Bayesian procedure is based on the Gibbs posterior, a decision theoretic generalization of standard Bayesian inference. We place a prior over a model class consisting of a parametrized ...
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Retrieval Analysis of the Emission Spectrum of WASP-12b: Sensitivity of Outcomes to Prior Assumptions and Implications for Formation History
We analyze the emission spectrum of the hot Jupiter WASP-12b using our HELIOS-R retrieval code and HELIOS-K opacity calculator. When interpreting Hubble and Spitzer data, the retrieval outcomes are found to be prior-dominated. When the prior distributions of the molecular abundances are assumed to be log-uniform, the...
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Model Learning for Look-ahead Exploration in Continuous Control
We propose an exploration method that incorporates look-ahead search over basic learnt skills and their dynamics, and use it for reinforcement learning (RL) of manipulation policies . Our skills are multi-goal policies learned in isolation in simpler environments using existing multigoal RL formulations, analogous to...
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Efficient and Scalable View Generation from a Single Image using Fully Convolutional Networks
Single-image-based view generation (SIVG) is important for producing 3D stereoscopic content. Here, handling different spatial resolutions as input and optimizing both reconstruction accuracy and processing speed is desirable. Latest approaches are based on convolutional neural network (CNN), and they generate promis...
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An Empirical Analysis of Approximation Algorithms for the Euclidean Traveling Salesman Problem
With applications to many disciplines, the traveling salesman problem (TSP) is a classical computer science optimization problem with applications to industrial engineering, theoretical computer science, bioinformatics, and several other disciplines. In recent years, there have been a plethora of novel approaches for...
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Dynamical compensation and structural identifiability: analysis, implications, and reconciliation
The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. Here we show that, according to its original definition, dynamical compensation is equivalent to lack of structural identifiability...
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Characterization of the beam from the RFQ of the PIP-II Injector Test
A 2.1 MeV, 10 mA CW RFQ has been installed and commissioned at Fermilab's test accelerator known as PIP-II Injector Test. This report describes the measurements of the beam properties after acceleration in the RFQ, including the energy and emittance.
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Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy
Softmax is a standard final layer used in Neural Nets (NNs) to summarize information encoded in the trained NN and return a prediction. However, Softmax leverages only a subset of the class-specific structure encoded in the trained model and ignores potentially valuable information: During training, models encode an ...
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Generalized Stieltjes constants and integrals involving the log-log function: Kummer's Theorem in action
In this note, we recall Kummer's Fourier series expansion of the 1-periodic function that coincides with the logarithm of the Gamma function on the unit interval $(0,1)$, and we use it to find closed forms for some numerical series related to the generalized Stieltjes constants, and some integrals involving the funct...
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On the Combinatorial Lower Bound for the Extension Complexity of 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 the trival (dimension) bound, $\Omega(n^2)$, the be...
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An Introduction to Classic DEVS
DEVS is a popular formalism for modelling complex dynamic systems using a discrete-event abstraction. At this abstraction level, a timed sequence ofpertinent "events" input to a system (or internal, in the case of timeouts) cause instantaneous changes to the state of the system. Between events, the state does not cha...
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Nanoscale Solid State Batteries Enabled By Thermal Atomic Layer Deposition of a Lithium Polyphosphazene Solid State Electrolyte
Several active areas of research in novel energy storage technologies, including three-dimensional solid state batteries and passivation coatings for reactive battery electrode components, require conformal solid state electrolytes. We describe an atomic layer deposition (ALD) process for a member of the lithium phos...
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Classification of crystallization outcomes using deep convolutional neural networks
The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups. Here, state-of-the-art machine learning algorithms are trained and tested on different parts of this data set. We ...
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Private Information, Credit Risk and Graph Structure in P2P Lending Networks
This research investigated the potential for improving Peer-to-Peer (P2P) credit scoring by using "private information" about communications and travels of borrowers. We found that P2P borrowers' ego networks exhibit scale-free behavior driven by underlying preferential attachment mechanisms that connect borrowers in...
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Nonmonotonous classical magneto-conductivity of a two-dimensional electron gas in a disordered array of obstacles
Magnetotransport measurements in combination with molecular dynamics (MD) simulations on two-dimensional disordered Lorentz gases in the classical regime are reported. In quantitative agreement between experiment and simulation, the magnetoconductivity displays a pronounced peak as a function of perpendicular magneti...
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Pushing STEM-education through a social-media-based contest format - experiences and lessons-learned from the H2020-project SciChallenge
Science education is a crucial issue with long-term impacts for Europe as the low enrolment rates in the STEM-fields, including (natural) science, technology, engineering and mathematics, will lead to a workforce problem in research and development. In order to address this challenge, the EU-funded research project S...
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Hidden area and mechanical nonlinearities in freestanding graphene
We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By c...
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Solving Partial Differential Equations on Manifolds From Incomplete Inter-Point Distance
Solutions of partial differential equations (PDEs) on manifolds have provided important applications in different fields in science and engineering. Existing methods are majorly based on discretization of manifolds as implicit functions, triangle meshes, or point clouds, where the manifold structure is approximated b...
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Zonal Flow Magnetic Field Interaction in the Semi-Conducting Region of Giant Planets
All four giant planets in the Solar System feature zonal flows on the order of 100 m/s in the cloud deck, and large-scale intrinsic magnetic fields on the order of 1 Gauss near the surface. The vertical structure of the zonal flows remains obscure. The end-member scenarios are shallow flows confined in the radiative ...
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Superpixel-based Semantic Segmentation Trained by Statistical Process Control
Semantic segmentation, like other fields of computer vision, has seen a remarkable performance advance by the use of deep convolution neural networks. However, considering that neighboring pixels are heavily dependent on each other, both learning and testing of these methods have a lot of redundant operations. To res...
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Photometric Stereo by Hemispherical Metric Embedding
Photometric Stereo methods seek to reconstruct the 3d shape of an object from motionless images obtained with varying illumination. Most existing methods solve a restricted problem where the physical reflectance model, such as Lambertian reflectance, is known in advance. In contrast, we do not restrict ourselves to a...
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Time Reversal, SU(N) Yang-Mills and Cobordisms: Interacting Topological Superconductors/Insulators and Quantum Spin Liquids in 3+1D
We introduce a web of strongly correlated interacting 3+1D topological superconductors/insulators of 10 particular global symmetry groups of Cartan classes, realizable in electronic condensed matter systems, and their new SU(N) generalizations. The symmetries include SU(N), SU(2), U(1), fermion parity, time reversal ...
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Forest-based methods and ensemble model output statistics for rainfall ensemble forecasting
Rainfall ensemble forecasts have to be skillful for both low precipitation and extreme events. We present statistical post-processing methods based on Quantile Regression Forests (QRF) and Gradient Forests (GF) with a parametric extension for heavy-tailed distributions. Our goal is to improve ensemble quality for all...
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Non interactive simulation of correlated distributions is decidable
A basic problem in information theory is the following: Let $\mathbf{P} = (\mathbf{X}, \mathbf{Y})$ be an arbitrary distribution where the marginals $\mathbf{X}$ and $\mathbf{Y}$ are (potentially) correlated. Let Alice and Bob be two players where Alice gets samples $\{x_i\}_{i \ge 1}$ and Bob gets samples $\{y_i\}_{...
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Effective Completeness for S4.3.1-Theories with Respect to Discrete Linear Models
The computable model theory of modal logic was initiated by Suman Ganguli and Anil Nerode in [4]. They use an effective Henkin-type construction to effectivize various completeness theorems from classical modal logic. This construction has the feature of only producing models whose frames can be obtained by adding ed...
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DeepTingle
DeepTingle is a text prediction and classification system trained on the collected works of the renowned fantastic gay erotica author Chuck Tingle. Whereas the writing assistance tools you use everyday (in the form of predictive text, translation, grammar checking and so on) are trained on generic, purportedly "neutr...
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Degrees of Freedom in Cached MIMO Relay Networks With Multiple Base Stations
The ability of physical layer relay caching to increase the degrees of freedom (DoF) of a single cell was recently illustrated. In this paper, we extend this result to the case of multiple cells in which a caching relay is shared among multiple non-cooperative base stations (BSs). In particular, we show that a large ...
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A perturbation theory for water with an associating reference fluid
The theoretical description of the thermodynamics of water is challenged by the structural transition towards tetrahedral symmetry at ambient conditions. As perturbation theories typically assume a spherically symmetric reference fluid, they are incapable of accurately describing the liquid properties of water at amb...
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Finite Sample Complexity of Sequential Monte Carlo Estimators
We present bounds for the finite sample error of sequential Monte Carlo samplers on static spaces. Our approach explicitly relates the performance of the algorithm to properties of the chosen sequence of distributions and mixing properties of the associated Markov kernels. This allows us to give the first finite samp...
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Reduced chemistry for butanol isomers at engine-relevant conditions
Butanol has received significant research attention as a second-generation biofuel in the past few years. In the present study, skeletal mechanisms for four butanol isomers were generated from two widely accepted, well-validated detailed chemical kinetic models for the butanol isomers. The detailed models were reduce...
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A Measure of Dependence Between Discrete and Continuous Variables
Mutual Information (MI) is an useful tool for the recognition of mutual dependence berween data sets. Differen methods for the estimation of MI have been developed when both data sets are discrete or when both data sets are continuous. The MI estimation between a discrete data set and a continuous data set has not re...
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Stein Variational Online Changepoint Detection with Applications to Hawkes Processes and Neural Networks
Bayesian online changepoint detection (BOCPD) (Adams & MacKay, 2007) offers a rigorous and viable way to identity changepoints in complex systems. In this work, we introduce a Stein variational online changepoint detection (SVOCD) method to provide a computationally tractable generalization of BOCPD beyond the expone...
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Quantum Teleportation and Super-dense Coding in Operator Algebras
Let $\mathcal{B}_d$ be the unital $C^*$-algebra generated by the elements $u_{jk}, \, 0 \le i, j \le d-1$, satisfying the relations that $[u_{j,k}]$ is a unitary operator, and let $C^*(\mathbb{F}_{d^2})$ be the full group $C^*$-algebra of free group of $d^2$ generators. Based on the idea of teleportation and super-de...
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A Practical Randomized CP Tensor Decomposition
The CANDECOMP/PARAFAC (CP) decomposition is a leading method for the analysis of multiway data. The standard alternating least squares algorithm for the CP decomposition (CP-ALS) involves a series of highly overdetermined linear least squares problems. We extend randomized least squares methods to tensors and show th...
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Two dimensional potential flow around a rectangular pole solved by a multiple linear regression
A potential flow around a circular cylinder is a commonly examined problem in an introductory physics class. We pose a similar problem but with different boundary conditions where a rectangular pole replaces a circular cylinder. We demonstrate to solve the problem by deriving a general solution for the flow in the fo...
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Fixed Price Approximability of the Optimal Gain From Trade
Bilateral trade is a fundamental economic scenario comprising a strategically acting buyer and seller, each holding valuations for the item, drawn from publicly known distributions. A mechanism is supposed to facilitate trade between these agents, if such trade is beneficial. It was recently shown that the only mecha...
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$^{139}$La and $^{63}$Cu NMR investigation of charge order in La$_{2}$CuO$_{4+y}$ ($T_{c}=42$K)
We report $^{139}$La and $^{63}$Cu NMR investigation of the successive charge order, spin order, and superconducting transitions in super-oxygenated La$_2$CuO$_{4+y}$ single crystal with stage-4 excess oxygen order at $T_{stage}\simeq 290$ K. We show that the stage-4 order induces tilting of CuO$_6$ octahedra below $...
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An Exploratory Study of Field Failures
Field failures, that is, failures caused by faults that escape the testing phase leading to failures in the field, are unavoidable. Improving verification and validation activities before deployment can identify and timely remove many but not all faults, and users may still experience a number of annoying problems wh...
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Crowdsourcing Predictors of Residential Electric Energy Usage
Crowdsourcing has been successfully applied in many domains including astronomy, cryptography and biology. In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd can contribute predictive hypotheses to a model of residential electric energy c...
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One-dimensional fluids with positive potentials
We study a class of one-dimensional classical fluids with penetrable particles interacting through positive, purely repulsive, pair-potentials. Starting from some lower bounds to the total potential energy, we draw results on the thermodynamic limit of the given model.
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Recovery of Sparse and Low Rank Components of Matrices Using Iterative Method with Adaptive Thresholding
In this letter, we propose an algorithm for recovery of sparse and low rank components of matrices using an iterative method with adaptive thresholding. In each iteration, the low rank and sparse components are obtained using a thresholding operator. This algorithm is fast and can be implemented easily. We compare it...
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Reduced Order Modelling for the Simulation of Quenches in Superconducting Magnets
This contributions discusses the simulation of magnetothermal effects in superconducting magnets as used in particle accelerators. An iterative coupling scheme using reduced order models between a magnetothermal partial differential model and an electrical lumped-element circuit is demonstrated. The multiphysics, mul...
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Life in the "Matrix": Human Mobility Patterns in the Cyber Space
With the wide adoption of the multi-community setting in many popular social media platforms, the increasing user engagements across multiple online communities warrant research attention. In this paper, we introduce a novel analogy between the movements in the cyber space and the physical space. This analogy implies...
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A Novel Subclass of Univalent Functions Involving Operators of Fractional Calculus
In this paper, we introduce and investigate a novel class of analytic and univalent functions of negative coefficients in the open unit disk. For this function class, we obtain characterization and distortion theorems as well as the radii of close-to-convexity, starlikeness and convexity by using fractional calculus ...
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Local bandwidth selection for kernel density estimation in bifurcating Markov chain model
We propose an adaptive estimator for the stationary distribution of a bifurcating Markov Chain on $\mathbb R^d$. Bifurcating Markov chains (BMC for short) are a class of stochastic processes indexed by regular binary trees. A kernel estimator is proposed whose bandwidth is selected by a method inspired by the works o...
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Sparse geometries handling in lattice-Boltzmann method implementation for graphic processors
We describe a high-performance implementation of the lattice-Boltzmann method (LBM) for sparse geometries on graphic processors. In our implementation we cover the whole geometry with a uniform mesh of small tiles and carry out calculations for each tile independently with a proper data synchronization at tile edges....
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From Multimodal to Unimodal Webpages for Developing Countries
The multimodal web elements such as text and images are associated with inherent memory costs to store and transfer over the Internet. With the limited network connectivity in developing countries, webpage rendering gets delayed in the presence of high-memory demanding elements such as images (relative to text). To o...
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Light curves of hydrogen-poor Superluminous Supernovae from the Palomar Transient Factory
We investigate the light-curve properties of a sample of 26 spectroscopically confirmed hydrogen-poor superluminous supernovae (SLSNe-I) in the Palomar Transient Factory (PTF) survey. These events are brighter than SNe Ib/c and SNe Ic-BL, on average, by about 4 and 2~mag, respectively. The peak absolute magnitudes of...
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Sharing Means Renting?: An Entire-marketplace Analysis of Airbnb
Airbnb, an online marketplace for accommodations, has experienced a staggering growth accompanied by intense debates and scattered regulations around the world. Current discourses, however, are largely focused on opinions rather than empirical evidences. Here, we aim to bridge this gap by presenting the first large-s...
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What Happens - After the First Race? Enhancing the Predictive Power of Happens - Before Based Dynamic Race Detection
Dynamic race detection is the problem of determining if an observed program execution reveals the presence of a data race in a program. The classical approach to solving this problem is to detect if there is a pair of conflicting memory accesses that are unordered by Lamport's happens-before (HB) relation. HB based r...
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Proceedings of the Workshop on Data Mining for Oil and Gas
The process of exploring and exploiting Oil and Gas (O&G) generates a lot of data that can bring more efficiency to the industry. The opportunities for using data mining techniques in the "digital oil-field" remain largely unexplored or uncharted. With the high rate of data expansion, companies are scrambling to deve...
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Chiral magnetic effect of light
We study a photonic analog of the chiral magnetic (vortical) effect. We discuss that the vector component of magnetoelectric tensors plays a role of "vector potential," and its rotation is understood as "magnetic field" of a light. Using the geometrical optics approximation, we show that "magnetic fields" cause an an...
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New Pressure-Induced Polymorphic Transitions of Anhydrous Magnesium Sulfate
The effects of pressure on the crystal structure of the three known polymorphs of magnesium sulfate have been theoretically study by means of DFT calculations up to 45 GPa. We determined that at ambient conditions gamma MgSO4 is an unstable polymorph, which decompose into MgO and SO3, and that the response of the oth...
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Optimal transport and integer partitions
We link the theory of optimal transportation to the theory of integer partitions. Let $\mathscr P(n)$ denote the set of integer partitions of $n \in \mathbb N$ and write partitions $\pi \in \mathscr P(n)$ as $(n_1, \dots, n_{k(\pi)})$. Using terminology from optimal transport, we characterize certain classes of parti...
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An Automated Auto-encoder Correlation-based Health-Monitoring and Prognostic Method for Machine Bearings
This paper studies an intelligent ultimate technique for health-monitoring and prognostic of common rotary machine components, particularly bearings. During a run-to-failure experiment, rich unsupervised features from vibration sensory data are extracted by a trained sparse auto-encoder. Then, the correlation of the ...
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Temporal Type Theory: A topos-theoretic approach to systems and behavior
This book introduces a temporal type theory, the first of its kind as far as we know. It is based on a standard core, and as such it can be formalized in a proof assistant such as Coq or Lean by adding a number of axioms. Well-known temporal logics---such as Linear and Metric Temporal Logic (LTL and MTL)---embed with...
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On Poletsky theory of discs in compact manifolds
We provide a direct construction of Poletsky discs via local arc approximation and a Runge-type theorem by A. Gournay.
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Continuous DR-submodular Maximization: Structure and Algorithms
DR-submodular continuous functions are important objectives with wide real-world applications spanning MAP inference in determinantal point processes (DPPs), and mean-field inference for probabilistic submodular models, amongst others. DR-submodularity captures a subclass of non-convex functions that enables both exa...
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A Structural Characterization for Certifying Robinsonian Matrices
A symmetric matrix is Robinsonian if its rows and columns can be simultaneously reordered in such a way that entries are monotone nondecreasing in rows and columns when moving toward the diagonal. The adjacency matrix of a graph is Robinsonian precisely when the graph is a unit interval graph, so that Robinsonian mat...
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A new scenario for gravity detection in plants: the position sensor hypothesis
The detection of gravity plays a fundamental role during the growth and evolution of plants. Although progress has been made in our understanding of the molecular, cellular and physical mechanisms involved in the gravity detection, a coherent scenario consistent with all the observations is still lacking. In this per...
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Techniques for proving Asynchronous Convergence results for Markov Chain Monte Carlo methods
Markov Chain Monte Carlo (MCMC) methods such as Gibbs sampling are finding widespread use in applied statistics and machine learning. These often lead to difficult computational problems, which are increasingly being solved on parallel and distributed systems such as compute clusters. Recent work has proposed running...
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Predicting Hurricane Trajectories using a Recurrent Neural Network
Hurricanes are cyclones circulating about a defined center whose closed wind speeds exceed 75 mph originating over tropical and subtropical waters. At landfall, hurricanes can result in severe disasters. The accuracy of predicting their trajectory paths is critical to reduce economic loss and save human lives. Given ...
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HJB equations in infinite dimension and optimal control of stochastic evolution equations via generalized Fukushima decomposition
A stochastic optimal control problem driven by an abstract evolution equation in a separable Hilbert space is considered. Thanks to the identification of the mild solution of the state equation as $\nu$-weak Dirichlet process, the value processes is proved to be a real weak Dirichlet process. The uniqueness of the co...
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Developing a Method to Determine Electrical Conductivity in Meteoritic Materials with Applications to Induction Heating Theory (2008 Student Thesis)
Magnetic induction was first proposed as a planetary heating mechanism by Sonett and Colburn in 1968, in recent years this theory has lost favor as a plausible source of heating in the early solar system. However, new models of proto-planetary disk evolution suggest that magnetic fields play an important role in sola...
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A KiDS weak lensing analysis of assembly bias in GAMA galaxy groups
We investigate possible signatures of halo assembly bias for spectroscopically selected galaxy groups from the GAMA survey using weak lensing measurements from the spatially overlapping regions of the deeper, high-imaging-quality photometric KiDS survey. We use GAMA groups with an apparent richness larger than 4 to i...
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