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Genetic Algorithms for Mentor-Assisted Evaluation Function Optimization
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function's parameters for computer chess. Our results show that using an appropriate mentor, we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Ches...
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Universal Constraints on the Location of Extrema of Eigenfunctions of Non-Local Schrödinger Operators
We derive a lower bound on the location of global extrema of eigenfunctions for a large class of non-local Schrödinger operators in convex domains under Dirichlet exterior conditions, featuring the symbol of the kinetic term, the strength of the potential, and the corresponding eigenvalue, and involving a new univers...
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InScript: Narrative texts annotated with script information
This paper presents the InScript corpus (Narrative Texts Instantiating Script structure). InScript is a corpus of 1,000 stories centered around 10 different scenarios. Verbs and noun phrases are annotated with event and participant types, respectively. Additionally, the text is annotated with coreference information....
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Semimetallic and charge-ordered $α$-(BEDT-TTF)$_2$I$_3$: on the role of disorder in dc transport and dielectric properties
$\alpha$-(BEDT-TTF)$_2$I$_3$ is a prominent example of charge ordering among organic conductors. In this work we explore the details of transport within the charge-ordered as well as semimetallic phase at ambient pressure. In the high-temperature semimetallic phase, the mobilities and concentrations of both electrons...
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Robust Photometric Stereo Using Learned Image and Gradient Dictionaries
Photometric stereo is a method for estimating the normal vectors of an object from images of the object under varying lighting conditions. Motivated by several recent works that extend photometric stereo to more general objects and lighting conditions, we study a new robust approach to photometric stereo that utilize...
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Toward Low-Flying Autonomous MAV Trail Navigation using Deep Neural Networks for Environmental Awareness
We present a micro aerial vehicle (MAV) system, built with inexpensive off-the-shelf hardware, for autonomously following trails in unstructured, outdoor environments such as forests. The system introduces a deep neural network (DNN) called TrailNet for estimating the view orientation and lateral offset of the MAV wi...
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Origin of Charge Separation at Organic Photovoltaic Heterojunctions: A Mesoscale Quantum Mechanical View
The high efficiency of charge generation within organic photovoltaic blends apparently contrasts with the strong "classical" attraction between newly formed electron-hole pairs. Several factors have been identified as possible facilitators of charge dissociation, such as quantum mechanical coherence and delocalizatio...
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Spectral Decimation for Families of Self-Similar Symmetric Laplacians on the Sierpinski Gasket
We construct a one-parameter family of Laplacians on the Sierpinski Gasket that are symmetric and self-similar for the 9-map iterated function system obtained by iterating the standard 3-map iterated function system. Our main result is the fact that all these Laplacians satisfy a version of spectral decimation that b...
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Identification of multi-object dynamical systems: consistency and Fisher information
Learning the model parameters of a multi-object dynamical system from partial and perturbed observations is a challenging task. Despite recent numerical advancements in learning these parameters, theoretical guarantees are extremely scarce. In this article, we study the identifiability of these parameters and the con...
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Elliptic curves maximal over extensions of finite base fields
Given an elliptic curve $E$ over a finite field $\mathbb{F}_q$ we study the finite extensions $\mathbb{F}_{q^n}$ of $\mathbb{F}_q$ such that the number of $\mathbb{F}_{q^n}$-rational points on $E$ attains the Hasse upper bound. We obtain an upper bound on the degree $n$ for $E$ ordinary using an estimate for linear f...
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CURE: Curvature Regularization For Missing Data Recovery
Missing data recovery is an important and yet challenging problem in imaging and data science. Successful models often adopt certain carefully chosen regularization. Recently, the low dimension manifold model (LDMM) was introduced by S.Osher et al. and shown effective in image inpainting. They observed that enforcing...
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Nonlinear parametric excitation effect induces stability transitions in swimming direction of flexible superparamagnetic microswimmers
Microscopic artificial swimmers have recently become highly attractive due to their promising potential for biomedical applications. The pioneering work of Dreyfus et al (2005) has demonstrated the motion of a microswimmer with an undulating chain of superparamagnetic beads, which is actuated by an oscillating extern...
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$L^p$ Mapping Properties for the Cauchy-Riemann Equations on Lipschitz Domains Admitting Subelliptic Estimates
We show that on bounded Lipschitz pseudoconvex domains that admit good weight functions the $\overline{\partial}$-Neumann operators $N_q, \overline{\partial}^* N_{q}$, and $\overline{\partial} N_{q}$ are bounded on $L^p$ spaces for some values of $p$ greater than 2.
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Fast dose optimization for rotating shield brachytherapy
Purpose: To provide a fast computational method, based on the proximal graph solver (POGS) - a convex optimization solver using the alternating direction method of multipliers (ADMM), for calculating an optimal treatment plan in rotating shield brachytherapy (RSBT). RSBT treatment planning has more degrees of freedom...
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3D Modeling of Electric Fields in the LUX Detector
This work details the development of a three-dimensional (3D) electric field model for the LUX detector. The detector took data during two periods of searching for weakly interacting massive particle (WIMP) searches. After the first period completed, a time-varying non-uniform negative charge developed in the polytet...
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Optimal Communication Strategies in Networked Cyber-Physical Systems with Adversarial Elements
This paper studies optimal communication and coordination strategies in cyber-physical systems for both defender and attacker within a game-theoretic framework. We model the communication network of a cyber-physical system as a sensor network which involves one single Gaussian source observed by many sensors, subject...
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First- and Second-Order Models of Recursive Arithmetics
We study a quadruple of interrelated subexponential subsystems of arithmetic WKL$_0^-$, RCA$^-_0$, I$\Delta_0$, and $\Delta$RA$_1$, which complement the similarly related quadruple WKL$_0$, RCA$_0$, I$\Sigma_1$, and PRA studied by Simpson, and the quadruple WKL$_0^\ast$, RCA$_0^\ast$, I$\Delta_0$(exp), and EFA studie...
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Land Cover Classification via Multi-temporal Spatial Data by Recurrent Neural Networks
Nowadays, modern earth observation programs produce huge volumes of satellite images time series (SITS) that can be useful to monitor geographical areas through time. How to efficiently analyze such kind of information is still an open question in the remote sensing field. Recently, deep learning methods proved suita...
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Disentangling by Factorising
We define and address the problem of unsupervised learning of disentangled representations on data generated from independent factors of variation. We propose FactorVAE, a method that disentangles by encouraging the distribution of representations to be factorial and hence independent across the dimensions. We show t...
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Symmetries and synchronization in multilayer random networks
In the light of the recently proposed scenario of asymmetry-induced synchronization (AISync), in which dynamical uniformity and consensus in a distributed system would demand certain asymmetries in the underlying network, we investigate here the influence of some regularities in the interlayer connection patterns on ...
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Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation
As part of autonomous car driving systems, semantic segmentation is an essential component to obtain a full understanding of the car's environment. One difficulty, that occurs while training neural networks for this purpose, is class imbalance of training data. Consequently, a neural network trained on unbalanced dat...
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Muchnik degrees and cardinal characteristics
We provide a pair of dual results, each stating the coincidence of highness properties from computability theory. We provide an analogous pair of dual results on the coincidence of cardinal characteristics within ZFC. A mass problem is a set of functions on $\omega$. For mass problems $\mathcal C, \mathcal D$, one sa...
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Existence of solutions for a semirelativistic Hartree equation with unbounded potentials
We prove the existence of a solution to the semirelativistic Hartree equation $$\sqrt{-\Delta+m^2}u+ V(x) u = A(x)\left( W * |u|^p \right) |u|^{p-2}u $$ under suitable growth assumption on the potential functions $V$ and $A$. In particular, both can be unbounded from above.
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Lattice Operations on Terms over Similar Signatures
Unification and generalization are operations on two terms computing respectively their greatest lower bound and least upper bound when the terms are quasi-ordered by subsumption up to variable renaming (i.e., $t_1\preceq t_2$ iff $t_1 = t_2\sigma$ for some variable substitution $\sigma$). When term signatures are su...
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Towards Physically Safe Reinforcement Learning under Supervision
This paper addresses the question of how a previously available control policy $\pi_s$ can be used as a supervisor to more quickly and safely train a new learned control policy $\pi_L$ for a robot. A weighted average of the supervisor and learned policies is used during trials, with a heavier weight initially on the ...
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Complex Valued Risk Diversification
Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some constrains including expected returns. We propose a portfolio construction method that incorporates the complex valued principal component an...
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An Overview on Application of Machine Learning Techniques in Optical Networks
Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information fro...
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Study of Minor Actinides Transmutation in PWR MOX fuel
The management of long-lived radionuclides in spent fuel is a key issue to achieve the closed nuclear fuel cycle and the sustainable development of nuclear energy. Partitioning-Transmutation is supposed to be an efficient method to treat the long-lived radionuclides in spent fuel. Some Minor Actinides (MAs) have very...
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Undesired parking spaces and contractible pieces of the noncrossing partition link
There are two natural simplicial complexes associated to the noncrossing partition lattice: the order complex of the full lattice and the order complex of the lattice with its bounding elements removed. The latter is a complex that we call the noncrossing partition link because it is the link of an edge in the former...
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Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization
Due to their simplicity and excellent performance, parallel asynchronous variants of stochastic gradient descent have become popular methods to solve a wide range of large-scale optimization problems on multi-core architectures. Yet, despite their practical success, support for nonsmooth objectives is still lacking, ...
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Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems
We consider the inverse problem of recovering an unknown functional parameter $u$ in a separable Banach space, from a noisy observation $y$ of its image through a known possibly non-linear ill-posed map ${\mathcal G}$. The data $y$ is finite-dimensional and the noise is Gaussian. We adopt a Bayesian approach to the p...
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Non-LTE line formation of Fe in late-type stars IV: Modelling of the solar centre-to-limb variation in 3D
Our ability to model the shapes and strengths of iron lines in the solar spectrum is a critical test of the accuracy of the solar iron abundance, which sets the absolute zero-point of all stellar metallicities. We use an extensive 463-level Fe atom with new photoionisation cross-sections for FeI as well as quantum me...
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Transmission clusters in the HIV-1 epidemic among men who have sex with men in Montreal, Quebec, Canada
Background. Several studies have used phylogenetics to investigate Human Immunodeficiency Virus (HIV) transmission among Men who have Sex with Men (MSMs) in Montreal, Quebec, Canada, revealing many transmission clusters. The Quebec HIV genotyping program sequence database now includes viral sequences from close to 4,...
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Conformal blocks attached to twisted groups
The aim of this paper is to generalize the notion of conformal blocks to the situation in which the Lie algebra they are attached to is not defined over a field, but depends on covering data of curves. The result will be a sheaf of conformal blocks on the Hurwitz stack parametrizing Galois coverings of curves. Many f...
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Statistical study on propagation characteristics of Omega signals (VLF) in magnetosphere detected by the Akebono satellite
This paper shows a statistical analysis of 10.2 kHz Omega broadcasts of an artificial signal broadcast from ground stations, propagated in the plasmasphere, and detected using an automatic detection method we developed. We study the propagation patterns of the Omega signals to understand the propagation characteristi...
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Thermally induced stresses in boulders on airless body surfaces, and implications for rock breakdown
This work investigates the macroscopic thermomechanical behavior of lunar boulders by modeling their response to diurnal thermal forcing. Our results reveal a bimodal, spatiotemporally-complex stress response. During sunrise, stresses occur in the boulders' interiors that are associated with large-scale temperature g...
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Some observations about generalized quantifiers in logics of imperfect information
We analyze the definitions of generalized quantifiers of imperfect information that have been proposed by F.Engström. We argue that these definitions are just embeddings of the first-order generalized quantifiers into team semantics, and fail to capture an adequate notion of team-theoretical generalized quantifier, s...
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Predicting Demographics of High-Resolution Geographies with Geotagged Tweets
In this paper, we consider the problem of predicting demographics of geographic units given geotagged Tweets that are composed within these units. Traditional survey methods that offer demographics estimates are usually limited in terms of geographic resolution, geographic boundaries, and time intervals. Thus, it wou...
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Text Compression for Sentiment Analysis via Evolutionary Algorithms
Can textual data be compressed intelligently without losing accuracy in evaluating sentiment? In this study, we propose a novel evolutionary compression algorithm, PARSEC (PARts-of-Speech for sEntiment Compression), which makes use of Parts-of-Speech tags to compress text in a way that sacrifices minimal classificati...
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Training large margin host-pathogen protein-protein interaction predictors
Detection of protein-protein interactions (PPIs) plays a vital role in molecular biology. Particularly, infections are caused by the interactions of host and pathogen proteins. It is important to identify host-pathogen interactions (HPIs) to discover new drugs to counter infectious diseases. Conventional wet lab PPI ...
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A Useful Solution of the Coupon Collector's Problem
The Coupon Collector's Problem is one of the few mathematical problems that make news headlines regularly. The reasons for this are on one hand the immense popularity of soccer albums (called Paninimania) and on the other hand that no solution is known that is able to take into account all effects such as replacement...
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Accretion driven turbulence in filaments I: Non-gravitational accretion
We study accretion driven turbulence for different inflow velocities in star forming filaments using the code ramses. Filaments are rarely isolated objects and their gravitational potential will lead to radially dominated accretion. In the non-gravitational case, accretion by itself can already provoke non-isotropic,...
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Contextual Outlier Interpretation
Outlier detection plays an essential role in many data-driven applications to identify isolated instances that are different from the majority. While many statistical learning and data mining techniques have been used for developing more effective outlier detection algorithms, the interpretation of detected outliers ...
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Game Theory for Secure Critical Interdependent Gas-Power-Water Infrastructure
A city's critical infrastructure such as gas, water, and power systems, are largely interdependent since they share energy, computing, and communication resources. This, in turn, makes it challenging to endow them with fool-proof security solutions. In this paper, a unified model for interdependent gas-power-water in...
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Implicit Entity Linking in Tweets
Over the years, Twitter has become one of the largest communication platforms providing key data to various applications such as brand monitoring, trend detection, among others. Entity linking is one of the major tasks in natural language understanding from tweets and it associates entity mentions in text to correspo...
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Non-cocompact Group Actions and $π_1$-Semistability at Infinity
A finitely presented 1-ended group $G$ has {\it semistable fundamental group at infinity} if $G$ acts geometrically on a simply connected and locally compact ANR $Y$ having the property that any two proper rays in $Y$ are properly homotopic. This property of $Y$ captures a notion of connectivity at infinity stronger ...
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Robust Distributed Control of DC Microgrids with Time-Varying Power Sharing
This paper addresses the problem of output voltage regulation for multiple DC/DC converters connected to a microgrid, and prescribes a scheme for sharing power among different sources. This architecture is structured in such a way that it admits quantifiable analysis of the closed-loop performance of the network of c...
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Quantum Lower Bounds for Tripartite Versions of the Hidden Shift and the Set Equality Problems
In this paper, we study quantum query complexity of the following rather natural tripartite generalisations (in the spirit of the 3-sum problem) of the hidden shift and the set equality problems, which we call the 3-shift-sum and the 3-matching-sum problems. The 3-shift-sum problem is as follows: given a table of $3\...
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A Parallel Direct Cut Algorithm for High-Order Overset Methods with Application to a Spinning Golf Ball
Overset methods are commonly employed to enable the effective simulation of problems involving complex geometries and moving objects such as rotorcraft. This paper presents a novel overset domain connectivity algorithm based upon the direct cut approach suitable for use with GPU-accelerated solvers on high-order curv...
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A data assimilation algorithm: the paradigm of the 3D Leray-alpha model of turbulence
In this paper we survey the various implementations of a new data assimilation (downscaling) algorithm based on spatial coarse mesh measurements. As a paradigm, we demonstrate the application of this algorithm to the 3D Leray-$\alpha$ subgrid scale turbulence model. Most importantly, we use this paradigm to show that...
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Playing a true Parrondo's game with a three state coin on a quantum walk
Playing a Parrondo's game with a qutrit is the subject of this paper. We show that a true quantum Parrondo's game can be played with a 3 state coin(qutrit) in a 1D quantum walk in contrast to the fact that playing a true Parrondo's game with a 2 state coin(qubit) in 1D quantum walk fails in the asymptotic limits.
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Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data
We analyse multimodal time-series data corresponding to weight, sleep and steps measurements. We focus on predicting whether a user will successfully achieve his/her weight objective. For this, we design several deep long short-term memory (LSTM) architectures, including a novel cross-modal LSTM (X-LSTM), and demonst...
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Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions
The key idea of variational auto-encoders (VAEs) resembles that of traditional auto-encoder models in which spatial information is supposed to be explicitly encoded in the latent space. However, the latent variables in VAEs are vectors, which can be interpreted as multiple feature maps of size 1x1. Such representatio...
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Optimal Ramp Schemes and Related Combinatorial Objects
In 1996, Jackson and Martin proved that a strong ideal ramp scheme is equivalent to an orthogonal array. However, there was no good characterization of ideal ramp schemes that are not strong. Here we show the equivalence of ideal ramp schemes to a new variant of orthogonal arrays that we term augmented orthogonal arr...
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Do Neural Nets Learn Statistical Laws behind Natural Language?
The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precis...
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Super-speeds with Zero-RAM: Next Generation Large-Scale Optimization in Your Laptop!
This article presents the novel breakthrough general purpose algorithm for large scale optimization problems. The novel algorithm is capable of achieving breakthrough speeds for very large-scale optimization on general purpose laptops and embedded systems. Application of the algorithm to the Griewank function was pos...
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Recoverable Energy of Dissipative Electromagnetic Systems
Ambiguities in the definition of stored energy within distributed or radiating electromagnetic systems motivate the discussion of the well-defined concept of recoverable energy. This concept is commonly overlooked by the community and the purpose of this communication is to recall its existence and to discuss its rel...
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Elliptic Hall algebra on $\mathbb{F}_1$
We construct Hall algebra of elliptic curve over $\mathbb{F}_1$ using the theory of monoidal scheme due to Deitmar and the theory of Hall algebra for monoidal representations due to Szczesny. The resulting algebra is shown to be a specialization of elliptic Hall algebra studied by Burban and Schiffmann. Thus our alge...
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Approximate Bayesian inference with queueing networks and coupled jump processes
Queueing networks are systems of theoretical interest that give rise to complex families of stochastic processes, and find widespread use in the performance evaluation of interconnected resources. Yet, despite their importance within applications, and in comparison to their counterpart stochastic models in genetics o...
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Universal features of price formation in financial markets: perspectives from Deep Learning
Using a large-scale Deep Learning approach applied to a high-frequency database containing billions of electronic market quotes and transactions for US equities, we uncover nonparametric evidence for the existence of a universal and stationary price formation mechanism relating the dynamics of supply and demand for a...
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A New Tracking Algorithm for Multiple Colloidal Particles Close to Contact
In this paper, we propose a new algorithm based on radial symmetry center method to track colloidal particles close to contact, where the optical images of the particles start to overlap in digital video microscopy. This overlapping effect is important to observe the pair interaction potential in colloidal studies an...
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Critical Percolation Without Fine Tuning on the Surface of a Topological Superconductor
We present numerical evidence that most two-dimensional surface states of a bulk topological superconductor (TSC) sit at an integer quantum Hall plateau transition. We study TSC surface states in class CI with quenched disorder. Low-energy (finite-energy) surface states were expected to be critically delocalized (And...
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Low-luminosity stellar wind accretion onto neutron stars in HMXBs
Features and applications of quasi-spherical settling accretion onto rotating magnetized neutron stars in high-mass X-ray binaries are discussed. The settling accretion occurs in wind-fed HMXBs when the plasma cooling time is longer than the free-fall time from the gravitational capture radius, which can take place i...
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Faithful Inversion of Generative Models for Effective Amortized Inference
Inference amortization methods share information across multiple posterior-inference problems, allowing each to be carried out more efficiently. Generally, they require the inversion of the dependency structure in the generative model, as the modeller must learn a mapping from observations to distributions approximat...
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A social Network Analysis of the Operations Research/Industrial Engineering Faculty Hiring Network
We study the U.S. Operations Research/Industrial-Systems Engineering (ORIE) faculty hiring network, consisting of 1,179 faculty origin and destination data together with attribute data from 83 ORIE departments. A social network analysis of faculty hires can reveal important patterns in an academic field, such as the ...
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One-sample aggregate data meta-analysis of medians
An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (e.g., the sample mean and its stan...
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QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts
Large inter-datacenter transfers are crucial for cloud service efficiency and are increasingly used by organizations that have dedicated wide area networks between datacenters. A recent work uses multicast forwarding trees to reduce the bandwidth needs and improve completion times of point-to-multipoint transfers. Us...
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Contemporary machine learning: a guide for practitioners in the physical sciences
Machine learning is finding increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. We present a tutorial on current techniques in machine learning...
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Uniform diamond coatings on WC-Co hard alloy cutting inserts deposited by a microwave plasma CVD
Polycrystalline diamond coatings have been grown on cemented carbide substrates with different aspect ratios by a microwave plasma CVD in methane-hydrogen gas mixtures. To protect the edges of the substrates from non-uniform heating due to the plasma edge effect, a special plateholder with pockets for group growth ha...
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Analysing Soccer Games with Clustering and Conceptors
We present a new approach for identifying situations and behaviours, which we call "moves", from soccer games in the 2D simulation league. Being able to identify key situations and behaviours are useful capabilities for analysing soccer matches, anticipating opponent behaviours to aid selection of appropriate tactics...
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On the Efficient Simulation of the Left-Tail of the Sum of Correlated Log-normal Variates
The sum of Log-normal variates is encountered in many challenging applications such as in performance analysis of wireless communication systems and in financial engineering. Several approximation methods have been developed in the literature, the accuracy of which is not ensured in the tail regions. These regions ar...
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Why optional stopping is a problem for Bayesians
Recently, optional stopping has been a subject of debate in the Bayesian psychology community. Rouder (2014) argues that optional stopping is no problem for Bayesians, and even recommends the use of optional stopping in practice, as do Wagenmakers et al. (2012). This article addresses the question whether optional st...
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