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Continuous Authentication of Smartphones Based on Application Usage
An empirical investigation of active/continuous authentication for smartphones is presented in this paper by exploiting users' unique application usage data, i.e., distinct patterns of use, modeled by a Markovian process. Variations of Hidden Markov Models (HMMs) are evaluated for continuous user verification, and ch...
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On the Universality of Invariant Networks
Constraining linear layers in neural networks to respect symmetry transformations from a group $G$ is a common design principle for invariant networks that has found many applications in machine learning. In this paper, we consider a fundamental question that has received little attention to date: Can these networks ...
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Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms?
We study how the behavior of deep policy gradient algorithms reflects the conceptual framework motivating their development. We propose a fine-grained analysis of state-of-the-art methods based on key aspects of this framework: gradient estimation, value prediction, optimization landscapes, and trust region enforceme...
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Achieving Privacy in the Adversarial Multi-Armed Bandit
In this paper, we improve the previously best known regret bound to achieve $\epsilon$-differential privacy in oblivious adversarial bandits from $\mathcal{O}{(T^{2/3}/\epsilon)}$ to $\mathcal{O}{(\sqrt{T} \ln T /\epsilon)}$. This is achieved by combining a Laplace Mechanism with EXP3. We show that though EXP3 is alr...
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Proximity Variational Inference
Variational inference is a powerful approach for approximate posterior inference. However, it is sensitive to initialization and can be subject to poor local optima. In this paper, we develop proximity variational inference (PVI). PVI is a new method for optimizing the variational objective that constrains subsequent...
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Mandarin tone modeling using recurrent neural networks
We propose an Encoder-Classifier framework to model the Mandarin tones using recurrent neural networks (RNN). In this framework, extracted frames of features for tone classification are fed in to the RNN and casted into a fixed dimensional vector (tone embedding) and then classified into tone types using a softmax la...
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Shallow water models with constant vorticity
We modify the nonlinear shallow water equations, the Korteweg-de Vries equation, and the Whitham equation, to permit constant vorticity, and examine wave breaking, or the lack thereof. By wave breaking, we mean that the solution remains bounded but its slope becomes unbounded in finite time. We show that a solution o...
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Tensor Balancing on Statistical Manifold
We solve tensor balancing, rescaling an Nth order nonnegative tensor by multiplying N tensors of order N - 1 so that every fiber sums to one. This generalizes a fundamental process of matrix balancing used to compare matrices in a wide range of applications from biology to economics. We present an efficient balancing...
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Learning Unknown Markov Decision Processes: A Thompson Sampling Approach
We consider the problem of learning an unknown Markov Decision Process (MDP) that is weakly communicating in the infinite horizon setting. We propose a Thompson Sampling-based reinforcement learning algorithm with dynamic episodes (TSDE). At the beginning of each episode, the algorithm generates a sample from the pos...
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Models of Random Knots
The study of knots and links from a probabilistic viewpoint provides insight into the behavior of "typical" knots, and opens avenues for new constructions of knots and other topological objects with interesting properties. The knotting of random curves arises also in applications to the natural sciences, such as in t...
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Revival structures of coherent states for Xm exceptional orthogonal polynomials of the Scarf I potential within position-dependent effective mass
The revival structures for the X_m exceptional orthogonal polynomials of the Scarf I potential endowed with position-dependent effective mass is studied in the context of the generalized Gazeau-Klauder coherent states. It is shown that in the case of the constant mass, the deduced coherent states mimic full and fract...
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Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming
Autonomous aerial cinematography has the potential to enable automatic capture of aesthetically pleasing videos without requiring human intervention, empowering individuals with the capability of high-end film studios. Current approaches either only handle off-line trajectory generation, or offer strategies that reas...
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Fifth order finite volume WENO in general orthogonally-curvilinear coordinates
High order reconstruction in the finite volume (FV) approach is achieved by a more fundamental form of the fifth order WENO reconstruction in the framework of orthogonally-curvilinear coordinates, for solving the hyperbolic conservation equations. The derivation employs a piecewise parabolic polynomial approximation ...
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Traffic Minimizing Caching and Latent Variable Distributions of Order Statistics
Given a statistical model for the request frequencies and sizes of data objects in a caching system, we derive the probability density of the size of the file that accounts for the largest amount of data traffic. This is equivalent to finding the required size of the cache for a caching placement that maximizes the e...
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Maximizing the information learned from finite data selects a simple model
We use the language of uninformative Bayesian prior choice to study the selection of appropriately simple effective models. We advocate for the prior which maximizes the mutual information between parameters and predictions, learning as much as possible from limited data. When many parameters are poorly constrained b...
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Aging Feynman-Kac Equation
Aging, the process of growing old or maturing, is one of the most widely seen natural phenomena in the world. For the stochastic processes, sometimes the influence of aging can not be ignored. For example, in this paper, by analyzing the functional distribution of the trajectories of aging particles performing anomal...
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Effective optimization using sample persistence: A case study on quantum annealers and various Monte Carlo optimization methods
We present and apply a general-purpose, multi-start algorithm for improving the performance of low-energy samplers used for solving optimization problems. The algorithm iteratively fixes the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are s...
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BOOK: Storing Algorithm-Invariant Episodes for Deep Reinforcement Learning
We introduce a novel method to train agents of reinforcement learning (RL) by sharing knowledge in a way similar to the concept of using a book. The recorded information in the form of a book is the main means by which humans learn knowledge. Nevertheless, the conventional deep RL methods have mainly focused either o...
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A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with realistic particle dynamics (NEMO-ProThorP 0.1)
In this paper, we set forth a 3-D ocean model of the radioactive trace isotopes Th-230 and Pa-231. The interest arises from the fact that these isotopes are extensively used for investigating particle transport in the ocean and reconstructing past ocean circulation. The tracers are reversibly scavenged by biogenic an...
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The Dynamic Geometry of Interaction Machine: A Call-by-need Graph Rewriter
Girard's Geometry of Interaction (GoI), a semantics designed for linear logic proofs, has been also successfully applied to programming language semantics. One way is to use abstract machines that pass a token on a fixed graph along a path indicated by the GoI. These token-passing abstract machines are space efficien...
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Classification of finite W-groups
We determine the structure of the W-group $\mathcal{G}_F$, the small Galois quotient of the absolute Galois group $G_F$ of the Pythagorean formally real field $F$ when the space of orderings $X_F$ has finite order. Based on Marshall's work (1979), we reduce the structure of $\mathcal{G}_F$ to that of $\mathcal{G}_{\b...
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A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices
Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality ...
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Chromospheric Activity of HAT-P-11: an Unusually Active Planet-Hosting K Star
Kepler photometry of the hot Neptune host star HAT-P-11 suggests that its spot latitude distribution is comparable to the Sun's near solar maximum. We search for evidence of an activity cycle in the CaII H & K chromospheric emission $S$-index with archival Keck/HIRES spectra and observations from the echelle spectrog...
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Automated Detection of Serializability Violations under Weak Consistency
While a number of weak consistency mechanisms have been developed in recent years to improve performance and ensure availability in distributed, replicated systems, ensuring correctness of transactional applications running on top of such systems remains a difficult and important problem. Serializability is a well-un...
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Andreev reflection in 2D relativistic materials with realistic tunneling transparency in normal-metal-superconductor junctions
The Andreev conductance across 2d normal metal (N)/superconductor (SC) junctions with relativistic Dirac spectrum is investigated theoretically in the Blonder-Tinkham-Klapwijk formalism. It is shown that for relativistic materials, due to the Klein tunneling instead of impurity potentials, the local strain in the jun...
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Multi-Task Learning for Contextual Bandits
Contextual bandits are a form of multi-armed bandit in which the agent has access to predictive side information (known as the context) for each arm at each time step, and have been used to model personalized news recommendation, ad placement, and other applications. In this work, we propose a multi-task learning fra...
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Admissible topologies on $C(Y,Z)$ and ${\cal O}_Z(Y)$
Let $Y$ and $Z$ be two given topological spaces, ${\cal O}(Y)$ (respectively, ${\cal O}(Z)$) the set of all open subsets of $Y$ (respectively, $Z$), and $C(Y,Z)$ the set of all continuous maps from $Y$ to $Z$. We study Scott type topologies on ${\mathcal O}(Y)$ and we construct admissible topologies on $C(Y,Z)$ and $...
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Weighted spherical means generated by generalized translation and general Euler-Poisson-Darboux equation
We consider the spherical mean generated by a multidimensional generalized translation and general Euler-Poisson-Darboux equation corresponding to this mean. The Asgeirsson property of solutions of the ultrahyperbolic equation that includes singular differential Bessel operators acting by each variable is provided.
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K-Means Clustering using Tabu Search with Quantized Means
The Tabu Search (TS) metaheuristic has been proposed for K-Means clustering as an alternative to Lloyd's algorithm, which for all its ease of implementation and fast runtime, has the major drawback of being trapped at local optima. While the TS approach can yield superior performance, it involves a high computational...
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In-silico Feedback Control of a MIMO Synthetic Toggle Switch via Pulse-Width Modulation
The synthetic toggle switch, first proposed by Gardner & Collins [1] is a MIMO control system that can be controlled by varying the concentrations of two inducer molecules, aTc and IPTG, to achieve a desired level of expression of the two genes it comprises. It has been shown [2] that this can be accomplished through...
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Holomorphic foliations tangent to Levi-flat subsets
We study Segre varieties associated to Levi-flat subsets in complex manifolds and apply them to establish local and global results on the integration of tangent holomorphic foliations.
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Real-Time Panoramic Tracking for Event Cameras
Event cameras are a paradigm shift in camera technology. Instead of full frames, the sensor captures a sparse set of events caused by intensity changes. Since only the changes are transferred, those cameras are able to capture quick movements of objects in the scene or of the camera itself. In this work we propose a ...
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Halo nonlinear reconstruction
We apply the nonlinear reconstruction method to simulated halo fields. For halo number density $2.77\times 10^{-2}$ $(h^{-1} {\rm Mpc})^{-3}$ at $z=0$, corresponding to the SDSS main sample density, we find the scale where the noise saturates the linear signal is improved to $k\gtrsim0.36\ h {\rm Mpc}^{-1}$, a factor...
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Molecular semimetallic hydrogen
Establishing metallic hydrogen is a goal of intensive theoretical and experimental work since 1935 when Wigner and Hungtinton [1] predicted that insulating molecular hydrogen will dissociate at high pressures and transform to a metal. This metal is predicted to be a superconductor with very high critical temperature ...
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Order-Sensitivity and Equivariance of Scoring Functions
The relative performance of competing point forecasts is usually measured in terms of loss or scoring functions. It is widely accepted that these scoring function should be strictly consistent in the sense that the expected score is minimized by the correctly specified forecast for a certain statistical functional su...
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Light in Power: A General and Parameter-free Algorithm for Caustic Design
We present in this paper a generic and parameter-free algorithm to efficiently build a wide variety of optical components, such as mirrors or lenses, that satisfy some light energy constraints. In all of our problems, one is given a collimated or point light source and a desired illumination after reflection or refra...
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Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data
In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with LWIR data. Measurements from a multi-sensor field campaign represent the benchmark dataset which contains measured hyperspectral, LWIR, and soil-moisture data conducted on grassland site....
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Distilling a Neural Network Into a Soft Decision Tree
Deep neural networks have proved to be a very effective way to perform classification tasks. They excel when the input data is high dimensional, the relationship between the input and the output is complicated, and the number of labeled training examples is large. But it is hard to explain why a learned network makes...
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A General Scheme Implicit Force Control for a Flexible-Link Manipulator
In this paper we propose an implicit force control scheme for a one-link flexible manipulator that interact with a compliant environment. The controller was based in the mathematical model of the manipulator, considering the dynamics of the beam flexible and the gravitational force. With this method, the controller p...
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CNN-based MultiChannel End-to-End Speech Recognition for everyday home environments
Casual conversations involving multiple speakers and noises from surrounding devices are part of everyday environments and pose challenges for automatic speech recognition systems. These challenges in speech recognition are target for the CHiME-5 challenge. In the present study, an attempt is made to overcome these c...
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Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision
Tool manipulation is vital for facilitating robots to complete challenging task goals. It requires reasoning about the desired effect of the task and thus properly grasping and manipulating the tool to achieve the task. Task-agnostic grasping optimizes for grasp robustness while ignoring crucial task-specific constra...
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Classification of Minimal Separating Sets in Low Genus Surfaces
Consider a surface $S$ and let $M\subset S$. If $S\setminus M$ is not connected, then we say $M$ \emph{separates} $S$, and we refer to $M$ as a \emph{separating set} of $S$. If $M$ separates $S$, and no proper subset of $M$ separates $S$, then we say $M$ is a \emph{minimal separating set} of $S$. In this paper we use...
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A feasibility study on SSVEP-based interaction with motivating and immersive virtual and augmented reality
Non-invasive steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) systems offer high bandwidth compared to other BCI types and require only minimal calibration and training. Virtual reality (VR) has been already validated as effective, safe, affordable and motivating feedback modality for...
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Intelligent User Interfaces - A Tutorial
IUIs aim to incorporate intelligent automated capabilities in human computer interaction, where the net impact is a human-computer interaction that improves performance or usability in critical ways. It also involves designing and implementing an artificial intelligence (AI) component that effectively leverages human...
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Graph Partitioning with Acyclicity Constraints
Graphs are widely used to model execution dependencies in applications. In particular, the NP-complete problem of partitioning a graph under constraints receives enormous attention by researchers because of its applicability in multiprocessor scheduling. We identified the additional constraint of acyclic dependencies...
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Learning Sublinear-Time Indexing for Nearest Neighbor Search
Most of the efficient sublinear-time indexing algorithms for the high-dimensional nearest neighbor search problem (NNS) are based on space partitions of the ambient space $\mathbb{R}^d$. Inspired by recent theoretical work on NNS for general metric spaces [Andoni, Naor, Nikolov, Razenshteyn, Waingarten STOC 2018, FOC...
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Lempel-Ziv Jaccard Distance, an Effective Alternative to Ssdeep and Sdhash
Recent work has proposed the Lempel-Ziv Jaccard Distance (LZJD) as a method to measure the similarity between binary byte sequences for malware classification. We propose and test LZJD's effectiveness as a similarity digest hash for digital forensics. To do so we develop a high performance Java implementation with th...
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Graded Steinberg algebras and their representations
We study the category of left unital graded modules over the Steinberg algebra of a graded ample Hausdorff groupoid. In the first part of the paper, we show that this category is isomorphic to the category of unital left modules over the Steinberg algebra of the skew-product groupoid arising from the grading. To do t...
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Movement of time-delayed hot spots in Euclidean space for special initial states
We consider the Cauchy problem for the damped wave equation under the initial state that the sum of an initial position and an initial velocity vanishes. When the initial position is non-zero, non-negative and compactly supported, we study the large time behavior of the spatial null, critical, maximum and minimum set...
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Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction
Time series prediction has been studied in a variety of domains. However, it is still challenging to predict future series given historical observations and past exogenous data. Existing methods either fail to consider the interactions among different components of exogenous variables which may affect the prediction ...
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Mass distribution and skewness for passive scalar transport in pipes with polygonal and smooth cross-sections
We extend our previous results characterizing the loading properties of a diffusing passive scalar advected by a laminar shear flow in ducts and channels to more general cross-sectional shapes, including regular polygons and smoothed corner ducts originating from deformations of ellipses. For the case of the triangle...
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An Optics-Based Approach to Thermal Management of Photovoltaics: Selective-Spectral and Radiative Cooling
For commercial one-sun solar modules, up to 80% of the incoming sunlight may be dissipated as heat, potentially raising the temperature 20 C - 30 C higher than the ambient. In the long term, extreme self-heating erodes efficiency and shortens lifetime, thereby dramatically reducing the total energy output. Therefore,...
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GOLDRUSH. II. Clustering of Galaxies at $z\sim 4-6$ Revealed with the Half-Million Dropouts Over the 100 deg$^2$ Area Corresponding to 1 Gpc$^3$
We present clustering properties from 579,492 Lyman break galaxies (LBGs) at z~4-6 over the 100 deg^2 sky (corresponding to a 1.4 Gpc^3 volume) identified in early data of the Hyper Suprime-Cam (HSC) Subaru strategic program survey. We derive angular correlation functions (ACFs) of the HSC LBGs with unprecedentedly h...
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The Least-Area Tetrahedral Tile of Space
We prove the least-area, unit-volume, tetrahedral tile of Euclidean space, without the assumption of Gallagher et al. that the tiling uses only orientation-preserving images of the tile. The winner remains Sommerville's type 4v.
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Renormalization group theory for percolation in time-varying networks
Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether...
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Spectral properties and breathing dynamics of a few-body Bose-Bose mixture in a 1D harmonic trap
We investigate a few-body mixture of two bosonic components, each consisting of two particles confined in a quasi one-dimensional harmonic trap. By means of exact diagonalization with a correlated basis approach we obtain the low-energy spectrum and eigenstates for the whole range of repulsive intra- and inter-compon...
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Study of secondary neutron interactions with $^{232}$Th, $^{129}$I, and $^{127}$I nuclei with the uranium assembly "QUINTA" at 2, 4, and 8 GeV deuteron beams of the JINR Nuclotron accelerator
The natural uranium assembly, "QUINTA", was irradiated with 2, 4, and 8 GeV deuterons. The $^{232}$Th, $^{127}$I, and $^{129}$I samples have been exposed to secondary neutrons produced in the assembly at a 20-cm radial distance from the deuteron beam axis. The spectra of gamma rays emitted by the activated $^{232}$Th...
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Short Proofs for Slow Consistency
Let $\operatorname{Con}(\mathbf T)\!\restriction\!x$ denote the finite consistency statement "there are no proofs of contradiction in $\mathbf T$ with $\leq x$ symbols". For a large class of natural theories $\mathbf T$, Pudlák has shown that the lengths of the shortest proofs of $\operatorname{Con}(\mathbf T)\!\rest...
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Response to Comment on "Cell nuclei have lower refractive index and mass density than cytoplasm"
In a recent study entitled "Cell nuclei have lower refractive index and mass density than cytoplasm", we provided strong evidence indicating that the nuclear refractive index (RI) is lower than the RI of the cytoplasm for several cell lines. In a complementary study in 2017, entitled "Is the nuclear refractive index ...
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On the composition of an arbitrary collection of $SU(2)$ spins: An Enumerative Combinatoric Approach
The whole enterprise of spin compositions can be recast as simple enumerative combinatoric problems. We show here that enumerative combinatorics (EC)\citep{book:Stanley-2011} is a natural setting for spin composition, and easily leads to very general analytic formulae -- many of which hitherto not present in the lite...
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Perceived Performance of Webpages In the Wild: Insights from Large-scale Crowdsourcing of Above-the-Fold QoE
Clearly, no one likes webpages with poor quality of experience (QoE). Being perceived as slow or fast is a key element in the overall perceived QoE of web applications. While extensive effort has been put into optimizing web applications (both in industry and academia), not a lot of work exists in characterizing what...
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Entanglement and exotic superfluidity in spin-imbalanced lattices
We investigate the properties of entanglement in one-dimensional fermionic lattices at the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) superfluid regime. By analyzing occupation probabilities, which are concepts closely related to FFLO and entanglement, we obtain approximate analytical expressions for the spin-flip proce...
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Informed Non-convex Robust Principal Component Analysis with Features
We revisit the problem of robust principal component analysis with features acting as prior side information. To this aim, a novel, elegant, non-convex optimization approach is proposed to decompose a given observation matrix into a low-rank core and the corresponding sparse residual. Rigorous theoretical analysis of...
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A note on self orbit equivalences of Anosov flows and bundles with fiberwise Anosov flows
We show that a self orbit equivalence of a transitive Anosov flow on a $3$-manifold which is homotopic to identity has to either preserve every orbit or the Anosov flow is $\mathbb{R}$-covered and the orbit equivalence has to be of a specific type. This result shows that one can remove a relatively unnatural assumpti...
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The Metallicity of the Intracluster Medium Over Cosmic Time: Further Evidence for Early Enrichment
We use Chandra X-ray data to measure the metallicity of the intracluster medium (ICM) in 245 massive galaxy clusters selected from X-ray and Sunyaev-Zel'dovich (SZ) effect surveys, spanning redshifts $0<z<1.2$. Metallicities were measured in three different radial ranges, spanning cluster cores through their outskirt...
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Graphical Models: An Extension to Random Graphs, Trees, and Other Objects
In this work, we consider an extension of graphical models to random graphs, trees, and other objects. To do this, many fundamental concepts for multivariate random variables (e.g., marginal variables, Gibbs distribution, Markov properties) must be extended to other mathematical objects; it turns out that this extens...
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Boundary Control method and De Branges spaces. Schrödinger equation, Dirac system and Discrete Schrödinger operator
In the framework of the application of the Boundary Control method to solving the inverse dynamical problems for the one-dimensional Schrödinger and Dirac operators on the half-line and semi-infinite discrete Schrödinger operator, we establish the connections with the method of De Branges: for each of the system we c...
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On the evolution of galaxy spin in a cosmological hydrodynamic simulation of galaxy clusters
The traditional view of the morphology-spin connection is being challenged by recent integral-field-unit observations, as the majority of early-type galaxies are found to have a rotational component that is often as large as a dispersion component. Mergers are often suspected to be critical in galaxy spin evolution, ...
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Diagrammatic Approach to Multiphoton Scattering
We present a method to systematically study multi-photon transmission in one dimensional systems comprised of correlated quantum emitters coupled to input and output waveguides. Within the Green's function approach of the scattering matrix (S-matrix), we develop a diagrammatic technique to analytically obtain the sys...
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Efficient Computation of Feedback Control for Constrained Systems
A method is presented for solving the discrete-time finite-horizon Linear Quadratic Regulator (LQR) problem subject to auxiliary linear equality constraints, such as fixed end-point constraints. The method explicitly determines an affine relationship between the control and state variables, as in standard Riccati rec...
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A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations
As the size of modern data sets exceeds the disk and memory capacities of a single computer, machine learning practitioners have resorted to parallel and distributed computing. Given that optimization is one of the pillars of machine learning and predictive modeling, distributed optimization methods have recently gar...
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Unified Model of D-Term Inflation
Hybrid inflation, driven by a Fayet-Iliopoulos (FI) D term, is an intriguing inflationary model. In its usual formulation, it however suffers from several shortcomings. These pertain to the origin of the FI mass scale, the stability of scalar fields during inflation, gravitational corrections in supergravity, as well...
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Signal Recovery from Unlabeled Samples
In this paper, we study the recovery of a signal from a set of noisy linear projections (measurements), when such projections are unlabeled, that is, the correspondence between the measurements and the set of projection vectors (i.e., the rows of the measurement matrix) is not known a priori. We consider a special ca...
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Piecewise linear generalized Alexander's theorem in dimension at most 5
We study piecewise linear co-dimension two embeddings of closed oriented manifolds in Euclidean space, and show that any such embedding can always be isotoped to be a closed braid as long as the ambient dimension is at most five, extending results of Alexander (in ambient dimension three), and Viro and independently ...
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Sample complexity of population recovery
The problem of population recovery refers to estimating a distribution based on incomplete or corrupted samples. Consider a random poll of sample size $n$ conducted on a population of individuals, where each pollee is asked to answer $d$ binary questions. We consider one of the two polling impediments: (a) in lossy p...
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Asymptotic Exponentiality of the First Exit Time of the Shiryaev-Roberts Diffusion with Constant Positive Drift
We consider the first exit time of a Shiryaev-Roberts diffusion with constant positive drift from the interval $[0,A]$ where $A>0$. We show that the moment generating function (Laplace transform) of a suitably standardized version of the first exit time converges to that of the unit-mean exponential distribution as $...
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Learning to Teach Reinforcement Learning Agents
In this article we study the transfer learning model of action advice under a budget. We focus on reinforcement learning teachers providing action advice to heterogeneous students playing the game of Pac-Man under a limited advice budget. First, we examine several critical factors affecting advice quality in this set...
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Giant room-temperature barocaloric effects in PDMS rubber at low pressures
The barocaloric effect is still an incipient scientific topic, but it has been attracting an increasing attention in the last years due to the promising perspectives for its application in alternative cooling devices. Here, we present giant values of barocaloric entropy change and temperature change induced by low pr...
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$({\mathfrak{gl}}_M, {\mathfrak{gl}}_N)$-Dualities in Gaudin Models with Irregular Singularities
We establish $({\mathfrak{gl}}_M, {\mathfrak{gl}}_N)$-dualities between quantum Gaudin models with irregular singularities. Specifically, for any $M, N \in {\mathbb Z}_{\geq 1}$ we consider two Gaudin models: the one associated with the Lie algebra ${\mathfrak{gl}}_M$ which has a double pole at infinity and $N$ poles...
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Dynamic coupling of a finite element solver to large-scale atomistic simulations
We propose a method for efficiently coupling the finite element method with atomistic simulations, while using molecular dynamics or kinetic Monte Carlo techniques. Our method can dynamically build an optimized unstructured mesh that follows the geometry defined by atomistic data. On this mesh, different multiphysics...
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A study of periodograms standardized using training data sets and application to exoplanet detection
When the noise affecting time series is colored with unknown statistics, a difficulty for sinusoid detection is to control the true significance level of the test outcome. This paper investigates the possibility of using training data sets of the noise to improve this control. Specifically, we analyze the performance...
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An Efficient Deep Learning Technique for the Navier-Stokes Equations: Application to Unsteady Wake Flow Dynamics
We present an efficient deep learning technique for the model reduction of the Navier-Stokes equations for unsteady flow problems. The proposed technique relies on the Convolutional Neural Network (CNN) and the stochastic gradient descent method. Of particular interest is to predict the unsteady fluid forces for diff...
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Accurate fast computation of steady two-dimensional surface gravity waves in arbitrary depth
This paper describes an efficient algorithm for computing steady two-dimensional surface gravity wave in irrotational motion. The algorithm complexity is O(N log N), N being the number of Fourier modes. The algorithm allows the arbitrary precision computation of waves in arbitrary depth, i.e., it works efficiently fo...
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AutoWIG: Automatic Generation of Python Bindings for C++ Libraries
Most of Python and R scientific packages incorporate compiled scientific libraries to speed up the code and reuse legacy libraries. While several semi-automatic solutions exist to wrap these compiled libraries, the process of wrapping a large library is cumbersome and time consuming. In this paper, we introduce AutoW...
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Fate of Weyl semimetals in the presence of incommensurate potentials
We investigate the effect of the incommensurate potential on Weyl semimetal, which is proposed to be realized in ultracold atomic systems trapped in three-dimensional optical lattices. For the system without the Fermi arc, we find that the Weyl points are robust against the incommensurate potential and the system ent...
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Word equations in linear space
Word equations are an important problem on the intersection of formal languages and algebra. Given two sequences consisting of letters and variables we are to decide whether there is a substitution for the variables that turns this equation into true equality of strings. The computational complexity of this problem r...
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Selective Strong Structural Minimum Cost Resilient Co-Design for Regular Descriptor Linear Systems
This paper addresses the problem of minimum cost resilient actuation-sensing-communication co-design for regular descriptor systems while ensuring selective strong structural system's properties. More specifically, the problem consists of determining the minimum cost deployment of actuation and sensing technology, as...
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Maximum a Posteriori Policy Optimisation
We introduce a new algorithm for reinforcement learning called Maximum aposteriori Policy Optimisation (MPO) based on coordinate ascent on a relative entropy objective. We show that several existing methods can directly be related to our derivation. We develop two off-policy algorithms and demonstrate that they are c...
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On Geodesic Completeness for Riemannian Metrics on Smooth Probability Densities
The geometric approach to optimal transport and information theory has triggered the interpretation of probability densities as an infinite-dimensional Riemannian manifold. The most studied Riemannian structures are Otto's metric, yielding the $L^2$-Wasserstein distance of optimal mass transport, and the Fisher--Rao ...
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Hacker Combat: A Competitive Sport from Programmatic Dueling & Cyberwarfare
The history of humanhood has included competitive activities of many different forms. Sports have offered many benefits beyond that of entertainment. At the time of this article, there exists not a competitive ecosystem for cyber security beyond that of conventional capture the flag competitions, and the like. This p...
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Providing Effective Real-time Feedback in Simulation-based Surgical Training
Virtual reality simulation is becoming popular as a training platform in surgical education. However, one important aspect of simulation-based surgical training that has not received much attention is the provision of automated real-time performance feedback to support the learning process. Performance feedback is ac...
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Large-Scale Classification of Structured Objects using a CRF with Deep Class Embedding
This paper presents a novel deep learning architecture to classify structured objects in datasets with a large number of visually similar categories. We model sequences of images as linear-chain CRFs, and jointly learn the parameters from both local-visual features and neighboring classes. The visual features are com...
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code2seq: Generating Sequences from Structured Representations of Code
The ability to generate natural language sequences from source code snippets has a variety of applications such as code summarization, documentation, and retrieval. Sequence-to-sequence (seq2seq) models, adopted from neural machine translation (NMT), have achieved state-of-the-art performance on these tasks by treati...
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Learning Neural Parsers with Deterministic Differentiable Imitation Learning
We explore the problem of learning to decompose spatial tasks into segments, as exemplified by the problem of a painting robot covering a large object. Inspired by the ability of classical decision tree algorithms to construct structured partitions of their input spaces, we formulate the problem of decomposing object...
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Dimension of the minimum set for the real and complex Monge-Ampère equations in critical Sobolev spaces
We prove that the zero set of a nonnegative plurisubharmonic function that solves $\det (\partial \overline{\partial} u) \geq 1$ in $\mathbb{C}^n$ and is in $W^{2, \frac{n(n-k)}{k}}$ contains no analytic sub-variety of dimension $k$ or larger. Along the way we prove an analogous result for the real Monge-Ampère equat...
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Road Detection Technique Using Filters with Application to Autonomous Driving System
Autonomous driving systems are broadly used equipment in the industries and in our daily lives, they assist in production, but are majorly used for exploration in dangerous or unfamiliar locations. Thus, for a successful exploration, navigation plays a significant role. Road detection is an essential factor that assi...
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Relativistic Spacecraft Propelled by Directed Energy
Achieving relativistic flight to enable extrasolar exploration is one of the dreams of humanity and the long term goal of our NASA Starlight program. We derive a fully relativistic solution for the motion of a spacecraft propelled by radiation pressure from a directed energy system. Depending on the system parameters...
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Outward Influence and Cascade Size Estimation in Billion-scale Networks
Estimating cascade size and nodes' influence is a fundamental task in social, technological, and biological networks. Yet this task is extremely challenging due to the sheer size and the structural heterogeneity of networks. We investigate a new influence measure, termed outward influence (OI), defined as the (expect...
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Estimation of a noisy subordinated Brownian Motion via two-scales power variations
High frequency based estimation methods for a semiparametric pure-jump subordinated Brownian motion exposed to a small additive microstructure noise are developed building on the two-scales realized variations approach originally developed by Zhang et. al. (2005) for the estimation of the integrated variance of a con...
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Mirror actuation design for the interferometer control of the KAGRA gravitational wave telescope
KAGRA is a 3-km cryogenic interferometric gravitational wave telescope located at an underground site in Japan. In order to achieve its target sensitivity, the relative positions of the mirrors of the interferometer must be finely adjusted with attached actuators. We have developed a model to simulate the length cont...
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