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Miraculous cancellations for quantum $SL_2$
In earlier work, Helen Wong and the author discovered certain "miraculous cancellations" for the quantum trace map connecting the Kauffman bracket skein algebra of a surface to its quantum Teichmueller space, occurring when the quantum parameter $q$ is a root of unity. The current paper is devoted to giving a more re...
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Energy and time measurements with high-granular silicon devices
This note is a short summary of the workshop on "Energy and time measurements with high-granular silicon devices" that took place on the 13/6/16 and the 14/6/16 at DESY/Hamburg in the frame of the first AIDA-2020 Annual Meeting. This note tries to put forward trends that could be spotted and to emphasise in particula...
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Action Tubelet Detector for Spatio-Temporal Action Localization
Current state-of-the-art approaches for spatio-temporal action localization rely on detections at the frame level that are then linked or tracked across time. In this paper, we leverage the temporal continuity of videos instead of operating at the frame level. We propose the ACtion Tubelet detector (ACT-detector) tha...
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Significance of Side Information in the Graph Matching Problem
Percolation based graph matching algorithms rely on the availability of seed vertex pairs as side information to efficiently match users across networks. Although such algorithms work well in practice, there are other types of side information available which are potentially useful to an attacker. In this paper, we c...
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Extended Gray-Wyner System with Complementary Causal Side Information
We establish the rate region of an extended Gray-Wyner system for 2-DMS $(X,Y)$ with two additional decoders having complementary causal side information. This extension is interesting because in addition to the operationally significant extreme points of the Gray-Wyner rate region, which include Wyner's common infor...
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Learning Powers of Poisson Binomial Distributions
We introduce the problem of simultaneously learning all powers of a Poisson Binomial Distribution (PBD). A PBD of order $n$ is the distribution of a sum of $n$ mutually independent Bernoulli random variables $X_i$, where $\mathbb{E}[X_i] = p_i$. The $k$'th power of this distribution, for $k$ in a range $[m]$, is the ...
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Geometry of simplices in Minkowski spaces
There are many problems and configurations in Euclidean geometry that were never extended to the framework of (normed or) finite dimensional real Banach spaces, although their original versions are inspiring for this type of generalization, and the analogous definitions for normed spaces represent a promising topic. ...
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DLR : Toward a deep learned rhythmic representation for music content analysis
In the use of deep neural networks, it is crucial to provide appropriate input representations for the network to learn from. In this paper, we propose an approach to learn a representation that focus on rhythmic representation which is named as DLR (Deep Learning Rhythmic representation). The proposed approach aims ...
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Phylogeny-based tumor subclone identification using a Bayesian feature allocation model
Tumor cells acquire different genetic alterations during the course of evolution in cancer patients. As a result of competition and selection, only a few subgroups of cells with distinct genotypes survive. These subgroups of cells are often referred to as subclones. In recent years, many statistical and computational...
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Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Predicting properties of nodes in a graph is an important problem with applications in a variety of domains. Graph-based Semi-Supervised Learning (SSL) methods aim to address this problem by labeling a small subset of the nodes as seeds and then utilizing the graph structure to predict label scores for the rest of th...
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Long-range fluctuations and multifractality in connectivity density time series of a wind speed monitoring network
This paper studies the daily connectivity time series of a wind speed-monitoring network using multifractal detrended fluctuation analysis. It investigates the long-range fluctuation and multifractality in the residuals of the connectivity time series. Our findings reveal that the daily connectivity of the correlatio...
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The Dynamics of Norm Change in the Cultural Evolution of Language
What happens when a new social convention replaces an old one? While the possible forces favoring norm change - such as institutions or committed activists - have been identified since a long time, little is known about how a population adopts a new convention, due to the difficulties of finding representative data. ...
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Bayesian Joint Spike-and-Slab Graphical Lasso
In this article, we propose a new class of priors for Bayesian inference with multiple Gaussian graphical models. We introduce fully Bayesian treatments of two popular procedures, the group graphical lasso and the fused graphical lasso, and extend them to a continuous spike-and-slab framework to allow self-adaptive s...
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Variations on the theme of the uniform boundary condition
The uniform boundary condition in a normed chain complex asks for a uniform linear bound on fillings of null-homologous cycles. For the $\ell^1$-norm on the singular chain complex, Matsumoto and Morita established a characterisation of the uniform boundary condition in terms of bounded cohomology. In particular, spac...
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revisit: a Workflow Tool for Data Science
In recent years there has been widespread concern in the scientific community over a reproducibility crisis. Among the major causes that have been identified is statistical: In many scientific research the statistical analysis (including data preparation) suffers from a lack of transparency and methodological problem...
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Programmatically Interpretable Reinforcement Learning
We present a reinforcement learning framework, called Programmatically Interpretable Reinforcement Learning (PIRL), that is designed to generate interpretable and verifiable agent policies. Unlike the popular Deep Reinforcement Learning (DRL) paradigm, which represents policies by neural networks, PIRL represents pol...
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Kinetic Simulation of Collisional Magnetized Plasmas with Semi-Implicit Time Integration
Plasmas with varying collisionalities occur in many applications, such as tokamak edge regions, where the flows are characterized by significant variations in density and temperature. While a kinetic model is necessary for weakly-collisional high-temperature plasmas, high collisionality in colder regions render the e...
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VC-dimension of short Presburger formulas
We study VC-dimension of short formulas in Presburger Arithmetic, defined to have a bounded number of variables, quantifiers and atoms. We give both lower and upper bounds, which are tight up to a polynomial factor in the bit length of the formula.
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Real-time Traffic Accident Risk Prediction based on Frequent Pattern Tree
Traffic accident data are usually noisy, contain missing values, and heterogeneous. How to select the most important variables to improve real-time traffic accident risk prediction has become a concern of many recent studies. This paper proposes a novel variable selection method based on the Frequent Pattern tree (FP...
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Do Developers Update Their Library Dependencies? An Empirical Study on the Impact of Security Advisories on Library Migration
Third-party library reuse has become common practice in contemporary software development, as it includes several benefits for developers. Library dependencies are constantly evolving, with newly added features and patches that fix bugs in older versions. To take full advantage of third-party reuse, developers should...
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Is Smaller Better: A Proposal To Consider Bacteria For Biologically Inspired Modeling
Bacteria are easily characterizable model organisms with an impressively complicated set of capabilities. Among their capabilities is quorum sensing, a detailed cell-cell signaling system that may have a common origin with eukaryotic cell-cell signaling. Not only are the two phenomena similar, but quorum sensing, as ...
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A Bayesian Data Augmentation Approach for Learning Deep Models
Data augmentation is an essential part of the training process applied to deep learning models. The motivation is that a robust training process for deep learning models depends on large annotated datasets, which are expensive to be acquired, stored and processed. Therefore a reasonable alternative is to be able to a...
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Interpreting Embedding Models of Knowledge Bases: A Pedagogical Approach
Knowledge bases are employed in a variety of applications from natural language processing to semantic web search; alas, in practice their usefulness is hurt by their incompleteness. Embedding models attain state-of-the-art accuracy in knowledge base completion, but their predictions are notoriously hard to interpret...
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Parameterized complexity of machine scheduling: 15 open problems
Machine scheduling problems are a long-time key domain of algorithms and complexity research. A novel approach to machine scheduling problems are fixed-parameter algorithms. To stimulate this thriving research direction, we propose 15 open questions in this area whose resolution we expect to lead to the discovery of ...
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Potential Conditional Mutual Information: Estimators, Properties and Applications
The conditional mutual information I(X;Y|Z) measures the average information that X and Y contain about each other given Z. This is an important primitive in many learning problems including conditional independence testing, graphical model inference, causal strength estimation and time-series problems. In several ap...
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A new approach to divergences in quantum electrodynamics, concrete examples
An interesting attempt for solving infrared divergence problems via the theory of generalized wave operators was made by P. Kulish and L. Faddeev. Our method of using the ideas from the theory of generalized wave operators is essentially different. We assume that the unperturbed operator $A_0$ is known and that the s...
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Indefinite boundary value problems on graphs
We consider the spectral structure of indefinite second order boundary-value problems on graphs. A variational formulation for such boundary-value problems on graphs is given and we obtain both full and half-range completeness results. This leads to a max-min principle and as a consequence we can formulate an analogu...
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Integral curvatures of Finsler manifolds and applications
In this paper, we study the integral curvatures of Finsler manifolds. Some Bishop-Gromov relative volume comparisons and several Myers type theorems are obtained. We also establish a Gromov type precompactness theorem and a Yamaguchi type finiteness theorem. Furthermore, the isoperimetric and Sobolev constants of a c...
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L-functions and sharp resonances of infinite index congruence subgroups of $SL_2(\mathbb{Z})$
For convex co-compact subgroups of SL2(Z) we consider the "congruence subgroups" for p prime. We prove a factorization formula for the Selberg zeta function in term of L-functions related to irreducible representations of the Galois group SL2(Fp) of the covering, together with a priori bounds and analytic continuatio...
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An Enhanced Lumped Element Electrical Model of a Double Barrier Memristive Device
The massive parallel approach of neuromorphic circuits leads to effective methods for solving complex problems. It has turned out that resistive switching devices with a continuous resistance range are potential candidates for such applications. These devices are memristive systems - nonlinear resistors with memory. ...
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Non-perturbative positive Lyapunov exponent of Schrödinger equations and its applications to skew-shift
We first study the discrete Schrödinger equations with analytic potentials given by a class of transformations. It is shown that if the coupling number is large, then its logarithm equals approximately to the Lyapunov exponents. When the transformation becomes the skew-shift, we prove that the Lyapunov exponent is we...
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Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees
Greedy optimization methods such as Matching Pursuit (MP) and Frank-Wolfe (FW) algorithms regained popularity in recent years due to their simplicity, effectiveness and theoretical guarantees. MP and FW address optimization over the linear span and the convex hull of a set of atoms, respectively. In this paper, we co...
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Probing the accretion disc structure by the twin kHz QPOs and spins of neutron stars in LMXBs
We analyze the relation between the emission radii of twin kilohertz quasi-periodic oscillations (kHz QPOs) and the co-rotation radii of the 12 neutron star low mass X-ray binaries (NS-LMXBs) which are simultaneously detected with the twin kHz QPOs and NS spins. We find that the average co-rotation radius of these so...
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Can scientists and their institutions become their own open access publishers?
This article offers a personal perspective on the current state of academic publishing, and posits that the scientific community is beset with journals that contribute little valuable knowledge, overload the community's capacity for high-quality peer review, and waste resources. Open access publishing can offer solut...
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Character sums for elliptic curve densities
If $E$ is an elliptic curve over $\mathbb{Q}$, then it follows from work of Serre and Hooley that, under the assumption of the Generalized Riemann Hypothesis, the density of primes $p$ such that the group of $\mathbb{F}_p$-rational points of the reduced curve $\tilde{E}(\mathbb{F}_p)$ is cyclic can be written as an i...
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A monolithic fluid-structure interaction formulation for solid and liquid membranes including free-surface contact
A unified fluid-structure interaction (FSI) formulation is presented for solid, liquid and mixed membranes. Nonlinear finite elements (FE) and the generalized-alpha scheme are used for the spatial and temporal discretization. The membrane discretization is based on curvilinear surface elements that can describe large...
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Different Non-extensive Models for heavy-ion collisions
The transverse momentum ($p_T$) spectra from heavy-ion collisions at intermediate momenta are described by non-extensive statistical models. Assuming a fixed relative variance of the temperature fluctuating event by event or alternatively a fixed mean multiplicity in a negative binomial distribution (NBD), two differ...
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Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees
Toxicity prediction of chemical compounds is a grand challenge. Lately, it achieved significant progress in accuracy but using a huge set of features, implementing a complex blackbox technique such as a deep neural network, and exploiting enormous computational resources. In this paper, we strongly argue for the mode...
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Minmax Hierarchies and Minimal Surfaces in Manifolds
We introduce a general scheme that permits to generate successive min-max problems for producing critical points of higher and higher indices to Palais-Smale Functionals in Banach manifolds equipped with Finsler structures. We call the resulting tree of minmax problems a minmax hierarchy. Using the viscosity approach...
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Nonseparable Multinomial Choice Models in Cross-Section and Panel Data
Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models when the choice utilities are nonseparable in observed attributes and multidimensional unobserved heterogeneity with cross-section and pan...
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Corona limits of tilings : Periodic case
We study the limit shape of successive coronas of a tiling, which models the growth of crystals. We define basic terminologies and discuss the existence and uniqueness of corona limits, and then prove that corona limits are completely characterized by directional speeds. As an application, we give another proof that ...
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The Spatial Range of Conformity
Properties of galaxies like their absolute magnitude and their stellar mass content are correlated. These correlations are tighter for close pairs of galaxies, which is called galactic conformity. In hierarchical structure formation scenarios, galaxies form within dark matter halos. To explain the amplitude and the s...
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Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis
Stochastic Gradient Langevin Dynamics (SGLD) is a popular variant of Stochastic Gradient Descent, where properly scaled isotropic Gaussian noise is added to an unbiased estimate of the gradient at each iteration. This modest change allows SGLD to escape local minima and suffices to guarantee asymptotic convergence to...
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Multilevel preconditioner of Polynomial Chaos Method for quantifying uncertainties in a blood pump
More than 23 million people are suffered by Heart failure worldwide. Despite the modern transplant operation is well established, the lack of heart donations becomes a big restriction on transplantation frequency. With respect to this matter, ventricular assist devices (VADs) can play an important role in supporting ...
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Superradiant Mott Transition
The combination of strong correlation and emergent lattice can be achieved when quantum gases are confined in a superradiant Fabry-Perot cavity. In addition to the discoveries of exotic phases, such as density wave ordered Mott insulator and superfluid, a surprising kink structure is found in the slope of the cavity ...
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Communication via FRET in Nanonetworks of Mobile Proteins
A practical, biologically motivated case of protein complexes (immunoglobulin G and FcRII receptors) moving on the surface of mastcells, that are common parts of an immunological system, is investigated. Proteins are considered as nanomachines creating a nanonetwork. Accurate molecular models of the proteins and the ...
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Multivariate generalized Pareto distributions: parametrizations, representations, and properties
Multivariate generalized Pareto distributions arise as the limit distributions of exceedances over multivariate thresholds of random vectors in the domain of attraction of a max-stable distribution. These distributions can be parametrized and represented in a number of different ways. Moreover, generalized Pareto dis...
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Invertibility of spectral x-ray data with pileup--two dimension-two spectrum case
In the Alvarez-Macovski method, the line integrals of the x-ray basis set coefficients are computed from measurements with multiple spectra. An important question is whether the transformation from measurements to line integrals is invertible. This paper presents a proof that for a system with two spectra and a photo...
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Steinberg representations and harmonic cochains for split adjoint quasi-simple groups
Let $G$ be an adjoint quasi-simple group defined and split over a non-archimedean local field $K$. We prove that the dual of the Steinberg representation of $G$ is isomorphic to a certain space of harmonic cochains on the Bruhat-Tits building of $G$. The Steinberg representation is considered with coefficients in any...
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Lorentzian surfaces and the curvature of the Schmidt metric
The b-boundary is a mathematical tool used to attach a topological boundary to incomplete Lorentzian manifolds using a Riemaniann metric called the Schmidt metric on the frame bundle. In this paper, we give the general form of the Schmidt metric in the case of Lorentzian surfaces. Furthermore, we write the Ricci scal...
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Mixed Precision Solver Scalable to 16000 MPI Processes for Lattice Quantum Chromodynamics Simulations on the Oakforest-PACS System
Lattice Quantum Chromodynamics (Lattice QCD) is a quantum field theory on a finite discretized space-time box so as to numerically compute the dynamics of quarks and gluons to explore the nature of subatomic world. Solving the equation of motion of quarks (quark solver) is the most compute-intensive part of the latti...
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A spectral/hp element MHD solver
A new MHD solver, based on the Nektar++ spectral/hp element framework, is presented in this paper. The velocity and electric potential quasi-static MHD model is used. The Hartmann flow in plane channel and its stability, the Hartmann flow in rectangular duct, and the stability of Hunt's flow are explored as examples....
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Journalists' information needs, seeking behavior, and its determinants on social media
We describe the results of a qualitative study on journalists' information seeking behavior on social media. Based on interviews with eleven journalists along with a study of a set of university level journalism modules, we determined the categories of information need types that lead journalists to social media. We ...
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Fast Low-Rank Bayesian Matrix Completion with Hierarchical Gaussian Prior Models
The problem of low rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a...
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Emergence of superconductivity in the canonical heavy-electron metal YbRh2Si2
We report magnetic and calorimetric measurements down to T = 1 mK on the canonical heavy-electron metal YbRh2Si2. The data reveal the development of nuclear antiferromagnetic order slightly above 2 mK. The latter weakens the primary electronic antiferromagnetism, thereby paving the way for heavy-electron superconduct...
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Obtaining a Proportional Allocation by Deleting Items
We consider the following control problem on fair allocation of indivisible goods. Given a set $I$ of items and a set of agents, each having strict linear preference over the items, we ask for a minimum subset of the items whose deletion guarantees the existence of a proportional allocation in the remaining instance;...
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DeepFace: Face Generation using Deep Learning
We use CNNs to build a system that both classifies images of faces based on a variety of different facial attributes and generates new faces given a set of desired facial characteristics. After introducing the problem and providing context in the first section, we discuss recent work related to image generation in Se...
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High quality mesh generation using cross and asterisk fields: Application on coastal domains
This paper presents a method to generate high quality triangular or quadrilateral meshes that uses direction fields and a frontal point insertion strategy. Two types of direction fields are considered: asterisk fields and cross fields. With asterisk fields we generate high quality triangulations, while with cross fie...
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ELFI: Engine for Likelihood-Free Inference
Engine for Likelihood-Free Inference (ELFI) is a Python software library for performing likelihood-free inference (LFI). ELFI provides a convenient syntax for arranging components in LFI, such as priors, simulators, summaries or distances, to a network called ELFI graph. The components can be implemented in a wide va...
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Boosting Adversarial Attacks with Momentum
Deep neural networks are vulnerable to adversarial examples, which poses security concerns on these algorithms due to the potentially severe consequences. Adversarial attacks serve as an important surrogate to evaluate the robustness of deep learning models before they are deployed. However, most of existing adversar...
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Information spreading during emergencies and anomalous events
The most critical time for information to spread is in the aftermath of a serious emergency, crisis, or disaster. Individuals affected by such situations can now turn to an array of communication channels, from mobile phone calls and text messages to social media posts, when alerting social ties. These channels drast...
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Large-Scale Plant Classification with Deep Neural Networks
This paper discusses the potential of applying deep learning techniques for plant classification and its usage for citizen science in large-scale biodiversity monitoring. We show that plant classification using near state-of-the-art convolutional network architectures like ResNet50 achieves significant improvements i...
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Deep Reinforcement Learning for General Video Game AI
The General Video Game AI (GVGAI) competition and its associated software framework provides a way of benchmarking AI algorithms on a large number of games written in a domain-specific description language. While the competition has seen plenty of interest, it has so far focused on online planning, providing a forwar...
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Purely infinite labeled graph $C^*$-algebras
In this paper, we consider pure infiniteness of generalized Cuntz-Krieger algebras associated to labeled spaces $(E,\mathcal{L},\mathcal{E})$. It is shown that a $C^*$-algebra $C^*(E,\mathcal{L},\mathcal{E})$ is purely infinite in the sense that every nonzero hereditary subalgebra contains an infinite projection (we ...
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From safe screening rules to working sets for faster Lasso-type solvers
Convex sparsity-promoting regularizations are ubiquitous in modern statistical learning. By construction, they yield solutions with few non-zero coefficients, which correspond to saturated constraints in the dual optimization formulation. Working set (WS) strategies are generic optimization techniques that consist in...
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Exoplanet Radius Gap Dependence on Host Star Type
Exoplanets smaller than Neptune are numerous, but the nature of the planet populations in the 1-4 Earth radii range remains a mystery. The complete Kepler sample of Q1-Q17 exoplanet candidates shows a radius gap at ~ 2 Earth radii, as reported by us in January 2017 in LPSC conference abstract #1576 (Zeng et al. 2017)...
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Mapping the Invocation Structure of Online Political Interaction
The surge in political information, discourse, and interaction has been one of the most important developments in social media over the past several years. There is rich structure in the interaction among different viewpoints on the ideological spectrum. However, we still have only a limited analytical vocabulary for...
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Collective decision for open set recognition
In open set recognition (OSR), almost all existing methods are designed specially for recognizing individual instances, even these instances are collectively coming in batch. Recognizers in decision either reject or categorize them to some known class using empirically-set threshold. Thus the threshold plays a key ro...
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HARPS-N high spectral resolution observations of Cepheids I. The Baade-Wesselink projection factor of δ Cep revisited
The projection factor p is the key quantity used in the Baade-Wesselink (BW) method for distance determination; it converts radial velocities into pulsation velocities. Several methods are used to determine p, such as geometrical and hydrodynamical models or the inverse BW approach when the distance is known. We anal...
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Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US
The United States spends more than $1B each year on initiatives such as the American Community Survey (ACS), a labor-intensive door-to-door study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic factors. Although a comprehensive source of data, the lag betw...
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Gaussian Process Neurons Learn Stochastic Activation Functions
We propose stochastic, non-parametric activation functions that are fully learnable and individual to each neuron. Complexity and the risk of overfitting are controlled by placing a Gaussian process prior over these functions. The result is the Gaussian process neuron, a probabilistic unit that can be used as the bas...
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The short-term price impact of trades is universal
We analyze a proprietary dataset of trades by a single asset manager, comparing their price impact with that of the trades of the rest of the market. In the context of a linear propagator model we find no significant difference between the two, suggesting that both the magnitude and time dependence of impact are univ...
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Questions on mod p representations of reductive p-adic groups
This is a list of questions raised by our joint work arXiv:1412.0737 and its sequels.
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Filamentary superconductivity in semiconducting policrystalline ZrSe2 compound with Zr vacancies
ZrSe2 is a band semiconductor studied long time ago. It has interesting electronic properties, and because its layers structure can be intercalated with different atoms to change some of the physical properties. In this investigation we found that Zr deficiencies alter the semiconducting behavior and the compound can...
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Stochastic Block Model Reveals the Map of Citation Patterns and Their Evolution in Time
In this study we map out the large-scale structure of citation networks of science journals and follow their evolution in time by using stochastic block models (SBMs). The SBM fitting procedures are principled methods that can be used to find hierarchical grouping of journals into blocks that show similar incoming an...
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Limits on the anomalous speed of gravitational waves from binary pulsars
A large class of modified theories of gravity used as models for dark energy predict a propagation speed for gravitational waves which can differ from the speed of light. This difference of propagations speeds for photons and gravitons has an impact in the emission of gravitational waves by binary systems. Thus, we r...
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Central limit theorems for entropy-regularized optimal transport on finite spaces and statistical applications
The notion of entropy-regularized optimal transport, also known as Sinkhorn divergence, has recently gained popularity in machine learning and statistics, as it makes feasible the use of smoothed optimal transportation distances for data analysis. The Sinkhorn divergence allows the fast computation of an entropically...
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Inference for Stochastically Contaminated Variable Length Markov Chains
In this paper, we present a methodology to estimate the parameters of stochastically contaminated models under two contamination regimes. In both regimes, we assume that the original process is a variable length Markov chain that is contaminated by a random noise. In the first regime we consider that the random noise...
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Variable-Length Resolvability for General Sources and Channels
We introduce the problem of variable-length source resolvability, where a given target probability distribution is approximated by encoding a variable-length uniform random number, and the asymptotically minimum average length rate of the uniform random numbers, called the (variable-length) resolvability, is investig...
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Diattenuation of Brain Tissue and its Impact on 3D Polarized Light Imaging
3D-Polarized Light Imaging (3D-PLI) reconstructs nerve fibers in histological brain sections by measuring their birefringence. This study investigates another effect caused by the optical anisotropy of brain tissue - diattenuation. Based on numerical and experimental studies and a complete analytical description of t...
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Higgs Modes in the Pair Density Wave Superconducting State
The pair density wave (PDW) superconducting state has been proposed to explain the layer- decoupling effect observed in the compound La$_{2-x}$Ba$_x$CuO$_4$ at $x=1/8$ (Phys. Rev. Lett. 99, 127003). In this state the superconducting order parameter is spatially modulated, in contrast with the usual superconducting (S...
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A Serverless Tool for Platform Agnostic Computational Experiment Management
Neuroscience has been carried into the domain of big data and high performance computing (HPC) on the backs of initiatives in data collection and an increasingly compute-intensive tools. While managing HPC experiments requires considerable technical acumen, platforms and standards have been developed to ease this bur...
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Traveling-wave parametric amplifier based on three-wave mixing in a Josephson metamaterial
We have developed a recently proposed Josephson traveling-wave parametric amplifier with three-wave mixing [A. B. Zorin, Phys. Rev. Applied 6, 034006, 2016]. The amplifier consists of a microwave transmission line formed by a serial array of nonhysteretic one-junction SQUIDs. These SQUIDs are flux-biased in a way tha...
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Measuring LDA Topic Stability from Clusters of Replicated Runs
Background: Unstructured and textual data is increasing rapidly and Latent Dirichlet Allocation (LDA) topic modeling is a popular data analysis methods for it. Past work suggests that instability of LDA topics may lead to systematic errors. Aim: We propose a method that relies on replicated LDA runs, clustering, and ...
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Continuum Foreground Polarization and Na~I Absorption in Type Ia SNe
We present a study of the continuum polarization over the 400--600 nm range of 19 Type Ia SNe obtained with FORS at the VLT. We separate them in those that show Na I D lines at the velocity of their hosts and those that do not. Continuum polarization of the sodium sample near maximum light displays a broad range of v...
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Toward Faultless Content-Based Playlists Generation for Instrumentals
This study deals with content-based musical playlists generation focused on Songs and Instrumentals. Automatic playlist generation relies on collaborative filtering and autotagging algorithms. Autotagging can solve the cold start issue and popularity bias that are critical in music recommender systems. However, autot...
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Direct observation of the band gap transition in atomically thin ReS$_2$
ReS$_2$ is considered as a promising candidate for novel electronic and sensor applications. The low crystal symmetry of the van der Waals compound ReS$_2$ leads to a highly anisotropic optical, vibrational, and transport behavior. However, the details of the electronic band structure of this fascinating material are...
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Lattice embeddings between types of fuzzy sets. Closed-valued fuzzy sets
In this paper we deal with the problem of extending Zadeh's operators on fuzzy sets (FSs) to interval-valued (IVFSs), set-valued (SVFSs) and type-2 (T2FSs) fuzzy sets. Namely, it is known that seeing FSs as SVFSs, or T2FSs, whose membership degrees are singletons is not order-preserving. We then describe a family of ...
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Coupling of Magneto-Thermal and Mechanical Superconducting Magnet Models by Means of Mesh-Based Interpolation
In this paper we present an algorithm for the coupling of magneto-thermal and mechanical finite element models representing superconducting accelerator magnets. The mechanical models are used during the design of the mechanical structure as well as the optimization of the magnetic field quality under nominal conditio...
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Converging expansions for Lipschitz self-similar perforations of a plane sector
In contrast with the well-known methods of matching asymptotics and multiscale (or compound) asymptotics, the " functional analytic approach " of Lanza de Cristoforis (Analysis 28, 2008) allows to prove convergence of expansions around interior small holes of size $\epsilon$ for solutions of elliptic boundary value p...
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A Viral Timeline Branching Process to study a Social Network
Bio-inspired paradigms are proving to be useful in analyzing propagation and dissemination of information in networks. In this paper we explore the use of multi-type branching processes to analyse viral properties of content in a social network, with and without competition from other sources. We derive and compute v...
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Algorithmic Bio-surveillance For Precise Spatio-temporal Prediction of Zoonotic Emergence
Viral zoonoses have emerged as the key drivers of recent pandemics. Human infection by zoonotic viruses are either spillover events -- isolated infections that fail to cause a widespread contagion -- or species jumps, where successful adaptation to the new host leads to a pandemic. Despite expensive bio-surveillance ...
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Practical Machine Learning for Cloud Intrusion Detection: Challenges and the Way Forward
Operationalizing machine learning based security detections is extremely challenging, especially in a continuously evolving cloud environment. Conventional anomaly detection does not produce satisfactory results for analysts that are investigating security incidents in the cloud. Model evaluation alone presents its o...
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SOI RF Switch for Wireless Sensor Network
The objective of this research was to design a 0-5 GHz RF SOI switch, with 0.18um power Jazz SOI technology by using Cadence software, for health care applications. This paper introduces the design of a RF switch implemented in shunt-series topology. An insertion loss of 0.906 dB and an isolation of 30.95 dB were obt...
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The Pentagonal Inequality
Given a positive linear combination of five (respectively seven) cosines, where the angles are positive and sum to pi, the aim of this article is to express the sharp bound of the combination as a Positive Real Fraction in the coefficients (hence cosine-free). The method uses algebraic and arithmetic manipulations wi...
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The Landscape of Deep Learning Algorithms
This paper studies the landscape of empirical risk of deep neural networks by theoretically analyzing its convergence behavior to the population risk as well as its stationary points and properties. For an $l$-layer linear neural network, we prove its empirical risk uniformly converges to its population risk at the r...
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The effect of the environment on the structure, morphology and star-formation history of intermediate-redshift galaxies
With the aim of understanding the effect of the environment on the star formation history and morphological transformation of galaxies, we present a detailed analysis of the colour, morphology and internal structure of cluster and field galaxies at $0.4 \le z \le 0.8$. We use {\em HST} data for over 500 galaxies from...
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Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning
Recommender systems play a crucial role in mitigating the problem of information overload by suggesting users' personalized items or services. The vast majority of traditional recommender systems consider the recommendation procedure as a static process and make recommendations following a fixed strategy. In this pap...
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Accumulated Gradient Normalization
This work addresses the instability in asynchronous data parallel optimization. It does so by introducing a novel distributed optimizer which is able to efficiently optimize a centralized model under communication constraints. The optimizer achieves this by pushing a normalized sequence of first-order gradients to a ...
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An Optimal Algorithm for Changing from Latitudinal to Longitudinal Formation of Autonomous Aircraft Squadrons
This work presents an algorithm for changing from latitudinal to longitudinal formation of autonomous aircraft squadrons. The maneuvers are defined dynamically by using a predefined set of 3D basic maneuvers. This formation changing is necessary when the squadron has to perform tasks which demand both formations, suc...
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