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Predictive and Prescriptive Analytics for Location Selection of Add-on Retail Products
In this paper, we study an analytical approach to selecting expansion locations for retailers selling add-on products whose demand is derived from the demand of another base product. Demand for the add-on product is realized only as a supplement to the demand of the base product. In our context, either of the two pro...
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Algebraic characterization of regular fractions under level permutations
In this paper we study the behavior of the fractions of a factorial design under permutations of the factor levels. We focus on the notion of regular fraction and we introduce methods to check whether a given symmetric orthogonal array can or can not be transformed into a regular fraction by means of suitable permuta...
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Biomedical Event Trigger Identification Using Bidirectional Recurrent Neural Network Based Models
Biomedical events describe complex interactions between various biomedical entities. Event trigger is a word or a phrase which typically signifies the occurrence of an event. Event trigger identification is an important first step in all event extraction methods. However many of the current approaches either rely on ...
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Modern-day Universities and Regional Development
Nowadays it is quite evident that knowledge-based society necessarily involves the revaluation of human and intangible assets, as the advancement of local economies significantly depend on the qualitative and quantitative characteristics of human capital[Lundvall, 2004]. As we can instantaneously link the universitie...
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Method of Reduction of Variables for Bilinear Matrix Inequality Problems in System and Control Designs
Bilinear matrix inequality (BMI) problems in system and control designs are investigated in this paper. A solution method of reduction of variables (MRVs) is proposed. This method consists of a principle of variable classification, a procedure for problem transformation, and a hybrid algorithm that combines determini...
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Nonlinear transport associated with spin-density-wave dynamics in Ca$_3$Co$_{4}$O$_9$
We have carried out the transient nonlinear transport measurements on the layered cobalt oxide Ca$_3$Co$_{4}$O$_9$, in which a spin density wave (SDW) transition is proposed at $T_{\rm SDW} \simeq 30$ K. We find that, below $T_{\rm SDW}$, the electrical conductivity systematically varies with both the applied current...
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Bayesian Compression for Deep Learning
Compression and computational efficiency in deep learning have become a problem of great significance. In this work, we argue that the most principled and effective way to attack this problem is by adopting a Bayesian point of view, where through sparsity inducing priors we prune large parts of the network. We introd...
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The Observability Concept in a Class of Hybrid Control systems
In the discrete modeling approach for hybrid control systems, the continuous plant is reduced to a discrete event approximation, called the DES-plant, that is governed by a discrete event system, representing the controller. The observability of the DES-plant model is crucial for the synthesis of the controller and f...
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Towards a More Reliable Privacy-preserving Recommender System
This paper proposes a privacy-preserving distributed recommendation framework, Secure Distributed Collaborative Filtering (SDCF), to preserve the privacy of value, model and existence altogether. That says, not only the ratings from the users to the items, but also the existence of the ratings as well as the learned ...
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A study of posture judgement on vehicles using wearable acceleration sensor
We study methods to estimate drivers' posture in vehicles using acceleration data of wearable sensor and conduct field tests. To prevent fatal accidents, demands for safety management of bus and taxi are high. However, acceleration of vehicles is added to wearable sensor in vehicles. Therefore, we study methods to es...
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Smoothed nonparametric two-sample tests
We propose new smoothed median and the Wilcoxon's rank sum test. As is pointed out by Maesono et al.(2016), some nonparametric discrete tests have a problem with their significance probability. Because of this problem, the selection of the median and the Wilcoxon's test can be biased too, however, we show new smoothe...
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The Complexity of Graph-Based Reductions for Reachability in Markov Decision Processes
We study the never-worse relation (NWR) for Markov decision processes with an infinite-horizon reachability objective. A state q is never worse than a state p if the maximal probability of reaching the target set of states from p is at most the same value from q, regard- less of the probabilities labelling the transi...
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A stack-vector routing protocol for automatic tunneling
In a network, a tunnel is a part of a path where a protocol is encapsulated in another one. A tunnel starts with an encapsulation and ends with the corresponding decapsulation. Several tunnels can be nested at some stage, forming a protocol stack. Tunneling is very important nowadays and it is involved in several tas...
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Using of heterogeneous corpora for training of an ASR system
The paper summarizes the development of the LVCSR system built as a part of the Pashto speech-translation system at the SCALE (Summer Camp for Applied Language Exploration) 2015 workshop on "Speech-to-text-translation for low-resource languages". The Pashto language was chosen as a good "proxy" low-resource language,...
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Inferring Narrative Causality between Event Pairs in Films
To understand narrative, humans draw inferences about the underlying relations between narrative events. Cognitive theories of narrative understanding define these inferences as four different types of causality, that include pairs of events A, B where A physically causes B (X drop, X break), to pairs of events where...
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On Hom-Gerstenhaber algebras and Hom-Lie algebroids
We define the notion of hom-Batalin-Vilkovisky algebras and strong differential hom-Gerstenhaber algebras as a special class of hom-Gerstenhaber algebras and provide canonical examples associated to some well-known hom-structures. Representations of a hom-Lie algebroid on a hom-bundle are defined and a cohomology of ...
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Global existence in the 1D quasilinear parabolic-elliptic chemotaxis system with critical nonlinearity
The paper should be viewed as complement of an earlier result in [8]. In the paper just mentioned it is shown that 1d case of a quasilinear parabolic-elliptic Keller-Segel system is very special. Namely, unlike in higher dimensions, there is no critical nonlinearity. Indeed, for the nonlinear diffusion of the form 1/...
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Supercongruences between truncated ${}_3F_2$ hypergeometric series
We establish four supercongruences between truncated ${}_3F_2$ hypergeometric series involving $p$-adic Gamma functions, which extend some of the Rodriguez-Villegas supercongruences.
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Indoor Localization Using Visible Light Via Fusion Of Multiple Classifiers
A multiple classifiers fusion localization technique using received signal strengths (RSSs) of visible light is proposed, in which the proposed system transmits different intensity modulated sinusoidal signals by LEDs and the signals received by a Photo Diode (PD) placed at various grid points. First, we obtain some ...
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Node Centralities and Classification Performance for Characterizing Node Embedding Algorithms
Embedding graph nodes into a vector space can allow the use of machine learning to e.g. predict node classes, but the study of node embedding algorithms is immature compared to the natural language processing field because of a diverse nature of graphs. We examine the performance of node embedding algorithms with res...
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Data Fusion Reconstruction of Spatially Embedded Complex Networks
We introduce a kernel Lasso (kLasso) optimization that simultaneously accounts for spatial regularity and network sparsity to reconstruct spatial complex networks from data. Through a kernel function, the proposed approach exploits spatial embedding distances to penalize overabundance of spatially long-distance conne...
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Reconstruction from Periodic Nonlinearities, With Applications to HDR Imaging
We consider the problem of reconstructing signals and images from periodic nonlinearities. For such problems, we design a measurement scheme that supports efficient reconstruction; moreover, our method can be adapted to extend to compressive sensing-based signal and image acquisition systems. Our techniques can be po...
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Multirole Logic (Extended Abstract)
We identify multirole logic as a new form of logic in which conjunction/disjunction is interpreted as an ultrafilter on the power set of some underlying set (of roles) and the notion of negation is generalized to endomorphisms on this underlying set. We formalize both multirole logic (MRL) and linear multirole logic ...
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Interpreting Classifiers through Attribute Interactions in Datasets
In this work we present the novel ASTRID method for investigating which attribute interactions classifiers exploit when making predictions. Attribute interactions in classification tasks mean that two or more attributes together provide stronger evidence for a particular class label. Knowledge of such interactions ma...
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A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction
In this paper, we propose a modified Levy jump diffusion model with market sentiment memory for stock prices, where the market sentiment comes from data mining implementation using Tweets on Twitter. We take the market sentiment process, which has memory, as the signal of Levy jumps in the stock price. An online lear...
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Testing approximate predictions of displacements of cosmological dark matter halos
We present a test to quantify how well some approximate methods, designed to reproduce the mildly non-linear evolution of perturbations, are able to reproduce the clustering of DM halos once the grouping of particles into halos is defined and kept fixed. The following methods have been considered: Lagrangian Perturba...
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Efficient and Secure Routing Protocol for WSN-A Thesis
Advances in Wireless Sensor Network (WSN) have provided the availability of small and low-cost sensors with the capability of sensing various types of physical and environmental conditions, data processing, and wireless communication. Since WSN protocols are application specific, the focus has been given to the routi...
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Jackknife variance estimation for common mean estimators under ordered variances and general two-sample statistics
Samples with a common mean but possibly different, ordered variances arise in various fields such as interlaboratory experiments, field studies or the analysis of sensor data. Estimators for the common mean under ordered variances typically employ random weights, which depend on the sample means and the unbiased vari...
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ISM properties of a Massive Dusty Star-Forming Galaxy discovered at z ~ 7
We report the discovery and constrain the physical conditions of the interstellar medium of the highest-redshift millimeter-selected dusty star-forming galaxy (DSFG) to date, SPT-S J031132-5823.4 (hereafter SPT0311-58), at $z=6.900 +/- 0.002$. SPT0311-58 was discovered via its 1.4mm thermal dust continuum emission in...
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A convex formulation of traffic dynamics on transportation networks
This article proposes a numerical scheme for computing the evolution of vehicular traffic on a road network over a finite time horizon. The traffic dynamics on each link is modeled by the Hamilton-Jacobi (HJ) partial differential equation (PDE), which is an equivalent form of the Lighthill-Whitham-Richards PDE. The m...
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Computational and informatics advances for reproducible data analysis in neuroimaging
The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosystem for open and transparent science that has emerged within the human neuroimaging community. We discuss the range of open data sharing ...
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HPD-invariance of the Tate, Beilinson and Parshin conjectures
We prove that the Tate, Beilinson and Parshin conjectures are invariant under Homological Projective Duality (=HPD). As an application, we obtain a proof of these celebrated conjectures (as well as of the strong form of the Tate conjecture) in the new cases of linear sections of determinantal varieties and complete i...
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Multi-dueling Bandits with Dependent Arms
The dueling bandits problem is an online learning framework for learning from pairwise preference feedback, and is particularly well-suited for modeling settings that elicit subjective or implicit human feedback. In this paper, we study the problem of multi-dueling bandits with dependent arms, which extends the origi...
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New constraints on the millimetre emission of six debris disks
The presence of dusty debris around main sequence stars denotes the existence of planetary systems. Such debris disks are often identified by the presence of excess continuum emission at infrared and (sub-)millimetre wavelengths, with measurements at longer wavelengths tracing larger and cooler dust grains. The expon...
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Bosonic integer quantum Hall effect as topological pumping
Based on a quasi-one-dimensional limit of quantum Hall states on a thin torus, we construct a model of interaction-induced topological pumping which mimics the Hall response of the bosonic integer quantum Hall (BIQH) state. The quasi-one-dimensional counterpart of the BIQH state is identified as the Haldane phase com...
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Connected Vehicular Transportation: Data Analytics and Traffic-dependent Networking
With onboard operating systems becoming increasingly common in vehicles, the real-time broadband infotainment and Intelligent Transportation System (ITS) service applications in fast-motion vehicles become ever demanding, which are highly expected to significantly improve the efficiency and safety of our daily on-roa...
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Strongly ergodic equivalence relations: spectral gap and type III invariants
We obtain a spectral gap characterization of strongly ergodic equivalence relations on standard measure spaces. We use our spectral gap criterion to prove that a large class of skew-product equivalence relations arising from measurable $1$-cocycles with values into locally compact abelian groups are strongly ergodic....
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On-the-fly Operation Batching in Dynamic Computation Graphs
Dynamic neural network toolkits such as PyTorch, DyNet, and Chainer offer more flexibility for implementing models that cope with data of varying dimensions and structure, relative to toolkits that operate on statically declared computations (e.g., TensorFlow, CNTK, and Theano). However, existing toolkits - both stat...
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Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers
Clustering is the process of finding and analyzing underlying group structure in data. In recent years, data as become increasingly higher dimensional and, therefore, an increased need has arisen for dimension reduction techniques for clustering. Although such techniques are firmly established in the literature for m...
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Transfer Learning to Learn with Multitask Neural Model Search
Deep learning models require extensive architecture design exploration and hyperparameter optimization to perform well on a given task. The exploration of the model design space is often made by a human expert, and optimized using a combination of grid search and search heuristics over a large space of possible choic...
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Hierarchical Game-Theoretic Planning for Autonomous Vehicles
The actions of an autonomous vehicle on the road affect and are affected by those of other drivers, whether overtaking, negotiating a merge, or avoiding an accident. This mutual dependence, best captured by dynamic game theory, creates a strong coupling between the vehicle's planning and its predictions of other driv...
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Observable dictionary learning for high-dimensional statistical inference
This paper introduces a method for efficiently inferring a high-dimensional distributed quantity from a few observations. The quantity of interest (QoI) is approximated in a basis (dictionary) learned from a training set. The coefficients associated with the approximation of the QoI in the basis are determined by min...
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Counterintuitive Reconstruction of the Polar O-Terminated ZnO Surface With Zinc Vacancies and Hydrogen
Understanding the structure of ZnO surface reconstructions and their resultant properties is crucial to the rational design of ZnO-containing devices ranging from optoelectronics to catalysts. Here, we are motivated by recent experimental work which showed a new surface reconstruction containing Zn vacancies ordered ...
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A Finite-Tame-Wild Trichotomy Theorem for Tensor Diagrams
In this paper, we consider the problem of determining when two tensor networks are equivalent under a heterogeneous change of basis. In particular, to a string diagram in a certain monoidal category (which we call tensor diagrams), we formulate an associated abelian category of representations. Each representation co...
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Decomposing the Quantile Ratio Index with applications to Australian income and wealth data
The quantile ratio index introduced by Prendergast and Staudte 2017 is a simple and effective measure of relative inequality for income data that is resistant to outliers. It measures the average relative distance of a randomly chosen income from its symmetric quantile. Another useful property of this index is invest...
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Metamorphic Moving Horizon Estimation
This paper considers a practical scenario where a classical estimation method might have already been implemented on a certain platform when one tries to apply more advanced techniques such as moving horizon estimation (MHE). We are interested to utilize MHE to upgrade, rather than completely discard, the existing es...
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Erosion distance for generalized persistence modules
The persistence diagram of Cohen-Steiner, Edelsbrunner, and Harer was recently generalized by Patel to the case of constructible persistence modules with values in a symmetric monoidal category with images. Patel also introduced a distance for persistence diagrams, the erosion distance. Motivated by this work, we ext...
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Efficient Adjoint Computation for Wavelet and Convolution Operators
First-order optimization algorithms, often preferred for large problems, require the gradient of the differentiable terms in the objective function. These gradients often involve linear operators and their adjoints, which must be applied rapidly. We consider two example problems and derive methods for quickly evaluat...
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RCD: Rapid Close to Deadline Scheduling for Datacenter Networks
Datacenter-based Cloud Computing services provide a flexible, scalable and yet economical infrastructure to host online services such as multimedia streaming, email and bulk storage. Many such services perform geo-replication to provide necessary quality of service and reliability to users resulting in frequent large...
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Real representations of finite symplectic groups over fields of characteristic two
We prove that when $q$ is a power of $2$, every complex irreducible representation of $\mathrm{Sp}(2n, \mathbb{F}_q)$ may be defined over the real numbers, that is, all Frobenius-Schur indicators are 1. We also obtain a generating function for the sum of the degrees of the unipotent characters of $\mathrm{Sp}(2n, \ma...
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Risk measure estimation for $β$-mixing time series and applications
In this paper, we discuss the application of extreme value theory in the context of stationary $\beta$-mixing sequences that belong to the Fréchet domain of attraction. In particular, we propose a methodology to construct bias-corrected tail estimators. Our approach is based on the combination of two estimators for t...
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Transfer entropy between communities in complex networks
With the help of transfer entropy, we analyze information flows between communities of complex networks. We show that the transfer entropy provides a coherent description of interactions between communities, including non-linear interactions. To put some flesh on the bare bones, we analyze transfer entropies between ...
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Disentangled VAE Representations for Multi-Aspect and Missing Data
Many problems in machine learning and related application areas are fundamentally variants of conditional modeling and sampling across multi-aspect data, either multi-view, multi-modal, or simply multi-group. For example, sampling from the distribution of English sentences conditioned on a given French sentence or sa...
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On the spectral geometry of manifolds with conic singularities
In the previous article we derived a detailed asymptotic expansion of the heat trace for the Laplace-Beltrami operator on functions on manifolds with conic singularities. In this article we investigate how the terms in the expansion reflect the geometry of the manifold. Since the general expansion contains a logarith...
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Neural Task Programming: Learning to Generalize Across Hierarchical Tasks
In this work, we propose a novel robot learning framework called Neural Task Programming (NTP), which bridges the idea of few-shot learning from demonstration and neural program induction. NTP takes as input a task specification (e.g., video demonstration of a task) and recursively decomposes it into finer sub-task s...
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Discovery of potential collaboration networks from open knowledge sources
Scientific publishing conveys the outputs of an academic or research activity, in this sense; it also reflects the efforts and issues in which people engage. To identify potential collaborative networks one of the simplest approaches is to leverage the co-authorship relations. In this approach, semantic and hierarchi...
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Towards Planning and Control of Hybrid Systems with Limit Cycle using LQR Trees
We present a multi-query recovery policy for a hybrid system with goal limit cycle. The sample trajectories and the hybrid limit cycle of the dynamical system are stabilized using locally valid Time Varying LQR controller policies which probabilistically cover a bounded region of state space. The original LQR Tree al...
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Clustering with t-SNE, provably
t-distributed Stochastic Neighborhood Embedding (t-SNE), a clustering and visualization method proposed by van der Maaten & Hinton in 2008, has rapidly become a standard tool in a number of natural sciences. Despite its overwhelming success, there is a distinct lack of mathematical foundations and the inner workings ...
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The Observable Properties of Cool Winds from Galaxies, AGN, and Star Clusters. I. Theoretical Framework
Winds arising from galaxies, star clusters, and active galactic nuclei are crucial players in star and galaxy formation, but it has proven remarkably difficult to use observations of them to determine physical properties of interest, particularly mass fluxes. Much of the difficulty stems from a lack of a theory that ...
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Noise Flooding for Detecting Audio Adversarial Examples Against Automatic Speech Recognition
Neural models enjoy widespread use across a variety of tasks and have grown to become crucial components of many industrial systems. Despite their effectiveness and extensive popularity, they are not without their exploitable flaws. Initially applied to computer vision systems, the generation of adversarial examples ...
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Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems
In this paper, we propose a novel ranking framework for collaborative filtering with the overall aim of learning user preferences over items by minimizing a pairwise ranking loss. We show the minimization problem involves dependent random variables and provide a theoretical analysis by proving the consistency of the ...
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On the Sublinear Regret of Distributed Primal-Dual Algorithms for Online Constrained Optimization
This paper introduces consensus-based primal-dual methods for distributed online optimization where the time-varying system objective function $f_t(\mathbf{x})$ is given as the sum of local agents' objective functions, i.e., $f_t(\mathbf{x}) = \sum_i f_{i,t}(\mathbf{x}_i)$, and the system constraint function $\mathbf...
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Reliability study of proportional odds family of discrete distributions
The proportional odds model gives a method of generating new family of distributions by adding a parameter, called tilt parameter, to expand an existing family of distributions. The new family of distributions so obtained is known as Marshall-Olkin family of distributions or Marshall-Olkin extended distributions. In ...
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Global Orientifolded Quivers with Inflation
We describe global embeddings of fractional D3 branes at orientifolded singularities in type IIB flux compactifications. We present an explicit Calabi-Yau example where the chiral visible sector lives on a local orientifolded quiver while non-perturbative effects, $\alpha'$ corrections and a T-brane hidden sector lea...
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Discretization of Springer fibers
Consider a nilpotent element e in a simple complex Lie algebra. The Springer fibre corresponding to e admits a discretization (discrete analogue) introduced by the author in 1999. In this paper we propose a conjectural description of that discretization which is more amenable to computation.
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On the Underapproximation of Reach Sets of Abstract Continuous-Time Systems
We consider the problem of proving that each point in a given set of states ("target set") can indeed be reached by a given nondeterministic continuous-time dynamical system from some initial state. We consider this problem for abstract continuous-time models that can be concretized as various kinds of continuous and...
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A Bayesian nonparametric approach to log-concave density estimation
The estimation of a log-concave density on $\mathbb{R}$ is a canonical problem in the area of shape-constrained nonparametric inference. We present a Bayesian nonparametric approach to this problem based on an exponentiated Dirichlet process mixture prior and show that the posterior distribution converges to the log-...
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A Complete Characterization of the 1-Dimensional Intrinsic Cech Persistence Diagrams for Metric Graphs
Metric graphs are special types of metric spaces used to model and represent simple, ubiquitous, geometric relations in data such as biological networks, social networks, and road networks. We are interested in giving a qualitative description of metric graphs using topological summaries. In particular, we provide a ...
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Critical exponent $ω$ in the Gross-Neveu-Yukawa model at $O(1/N)$
The critcal exponent $\omega$ is evaluated at $O(1/N)$ in $d$-dimensions in the Gross-Neveu model using the large $N$ critical point formalism. It is shown to be in agreement with the recently determined three loop $\beta$-functions of the Gross-Neveu-Yukawa model in four dimensions. The same exponent is computed for...
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Path Planning for Multiple Heterogeneous Unmanned Vehicles with Uncertain Service Times
This article presents a framework and develops a formulation to solve a path planning problem for multiple heterogeneous Unmanned Vehicles (UVs) with uncertain service times for each vehicle--target pair. The vehicles incur a penalty proportional to the duration of their total service time in excess of a preset const...
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Dropout-based Active Learning for Regression
Active learning is relevant and challenging for high-dimensional regression models when the annotation of the samples is expensive. Yet most of the existing sampling methods cannot be applied to large-scale problems, consuming too much time for data processing. In this paper, we propose a fast active learning algorit...
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Modeling Human Categorization of Natural Images Using Deep Feature Representations
Over the last few decades, psychologists have developed sophisticated formal models of human categorization using simple artificial stimuli. In this paper, we use modern machine learning methods to extend this work into the realm of naturalistic stimuli, enabling human categorization to be studied over the complex vi...
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BARCHAN: Blob Alignment for Robust CHromatographic ANalysis
Comprehensive Two dimensional gas chromatography (GCxGC) plays a central role into the elucidation of complex samples. The automation of the identification of peak areas is of prime interest to obtain a fast and repeatable analysis of chromatograms. To determine the concentration of compounds or pseudo-compounds, tem...
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Homogeneity Pursuit in Single Index Models based Panel Data Analysis
Panel data analysis is an important topic in statistics and econometrics. Traditionally, in panel data analysis, all individuals are assumed to share the same unknown parameters, e.g. the same coefficients of covariates when the linear models are used, and the differences between the individuals are accounted for by ...
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Feeding vs. Falling: The growth and collapse of molecular clouds in a turbulent interstellar medium
In order to understand the origin of observed molecular cloud properties, it is critical to understand how clouds interact with their environments during their formation, growth, and collapse. It has been suggested that accretion-driven turbulence can maintain clouds in a highly turbulent state, preventing runaway co...
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Complex waveguide based on a magneto-optic layer and a dielectric photonic crystal
We theoretically investigate the dispersion and polarization properties of the electromagnetic waves in a multi-layered structure composed of a magneto-optic waveguide on dielectric substrate covered by one-dimensional dielectric photonic crystal. The numerical analysis of such a complex structure shows polarization ...
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Discriminants of complete intersection space curves
In this paper, we develop a new approach to the discrimi-nant of a complete intersection curve in the 3-dimensional projective space. By relying on the resultant theory, we first prove a new formula that allows us to define this discrimi-nant without ambiguity and over any commutative ring, in particular in any chara...
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On the Characteristic and Permanent Polynomials of a Matrix
There is a digraph corresponding to every square matrix over $\mathbb{C}$. We generate a recurrence relation using the Laplace expansion to calculate the characteristic, and permanent polynomials of a square matrix. Solving this recurrence relation, we found that the characteristic, and permanent polynomials can be c...
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A bulk-boundary correspondence for dynamical phase transitions in one-dimensional topological insulators and superconductors
We study the Loschmidt echo for quenches in open one-dimensional lattice models with symmetry protected topological phases. For quenches where dynamical quantum phase transitions do occur we find that cusps in the bulk return rate at critical times tc are associated with sudden changes in the boundary contribution. F...
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The Consciousness Prior
A new prior is proposed for representation learning, which can be combined with other priors in order to help disentangling abstract factors from each other. It is inspired by the phenomenon of consciousness seen as the formation of a low-dimensional combination of a few concepts constituting a conscious thought, i.e...
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Multi-Scale Pipeline for the Search of String-Induced CMB Anisotropies
We propose a multi-scale edge-detection algorithm to search for the Gott-Kaiser-Stebbins imprints of a cosmic string (CS) network on the Cosmic Microwave Background (CMB) anisotropies. Curvelet decomposition and extended Canny algorithm are used to enhance the string detectability. Various statistical tools are then ...
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A simultaneous generalization of the theorems of Chevalley-Warning and Morlaye
Inspired by recent work of I. Baoulina, we give a simultaneous generalization of the theorems of Chevalley-Warning and Morlaye.
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Some Time-changed fractional Poisson processes
In this paper, we study the fractional Poisson process (FPP) time-changed by an independent Lévy subordinator and the inverse of the Lévy subordinator, which we call TCFPP-I and TCFPP-II, respectively. Various distributional properties of these processes are established. We show that, under certain conditions, the TC...
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Fast algorithm of adaptive Fourier series
Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in ...
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Hybrid Indexes to Expedite Spatial-Visual Search
Due to the growth of geo-tagged images, recent web and mobile applications provide search capabilities for images that are similar to a given query image and simultaneously within a given geographical area. In this paper, we focus on designing index structures to expedite these spatial-visual searches. We start by ba...
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Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography
Electron Cryo-Tomography (ECT) enables 3D visualization of macromolecule structure inside single cells. Macromolecule classification approaches based on convolutional neural networks (CNN) were developed to separate millions of macromolecules captured from ECT systematically. However, given the fast accumulation of E...
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Low quasiparticle coherence temperature in the one band-Hubbard model: A slave-boson approach
We use the Kotliar-Ruckenstein slave-boson formalism to study the temperature dependence of paramagnetic phases of the one-band Hubbard model for a variety of band structures. We calculate the Fermi liquid quasiparticle spectral weight $Z$ and identify the temperature at which it decreases significantly to a crossove...
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A Note on Iterated Consistency and Infinite Proofs
Schmerl and Beklemishev's work on iterated reflection achieves two aims: It introduces the important notion of $\Pi^0_1$-ordinal, characterizing the $\Pi^0_1$-theorems of a theory in terms of transfinite iterations of consistency; and it provides an innovative calculus to compute the $\Pi^0_1$-ordinals for a range of...
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Turning Internet of Things(IoT) into Internet of Vulnerabilities (IoV) : IoT Botnets
Internet of Things (IoT) is the next big evolutionary step in the world of internet. The main intention behind the IoT is to enable safer living and risk mitigation on different levels of life. With the advent of IoT botnets, the view towards IoT devices has changed from enabler of enhanced living into Internet of vu...
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Cwikel estimates revisited
In this paper, we propose a new approach to Cwikel estimates both for the Euclidean space and for the noncommutative Euclidean space.
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Smooth Pinball Neural Network for Probabilistic Forecasting of Wind Power
Uncertainty analysis in the form of probabilistic forecasting can significantly improve decision making processes in the smart power grid for better integrating renewable energy sources such as wind. Whereas point forecasting provides a single expected value, probabilistic forecasts provide more information in the fo...
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Asynchronous Coordinate Descent under More Realistic Assumptions
Asynchronous-parallel algorithms have the potential to vastly speed up algorithms by eliminating costly synchronization. However, our understanding to these algorithms is limited because the current convergence of asynchronous (block) coordinate descent algorithms are based on somewhat unrealistic assumptions. In par...
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Zero-temperature magnetic response of small fullerene molecules at the classical and full quantum limit
The ground-state magnetic response of fullerene molecules with up to 36 vertices is calculated, when spins classical or with magnitude $s=\frac{1}{2}$ are located on their vertices and interact according to the nearest-neighbor antiferromagnetic Heisenberg model. The frustrated topology, which originates in the penta...
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Stochastic Chemical Reaction Networks for Robustly Approximating Arbitrary Probability Distributions
We show that discrete distributions on the $d$-dimensional non-negative integer lattice can be approximated arbitrarily well via the marginals of stationary distributions for various classes of stochastic chemical reaction networks. We begin by providing a class of detailed balanced networks and prove that they can a...
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Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes
The incorporation of macro-actions (temporally extended actions) into multi-agent decision problems has the potential to address the curse of dimensionality associated with such decision problems. Since macro-actions last for stochastic durations, multiple agents executing decentralized policies in cooperative enviro...
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Early Salient Region Selection Does Not Drive Rapid Visual Categorization
The current dominant visual processing paradigm in both human and machine research is the feedforward, layered hierarchy of neural-like processing elements. Within this paradigm, visual saliency is seen by many to have a specific role, namely that of early selection. Early selection is thought to enable very fast vis...
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Bonsai: Synthesis-Based Reasoning for Type Systems
We describe algorithms for symbolic reasoning about executable models of type systems, supporting three queries intended for designers of type systems. First, we check for type soundness bugs and synthesize a counterexample program if such a bug is found. Second, we compare two versions of a type system, synthesizing...
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Preference-based performance measures for Time-Domain Global Similarity method
For Time-Domain Global Similarity (TDGS) method, which transforms the data cleaning problem into a binary classification problem about the physical similarity between channels, directly adopting common performance measures could only guarantee the performance for physical similarity. Nevertheless, practical data clea...
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On the Prospects for Detecting a Net Photon Circular Polarization Produced by Decaying Dark Matter
If dark matter interactions with Standard Model particles are $CP$-violating, then dark matter annihilation/decay can produce photons with a net circular polarization. We consider the prospects for experimentally detecting evidence for such a circular polarization. We identify optimal models for dark matter interacti...
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Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model
We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfe's law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least four occasions, by ...
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