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An Online Hierarchical Algorithm for Extreme Clustering
Many modern clustering methods scale well to a large number of data items, N, but not to a large number of clusters, K. This paper introduces PERCH, a new non-greedy algorithm for online hierarchical clustering that scales to both massive N and K--a problem setting we term extreme clustering. Our algorithm efficientl...
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Wave and Dirac equations on manifolds
We review some recent results on geometric equations on Lorentzian manifolds such as the wave and Dirac equations. This includes well-posedness and stability for various initial value problems, as well as results on the structure of these equations on black-hole spacetimes (in particular, on the Kerr solution), the i...
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The Efimov effect for heteronuclear three-body systems at positive scattering length and finite temperature
We study the recombination process of three atoms scattering into an atom and diatomic molecule in heteronuclear mixtures of ultracold atomic gases with large and positive interspecies scattering length at finite temperature. We calculate the temperature dependence of the three-body recombination rates by extracting ...
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Mean-Field Controllability and Decentralized Stabilization of Markov Chains, Part II: Asymptotic Controllability and Polynomial Feedbacks
This paper, the second of a two-part series, presents a method for mean-field feedback stabilization of a swarm of agents on a finite state space whose time evolution is modeled as a continuous time Markov chain (CTMC). The resulting (mean-field) control problem is that of controlling a nonlinear system with desired ...
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The kinematics of σ-drop bulges from spectral synthesis modelling of a hydrodynamical simulation
A minimum in stellar velocity dispersion is often observed in the central regions of disc galaxies. To investigate the origin of this feature, known as a {\sigma}-drop, we analyse the stellar kinematics of a high-resolution N-body + smooth particle hydrodynamical simulation, which models the secular evolution of an u...
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Algorithms and Architecture for Real-time Recommendations at News UK
Recommendation systems are recognised as being hugely important in industry, and the area is now well understood. At News UK, there is a requirement to be able to quickly generate recommendations for users on news items as they are published. However, little has been published about systems that can generate recommen...
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A Physics Tragedy
The measurement problem and three other vexing experiments in quantum physics are described. It is shown how Quantum Field Theory, as formulated by Julian Schwinger, provides simple solutions for all four experiments. It is also shown how this theory resolves many other problems of Quantum Mechanics and Relativity, i...
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Dynamical Mass Generation in Pseudo Quantum Electrodynamics with Four-Fermion Interactions
We describe dynamical symmetry breaking in a system of massless Dirac fermions with both electromagnetic and four-fermion interactions in (2+1) dimensions. The former is described by the Pseudo Quantum Electrodynamics (PQED) and the latter is given by the so-called Gross-Neveu action. We apply the Hubbard-Stratonovic...
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Computational Methods for Path-based Robust Flows
Real world networks are often subject to severe uncertainties which need to be addressed by any reliable prescriptive model. In the context of the maximum flow problem subject to arc failure, robust models have gained particular attention. For a path-based model, the resulting optimization problem is assumed to be di...
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A game theoretic approach to a network cloud storage problem
The use of game theory in the design and control of large scale networked systems is becoming increasingly more important. In this paper, we follow this approach to efficiently solve a network allocation problem motivated by peer-to- peer cloud storage models as alternatives to classical centralized cloud storage ser...
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A Survey of the State-of-the-Art Parallel Multiple Sequence Alignment Algorithms on Multicore Systems
Evolutionary modeling applications are the best way to provide full information to support in-depth understanding of evaluation of organisms. These applications mainly depend on identifying the evolutionary history of existing organisms and understanding the relations between them, which is possible through the deep ...
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Learning Wasserstein Embeddings
The Wasserstein distance received a lot of attention recently in the community of machine learning, especially for its principled way of comparing distributions. It has found numerous applications in several hard problems, such as domain adaptation, dimensionality reduction or generative models. However, its use is s...
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Contextual Stochastic Block Models
We provide the first information theoretic tight analysis for inference of latent community structure given a sparse graph along with high dimensional node covariates, correlated with the same latent communities. Our work bridges recent theoretical breakthroughs in the detection of latent community structure without ...
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Tensor Regression Meets Gaussian Processes
Low-rank tensor regression, a new model class that learns high-order correlation from data, has recently received considerable attention. At the same time, Gaussian processes (GP) are well-studied machine learning models for structure learning. In this paper, we demonstrate interesting connections between the two, es...
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Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition
The Canonical Polyadic decomposition (CPD) is a convenient and intuitive tool for tensor factorization; however, for higher-order tensors, it often exhibits high computational cost and permutation of tensor entries, these undesirable effects grow exponentially with the tensor order. Prior compression of tensor in-han...
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Social Learning and Diffusion of Pervasive Goods: An Empirical Study of an African App Store
In this study, the authors develop a structural model that combines a macro diffusion model with a micro choice model to control for the effect of social influence on the mobile app choices of customers over app stores. Social influence refers to the density of adopters within the proximity of other customers. Using ...
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Dynamic correlations at different time-scales with Empirical Mode Decomposition
The Empirical Mode Decomposition (EMD) provides a tool to characterize time series in terms of its implicit components oscillating at different time-scales. We apply this decomposition to intraday time series of the following three financial indices: the S\&P 500 (USA), the IPC (Mexico) and the VIX (volatility index ...
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Order-disorder transitions in lattice gases with annealed reactive constraints
We study equilibrium properties of catalytically-activated $A + A \to \oslash$ reactions taking place on a lattice of adsorption sites. The particles undergo continuous exchanges with a reservoir maintained at a constant chemical potential $\mu$ and react when they appear at the neighbouring sites, provided that some...
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Spherical CNNs
Convolutional Neural Networks (CNNs) have become the method of choice for learning problems involving 2D planar images. However, a number of problems of recent interest have created a demand for models that can analyze spherical images. Examples include omnidirectional vision for drones, robots, and autonomous cars, ...
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The Kelvin-Helmholtz instability in the Orion nebula: The effect of radiation pressure
The recent observations of rippled structures on the surface of the Orion molecular cloud (Berné et al. 2010), have been attributed to the Kelvin-Helmholtz (KH) instability. The wavelike structures which have mainly seen near star-forming regions taking place at the interface between the hot diffuse gas, which is ion...
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Holography and Koszul duality: the example of the $M2$ brane
Si Li and author suggested in that, in some cases, the AdS/CFT correspondence can be formulated in terms of the algebraic operation of Koszul duality. In this paper this suggestion is checked explicitly for $M2$ branes in an $\Omega$-background. The algebra of supersymmetric operators on a stack of $K$ $M2$ branes is...
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Uniqueness of the power of a meromorphic functions with its differential polynomial sharing a set
This paper is devoted to the uniqueness problem of the power of a meromorphic function with its differential polynomial sharing a set. Our result will extend a number of results obtained in the theory of normal families. Some questions are posed for future research.
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Link between the Superconducting Dome and Spin-Orbit Interaction in the (111) LaAlO$_3$/SrTiO$_3$ Interface
We measure the gate voltage ($V_g$) dependence of the superconducting properties and the spin-orbit interaction in the (111)-oriented LaAlO$_3$/SrTiO$_3$ interface. Superconductivity is observed in a dome-shaped region in the carrier density-temperature phase diagram with the maxima of superconducting transition temp...
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On the Dynamics of Deterministic Epidemic Propagation over Networks
In this work we review a class of deterministic nonlinear models for the propagation of infectious diseases over contact networks with strongly-connected topologies. We consider network models for susceptible-infected (SI), susceptible-infected-susceptible (SIS), and susceptible-infected-recovered (SIR) settings. In ...
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Comparison of Multiple Features and Modeling Methods for Text-dependent Speaker Verification
Text-dependent speaker verification is becoming popular in the speaker recognition society. However, the conventional i-vector framework which has been successful for speaker identification and other similar tasks works relatively poorly in this task. Researchers have proposed several new methods to improve performan...
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Estimation of lactate threshold with machine learning techniques in recreational runners
Lactate threshold is considered an essential parameter when assessing performance of elite and recreational runners and prescribing training intensities in endurance sports. However, the measurement of blood lactate concentration requires expensive equipment and the extraction of blood samples, which are inconvenient...
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A Coin-Tossing Conundrum
It is shown that an equiprobability hypothesis leads to a scenario in which it is possible to predict the outcome of a single toss of a fair coin with a success probability greater than 50%. We discuss whether this hypothesis might be independent of the usual hypotheses governing probability, as well as whether this ...
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Meridian Surfaces on Rotational Hypersurfaces with Lightlike Axis in ${\mathbb E}^4_2$
We construct a special class of Lorentz surfaces in the pseudo-Euclidean 4-space with neutral metric which are one-parameter systems of meridians of rotational hypersurfaces with lightlike axis and call them meridian surfaces. We give the complete classification of the meridian surfaces with constant Gauss curvature ...
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Hybrid Optimization Method for Reconfiguration of AC/DC Microgrids in All-Electric Ships
Since the limited power capacity, finite inertia, and dynamic loads make the shipboard power system (SPS) vulnerable, the automatic reconfiguration for failure recovery in SPS is an extremely significant but still challenging problem. It is not only required to operate accurately and optimally, but also to satisfy op...
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Looking at Outfit to Parse Clothing
This paper extends fully-convolutional neural networks (FCN) for the clothing parsing problem. Clothing parsing requires higher-level knowledge on clothing semantics and contextual cues to disambiguate fine-grained categories. We extend FCN architecture with a side-branch network which we refer outfit encoder to pred...
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Mermin-Wagner physics, (H,T) phase diagram, and candidate quantum spin-liquid phase in the spin-1/2 triangular-lattice antiferromagnet Ba8CoNb6O24
Ba$_8$CoNb$_6$O$_{24}$ presents a system whose Co$^{2+}$ ions have an effective spin 1/2 and construct a regular triangular-lattice antiferromagnet (TLAFM) with a very large interlayer spacing, ensuring purely two-dimensional character. We exploit this ideal realization to perform a detailed experimental analysis of ...
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Most Complex Non-Returning Regular Languages
A regular language $L$ is non-returning if in the minimal deterministic finite automaton accepting it there are no transitions into the initial state. Eom, Han and Jirásková derived upper bounds on the state complexity of boolean operations and Kleene star, and proved that these bounds are tight using two different b...
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ArtGAN: Artwork Synthesis with Conditional Categorical GANs
This paper proposes an extension to the Generative Adversarial Networks (GANs), namely as ARTGAN to synthetically generate more challenging and complex images such as artwork that have abstract characteristics. This is in contrast to most of the current solutions that focused on generating natural images such as room...
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Polynomial bound for the nilpotency index of finitely generated nil algebras
Working over an infinite field of positive characteristic, an upper bound is given for the nilpotency index of a finitely generated nil algebra of bounded nil index $n$ in terms of the maximal degree in a minimal homogenous generating system of the ring of simultaneous conjugation invariants of tuples of $n$ by $n$ m...
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CFAAR: Control Flow Alteration to Assist Repair
We present CFAAR, a program repair assistance technique that operates by selectively altering the outcome of suspicious predicates in order to yield expected behavior. CFAAR is applicable to defects that are repairable by negating predicates under specific conditions. CFAAR proceeds as follows: 1) it identifies predi...
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Cross-Sentence N-ary Relation Extraction with Graph LSTMs
Past work in relation extraction has focused on binary relations in single sentences. Recent NLP inroads in high-value domains have sparked interest in the more general setting of extracting n-ary relations that span multiple sentences. In this paper, we explore a general relation extraction framework based on graph ...
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Community Interaction and Conflict on the Web
Users organize themselves into communities on web platforms. These communities can interact with one another, often leading to conflicts and toxic interactions. However, little is known about the mechanisms of interactions between communities and how they impact users. Here we study intercommunity interactions across...
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Recurrence network measures for hypothesis testing using surrogate data: application to black hole light curves
Recurrence networks and the associated statistical measures have become important tools in the analysis of time series data. In this work, we test how effective the recurrence network measures are in analyzing real world data involving two main types of noise, white noise and colored noise. We use two prominent netwo...
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Diffraction-limited plenoptic imaging with correlated light
Traditional optical imaging faces an unavoidable trade-off between resolution and depth of field (DOF). To increase resolution, high numerical apertures (NA) are needed, but the associated large angular uncertainty results in a limited range of depths that can be put in sharp focus. Plenoptic imaging was introduced a...
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Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Complex performance measures, beyond the popular measure of accuracy, are increasingly being used in the context of binary classification. These complex performance measures are typically not even decomposable, that is, the loss evaluated on a batch of samples cannot typically be expressed as a sum or average of loss...
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Learning from Noisy Label Distributions
In this paper, we consider a novel machine learning problem, that is, learning a classifier from noisy label distributions. In this problem, each instance with a feature vector belongs to at least one group. Then, instead of the true label of each instance, we observe the label distribution of the instances associate...
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Commissioning of FLAG: A phased array feed for the GBT
Phased Array Feed (PAF) technology is the next major advancement in radio astronomy in terms of combining high sensitivity and large field of view. The Focal L-band Array for the Green Bank Telescope (FLAG) is one of the most sensitive PAFs developed so far. It consists of 19 dual-polarization elements mounted on a p...
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Arithmetic representations of fundamental groups I
Let $X$ be a normal algebraic variety over a finitely generated field $k$ of characteristic zero, and let $\ell$ be a prime. Say that a continuous $\ell$-adic representation $\rho$ of $\pi_1^{\text{ét}}(X_{\bar k})$ is arithmetic if there exists a representation $\tilde \rho$ of a finite index subgroup of $\pi_1^{\te...
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Optimization over Degree Sequences
We introduce and study the problem of optimizing arbitrary functions over degree sequences of hypergraphs and multihypergraphs. We show that over multihypergraphs the problem can be solved in polynomial time. For hypergraphs, we show that deciding if a given sequence is the degree sequence of a 3-hypergraph is NP-com...
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Interferometric Monitoring of Gamma-ray Bright AGNs: S5 0716+714
We present the results of very long baseline interferometry (VLBI) observations of gamma-ray bright blazar S5 0716+714 using the Korean VLBI Network (KVN) at the 22, 43, 86, and 129 GHz bands, as part of the Interferometric Monitoring of Gamma-ray Bright AGNs (iMOGABA) KVN key science program. Observations were condu...
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Parabolic equations with natural growth approximated by nonlocal equations
In this paper we study several aspects related with solutions of nonlocal problems whose prototype is $$ u_t =\displaystyle \int_{\mathbb{R}^N} J(x-y) \big( u(y,t) -u(x,t) \big) \mathcal G\big( u(y,t) -u(x,t) \big) dy \qquad \mbox{ in } \, \Omega \times (0,T)\,, $$ being $ u (x,t)=0 \mbox{ in } (\mathbb{R}^N\setminus...
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Excitonic gap generation in thin-film topological insulators
In this work, we analyze the excitonic gap generation in the strong-coupling regime of thin films of three-dimensional time-reversal-invariant topological insulators. We start by writing down the effective gauge theory in 2+1-dimensions from the projection of the 3+1-dimensional quantum electrodynamics. Within this m...
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Constructive Preference Elicitation over Hybrid Combinatorial Spaces
Preference elicitation is the task of suggesting a highly preferred configuration to a decision maker. The preferences are typically learned by querying the user for choice feedback over pairs or sets of objects. In its constructive variant, new objects are synthesized "from scratch" by maximizing an estimate of the ...
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Ginzburg-Landau equations on Riemann surfaces of higher genus
We study the Ginzburg-Landau equations on Riemann surfaces of arbitrary genus. In particular: we explicitly construct the (local moduli space of gauge-equivalent) solutions in a neighbourhood of a constant curvature branch of solutions; in linearizing the problem, we find a relation with de Rham cohomology groups of ...
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On the Hamming Auto- and Cross-correlation Functions of a Class of Frequency Hopping Sequences of Length $ p^{n} $
In this paper, a new class of frequency hopping sequences (FHSs) of length $ p^{n} $ is constructed by using Ding-Helleseth generalized cyclotomic classes of order 2, of which the Hamming auto- and cross-correlation functions are investigated (for the Hamming cross-correlation, only the case $ p\equiv 3\pmod 4 $ is c...
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Scikit-Multiflow: A Multi-output Streaming Framework
Scikit-multiflow is a multi-output/multi-label and stream data mining framework for the Python programming language. Conceived to serve as a platform to encourage democratization of stream learning research, it provides multiple state of the art methods for stream learning, stream generators and evaluators. scikit-mu...
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Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows
Distributed computing platforms provide a robust mechanism to perform large-scale computations by splitting the task and data among multiple locations, possibly located thousands of miles apart geographically. Although such distribution of resources can lead to benefits, it also comes with its associated problems suc...
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The Rational Sectional Category of Certain Universal Fibrations
We prove that the sectional category of the universal fibration with fibre X, for X any space that satisfies a well-known conjecture of Halperin, equals one after rationalization.
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Characterising exo-ringsystems around fast-rotating stars using the Rossiter-McLaughlin effect
Planetary rings produce a distinct shape distortion in transit lightcurves. However, to accurately model such lightcurves the observations need to cover the entire transit, especially ingress and egress, as well as an out-of-transit baseline. Such observations can be challenging for long period planets, where the tra...
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Learning a Generative Model of Cancer Metastasis
We introduce a Unified Disentanglement Network (UFDN) trained on The Cancer Genome Atlas (TCGA). We demonstrate that the UFDN learns a biologically relevant latent space of gene expression data by applying our network to two classification tasks of cancer status and cancer type. Our UFDN specific algorithms perform c...
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Joint User Selection and Energy Minimization for Ultra-Dense Multi-channel C-RAN with Incomplete CSI
This paper provides a unified framework to deal with the challenges arising in dense cloud radio access networks (C-RAN), which include huge power consumption, limited fronthaul capacity, heavy computational complexity, unavailability of full channel state information (CSI), etc. Specifically, we aim to jointly optim...
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On Sidorenko's conjecture for determinants and Gaussian Markov random fields
We study a class of determinant inequalities that are closely related to Sidorenko's famous conjecture (Also conjectured by Erd\H os and Simonovits in a different form). Our results can also be interpreted as entropy inequalities for Gaussian Markov random fields (GMRF). We call a GMRF on a finite graph $G$ homogeneo...
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Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations
Power grids are critical infrastructure assets that face non-technical losses (NTL) such as electricity theft or faulty meters. NTL may range up to 40% of the total electricity distributed in emerging countries. Industrial NTL detection systems are still largely based on expert knowledge when deciding whether to carr...
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A model of reward-modulated motor learning with parallelcortical and basal ganglia pathways
Many recent studies of the motor system are divided into two distinct approaches: Those that investigate how motor responses are encoded in cortical neurons' firing rate dynamics and those that study the learning rules by which mammals and songbirds develop reliable motor responses. Computationally, the first approac...
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A de Sitter limit analysis for dark energy and modified gravity models
The effective field theory of dark energy and modified gravity is supposed to well describe, at low energies, the behaviour of the gravity modifications due to one extra scalar degree of freedom. The usual curvature perturbation is very useful when studying the conditions for the avoidance of ghost instabilities as w...
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Empirical Analysis on Comparing the Performance of Alpha Miner Algorithm in SQL Query Language and NoSQL Column-Oriented Databases Using Apache Phoenix
Process-Aware Information Systems (PAIS) is an IT system that support business processes and generate large amounts of event logs from the execution of business processes. An event log is represented as a tuple of CaseID, Timestamp, Activity and Actor. Process Mining is a new and emerging field that aims at analyzing...
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Cross-modal Deep Metric Learning with Multi-task Regularization
DNN-based cross-modal retrieval has become a research hotspot, by which users can search results across various modalities like image and text. However, existing methods mainly focus on the pairwise correlation and reconstruction error of labeled data. They ignore the semantically similar and dissimilar constraints b...
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$W$-entropy formulas on super Ricci flows and Langevin deformation on Wasserstein space over Riemannian manifolds
In this survey paper, we give an overview of our recent works on the study of the $W$-entropy for the heat equation associated with the Witten Laplacian on super-Ricci flows and the Langevin deformation on Wasserstein space over Riemannian manifolds. Inspired by Perelman's seminal work on the entropy formula for the ...
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Cancellable elements of the lattice of semigroup varieties
We completely determine all commutative semigroup varieties that are cancellable elements of the lattice SEM of all semigroup varieties. In particular, we prove that, for commutative varieties, the properties of being cancellable and modular elements of SEM are equivalent.
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Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
The availability of large scale event data with time stamps has given rise to dynamically evolving knowledge graphs that contain temporal information for each edge. Reasoning over time in such dynamic knowledge graphs is not yet well understood. To this end, we present Know-Evolve, a novel deep evolutionary knowledge...
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Mechanisms of dimensionality reduction and decorrelation in deep neural networks
Deep neural networks are widely used in various domains. However, the nature of computations at each layer of the deep networks is far from being well understood. Increasing the interpretability of deep neural networks is thus important. Here, we construct a mean-field framework to understand how compact representati...
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Detecting Strong Ties Using Network Motifs
Detecting strong ties among users in social and information networks is a fundamental operation that can improve performance on a multitude of personalization and ranking tasks. Strong-tie edges are often readily obtained from the social network as users often participate in multiple overlapping networks via features...
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Streaming Weak Submodularity: Interpreting Neural Networks on the Fly
In many machine learning applications, it is important to explain the predictions of a black-box classifier. For example, why does a deep neural network assign an image to a particular class? We cast interpretability of black-box classifiers as a combinatorial maximization problem and propose an efficient streaming a...
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Staging superstructures in high-$T_c$ Sr/O co-doped La$_{2-x}$Sr$_x$CuO$_{4+y}$
We present high energy X-ray diffraction studies on the structural phases of an optimal high-$T_c$ superconductor La$_{2-x}$Sr$_x$CuO$_{4+y}$ tailored by co-hole-doping. This is specifically done by varying the content of two very different chemical species, Sr and O, respectively, in order to study the influence of ...
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Interface magnetism and electronic structure: ZnO(0001)/Co3O4(111)
We have studied the structural, electronic and magnetic properties of spinel $\rm Co_3O_4$(111) surfaces and their interfaces with ZnO (0001) using density functional theory (DFT) within the Generalized Gradient Approximation with on-site Coulomb repulsion term (GGA+U). Two possible forms of spinel surface, containin...
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Bloch-type spaces and extended Cesàro operators in the unit ball of a complex Banach space
Let $\mathbb{B}$ be the unit ball of a complex Banach space $X$. In this paper, we will generalize the Bloch-type spaces and the little Bloch-type spaces to the open unit ball $\mathbb{B}$ by using the radial derivative. Next, we define an extended Cesàro operator $T_{\varphi}$ with holomorphic symbol $\varphi$ and c...
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Alchemist: An Apache Spark <=> MPI Interface
The Apache Spark framework for distributed computation is popular in the data analytics community due to its ease of use, but its MapReduce-style programming model can incur significant overheads when performing computations that do not map directly onto this model. One way to mitigate these costs is to off-load comp...
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Compositional (In)Finite Abstractions for Large-Scale Interconnected Stochastic Systems
This paper is concerned with a compositional approach for constructing both infinite (reduced-order models) and finite abstractions (a.k.a. finite Markov decision processes) of large-scale interconnected discrete-time stochastic control systems. The proposed framework is based on the notion of stochastic simulation f...
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Infinitely generated symbolic Rees algebras over finite fields
For the polynomial ring over an arbitrary field with twelve variables, there exists a prime ideal whose symbolic Rees algebra is not finitely generated.
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Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models
Deep generative neural networks have proven effective at both conditional and unconditional modeling of complex data distributions. Conditional generation enables interactive control, but creating new controls often requires expensive retraining. In this paper, we develop a method to condition generation without retr...
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Characterization of Zinc oxide & Aluminum Ferrite and Simulation studies of M-H plots of Cobalt/Cobaltoxide
Zinc oxide and Aluminum Ferrite were prepared Chemical route. The samples were characterized by XRD and VSM. Simulation of M-H plots of Co/CoO thin films were performed. Effect of parameters was observed on saturation magnetization.
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Poisson Structures and Potentials
We introduce a notion of weakly log-canonical Poisson structures on positive varieties with potentials. Such a Poisson structure is log-canonical up to terms dominated by the potential. To a compatible real form of a weakly log-canonical Poisson variety we assign an integrable system on the product of a certain real ...
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The closure of ideals of $\boldsymbol{\ell^1(Σ)}$ in its enveloping $\boldsymbol{\mathrm{C}^\ast}$-algebra
If $X$ is a compact Hausdorff space and $\sigma$ is a homeomorphism of $X$, then an involutive Banach algebra $\ell^1(\Sigma)$ of crossed product type is naturally associated with the topological dynamical system $\Sigma=(X,\sigma)$. We initiate the study of the relation between two-sided ideals of $\ell^1(\Sigma)$ a...
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An alternative quadratic formula
The classical quadratic formula and some of its lesser known variants for solving the quadratic equation are reviewed. Then, a new formula for the roots of a quadratic polynomial is presented.
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Sound event detection using weakly-labeled semi-supervised data with GCRNNS, VAT and Self-Adaptive Label Refinement
In this paper, we present a gated convolutional recurrent neural network based approach to solve task 4, large-scale weakly labelled semi-supervised sound event detection in domestic environments, of the DCASE 2018 challenge. Gated linear units and a temporal attention layer are used to predict the onset and offset o...
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Inflationary $α$-attractor cosmology: A global dynamical systems perspective
We study flat FLRW $\alpha$-attractor $\mathrm{E}$- and $\mathrm{T}$-models by introducing a dynamical systems framework that yields regularized unconstrained field equations on two-dimensional compact state spaces. This results in both illustrative figures and a complete description of the entire solution spaces of ...
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Symmetric Convex Sets with Minimal Gaussian Surface Area
Let $\Omega\subset\mathbb{R}^{n+1}$ have minimal Gaussian surface area among all sets satisfying $\Omega=-\Omega$ with fixed Gaussian volume. Let $A=A_{x}$ be the second fundamental form of $\partial\Omega$ at $x$, i.e. $A$ is the matrix of first order partial derivatives of the unit normal vector at $x\in\partial\Om...
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Advancements in Continuum Approximation Models for Logistics and Transportation Systems: 1996 - 2016
Continuum Approximation (CA) is an efficient and parsimonious technique for modeling complex logistics problems. In this paper,we review recent studies that develop CA models for transportation, distribution and logistics problems with the aim of synthesizing recent advancements and identifying current research gaps....
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On a free boundary problem and minimal surfaces
From minimal surfaces such as Simons' cone and catenoids, using refined Lyapunov-Schmidt reduction method, we construct new solutions for a free boundary problem whose free boundary has two components. In dimension $8$, using variational arguments, we also obtain solutions which are global minimizers of the correspon...
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Storing and retrieving long-term memories: cooperation and competition in synaptic dynamics
We first review traditional approaches to memory storage and formation, drawing on the literature of quantitative neuroscience as well as statistical physics. These have generally focused on the fast dynamics of neurons; however, there is now an increasing emphasis on the slow dynamics of synapses, whose weight chang...
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An algorithm for removing sensitive information: application to race-independent recidivism prediction
Predictive modeling is increasingly being employed to assist human decision-makers. One purported advantage of replacing or augmenting human judgment with computer models in high stakes settings-- such as sentencing, hiring, policing, college admissions, and parole decisions-- is the perceived "neutrality" of compute...
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A Question Answering Approach to Emotion Cause Extraction
Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identifi...
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Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting
Machine Learning on graph-structured data is an important and omnipresent task for a vast variety of applications including anomaly detection and dynamic network analysis. In this paper, a deep generative model is introduced to capture continuous probability densities corresponding to the nodes of an arbitrary graph....
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Quasisymmetrically co-Hopfian Sierpiński Spaces and Menger Curve
A metric space $X$ is quasisymmetrically co-Hopfian if every quasisymmetric embedding of $X$ into itself is onto. We construct the first examples of metric spaces homeomorphic to the universal Menger curve and higher dimensional Sierpiński spaces, which are quasisymmetrically co-Hopfian. We also show that the collect...
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Localization properties and high-fidelity state transfer in electronic hopping models with correlated disorder
We investigate a tight-binding electronic chain featuring diagonal and off-diagonal disorder, these being modelled through the long-range-correlated fractional Brownian motion. Particularly, by employing exact diagonalization methods, we evaluate how the eigenstate spectrum of the system and its related single-partic...
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On consistency of optimal pricing algorithms in repeated posted-price auctions with strategic buyer
We study revenue optimization learning algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation for a good and seeks to maximize his cumulative discounted surplus. For this setting, first, we propose a novel algorithm that never decrease...
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City-wide Analysis of Electronic Health Records Reveals Gender and Age Biases in the Administration of Known Drug-Drug Interactions
The occurrence of drug-drug-interactions (DDI) from multiple drug prescriptions is a serious problem, both for individuals and health-care systems, since patients with complications due to DDI are likely to re-enter the system at a costlier level. We present a large-scale longitudinal study of the DDI phenomenon at t...
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A remark on the disorienting of species due to the fluctuating environment
In this article we study the stabilizing of a primitive pattern of behaviour for the two-species community with chemotaxis due to the short-wavelength external signal. We use a system of Patlak-Keller-Segel type as a model of the community. It is well-known that such systems can produce complex unsteady patterns of b...
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Fourier optimization and prime gaps
We investigate some extremal problems in Fourier analysis and their connection to a problem in prime number theory. In particular, we improve the current bounds for the largest possible gap between consecutive primes assuming the Riemann hypothesis.
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An Interpretable Knowledge Transfer Model for Knowledge Base Completion
Knowledge bases are important resources for a variety of natural language processing tasks but suffer from incompleteness. We propose a novel embedding model, \emph{ITransF}, to perform knowledge base completion. Equipped with a sparse attention mechanism, ITransF discovers hidden concepts of relations and transfer s...
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Vecchia approximations of Gaussian-process predictions
Gaussian processes (GPs) are highly flexible function estimators used for geospatial analysis, nonparametric regression, and machine learning, but they are computationally infeasible for large datasets. Vecchia approximations of GPs have been used to enable fast evaluation of the likelihood for parameter inference. H...
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Long-Term Sequential Prediction Using Expert Advice
For the prediction with experts' advice setting, we consider some methods to construct forecasting algorithms that suffer loss not much more than any expert in the pool. In contrast to the standard approach, we investigate the case of long-term forecasting of time series. This approach implies that each expert issues...
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AMBER: Adaptive Multi-Batch Experience Replay for Continuous Action Control
In this paper, a new adaptive multi-batch experience replay scheme is proposed for proximal policy optimization (PPO) for continuous action control. On the contrary to original PPO, the proposed scheme uses the batch samples of past policies as well as the current policy for the update for the next policy, where the ...
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Magnetic states of MnP: muon-spin rotation studies
Muon-spin rotation data collected at ambient pressure ($p$) and at $p=2.42$ GPa in MnP were analyzed to check their consistency with various low- and high-pressure magnetic structures reported in the literature. Our analysis confirms that in MnP the low-temperature and low-pressure helimagnetic phase is characterised...
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The Hyper Suprime-Cam Software Pipeline
In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope's Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope's Data Management system, adding customizations for HSC, large-scale...
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