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Facial Keypoints Detection
Detect facial keypoints is a critical element in face recognition. However, there is difficulty to catch keypoints on the face due to complex influences from original images, and there is no guidance to suitable algorithms. In this paper, we study different algorithms that can be applied to locate keyponits. Specific...
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Transitions from a Kondo-like diamagnetic insulator into a modulated ferromagnetic metal in $\bm{\mathrm{FeGa}_{3-y}\mathrm{Ge}_y}$
One initial and essential question of magnetism is whether the magnetic properties of a material are governed by localized moments or itinerant electrons. Here we expose the case for the weakly ferromagnetic system FeGa$_{3-y}$Ge$_y$ wherein these two opposite models are reconciled, such that the magnetic susceptibil...
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Sample, computation vs storage tradeoffs for classification using tensor subspace models
In this paper, we exhibit the tradeoffs between the (training) sample, computation and storage complexity for the problem of supervised classification using signal subspace estimation. Our main tool is the use of tensor subspaces, i.e. subspaces with a Kronecker structure, for embedding the data into lower dimensions...
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One-step Estimation of Networked Population Size with Anonymity Using Respondent-Driven Capture-Recapture and Hashing
Estimates of population size for hidden and hard-to-reach individuals are of particular interest to health officials when health problems are concentrated in such populations. Efforts to derive these estimates are often frustrated by a range of factors including social stigma or an association with illegal activities...
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Real single ion solvation free energies with quantum mechanical simulation
Single ion solvation free energies are one of the most important properties of electrolyte solutions and yet there is ongoing debate about what these values are. Only the values for neutral ion pairs are known. Here, we use DFT interaction potentials with molecular dynamics simulation (DFT-MD) combined with a modifie...
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Crowdsourcing with Sparsely Interacting Workers
We consider estimation of worker skills from worker-task interaction data (with unknown labels) for the single-coin crowd-sourcing binary classification model in symmetric noise. We define the (worker) interaction graph whose nodes are workers and an edge between two nodes indicates whether or not the two workers par...
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Training deep learning based denoisers without ground truth data
Recent deep learning based denoisers often outperform state-of-the-art conventional denoisers such as BM3D. They are typically trained to minimize the mean squared error (MSE) between the output of a deep neural network and the ground truth image. In deep learning based denoisers, it is important to use high quality ...
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Language Design and Renormalization
Here we consider some well-known facts in syntax from a physics perspective, which allows us to establish some remarkable equivalences. Specifically, we observe that the operation MERGE put forward by N. Chomsky in 1995 can be interpreted as a physical information coarse-graining. Thus, MERGE in linguistics entails i...
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On the geometry of the moduli space of sheaves supported on curves of genus two in a quadric surface
We study the moduli space of stable sheaves of Euler characteristic 2, supported on curves of arithmetic genus 2 contained in a smooth quadric surface. We show that this moduli space is rational. We compute its Betti numbers and we give a classification of the stable sheaves involving locally free resolutions.
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Attention Solves Your TSP, Approximately
The development of efficient (heuristic) algorithms for practical combinatorial optimization problems is costly, so we want to automatically learn them instead. We show the feasibility of this approach on the important Travelling Salesman Problem (TSP). We learn a heuristic algorithm that uses a Neural Network policy...
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A Distributed Online Pricing Strategy for Demand Response Programs
We study a demand response problem from utility (also referred to as operator)'s perspective with realistic settings, in which the utility faces uncertainty and limited communication. Specifically, the utility does not know the cost function of consumers and cannot have multiple rounds of information exchange with co...
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Highly Nonlinear and Low Confinement Loss Photonic Crystal Fiber Using GaP Slot Core
This paper presents a triangular lattice photonic crystal fiber with very high nonlinear coefficient. Finite element method (FEM) is used to scrutinize different optical properties of proposed highly nonlinear photonic crystal fiber (HNL-PCF). The HNL-PCF exhibits a high nonlinearity up to $10\times10^{4} W^{-1}km^{-...
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Is Epicurus the father of Reinforcement Learning?
The Epicurean Philosophy is commonly thought as simplistic and hedonistic. Here I discuss how this is a misconception and explore its link to Reinforcement Learning. Based on the letters of Epicurus, I construct an objective function for hedonism which turns out to be equivalent of the Reinforcement Learning objectiv...
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Low-Precision Floating-Point Schemes for Neural Network Training
The use of low-precision fixed-point arithmetic along with stochastic rounding has been proposed as a promising alternative to the commonly used 32-bit floating point arithmetic to enhance training neural networks training in terms of performance and energy efficiency. In the first part of this paper, the behaviour o...
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Deep Person Re-Identification with Improved Embedding and Efficient Training
Person re-identification task has been greatly boosted by deep convolutional neural networks (CNNs) in recent years. The core of which is to enlarge the inter-class distinction as well as reduce the intra-class variance. However, to achieve this, existing deep models prefer to adopt image pairs or triplets to form ve...
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Unsupervised speech representation learning using WaveNet autoencoders
We consider the task of unsupervised extraction of meaningful latent representations of speech by applying autoencoding neural networks to speech waveforms. The goal is to learn a representation able to capture high level semantic content from the signal, e.g. phoneme identities, while being invariant to confounding ...
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Many-body localization caused by temporal disorder
The many-body localization (MBL) is commonly related to a strong spatial disorder. We show that MBL may alternatively be generated by adding a temporal disorder to periodically driven many-body systems. We reach this conclusion by mapping the evolution of such systems on the dynamics of the time-independent, disorder...
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Second-generation p-values: improved rigor, reproducibility, & transparency in statistical analyses
Verifying that a statistically significant result is scientifically meaningful is not only good scientific practice, it is a natural way to control the Type I error rate. Here we introduce a novel extension of the p-value - a second-generation p-value - that formally accounts for scientific relevance and leverages th...
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Latency Optimal Broadcasting in Noisy Wireless Mesh Networks
In this paper, we adopt a new noisy wireless network model introduced very recently by Censor-Hillel et al. in [ACM PODC 2017, CHHZ17]. More specifically, for a given noise parameter $p\in [0,1],$ any sender has a probability of $p$ of transmitting noise or any receiver of a single transmission in its neighborhood ha...
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Construction of Directed 2K Graphs
We study the problem of constructing synthetic graphs that resemble real-world directed graphs in terms of their degree correlations. We define the problem of directed 2K construction (D2K) that takes as input the directed degree sequence (DDS) and a joint degree and attribute matrix (JDAM) so as to capture degree co...
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Pattern Generation Strategies for Improving Recognition of Handwritten Mathematical Expressions
Recognition of Handwritten Mathematical Expressions (HMEs) is a challenging problem because of the ambiguity and complexity of two-dimensional handwriting. Moreover, the lack of large training data is a serious issue, especially for academic recognition systems. In this paper, we propose pattern generation strategies...
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Actions of automorphism groups of Lie groups
This is an expository article on properties of actions on Lie groups by subgroups of their automorphism groups. After recalling various results on the structure of the automorphism groups, we discuss actions with dense orbits, invariant and quasi-invariant measures, the induced actions on the spaces of probability me...
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Interplay between relativistic energy corrections and resonant excitations in x-ray multiphoton ionization dynamics of Xe atoms
In this paper, we theoretically study x-ray multiphoton ionization dynamics of heavy atoms taking into account relativistic and resonance effects. When an atom is exposed to an intense x-ray pulse generated by an x-ray free-electron laser (XFEL), it is ionized to a highly charged ion via a sequence of single-photon i...
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Collective spin excitations of helices and magnetic skyrmions: review and perspectives of magnonics in non-centrosymmetric magnets
Magnetic materials hosting correlated electrons play an important role for information technology and signal processing. The currently used ferro-, ferri- and antiferromagnetic materials provide microscopic moments (spins) that are mainly collinear. Recently more complex spin structures such as spin helices and cyclo...
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On the Relation between Color Image Denoising and Classification
Large amount of image denoising literature focuses on single channel images and often experimentally validates the proposed methods on tens of images at most. In this paper, we investigate the interaction between denoising and classification on large scale dataset. Inspired by classification models, we propose a nove...
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A simplicial decomposition framework for large scale convex quadratic programming
In this paper, we analyze in depth a simplicial decomposition like algorithmic framework for large scale convex quadratic programming. In particular, we first propose two tailored strategies for handling the master problem. Then, we describe a few techniques for speeding up the solution of the pricing problem. We rep...
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A Logic of Blockchain Updates
Blockchains are distributed data structures that are used to achieve consensus in systems for cryptocurrencies (like Bitcoin) or smart contracts (like Ethereum). Although blockchains gained a lot of popularity recently, there is no logic-based model for blockchains available. We introduce BCL, a dynamic logic to reas...
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A proof of the Flaherty-Keller formula on the effective property of densely packed elastic composites
We prove in a mathematically rigorous way the asymptotic formula of Flaherty and Keller on the effective property of densely packed periodic elastic composites with hard inclusions. The proof is based on the primal-dual variational principle, where the upper bound is derived by using the Keller-type test functions an...
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Regret Bounds for Reinforcement Learning via Markov Chain Concentration
We give a simple optimistic algorithm for which it is easy to derive regret bounds of $\tilde{O}(\sqrt{t_{\rm mix} SAT})$ after $T$ steps in uniformly ergodic Markov decision processes with $S$ states, $A$ actions, and mixing time parameter $t_{\rm mix}$. These bounds are the first regret bounds in the general, non-e...
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Superradiance with local phase-breaking effects
We study the superradiant evolution of a set of $N$ two-level systems spontaneously radiating under the effect of phase-breaking mechanisms. We investigate the dynamics generated by non-radiative losses and pure dephasing, and their interplay with spontaneous emission. Our results show that in the parameter region re...
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Kinetic model of selectivity and conductivity of the KcsA filter
We introduce a self-consistent multi-species kinetic theory based on the structure of the narrow voltage-gated potassium channel. Transition rates depend on a complete energy spectrum with contributions including the dehydration amongst species, interaction with the dipolar charge of the filter and, bulk solution pro...
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The affine approach to homogeneous geodesics in homogeneous Finsler spaces
In a recent paper, it was claimed that any homogeneous Finsler space of odd dimension admits a homogeneous geodesic through any point. For the proof, the algebraic method dealing with the reductive decomposition of the Lie algebra of the isometry group was used. However, the proof contains a serious gap. In the prese...
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About Synchronized Globular Cluster Formation over Supra-galactic Scales
Observational and theoretical arguments support the idea that violent events connected with $AGN$ activity and/or intense star forming episodes have played a significant role in the early phases of galaxy formation at high red shifts. Being old stellar systems, globular clusters seem adequate candidates to search for...
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Geometric counting on wavefront real spherical spaces
We provide $L^p$-versus $L^\infty$-bounds for eigenfunctions on a real spherical space $Z$ of wavefront type. It is shown that these bounds imply a non-trivial error term estimate for lattice counting on $Z$. The paper also serves as an introduction to geometric counting on spaces of the mentioned type. Section 7 on ...
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Fate of the spin-\frac{1}{2} Kondo effect in the presence of temperature gradients
We consider a strongly interacting quantum dot connected to two leads held at quite different temperatures. Our aim is to study the behavior of the Kondo effect in the presence of large thermal biases. We use three different approaches, namely, a perturbation formalism based on the Kondo Hamiltonian, a slave-boson me...
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Extragalactic source population studies at very high energies in the Cherenkov Telescope Array era
The Cherenkov Telescope Array (CTA) is the next generation ground-based $\gamma$-ray observatory. It will provide an order of magnitude better sensitivity and an extended energy coverage, 20 GeV - 300 TeV, relative to current Imaging Atmospheric Cherenkov Telescopes (IACTs). IACTs, despite featuring an excellent sens...
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Modeling the SBC Tanzania Production-Distribution Logistics Network
The increase in customer expectation in terms of cost and services rendered, coupled with competitive business environment and uncertainty in cost of raw materials have posed challenges on effective supply chain engineering making it essential to do cost-benefit analysis before making final decisions on production di...
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Dark matter in dwarf galaxies
Although the cusp-core controversy for dwarf galaxies is seen as a problem, I argue that the cored central profiles can be explained by flattened cusps because they suffer from conflicting measurements and poor statistics and because there is a large number of conventional processes that could have flattened them sin...
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A Survey of Parallel A*
A* is a best-first search algorithm for finding optimal-cost paths in graphs. A* benefits significantly from parallelism because in many applications, A* is limited by memory usage, so distributed memory implementations of A* that use all of the aggregate memory on the cluster enable problems that can not be solved b...
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Large second harmonic generation enhancement in SiN waveguides by all-optically induced quasi phase matching
Integrated waveguides exhibiting efficient second-order nonlinearities are crucial to obtain compact and low power optical signal processing devices. Silicon nitride (SiN) has shown second harmonic generation (SHG) capabilities in resonant structures and single-pass devices leveraging intermodal phase matching, which...
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Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning
In this paper, we revisit the large-scale constrained linear regression problem and propose faster methods based on some recent developments in sketching and optimization. Our algorithms combine (accelerated) mini-batch SGD with a new method called two-step preconditioning to achieve an approximate solution with a ti...
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Geometrical dependence of domain wall propagation and nucleation fields in magnetic domain wall sensor devices
We study the key domain wall properties in segmented nanowires loop-based structures used in domain wall based sensors. The two reasons for device failure, namely the distribution of domain wall propagation field (depinning) and the nucleation field are determined with Magneto-Optical Kerr Effect (MOKE) and Giant Mag...
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Faster Rates for Policy Learning
This article improves the existing proven rates of regret decay in optimal policy estimation. We give a margin-free result showing that the regret decay for estimating a within-class optimal policy is second-order for empirical risk minimizers over Donsker classes, with regret decaying at a faster rate than the stand...
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Anisotropic Exchange in ${\bf LiCu_2O_2}$
We investigate the magnetic properties of the multiferroic quantum-spin system LiCu$_2$O$_2$ by electron spin resonance (ESR) measurements at $X$- and $Q$-band frequencies in a wide temperature range $(T_{\rm N1} \leq T \leq 300$\,K). The observed anisotropies of the $g$ tensor and the ESR linewidth in untwinned sing...
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Which friends are more popular than you? Contact strength and the friendship paradox in social networks
The friendship paradox states that in a social network, egos tend to have lower degree than their alters, or, "your friends have more friends than you do". Most research has focused on the friendship paradox and its implications for information transmission, but treating the network as static and unweighted. Yet, peo...
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Stochastic Optimization with Bandit Sampling
Many stochastic optimization algorithms work by estimating the gradient of the cost function on the fly by sampling datapoints uniformly at random from a training set. However, the estimator might have a large variance, which inadvertently slows down the convergence rate of the algorithms. One way to reduce this vari...
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Learning Robust Options
Robust reinforcement learning aims to produce policies that have strong guarantees even in the face of environments/transition models whose parameters have strong uncertainty. Existing work uses value-based methods and the usual primitive action setting. In this paper, we propose robust methods for learning temporall...
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Levitation of non-magnetizable droplet inside ferrofluid
The central theme of this work is that a stable levitation of a denser non-magnetizable liquid droplet, against gravity, inside a relatively lighter ferrofluid -- a system barely considered in ferrohydrodynamics -- is possible, and exhibits unique interfacial features; the stability of the levitation trajectory, howe...
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Simultaneous Detection of H and D NMR Signals in a micro-Tesla Field
We present NMR spectra of remote-magnetized deuterated water, detected in an unshielded environment by means of a differential atomic magnetometer. The measurements are performed in a $\mu$T field, while pulsed techniques are applied -following the sample displacement- in a 100~$\mu$T field, to tip both D and H nucle...
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Learning Deep Networks from Noisy Labels with Dropout Regularization
Large datasets often have unreliable labels-such as those obtained from Amazon's Mechanical Turk or social media platforms-and classifiers trained on mislabeled datasets often exhibit poor performance. We present a simple, effective technique for accounting for label noise when training deep neural networks. We augme...
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On Efficiently Detecting Overlapping Communities over Distributed Dynamic Graphs
Modern networks are of huge sizes as well as high dynamics, which challenges the efficiency of community detection algorithms. In this paper, we study the problem of overlapping community detection on distributed and dynamic graphs. Given a distributed, undirected and unweighted graph, the goal is to detect overlappi...
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Structured Black Box Variational Inference for Latent Time Series Models
Continuous latent time series models are prevalent in Bayesian modeling; examples include the Kalman filter, dynamic collaborative filtering, or dynamic topic models. These models often benefit from structured, non mean field variational approximations that capture correlations between time steps. Black box variation...
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$L^p$ Norms of Eigenfunctions on Regular Graphs and on the Sphere
We prove upper bounds on the $L^p$ norms of eigenfunctions of the discrete Laplacian on regular graphs. We then apply these ideas to study the $L^p$ norms of joint eigenfunctions of the Laplacian and an averaging operator over a finite collection of algebraic rotations of the $2$-sphere. Under mild conditions, such j...
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Spatially distributed multipartite entanglement enables Einstein-Podolsky-Rosen steering of atomic clouds
A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. Yet, the robust generation and detection of nonlocal entanglement between spatially separated regions of an ultracold atomic system remains a challenge. Here, we use spin mixing in a tightly confined Bose-Eins...
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Multipath IP Routing on End Devices: Motivation, Design, and Performance
Most end devices are now equipped with multiple network interfaces. Applications can exploit all available interfaces and benefit from multipath transmission. Recently Multipath TCP (MPTCP) was proposed to implement multipath transmission at the transport layer and has attracted lots of attention from academia and in...
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Defense semantics of argumentation: encoding reasons for accepting arguments
In this paper we show how the defense relation among abstract arguments can be used to encode the reasons for accepting arguments. After introducing a novel notion of defenses and defense graphs, we propose a defense semantics together with a new notion of defense equivalence of argument graphs, and compare defense e...
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Fast Global Convergence via Landscape of Empirical Loss
While optimizing convex objective (loss) functions has been a powerhouse for machine learning for at least two decades, non-convex loss functions have attracted fast growing interests recently, due to many desirable properties such as superior robustness and classification accuracy, compared with their convex counter...
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Photodetector figures of merit in terms of POVMs
A photodetector may be characterized by various figures of merit such as response time, bandwidth, dark count rate, efficiency, wavelength resolution, and photon-number resolution. On the other hand, quantum theory says that any measurement device is fully described by its POVM, which stands for Positive-Operator-Val...
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Kinetics of Protein-DNA Interactions: First-Passage Analysis
All living systems can function only far away from equilibrium, and for this reason chemical kinetic methods are critically important for uncovering the mechanisms of biological processes. Here we present a new theoretical method of investigating dynamics of protein-DNA interactions, which govern all major biological...
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Jamming transitions induced by an attraction in pedestrian flow
We numerically study jamming transitions in pedestrian flow interacting with an attraction, mostly based on the social force model for pedestrians who can join the attraction. We formulate the joining probability as a function of social influence from others, reflecting that individual choice behavior is likely influ...
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A Deep Active Survival Analysis Approach for Precision Treatment Recommendations: Application of Prostate Cancer
Survival analysis has been developed and applied in the number of areas including manufacturing, finance, economics and healthcare. In healthcare domain, usually clinical data are high-dimensional, sparse and complex and sometimes there exists few amount of time-to-event (labeled) instances. Therefore building an acc...
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Detecting Topological Changes in Dynamic Community Networks
The study of time-varying (dynamic) networks (graphs) is of fundamental importance for computer network analytics. Several methods have been proposed to detect the effect of significant structural changes in a time series of graphs. The main contribution of this work is a detailed analysis of a dynamic community grap...
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Online Boosting Algorithms for Multi-label Ranking
We consider the multi-label ranking approach to multi-label learning. Boosting is a natural method for multi-label ranking as it aggregates weak predictions through majority votes, which can be directly used as scores to produce a ranking of the labels. We design online boosting algorithms with provable loss bounds f...
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Semisuper Efimov effect of two-dimensional bosons at a three-body resonance
Wave-particle duality in quantum mechanics allows for a halo bound state whose spatial extension far exceeds a range of the interaction potential. What is even more striking is that such quantum halos can be arbitrarily large on special occasions. The two examples known so far are the Efimov effect and the super Efim...
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Free quantitative fourth moment theorems on Wigner space
We prove a quantitative Fourth Moment Theorem for Wigner integrals of any order with symmetric kernels, generalizing an earlier result from Kemp et al. (2012). The proof relies on free stochastic analysis and uses a new biproduct formula for bi-integrals. A consequence of our main result is a Nualart-Ortiz-Latorre ty...
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Optimizing the Latent Space of Generative Networks
Generative Adversarial Networks (GANs) have been shown to be able to sample impressively realistic images. GAN training consists of a saddle point optimization problem that can be thought of as an adversarial game between a generator which produces the images, and a discriminator, which judges if the images are real....
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Conservativity of realizations on motives of abelian type over finite fields
We show that the l-adic realization functor is conservative when restricted to the Chow motives of abelian type over a finite field. A weak version of this conservativity result extends to mixed motives of abelian type.
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Towards understanding startup product development as effectual entrepreneurial behaviors
Software startups face with multiple technical and business challenges, which could make the startup journey longer, or even become a failure. Little is known about entrepreneurial decision making as a direct force to startup development outcome. In this study, we attempted to apply a behaviour theory of entrepreneur...
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Generalized Dirac structure beyond the linear regime in graphene
We show that a generalized Dirac structure survives beyond the linear regime of the low-energy dispersion relations of graphene. A generalized uncertainty principle of the kind compatible with specific quantum gravity scenarios with a fundamental minimal length (here graphene lattice spacing) and Lorentz violation (h...
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Generative Mixture of Networks
A generative model based on training deep architectures is proposed. The model consists of K networks that are trained together to learn the underlying distribution of a given data set. The process starts with dividing the input data into K clusters and feeding each of them into a separate network. After few iteratio...
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Shape-dependence of the barrier for skyrmions on a two-lane racetrack
Single magnetic skyrmions are localized whirls in the magnetization with an integer winding number. They have been observed on nano-meter scales up to room temperature in multilayer structures. Due to their small size, topological winding number, and their ability to be manipulated by extremely tiny forces, they are ...
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Further Results on Size and Power of Heteroskedasticity and Autocorrelation Robust Tests, with an Application to Trend Testing
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample results on size and power of heteroskedasticity and autocorrelation robust tests. These allows us, in particular, to show that the sufficient conditions for the existence of size-controlling critical values recently ob...
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A powerful approach to the study of moderate effect modification in observational studies
Effect modification means the magnitude or stability of a treatment effect varies as a function of an observed covariate. Generally, larger and more stable treatment effects are insensitive to larger biases from unmeasured covariates, so a causal conclusion may be considerably firmer if this pattern is noted if it oc...
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Ad-blocking: A Study on Performance, Privacy and Counter-measures
Many internet ventures rely on advertising for their revenue. However, users feel discontent by the presence of ads on the websites they visit, as the data-size of ads is often comparable to that of the actual content. This has an impact not only on the loading time of webpages, but also on the internet bill of the u...
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On the quantum differentiation of smooth real-valued functions
Calculating the value of $C^{k\in\{1,\infty\}}$ class of smoothness real-valued function's derivative in point of $\mathbb{R}^+$ in radius of convergence of its Taylor polynomial (or series), applying an analog of Newton's binomial theorem and $q$-difference operator. $(P,q)$-power difference introduced in section 5....
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On recognizing shapes of polytopes from their shadows
Let $P$ and $Q$ be two convex polytopes both contained in the interior of an Euclidean ball $r\textbf{B}^{d}$. We prove that $P=Q$ provided that their sight cones from any point on the sphere $rS^{d-1}$ are congruent. We also prove an analogous result for spherical projections.
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Variational methods for steady-state Darcy/Fick flow in swollen and poroelastic solids
Existence of steady states in elastic media at small strains with diffusion of a solvent or fluid due to Fick's or Darcy's laws is proved by combining usage of variational methods inspired from static situations with Schauder's fixed-point arguments. In the plain variant, the problem consists in the force equilibrium...
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Case Studies on Plasma Wakefield Accelerator Design
The field of plasma-based particle accelerators has seen tremendous progress over the past decade and experienced significant growth in the number of activities. During this process, the involved scientific community has expanded from traditional university-based research and is now encompassing many large research l...
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GANs for Biological Image Synthesis
In this paper, we propose a novel application of Generative Adversarial Networks (GAN) to the synthesis of cells imaged by fluorescence microscopy. Compared to natural images, cells tend to have a simpler and more geometric global structure that facilitates image generation. However, the correlation between the spati...
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An objective classification of Saturn cloud features from Cassini ISS images
A clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturns northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible-infrared images of Ear...
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The Peridynamic Stress Tensors and the Non-local to Local Passage
We re-examine the notion of stress in peridynamics. Based on the idea of traction we define two new peridynamic stress tensors $\mathbf{P}^{\mathbf{y}}$ and $\mathbf{P}$ which stand, respectively, for analogues of the Cauchy and 1st Piola-Kirchhoff stress tensors from classical elasticity. We show that the tensor $\m...
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Identification of Unmodeled Objects from Symbolic Descriptions
Successful human-robot cooperation hinges on each agent's ability to process and exchange information about the shared environment and the task at hand. Human communication is primarily based on symbolic abstractions of object properties, rather than precise quantitative measures. A comprehensive robotic framework th...
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Balanced News Using Constrained Bandit-based Personalization
We present a prototype for a news search engine that presents balanced viewpoints across liberal and conservative articles with the goal of de-polarizing content and allowing users to escape their filter bubble. The balancing is done according to flexible user-defined constraints, and leverages recent advances in con...
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Intuitionistic Layered Graph Logic: Semantics and Proof Theory
Models of complex systems are widely used in the physical and social sciences, and the concept of layering, typically building upon graph-theoretic structure, is a common feature. We describe an intuitionistic substructural logic called ILGL that gives an account of layering. The logic is a bunched system, combining ...
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Learning Efficient Image Representation for Person Re-Identification
Color names based image representation is successfully used in person re-identification, due to the advantages of being compact, intuitively understandable as well as being robust to photometric variance. However, there exists the diversity between underlying distribution of color names' RGB values and that of image ...
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Exciting Nucleons in Compton Scattering and Hydrogen-Like Atoms
This PhD thesis is devoted to the low-energy structure of the nucleon (proton and neutron) as seen through electromagnetic probes, e.g., electron and Compton scattering. The research presented here is based primarily on dispersion theory and chiral effective-field theory. The main motivation is the recent proton radi...
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Multiple universalities in order-disorder magnetic phase transitions
Phase transitions in isotropic quantum antiferromagnets are associated with the condensation of bosonic triplet excitations. In three dimensional quantum antiferromagnets, such as TlCuCl$_3$, condensation can be either pressure or magnetic field induced. The corresponding magnetic order obeys universal scaling with t...
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Exact Inference of Causal Relations in Dynamical Systems
From philosophers of ancient times to modern economists, biologists and other researchers are engaged in revealing causal relations. The most challenging problem is inferring the type of the causal relationship: whether it is uni- or bi-directional or only apparent - implied by a hidden common cause only. Modern tech...
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Privacy-Preserving Deep Inference for Rich User Data on The Cloud
Deep neural networks are increasingly being used in a variety of machine learning applications applied to rich user data on the cloud. However, this approach introduces a number of privacy and efficiency challenges, as the cloud operator can perform secondary inferences on the available data. Recently, advances in ed...
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Gradient Method With Inexact Oracle for Composite Non-Convex Optimization
In this paper, we develop new first-order method for composite non-convex minimization problems with simple constraints and inexact oracle. The objective function is given as a sum of "`hard"', possibly non-convex part, and "`simple"' convex part. Informally speaking, oracle inexactness means that, for the "`hard"' p...
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Kernel Implicit Variational Inference
Recent progress in variational inference has paid much attention to the flexibility of variational posteriors. One promising direction is to use implicit distributions, i.e., distributions without tractable densities as the variational posterior. However, existing methods on implicit posteriors still face challenges ...
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The Ringel dual of the Auslander-Dlab-Ringel algebra
The ADR algebra $R_A$ of a finite-dimensional algebra $A$ is a quasihereditary algebra. In this paper we study the Ringel dual $\mathcal{R}(R_A)$ of $R_A$. We prove that $\mathcal{R}(R_A)$ can be identified with $(R_{A^{op}})^{op}$, under certain 'minimal' regularity conditions for $A$. We also give necessary and suf...
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The socle filtrations of principal series representations of $SL(3,\mathbb{R})$ and $Sp(2,\mathbb{R})$
We study the structure of the $(\mathfrak{g},K)$-modules of the principal series representations of $SL(3,\mathbb{R})$ and $Sp(2,\mathbb{R})$ induced from minimal parabolic subgroups, in the case when the infinitesimal character is nonsingular. The composition factors of these modules are known by Kazhdan-Lusztig-Vog...
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Improving the phase response of an atom interferometer by means of temporal pulse shaping
We study theoretically and experimentally the influence of temporally shaping the light pulses in an atom interferometer, with a focus on the phase response of the interferometer. We show that smooth light pulse shapes allow rejecting high frequency phase fluctuations (above the Rabi frequency) and thus relax the req...
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Helium-like and Lithium-like ions: Ground state energy
It is shown that the non-relativistic ground state energy of helium-like and lithium-like ions with static nuclei can be interpolated in full physics range of nuclear charges $Z$ with accuracy of not less than 6 decimal digits (d.d.) or 7-8 significant digits (s.d.) using a meromorphic function in appropriate variabl...
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Improvement of training set structure in fusion data cleaning using Time-Domain Global Similarity method
Traditional data cleaning identifies dirty data by classifying original data sequences, which is a class$-$imbalanced problem since the proportion of incorrect data is much less than the proportion of correct ones for most diagnostic systems in Magnetic Confinement Fusion (MCF) devices. When using machine learning al...
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Eigenvalue Solvers for Modeling Nuclear Reactors on Leadership Class Machines
Three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a Rayleigh Quotient Iteration (RQI) eigenvalue solver, and a multigrid in energy (...
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Thermoregulation in mice, rats and humans: An insight into the evolution of human hairlessness
The thermoregulation system in animals removes body heat in hot temperatures and retains body heat in cold temperatures. The better the animal removes heat, the worse the animal retains heat and visa versa. It is the balance between these two conflicting goals that determines the mammal's size, heart rate and amount ...
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Koszul A-infinity algebras and free loop space homology
We introduce a notion of Koszul A-infinity algebra that generalizes Priddy's notion of a Koszul algebra and we use it to construct small A-infinity algebra models for Hochschild cochains. As an application, this yields new techniques for computing free loop space homology algebras of manifolds that are either formal ...
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Learning RBM with a DC programming Approach
By exploiting the property that the RBM log-likelihood function is the difference of convex functions, we formulate a stochastic variant of the difference of convex functions (DC) programming to minimize the negative log-likelihood. Interestingly, the traditional contrastive divergence algorithm is a special case of ...
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