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Manipulative Elicitation -- A New Attack on Elections with Incomplete Preferences
Lu and Boutilier proposed a novel approach based on "minimax regret" to use classical score based voting rules in the setting where preferences can be any partial (instead of complete) orders over the set of alternatives. We show here that such an approach is vulnerable to a new kind of manipulation which was not pre...
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Modeling The Intensity Function Of Point Process Via Recurrent Neural Networks
Event sequence, asynchronously generated with random timestamp, is ubiquitous among applications. The precise and arbitrary timestamp can carry important clues about the underlying dynamics, and has lent the event data fundamentally different from the time-series whereby series is indexed with fixed and equal time in...
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A note on relative amenable of finite von Neumann algebras
Let $M$ be a finite von Neumann algebra (resp. a type II$_{1}$ factor) and let $N\subset M$ be a II$_{1}$ factor (resp. $N\subset M$ have an atomic part). We prove that the inclusion $N\subset M$ is amenable implies the identity map on $M$ has an approximate factorization through $M_m(\mathbb{C})\otimes N $ via trace...
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Powerful numbers in $(1^{\ell}+q^{\ell})(2^{\ell}+q^{\ell})\cdots (n^{\ell}+q^{\ell})$
Let $q$ be a positive integer. Recently, Niu and Liu proved that if $n\ge \max\{q,1198-q\}$, then the product $(1^3+q^3)(2^3+q^3)\cdots (n^3+q^3)$ is not a powerful number. In this note, we prove that (i) for any odd prime power $\ell$ and $n\ge \max\{q,11-q\}$, the product $(1^{\ell}+q^{\ell})(2^{\ell}+q^{\ell})\cdo...
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LandmarkBoost: Efficient Visual Context Classifiers for Robust Localization
The growing popularity of autonomous systems creates a need for reliable and efficient metric pose retrieval algorithms. Currently used approaches tend to rely on nearest neighbor search of binary descriptors to perform the 2D-3D matching and guarantee realtime capabilities on mobile platforms. These methods struggle...
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On stably trivial spin torsors over low-dimensional schemes
The paper discusses stably trivial torsors for spin and orthogonal groups over smooth affine schemes over infinite perfect fields of characteristic unequal to 2. We give a complete description of all the invariants relevant for the classification of such objects over schemes of dimension at most $3$, along with many ...
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On the relation between dependency distance, crossing dependencies, and parsing. Comment on "Dependency distance: a new perspective on syntactic patterns in natural languages" by Haitao Liu et al
Liu et al. (2017) provide a comprehensive account of research on dependency distance in human languages. While the article is a very rich and useful report on this complex subject, here I will expand on a few specific issues where research in computational linguistics (specifically natural language processing) can in...
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Edge Erasures and Chordal Graphs
We prove several results about chordal graphs and weighted chordal graphs by focusing on exposed edges. These are edges that are properly contained in a single maximal complete subgraph. This leads to a characterization of chordal graphs via deletions of a sequence of exposed edges from a complete graph. Most interes...
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One-dimensional plasmonic hotspots located between silver nanowire dimers evaluated by surface-enhanced resonance Raman scattering
Hotspots of surface-enhanced resonance Raman scattering (SERRS) are localized within 1 nm at gaps or crevices of plasmonic nanoparticle (NP) dimers. We demonstrate SERRS hotspots with volumes that are extended in one dimension tens of thousand times compared to standard zero-dimensional hotspots using gaps or crevice...
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An efficient methodology for the analysis and modeling of computer experiments with large number of inputs
Complex computer codes are often too time expensive to be directly used to perform uncertainty, sensitivity, optimization and robustness analyses. A widely accepted method to circumvent this problem consists in replacing cpu-time expensive computer models by cpu inexpensive mathematical functions, called metamodels. ...
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Knowledge Adaptation: Teaching to Adapt
Domain adaptation is crucial in many real-world applications where the distribution of the training data differs from the distribution of the test data. Previous Deep Learning-based approaches to domain adaptation need to be trained jointly on source and target domain data and are therefore unappealing in scenarios w...
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A Datamining Approach for Emotions Extraction and Discovering Cricketers performance from Stadium to Sensex
Microblogging sites are the direct platform for the users to express their views. It has been observed from previous studies that people are viable to flaunt their emotions for events (eg. natural catastrophes, sports, academics etc.), for persons (actor/actress, sports person, scientist) and for the places they visi...
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Local Nonparametric Estimation for Second-Order Jump-Diffusion Model Using Gamma Asymmetric Kernels
This paper discusses the local linear smoothing to estimate the unknown first and second infinitesimal moments in second-order jump-diffusion model based on Gamma asymmetric kernels. Under the mild conditions, we obtain the weak consistency and the asymptotic normality of these estimators for both interior and bounda...
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Ergodic actions of the compact quantum group $O_{-1}(2)$
Among the ergodic actions of a compact quantum group $\mathbb{G}$ on possibly non-commutative spaces, those that are {\it embeddable} are the natural analogues of actions of a compact group on its homogeneous spaces. These can be realized as {\it coideal subalgebras} of the function algebra $\mathcal{O}(\mathbb{G})$ ...
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On Vector ARMA Models Consistent with a Finite Matrix Covariance Sequence
We formulate the so called "VARMA covariance matching problem" and demonstrate the existence of a solution using the degree theory from differential topology.
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Edge states in non-Fermi liquids
We devise an approach to the calculation of scaling dimensions of generic operators describing scattering within multi-channel Luttinger liquid. The local impurity scattering in an arbitrary configuration of conducting and insulating channels is investigated and the problem is reduced to a single algebraic matrix equ...
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RobustFill: Neural Program Learning under Noisy I/O
The problem of automatically generating a computer program from some specification has been studied since the early days of AI. Recently, two competing approaches for automatic program learning have received significant attention: (1) neural program synthesis, where a neural network is conditioned on input/output (I/...
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Review of flexible and transparent thin-film transistors based on zinc oxide and related materials
Flexible and transparent electronics presents a new era of electronic technologies. Ubiquitous applications involve wearable electronics, biosensors, flexible transparent displays, radio-frequency identifications (RFIDs), etc.Zinc oxide (ZnO) and related materials are the most commonly used inorganic semiconductors i...
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Updated physics design of the DAEdALUS and IsoDAR coupled cyclotrons for high intensity H2+ beam production
The Decay-At-rest Experiment for delta-CP violation At a Laboratory for Underground Science (DAEdALUS) and the Isotope Decay-At-Rest experiment (IsoDAR) are proposed experiments to search for CP violation in the neutrino sector, and "sterile" neutrinos, respectively. In order to be decisive within 5 years, the neutri...
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Scalable Gaussian Process Computations Using Hierarchical Matrices
We present a kernel-independent method that applies hierarchical matrices to the problem of maximum likelihood estimation for Gaussian processes. The proposed approximation provides natural and scalable stochastic estimators for its gradient and Hessian, as well as the expected Fisher information matrix, that are com...
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Evolutionary Data Systems
Anyone in need of a data system today is confronted with numerous complex options in terms of system architectures, such as traditional relational databases, NoSQL and NewSQL solutions as well as several sub-categories like column-stores, row-stores etc. This overwhelming array of choices makes bootstrapping data-dri...
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Optimal Learning for Sequential Decision Making for Expensive Cost Functions with Stochastic Binary Feedbacks
We consider the problem of sequentially making decisions that are rewarded by "successes" and "failures" which can be predicted through an unknown relationship that depends on a partially controllable vector of attributes for each instance. The learner takes an active role in selecting samples from the instance pool....
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Determination of hysteresis in finite-state random walks using Bayesian cross validation
Consider the problem of modeling hysteresis for finite-state random walks using higher-order Markov chains. This Letter introduces a Bayesian framework to determine, from data, the number of prior states of recent history upon which a trajectory is statistically dependent. The general recommendation is to use leave-o...
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Moyennes effectives de fonctions multiplicatives complexes
We establish effective mean-value estimates for a wide class of multiplicative arithmetic functions, thereby providing (essentially optimal) quantitative versions of Wirsing's classical estimates and extending those of Halász. Several applications are derived, including: estimates for the difference of mean-values of...
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Magnetic Excitations and Continuum of a Field-Induced Quantum Spin Liquid in $α$-RuCl$_3$
We report on terahertz spectroscopy of quantum spin dynamics in $\alpha$-RuCl$_3$, a system proximate to the Kitaev honeycomb model, as a function of temperature and magnetic field. An extended magnetic continuum develops below the structural phase transition at $T_{s2}=62$K. With the onset of a long-range magnetic o...
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Wireless Network-Level Partial Relay Cooperation: A Stable Throughput Analysis
In this work, we study the benefit of partial relay cooperation. We consider a two-node system consisting of one source and one relay node transmitting information to a common destination. The source and the relay have external traffic and in addition, the relay is equipped with a flow controller to regulate the inco...
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Improving Development Practices through Experimentation: an Industrial TDD Case
Test-Driven Development (TDD), an agile development approach that enforces the construction of software systems by means of successive micro-iterative testing coding cycles, has been widely claimed to increase external software quality. In view of this, some managers at Paf-a Nordic gaming entertainment company-were ...
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An explicit Gross-Zagier formula related to the Sylvester Conjecture
Let $p\equiv 4,7\mod 9$ be a rational prime number such that $3\mod p$ is not a cubic residue. In this paper we prove the 3-part of the product of the full BSD conjectures for $E_p$ and $E_{3p^3}$ is true using an explicit Gross-Zagier formula, where $E_p: x^3+y^3=p$ and $E_{3p^2}: x^3+y^3=3p^2$ are the elliptic curv...
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Case Studies of Exocomets in the System of HD 10180
The aim of our study is to investigate the dynamics of possible comets in the HD 10180 system. This investigation is motivated by the discovery of exocomets in various systems, especially $\beta$ Pictoris, as well as in at least ten other systems. Detailed theoretical studies about the formation and evolution of star...
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3D ab initio modeling in cryo-EM by autocorrelation analysis
Single-Particle Reconstruction (SPR) in Cryo-Electron Microscopy (cryo-EM) is the task of estimating the 3D structure of a molecule from a set of noisy 2D projections, taken from unknown viewing directions. Many algorithms for SPR start from an initial reference molecule, and alternate between refining the estimated ...
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Reinforcement Learning with a Corrupted Reward Channel
No real-world reward function is perfect. Sensory errors and software bugs may result in RL agents observing higher (or lower) rewards than they should. For example, a reinforcement learning agent may prefer states where a sensory error gives it the maximum reward, but where the true reward is actually small. We form...
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Divisor-sum fibers
Let $s(\cdot)$ denote the sum-of-proper-divisors function, that is, $s(n) = \sum_{d\mid n,~d<n}d$. Erdős-Granville-Pomerance-Spiro conjectured that for any set $\mathcal{A}$ of asymptotic density zero, the preimage set $s^{-1}(\mathcal{A})$ also has density zero. We prove a weak form of this conjecture: If $\epsilon(...
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New zirconium hydrides predicted by structure search method based on first principles calculations
The formation of precipitated zirconium (Zr) hydrides is closely related to the hydrogen embrittlement problem for the cladding materials of pressured water reactors (PWR). In this work, we systematically investigated the crystal structures of zirconium hydride (ZrHx) with different hydrogen concentrations (x = 0~2, ...
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Exchange striction driven magnetodielectric effect and potential photovoltaic effect in polar CaOFeS
CaOFeS is a semiconducting oxysulfide with polar layered triangular structure. Here a comprehensive theoretical study has been performed to reveal its physical properties, including magnetism, electronic structure, phase transition, magnetodielectric effect, as well as optical absorption. Our calculations confirm the...
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Studying Magnetic Fields using Low-frequency Pulsar Observations
Low-frequency polarisation observations of pulsars, facilitated by next-generation radio telescopes, provide powerful probes of astrophysical plasmas that span many orders of magnitude in magnetic field strength and scale: from pulsar magnetospheres to intervening magneto-ionic plasmas including the ISM and the ionos...
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Two-sided Facility Location
Recent years have witnessed the rise of many successful e-commerce marketplace platforms like the Amazon marketplace, AirBnB, Uber/Lyft, and Upwork, where a central platform mediates economic transactions between buyers and sellers. Motivated by these platforms, we formulate a set of facility location problems that w...
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Optimal hedging under fast-varying stochastic volatility
In a market with a rough or Markovian mean-reverting stochastic volatility there is no perfect hedge. Here it is shown how various delta-type hedging strategies perform and can be evaluated in such markets. A precise characterization of the hedging cost, the replication cost caused by the volatility fluctuations, is ...
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Personal Food Computer: A new device for controlled-environment agriculture
Due to their interdisciplinary nature, devices for controlled-environment agriculture have the possibility to turn into ideal tools not only to conduct research on plant phenology but also to create curricula in a wide range of disciplines. Controlled-environment devices are increasing their functionalities as well a...
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Quenched Noise and Nonlinear Oscillations in Bistable Multiscale Systems
Nonlinear oscillators are a key modelling tool in many applications. The influence of annealed noise on nonlinear oscillators has been studied intensively. It can induce effects in nonlinear oscillators not present in the deterministic setting. Yet, there is no theory regarding the quenched noise scenario of random p...
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Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning
The recently proposed Multi-Layer Convolutional Sparse Coding (ML-CSC) model, consisting of a cascade of convolutional sparse layers, provides a new interpretation of Convolutional Neural Networks (CNNs). Under this framework, the computation of the forward pass in a CNN is equivalent to a pursuit algorithm aiming to...
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Coble's group and the integrability of the Gosset-Elte polytopes and tessellations
This paper considers the planar figure of a combinatorial polytope or tessellation identified by the Coxeter symbol $k_{i,j}$ , inscribed in a conic, satisfying the geometric constraint that each octahedral cell has a centre. This realisation exists, and is movable, on account of some constraints being satisfied as a...
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Latent Hinge-Minimax Risk Minimization for Inference from a Small Number of Training Samples
Deep Learning (DL) methods show very good performance when trained on large, balanced data sets. However, many practical problems involve imbalanced data sets, or/and classes with a small number of training samples. The performance of DL methods as well as more traditional classifiers drops significantly in such sett...
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Autonomous Vehicle Speed Control for Safe Navigation of Occluded Pedestrian Crosswalk
Both humans and the sensors on an autonomous vehicle have limited sensing capabilities. When these limitations coincide with scenarios involving vulnerable road users, it becomes important to account for these limitations in the motion planner. For the scenario of an occluded pedestrian crosswalk, the speed of the ap...
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Statistical inference methods for cumulative incidence function curves at a fixed point in time
Competing risks data arise frequently in clinical trials. When the proportional subdistribution hazard assumption is violated or two cumulative incidence function (CIF) curves cross, rather than comparing the overall treatment effects, researchers may be interested in focusing on a comparison of clinical utility at s...
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Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines
We compare and contrast the statistical physics and quantum physics inspired approaches for unsupervised generative modeling of classical data. The two approaches represent probabilities of observed data using energy-based models and quantum states respectively.Classical and quantum information patterns of the target...
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A Cofibration Category on Closure Spaces
We construct a cofibration category structure on the category of closure spaces $\mathbf{Cl}$, the category whose objects are sets endowed with a Čech closure operator and whose morphisms are the continuous maps between them. We then study various closure structures on metric spaces, graphs, and simplicial complexes,...
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XSAT of Linear CNF Formulas
Open questions with respect to the computational complexity of linear CNF formulas in connection with regularity and uniformity are addressed. In particular it is proven that any l-regular monotone CNF formula is XSAT-unsatisfiable if its number of clauses m is not a multiple of l. For exact linear formulas one finds...
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Drone Squadron Optimization: a Self-adaptive Algorithm for Global Numerical Optimization
This paper proposes Drone Squadron Optimization, a new self-adaptive metaheuristic for global numerical optimization which is updated online by a hyper-heuristic. DSO is an artifact-inspired technique, as opposed to many algorithms used nowadays, which are nature-inspired. DSO is very flexible because it is not relat...
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A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets
The original ImageNet dataset is a popular large-scale benchmark for training Deep Neural Networks. Since the cost of performing experiments (e.g, algorithm design, architecture search, and hyperparameter tuning) on the original dataset might be prohibitive, we propose to consider a downsampled version of ImageNet. I...
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Stability of Conditional Sequential Monte Carlo
The particle Gibbs (PG) sampler is a Markov Chain Monte Carlo (MCMC) algorithm, which uses an interacting particle system to perform the Gibbs steps. Each Gibbs step consists of simulating a particle system conditioned on one particle path. It relies on a conditional Sequential Monte Carlo (cSMC) method to create the...
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Diffusion along chains of normally hyperbolic cylinders
The present paper is part of a series of articles dedicated to the existence of Arnold diffusion for cusp-residual perturbations of Tonelli Hamiltonians on $\mathbb{A}^3$. Our goal here is to construct an abstract geometric framework that can be used to prove the existence of diffusing orbits in the so-called a prior...
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Multi-wavelength Spectral Analysis of Ellerman Bombs Observed by FISS and IRIS
Ellerman bombs (EBs) are a kind of solar activities that is suggested to occur in the lower atmosphere. Recent observations using the Interface Region Imaging Spectrograph (IRIS) show connections of EBs and IRIS bombs (IBs), implying that EBs might be heated to a much higher temperature ($8\times10^{4}$ K) than previ...
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Numerical study of the Kadomtsev--Petviashvili equation and dispersive shock waves
A detailed numerical study of the long time behaviour of dispersive shock waves in solutions to the Kadomtsev-Petviashvili (KP) I equation is presented. It is shown that modulated lump solutions emerge from the dispersive shock waves. For the description of dispersive shock waves, Whitham modulation equations for KP ...
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Asymptotic power of Rao's score test for independence in high dimensions
Let ${\bf R}$ be the Pearson correlation matrix of $m$ normal random variables. The Rao's score test for the independence hypothesis $H_0 : {\bf R} = {\bf I}_m$, where ${\bf I}_m$ is the identity matrix of dimension $m$, was first considered by Schott (2005) in the high dimensional setting. In this paper, we study th...
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Sensing and Modeling Human Behavior Using Social Media and Mobile Data
In the past years we have witnessed the emergence of the new discipline of computational social science, which promotes a new data-driven and computation-based approach to social sciences. In this article we discuss how the availability of new technologies such as online social media and mobile smartphones has allowe...
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Interior transmission eigenvalue problems on compact manifolds with boundary conductivity parameters
In this paper, we consider an interior transmission eigenvalue (ITE) problem on some compact $C^{\infty }$-Riemannian manifolds with a common smooth boundary. In particular, these manifolds may have different topologies, but we impose some conditions of Riemannian metrics, indices of refraction and boundary conductiv...
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A superpolynomial lower bound for the size of non-deterministic complement of an unambiguous automaton
Unambiguous non-deterministic finite automata have intermediate expressive power and succinctness between deterministic and non-deterministic automata. It has been conjectured that every unambiguous non-deterministic one-way finite automaton (1UFA) recognizing some language L can be converted into a 1UFA recognizing ...
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Taxonomy Induction using Hypernym Subsequences
We propose a novel, semi-supervised approach towards domain taxonomy induction from an input vocabulary of seed terms. Unlike all previous approaches, which typically extract direct hypernym edges for terms, our approach utilizes a novel probabilistic framework to extract hypernym subsequences. Taxonomy induction fro...
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Identifying Clickbait Posts on Social Media with an Ensemble of Linear Models
The purpose of a clickbait is to make a link so appealing that people click on it. However, the content of such articles is often not related to the title, shows poor quality, and at the end leaves the reader unsatisfied. To help the readers, the organizers of the clickbait challenge (this http URL) asked the partici...
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WYS*: A DSL for Verified Secure Multi-party Computations
Secure multi-party computation (MPC) enables a set of mutually distrusting parties to cooperatively compute, using a cryptographic protocol, a function over their private data. This paper presents Wys*, a new domain-specific language (DSL) for writing mixed-mode MPCs. Wys* is an embedded DSL hosted in F*, a verificat...
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Probabilities of causation of climate changes
Multiple changes in Earth's climate system have been observed over the past decades. Determining how likely each of these changes are to have been caused by human influence, is important for decision making on mitigation and adaptation policy. Here we describe an approach for deriving the probability that anthropogen...
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A Realistic Dataset for the Smart Home Device Scheduling Problem for DCOPs
The field of Distributed Constraint Optimization has gained momentum in recent years thanks to its ability to address various applications related to multi-agent cooperation. While techniques to solve Distributed Constraint Optimization Problems (DCOPs) are abundant and have matured substantially since the field ince...
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The extra scalar degrees of freedom from the two Higgs doublet model for dark energy
In principle a minimal extension of the standard model of Particle Physics, the two Higgs doublet model, can be invoked to explain the scalar field responsible of dark energy. The two doublets are in general mixed. After diagonalization, the lightest CP-even Higgs and CP-odd Higgs are jointly taken to be the dark ene...
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Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
We consider the problem of transferring policies to the real world by training on a distribution of simulated scenarios. Rather than manually tuning the randomization of simulations, we adapt the simulation parameter distribution using a few real world roll-outs interleaved with policy training. In doing so, we are a...
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Revisiting Simple Neural Networks for Learning Representations of Knowledge Graphs
We address the problem of learning vector representations for entities and relations in Knowledge Graphs (KGs) for Knowledge Base Completion (KBC). This problem has received significant attention in the past few years and multiple methods have been proposed. Most of the existing methods in the literature use a predef...
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On the tail behavior of a class of multivariate conditionally heteroskedastic processes
Conditions for geometric ergodicity of multivariate autoregressive conditional heteroskedasticity (ARCH) processes, with the so-called BEKK (Baba, Engle, Kraft, and Kroner) parametrization, are considered. We show for a class of BEKK-ARCH processes that the invariant distribution is regularly varying. In order to acc...
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On the Complexity of Detecting Convexity over a Box
It has recently been shown that the problem of testing global convexity of polynomials of degree four is {strongly} NP-hard, answering an open question of N.Z. Shor. This result is minimal in the degree of the polynomial when global convexity is of concern. In a number of applications however, one is interested in te...
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Variance-Reduced Stochastic Learning under Random Reshuffling
Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizer. The existing convergence results assume uniform data sampling with replacement. However, it has been observed i...
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CELIO: An application development framework for interactive spaces
Developing applications for interactive space is different from developing cross-platform applications for personal computing. Input, output, and architectural variations in each interactive space introduce big overhead in terms of cost and time for developing, deploying and maintaining applications for interactive s...
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Single Iteration Conditional Based DSE Considering Spatial and Temporal Correlation
The increasing complexity of distribution network calls for advancement in distribution system state estimation (DSSE) to monitor the operating conditions more accurately. Sufficient number of measurements is imperative for a reliable and accurate state estimation. The limitation on the measurement devices is general...
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Enhanced Network Embeddings via Exploiting Edge Labels
Network embedding methods aim at learning low-dimensional latent representation of nodes in a network. While achieving competitive performance on a variety of network inference tasks such as node classification and link prediction, these methods treat the relations between nodes as a binary variable and ignore the ri...
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Virtual Constraints and Hybrid Zero Dynamics for Realizing Underactuated Bipedal Locomotion
Underactuation is ubiquitous in human locomotion and should be ubiquitous in bipedal robotic locomotion as well. This chapter presents a coherent theory for the design of feedback controllers that achieve stable walking gaits in underactuated bipedal robots. Two fundamental tools are introduced, virtual constraints a...
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Selective insulators and anomalous responses in correlated fermions with synthetic extra dimensions
We study a three-component fermionic fluid in an optical lattice in a regime of intermediate-to- strong interactions allowing for Raman processes connecting the different components, similar to those used to create artificial gauge fields (AGF). Using Dynamical Mean-Field Theory we show that the combined effect of in...
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Computation of optimal transport and related hedging problems via penalization and neural networks
This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it to a finite dimensional one which corresponds to optimizing a neural network ...
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Active particles in periodic lattices
Both natural and artificial small-scale swimmers may often self-propel in environments subject to complex geometrical constraints. While most past theoretical work on low-Reynolds number locomotion addressed idealised geometrical situations, not much is known on the motion of swimmers in heterogeneous environments. A...
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First measeurements in search for keV-sterile neutrino in tritium beta-decay by Troitsk nu-mass experiment
We present the first measurements of tritium beta-decay spectrum in the electron energy range 16-18.6 keV. The goal is to find distortions which may correspond to the presence of a heavy sterile neutrinos. A possible contribution of this kind would manifest itself as a kink in the spectrum with a similar shape but wi...
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Fractional Abelian topological phases of matter for fermions in two-dimensional space
These notes constitute chapter 7 from "l'Ecole de Physique des Houches" Session CIII, August 2014 dedicated to Topological Aspects of Condensed matter physics. The tenfold way in quasi-one-dimensional space is presented. The method of chiral Abelian bosonization is reviewed. It is then applied to the stability analys...
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A new construction of universal spaces for asymptotic dimension
For each $n$, we construct a separable metric space $\mathbb{U}_n$ that is universal in the coarse category of separable metric spaces with asymptotic dimension ($\mathop{asdim}$) at most $n$ and universal in the uniform category of separable metric spaces with uniform dimension ($\mathop{udim}$) at most $n$. Thus, $...
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A Comprehensive Framework for Dynamic Bike Rebalancing in a Large Bike Sharing Network
Bike sharing is a vital component of a modern multi-modal transportation system. However, its implementation can lead to bike supply-demand imbalance due to fluctuating spatial and temporal demands. This study proposes a comprehensive framework to develop optimal dynamic bike rebalancing strategies in a large bike sh...
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On Thin Air Reads: Towards an Event Structures Model of Relaxed Memory
To model relaxed memory, we propose confusion-free event structures over an alphabet with a justification relation. Executions are modeled by justified configurations, where every read event has a justifying write event. Justification alone is too weak a criterion, since it allows cycles of the kind that result in so...
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Tensor ring decomposition
Tensor decompositions such as the canonical format and the tensor train format have been widely utilized to reduce storage costs and operational complexities for high-dimensional data, achieving linear scaling with the input dimension instead of exponential scaling. In this paper, we investigate even lower storage-co...
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Combining Information from Multiple Forecasters: Inefficiency of Central Tendency
Even though the forecasting literature agrees that aggregating multiple predictions of some future outcome typically outperforms the individual predictions, there is no general consensus about the right way to do this. Most common aggregators are means, defined loosely as aggregators that always remain between the sm...
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QCD-Aware Recursive Neural Networks for Jet Physics
Recent progress in applying machine learning for jet physics has been built upon an analogy between calorimeters and images. In this work, we present a novel class of recursive neural networks built instead upon an analogy between QCD and natural languages. In the analogy, four-momenta are like words and the clusteri...
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A conjecture on $C$-matrices of cluster algebras
For a skew-symmetrizable cluster algebra $\mathcal A_{t_0}$ with principal coefficients at $t_0$, we prove that each seed $\Sigma_t$ of $\mathcal A_{t_0}$ is uniquely determined by its {\bf C-matrix}, which was proposed by Fomin and Zelevinsky in \cite{FZ3} as a conjecture. Our proof is based on the fact that the pos...
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Attacking Similarity-Based Link Prediction in Social Networks
Link prediction is one of the fundamental problems in computational social science. A particularly common means to predict existence of unobserved links is via structural similarity metrics, such as the number of common neighbors; node pairs with higher similarity are thus deemed more likely to be linked. However, a ...
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On algebraic branching programs of small width
In 1979 Valiant showed that the complexity class VP_e of families with polynomially bounded formula size is contained in the class VP_s of families that have algebraic branching programs (ABPs) of polynomially bounded size. Motivated by the problem of separating these classes we study the topological closure VP_e-bar...
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A lightweight thermal heat switch for redundant cryocooling on satellites
A previously designed cryogenic thermal heat switch for space applications has been optimized for low mass, high structural stability, and reliability. The heat switch makes use of the large linear thermal expansion coefficient (CTE) of the thermoplastic UHMW-PE for actuation. A structure model, which includes the te...
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Fast Automatic Smoothing for Generalized Additive Models
Multiple generalized additive models (GAMs) are a type of distributional regression wherein parameters of probability distributions depend on predictors through smooth functions, with selection of the degree of smoothness via $L_2$ regularization. Multiple GAMs allow finer statistical inference by incorporating expla...
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Stabilization and control of Majorana bound states with elongated skyrmions
We show that elongated magnetic skyrmions can host Majorana bound states in a proximity-coupled two-dimensional electron gas sandwiched between a chiral magnet and an $s$-wave superconductor. Our proposal requires stable skyrmions with unit topological charge, which can be realized in a wide range of multilayer magne...
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Meromorphic functions with small Schwarzian derivative
We consider the family of all meromorphic functions $f$ of the form $$ f(z)=\frac{1}{z}+b_0+b_1z+b_2z^2+\cdots $$ analytic and locally univalent in the puncture disk $\mathbb{D}_0:=\{z\in\mathbb{C}:\,0<|z|<1\}$. Our first objective in this paper is to find a sufficient condition for $f$ to be meromorphically convex o...
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Measure-geometric Laplacians for discrete distributions
In 2002 Freiberg and Zähle introduced and developed a harmonic calculus for measure-geometric Laplacians associated to continuous distributions. We show their theory can be extended to encompass distributions with finite support and give a matrix representation for the resulting operators. In the case of a uniform di...
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Optimal heat transfer and optimal exit times
A heat exchanger can be modeled as a closed domain containing an incompressible fluid. The moving fluid has a temperature distribution obeying the advection-diffusion equation, with zero temperature boundary conditions at the walls. Starting from a positive initial temperature distribution in the interior, the goal i...
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A Semantics Comparison Workbench for a Concurrent, Asynchronous, Distributed Programming Language
A number of high-level languages and libraries have been proposed that offer novel and simple to use abstractions for concurrent, asynchronous, and distributed programming. The execution models that realise them, however, often change over time---whether to improve performance, or to extend them to new language featu...
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Simulating Linear Logic in 1-Only Linear Logic
Linear Logic was introduced by Girard as a resource-sensitive refinement of classical logic. It turned out that full propositional Linear Logic is undecidable (Lincoln, Mitchell, Scedrov, and Shankar) and, hence, it is more expressive than (modalized) classical or intuitionistic logic. In this paper we focus on the s...
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Adaptive Network Coding Schemes for Satellite Communications
In this paper, we propose two novel physical layer aware adaptive network coding and coded modulation schemes for time variant channels. The proposed schemes have been applied to different satellite communications scenarios with different Round Trip Times (RTT). Compared to adaptive network coding, and classical non-...
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A Symbolic Computation Framework for Constitutive Modelling Based On Entropy Principles
The entropy principle in the formulation of Müller and Liu is a common tool used in constitutive modelling for the development of restrictions on the unknown constitutive functions describing material properties of various physical continua. In the current work, a symbolic software implementation of the Liu algorithm...
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Measuring bot and human behavioral dynamics
Bots, social media accounts controlled by software rather than by humans, have recently been under the spotlight for their association with various forms of online manipulation. To date, much work has focused on social bot detection, but little attention has been devoted to the characterization and measurement of the...
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Optimal control of elliptic equations with positive measures
Optimal control problems without control costs in general do not possess solutions due to the lack of coercivity. However, unilateral constraints together with the assumption of existence of strictly positive solutions of a pre-adjoint state equation, are sufficient to obtain existence of optimal solutions in the spa...
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Beyond Word Embeddings: Learning Entity and Concept Representations from Large Scale Knowledge Bases
Text representations using neural word embeddings have proven effective in many NLP applications. Recent researches adapt the traditional word embedding models to learn vectors of multiword expressions (concepts/entities). However, these methods are limited to textual knowledge bases (e.g., Wikipedia). In this paper,...
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Fraunhofer diffraction at the two-dimensional quadratically distorted (QD) Grating
A two-dimensional (2D) mathematical model of quadratically distorted (QD) grating is established with the principles of Fraunhofer diffraction and Fourier optics. Discrete sampling and bisection algorithm are applied for finding numerical solution of the diffraction pattern of QD grating. This 2D mathematical model a...
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