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Evidence for short-range magnetic order in the nematic phase of FeSe from anisotropic in-plane magnetostriction and susceptibility measurements
The nature of the nematic state in FeSe remains one of the major unsolved mysteries in Fe- based superconductors. Both spin and orbital physics have been invoked to explain the origin of this phase. Here we present experimental evidence for frustrated, short-range magnetic order, as suggested by several recent theore...
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Contextual Parameter Generation for Universal Neural Machine Translation
We propose a simple modification to existing neural machine translation (NMT) models that enables using a single universal model to translate between multiple languages while allowing for language specific parameterization, and that can also be used for domain adaptation. Our approach requires no changes to the model...
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Opinion Dynamics with Stubborn Agents
We consider the problem of optimizing the placement of stubborn agents in a social network in order to maximally impact population opinions. We assume individuals in a directed social network each have a latent opinion that evolves over time in response to social media posts by their neighbors. The individuals random...
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A Community Microgrid Architecture with an Internal Local Market
This work fits in the context of community microgrids, where members of a community can exchange energy and services among themselves, without going through the usual channels of the public electricity grid. We introduce and analyze a framework to operate a community microgrid, and to share the resulting revenues and...
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Extended nilHecke algebra and symmetric functions in type B
We formulate a type B extended nilHecke algebra, following the type A construction of Naisse and Vaz. We describe an action of this algebra on extended polynomials and describe some results on the structure on the extended symmetric polynomials. Finally, following Appel, Egilmez, Hogancamp, and Lauda, we prove a resu...
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One-Sided Unsupervised Domain Mapping
In unsupervised domain mapping, the learner is given two unmatched datasets $A$ and $B$. The goal is to learn a mapping $G_{AB}$ that translates a sample in $A$ to the analog sample in $B$. Recent approaches have shown that when learning simultaneously both $G_{AB}$ and the inverse mapping $G_{BA}$, convincing mappin...
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Adaptive Neural Networks for Efficient Inference
We present an approach to adaptively utilize deep neural networks in order to reduce the evaluation time on new examples without loss of accuracy. Rather than attempting to redesign or approximate existing networks, we propose two schemes that adaptively utilize networks. We first pose an adaptive network evaluation ...
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The phylogenetic effective sample size and jumps
The phylogenetic effective sample size is a parameter that has as its goal the quantification of the amount of independent signal in a phylogenetically correlated sample. It was studied for Brownian motion and Ornstein-Uhlenbeck models of trait evolution. Here, we study this composite parameter when the trait is allo...
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Bosonic symmetries of the extended fermionic $(2N,2M)$-Toda hierarchy
In this paper, we construct the additional symmetries of the fermionic $(2N,2M)$-Toda hierarchy basing on the generalization of the $N{=}(1|1)$ supersymmetric two dimensional Toda lattice hierarchy. These additional flows constitute a $w_{\infty}\times w_{\infty}$ Lie algebra. As a Bosonic reduction of the $N{=}(1|1)...
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Single-atom-resolved probing of lattice gases in momentum space
Measuring the full distribution of individual particles is of fundamental importance to characterize many-body quantum systems through correlation functions at any order. Here we demonstrate the possibility to reconstruct the momentum-space distribution of three-dimensional interacting lattice gases atom-by-atom. Thi...
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Provability Logics of Hierarchies
The branch of provability logic investigates the provability-based behavior of the mathematical theories. In a more precise way, it studies the relation between a mathematical theory $T$ and a modal logic $L$ via the provability interpretation which interprets the modality as the provability predicate of $T$. In this...
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On the Difference between Physics and Biology: Logical Branching and Biomolecules
Physical emergence - crystals, rocks, sandpiles, turbulent eddies, planets, stars - is fundamentally different from biological emergence - amoeba, cells, mice, humans - even though the latter is based in the former. This paper points out that an essential difference is that as well as involving physical causation, ca...
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Spin liquid and infinitesimal-disorder-driven cluster spin glass in the kagome lattice
The interplay between geometric frustration (GF) and bond disorder is studied in the Ising kagome lattice within a cluster approach. The model considers antiferromagnetic (AF) short-range couplings and long-range intercluster disordered interactions. The replica formalism is used to obtain an effective single cluster...
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A punishment voting algorithm based on super categories construction for acoustic scene classification
In acoustic scene classification researches, audio segment is usually split into multiple samples. Majority voting is then utilized to ensemble the results of the samples. In this paper, we propose a punishment voting algorithm based on the super categories construction method for acoustic scene classification. Speci...
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Strong and Weak Equilibria for Time-Inconsistent Stochastic Control in Continuous Time
A new definition of continuous-time equilibrium controls is introduced. As opposed to the standard definition, which involves a derivative-type operation, the new definition parallels how a discrete-time equilibrium is defined, and allows for unambiguous economic interpretation. The terms "strong equilibria" and "wea...
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Trading algorithms with learning in latent alpha models
Alpha signals for statistical arbitrage strategies are often driven by latent factors. This paper analyses how to optimally trade with latent factors that cause prices to jump and diffuse. Moreover, we account for the effect of the trader's actions on quoted prices and the prices they receive from trading. Under fair...
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Temporal Segment Networks for Action Recognition in Videos
Deep convolutional networks have achieved great success for image recognition. However, for action recognition in videos, their advantage over traditional methods is not so evident. We present a general and flexible video-level framework for learning action models in videos. This method, called temporal segment netwo...
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Neural Machine Translation between Herbal Prescriptions and Diseases
The current study applies deep learning to herbalism. Toward the goal, we acquired the de-identified health insurance reimbursements that were claimed in a 10-year period from 2004 to 2013 in the National Health Insurance Database of Taiwan, the total number of reimbursement records equaling 340 millions. Two artific...
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A Quantum-Proof Non-Malleable Extractor, With Application to Privacy Amplification against Active Quantum Adversaries
In privacy amplification, two mutually trusted parties aim to amplify the secrecy of an initial shared secret $X$ in order to establish a shared private key $K$ by exchanging messages over an insecure communication channel. If the channel is authenticated the task can be solved in a single round of communication usin...
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A Theory of Reversibility for Erlang
In a reversible language, any forward computation can be undone by a finite sequence of backward steps. Reversible computing has been studied in the context of different programming languages and formalisms, where it has been used for testing and verification, among others. In this paper, we consider a subset of Erla...
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Convergence and Consistency Analysis for A 3D Invariant-EKF SLAM
In this paper, we investigate the convergence and consistency properties of an Invariant-Extended Kalman Filter (RI-EKF) based Simultaneous Localization and Mapping (SLAM) algorithm. Basic convergence properties of this algorithm are proven. These proofs do not require the restrictive assumption that the Jacobians of...
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Optical Characterization of Electro-spun Polymer Nanofiber based Silver Nanotubes
Nanotubes of various kinds have been prepared in the last decade, starting from the discovery of carbon nanotubes. Recently other types of nanotubes including metallic (Au), inorganic (TiO2, HfS2, V7O16, CdSe, MoS2), and polymeric (polyaniline, polyacrylonitrile) have been produced. Herein we present a novel syntheti...
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Optimal Prediction for Additive Function-on-Function Regression
As with classic statistics, functional regression models are invaluable in the analysis of functional data. While there are now extensive tools with accompanying theory available for linear models, there is still a great deal of work to be done concerning nonlinear models for functional data. In this work we consider...
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Star chromatic index of subcubic multigraphs
The star chromatic index of a multigraph $G$, denoted $\chi'_{s}(G)$, is the minimum number of colors needed to properly color the edges of $G$ such that no path or cycle of length four is bi-colored. A multigraph $G$ is star $k$-edge-colorable if $\chi'_{s}(G)\le k$. Dvořák, Mohar and Šámal [Star chromatic index, J....
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The absolutely Koszul property of Veronese subrings and Segre products
Absolutely Koszul algebras are a class of rings over which any finite graded module has a rational Poincaré series. We provide a criterion to detect non-absolutely Koszul rings. Combining the criterion with machine computations, we identify large families of Veronese subrings and Segre products of polynomial rings wh...
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Learning Theory and Algorithms for Revenue Management in Sponsored Search
Online advertisement is the main source of revenue for Internet business. Advertisers are typically ranked according to a score that takes into account their bids and potential click-through rates(eCTR). Generally, the likelihood that a user clicks on an ad is often modeled by optimizing for the click through rates r...
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Isotropic functions revisited
To a smooth and symmetric function $f$ defined on a symmetric open set $\Gamma\subset\mathbb{R}^{n}$ and a real $n$-dimensional vector space $V$ we assign an associated operator function $F$ defined on an open subset $\Omega\subset\mathcal{L}(V)$ of linear transformations of $V$, such that for each inner product $g$ ...
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Condensates in double-well potential with synthetic gauge potentials and vortex seeding
We demonstrate an enhancement in the vortex generation when artificial gauge potential is introduced to condensates confined in a double well potential. This is due to the lower energy required to create a vortex in the low condensate density region within the barrier. Furthermore, we study the transport of vortices ...
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On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables
We investigate the sub-Gaussian property for almost surely bounded random variables. If sub-Gaussianity per se is de facto ensured by the bounded support of said random variables, then exciting research avenues remain open. Among these questions is how to characterize the optimal sub-Gaussian proxy variance? Another ...
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Fast Distributed Approximation for Max-Cut
Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their neighbors according to the underlying graph, known as the $\mathcal{LOCAL}$ or $\mathc...
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A note on Oliver's p-group conjecture
Let $S$ be a $p$-group for an odd prime $p$, Oliver proposed the conjecture that the Thompson subgroup $J(S)$ is always contained in the Oliver subgroup $\mathfrak{X}(S)$. That means he conjectured that $|J(S)\mathfrak{X}(S):\mathfrak{X}(S)|=1$. Let $\mathfrak{X}_1(S)$ be a subgroup of $S$ such that $\mathfrak{X}_1(S...
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Frobenius elements in Galois representations with SL_n image
Suppose we have a elliptic curve over a number field whose mod $l$ representation has image isomorphic to $SL_2(\mathbb{F}_l)$. We present a method to determine Frobenius elements of the associated Galois group which incorporates the linear structure available. We are able to distinguish $SL_n(\mathbb{F}_l)$-conjugac...
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CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks
The precise modeling of subatomic particle interactions and propagation through matter is paramount for the advancement of nuclear and particle physics searches and precision measurements. The most computationally expensive step in the simulation pipeline of a typical experiment at the Large Hadron Collider (LHC) is ...
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Measurement of ultrashort optical pulses via time lens imaging in CMOS compatible waveguides
We demonstrate temporal measurements of subpicosecond optical pulses via time-to-frequency conversion in a 45cm long CMOS compatible high index glass spiral waveguide. The measurements are based on efficient four wave mixing in the C-band, using around 1W of peak pump power. We achieve a resolution of 400fs over a ti...
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On the next-to-minimal weight of projective Reed-Muller codes
In this paper we present several values for the next-to-minimal weights of projective Reed-Muller codes. We work over $\mathbb{F}_q$ with $q \geq 3$ since in IEEE-IT 62(11) p. 6300-6303 (2016) we have determined the complete values for the next-to-minimal weights of binary projective Reed-Muller codes. As in loc. cit...
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Scalable Global Grid catalogue for LHC Run3 and beyond
The AliEn (ALICE Environment) file catalogue is a global unique namespace providing mapping between a UNIX-like logical name structure and the corresponding physical files distributed over 80 storage elements worldwide. Powerful search tools and hierarchical metadata information are integral parts of the system and a...
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A versatile UHV transport and measurement chamber for neutron reflectometry under UHV conditions
We report on a versatile mini ultra-high vacuum (UHV) chamber which is designed to be used on the MAgnetic Reflectometer with high Incident Angle of the Jülich Centre for Neutron Science at Heinz Maier-Leibnitz Zentrum in Garching, Germany. Samples are prepared in the adjacent thin film laboratory by molecular beam e...
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Dual gauge field theory of quantum liquid crystals in three dimensions
The dislocation-mediated quantum melting of solids into quantum liquid crystals is extended from two to three spatial dimensions, using a generalization of boson-vortex or Abelian-Higgs duality. Dislocations are now Burgers-vector-valued strings that trace out worldsheets in spacetime while the phonons of the solid d...
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Deformation mechanism map of Cu/Nb nanoscale metallic multilayers as a function of temperature and layer thickness
The mechanical properties and deformation mechanisms of Cu/Nb nanoscale metallic multilayers (NMMs) manufactured by accumulative roll bonding (ARB) are studied at 25C and 400C. Cu/Nb NMMs with individual layer thicknesses between 7 and 63 nm were tested by in-situ micropillar compression inside a scanning electron mi...
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Relations between Schramm spaces and generalized Wiener classes
We give necessary and sufficient conditions for the embeddings $\Lambda\text{BV}^{(p)}\subseteq \Gamma\text{BV}^{(q_n\uparrow q)}$ and $\Phi\text{BV}\subseteq\text{BV}^{(q_n\uparrow q)}$. As a consequence, a number of results in the literature, including a fundamental theorem of Perlman and Waterman, are simultaneous...
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Stability Selection for Structured Variable Selection
In variable or graph selection problems, finding a right-sized model or controlling the number of false positives is notoriously difficult. Recently, a meta-algorithm called Stability Selection was proposed that can provide reliable finite-sample control of the number of false positives. Its benefits were demonstrate...
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Vafa-Witten invariants for projective surfaces II: semistable case
We propose a definition of Vafa-Witten invariants counting semistable Higgs pairs on a polarised surface. We use virtual localisation applied to Mochizuki/Joyce-Song pairs. For $K_S\le0$ we expect our definition coincides with an alternative definition using weighted Euler characteristics. We prove this for deg $K_S<...
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Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds
The aggregation of many independent estimates can outperform the most accurate individual judgment. This centenarian finding, popularly known as the wisdom of crowds, has been applied to problems ranging from the diagnosis of cancer to financial forecasting. It is widely believed that social influence undermines coll...
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Summertime, and the livin is easy: Winter and summer pseudoseasonal life expectancy in the United States
In temperate climates, mortality is seasonal with a winter-dominant pattern, due in part to pneumonia and influenza. Cardiac causes, which are the leading cause of death in the United States, are also winter-seasonal although it is not clear why. Interactions between circulating respiratory viruses (f.e., influenza) ...
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Solving Horn Clauses on Inductive Data Types Without Induction
We address the problem of verifying the satisfiability of Constrained Horn Clauses (CHCs) based on theories of inductively defined data structures, such as lists and trees. We propose a transformation technique whose objective is the removal of these data structures from CHCs, hence reducing their satisfiability to a...
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The Power of Non-Determinism in Higher-Order Implicit Complexity
We investigate the power of non-determinism in purely functional programming languages with higher-order types. Specifically, we consider cons-free programs of varying data orders, equipped with explicit non-deterministic choice. Cons-freeness roughly means that data constructors cannot occur in function bodies and a...
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Upper-limit on the Advanced Virgo output mode cleaner cavity length noise
The Advanced Virgo detector uses two monolithic optical cavities at its output port to suppress higher order modes and radio frequency sidebands from the carrier light used for gravitational wave detection. These two cavities in series form the output mode cleaner. We present a measured upper limit on the length nois...
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Mobile impurities in integrable models
We use a mobile impurity or depleton model to study elementary excitations in one-dimensional integrable systems. For Lieb-Liniger and bosonic Yang-Gaudin models we express two phenomenological parameters characterising renormalised inter- actions of mobile impurities with superfluid background: the number of deplete...
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Time-dependent variational principle in matrix-product state manifolds: pitfalls and potential
We study the applicability of the time-dependent variational principle in matrix product state manifolds for the long time description of quantum interacting systems. By studying integrable and nonintegrable systems for which the long time dynamics are known we demonstrate that convergence of long time observables is...
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Self-supporting Topology Optimization for Additive Manufacturing
The paper presents a topology optimization approach that designs an optimal structure, called a self-supporting structure, which is ready to be fabricated via additive manufacturing without the usage of additional support structures. Such supports in general have to be created during the fabricating process so that t...
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Reward Shaping via Meta-Learning
Reward shaping is one of the most effective methods to tackle the crucial yet challenging problem of credit assignment in Reinforcement Learning (RL). However, designing shaping functions usually requires much expert knowledge and hand-engineering, and the difficulties are further exacerbated given multiple similar t...
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Regulous vector bundles
Among recently introduced new notions in real algebraic geometry is that of regulous functions. Such functions form a foundation for the development of regulous geometry. Several interesting results on regulous varieties and regulous sheaves are already available. In this paper, we define and investigate regulous vec...
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Remarks on the operator-norm convergence of the Trotter product formula
We revise the operator-norm convergence of the Trotter product formula for a pair {A,B} of generators of semigroups on a Banach space. Operator-norm convergence holds true if the dominating operator A generates a holomorphic contraction semigroup and B is a A-infinitesimally small generator of a contraction semigroup...
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Using data-compressors for statistical analysis of problems on homogeneity testing and classification
Nowadays data compressors are applied to many problems of text analysis, but many such applications are developed outside of the framework of mathematical statistics. In this paper we overcome this obstacle and show how several methods of classical mathematical statistics can be developed based on applications of the...
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Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections
Two-dimensional embeddings remain the dominant approach to visualize high dimensional data. The choice of embeddings ranges from highly non-linear ones, which can capture complex relationships but are difficult to interpret quantitatively, to axis-aligned projections, which are easy to interpret but are limited to bi...
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Exact Recovery with Symmetries for the Doubly-Stochastic Relaxation
Graph matching or quadratic assignment, is the problem of labeling the vertices of two graphs so that they are as similar as possible. A common method for approximately solving the NP-hard graph matching problem is relaxing it to a convex optimization problem over the set of doubly stochastic (DS) matrices. Recent an...
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Statistical physics of human cooperation
Extensive cooperation among unrelated individuals is unique to humans, who often sacrifice personal benefits for the common good and work together to achieve what they are unable to execute alone. The evolutionary success of our species is indeed due, to a large degree, to our unparalleled other-regarding abilities. ...
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Bayesian Hypernetworks
We study Bayesian hypernetworks: a framework for approximate Bayesian inference in neural networks. A Bayesian hypernetwork $\h$ is a neural network which learns to transform a simple noise distribution, $p(\vec\epsilon) = \N(\vec 0,\mat I)$, to a distribution $q(\pp) := q(h(\vec\epsilon))$ over the parameters $\pp$ ...
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Block Motion Changes in Japan Triggered by the 2011 Great Tohoku Earthquake
Plate motions are governed by equilibrium between basal and edge forces. Great earthquakes may induce differential static stress changes across tectonic plates, enabling a new equilibrium state. Here we consider the torque balance for idealized circular plates and find a simple scalar relationship for changes in rela...
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Learning the structure of Bayesian Networks: A quantitative assessment of the effect of different algorithmic schemes
One of the most challenging tasks when adopting Bayesian Networks (BNs) is the one of learning their structure from data. This task is complicated by the huge search space of possible solutions, and by the fact that the problem is NP-hard. Hence, full enumeration of all the possible solutions is not always feasible a...
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Thermal fracturing on comets. Applications to 67P/Churyumov-Gerasimenko
We simulate the stresses induced by temperature changes in a putative hard layer near the surface of comet 67P/Churyumov--Gerasimenko with a thermo-viscoelastic model. Such a layer could be formed by the recondensation or sintering of water ice (and dust grains), as suggested by laboratory experiments and computer si...
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ADN: An Information-Centric Networking Architecture for the Internet of Things
Forwarding data by name has been assumed to be a necessary aspect of an information-centric redesign of the current Internet architecture that makes content access, dissemination, and storage more efficient. The Named Data Networking (NDN) and Content-Centric Networking (CCNx) architectures are the leading examples o...
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Urban Delay Tolerant Network Simulator (UDTNSim v0.1)
Delay Tolerant Networking (DTN) is an approach to networking which handles network disruptions and high delays that may occur in many kinds of communication networks. The major reasons for high delay include partial connectivity of networks as can be seen in many types of ad hoc wireless networks with frequent networ...
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Regularized Ordinal Regression and the ordinalNet R Package
Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection. Ordinal regression models are widely used in applications where the use of regularizatio...
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Visual Multiple-Object Tracking for Unknown Clutter Rate
In multi-object tracking applications, model parameter tuning is a prerequisite for reliable performance. In particular, it is difficult to know statistics of false measurements due to various sensing conditions and changes in the field of views. In this paper we are interested in designing a multi-object tracking al...
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On Integrated $L^{1}$ Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations
We consider a general monotone regression estimation where we allow for independent and dependent regressors. We propose a modification of the classical isotonic least squares estimator and establish its rate of convergence for the integrated $L_1$-loss function. The methodology captures the shape of the data without...
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Towards Fast-Convergence, Low-Delay and Low-Complexity Network Optimization
Distributed network optimization has been studied for well over a decade. However, we still do not have a good idea of how to design schemes that can simultaneously provide good performance across the dimensions of utility optimality, convergence speed, and delay. To address these challenges, in this paper, we propos...
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On zeros of polynomials in best $L^p$-approximation and inserting mass points
The purpose of this note is to revive in $L^p$ spaces the original A. Markov ideas to study monotonicity of zeros of orthogonal polynomials. This allows us to prove and improve in a simple and unified way our previous result [Electron. Trans. Numer. Anal., 44 (2015), pp. 271-280] concerning the discrete version of A....
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Empirical likelihood inference for partial functional linear regression models based on B spline
In this paper, we apply empirical likelihood method to inference for the regression parameters in the partial functional linear regression models based on B spline. We prove that the empirical log likelihood ratio for the regression parameters converges in law to a weighted sum of independent chi square distributions...
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Dropout Inference in Bayesian Neural Networks with Alpha-divergences
To obtain uncertainty estimates with real-world Bayesian deep learning models, practical inference approximations are needed. Dropout variational inference (VI) for example has been used for machine vision and medical applications, but VI can severely underestimates model uncertainty. Alpha-divergences are alternativ...
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Semiparametric Mixtures of Regressions with Single-index for Model Based Clustering
In this article, we propose two classes of semiparametric mixture regression models with single-index for model based clustering. Unlike many semiparametric/nonparametric mixture regression models that can only be applied to low dimensional predictors, the new semiparametric models can easily incorporate high dimensi...
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Deep learning Approach for Classifying, Detecting and Predicting Photometric Redshifts of Quasars in the Sloan Digital Sky Survey Stripe 82
We apply a convolutional neural network (CNN) to classify and detect quasars in the Sloan Digital Sky Survey Stripe 82 and also to predict the photometric redshifts of quasars. The network takes the variability of objects into account by converting light curves into images. The width of the images, noted w, correspon...
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Sources of inter-model scatter in TRACMIP, the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project
We analyze the source of inter-model scatter in the surface temperature response to quadrupling CO2 in two sets of GCM simulations from the Tropical Rain Belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP; Voigt et al, 2016). TRACMIP provides simulations of idealized climates that allow...
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Sub-clustering in decomposable graphs and size-varying junction trees
This paper proposes a novel representation of decomposable graphs based on semi-latent tree-dependent bipartite graphs. The novel representation has two main benefits. First, it enables a form of sub-clustering within maximal cliques of the graph, adding informational richness to the general use of decomposable graph...
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The inflation technique solves completely the classical inference problem
The causal inference problem consists in determining whether a probability distribution over a set of observed variables is compatible with a given causal structure. In [arXiv:1609.00672], one of us introduced a hierarchy of necessary linear programming constraints which all the observed distributions compatible with...
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Magnetic charge injection in spin ice: a new way to fragmentation
The complexity embedded in condensed matter fertilizes the discovery of new states of matter, enriched by ingredients like frustration. Illustrating examples in magnetic systems are Kitaev spin liquids, skyrmions phases, or spin ices. These unconventional ground states support exotic excitations, for example the magn...
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Decentralized Task Allocation in Multi-Robot Systems via Bipartite Graph Matching Augmented with Fuzzy Clustering
Robotic systems, working together as a team, are becoming valuable players in different real-world applications, from disaster response to warehouse fulfillment services. Centralized solutions for coordinating multi-robot teams often suffer from poor scalability and vulnerability to communication disruptions. This pa...
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Combining Static and Dynamic Features for Multivariate Sequence Classification
Model precision in a classification task is highly dependent on the feature space that is used to train the model. Moreover, whether the features are sequential or static will dictate which classification method can be applied as most of the machine learning algorithms are designed to deal with either one or another ...
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Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods
Our goal is to improve variance reducing stochastic methods through better control variates. We first propose a modification of SVRG which uses the Hessian to track gradients over time, rather than to recondition, increasing the correlation of the control variates and leading to faster theoretical convergence close t...
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On spectral properties of Neuman-Poincare operator and plasmonic resonances in 3D elastostatics
We consider plasmon resonances and cloaking for the elastostatic system in $\mathbb{R}^3$ via the spectral theory of Neumann-Poincaré operator. We first derive the full spectral properties of the Neumann-Poincaré operator for the 3D elastostatic system in the spherical geometry. The spectral result is of significant ...
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A hybridizable discontinuous Galerkin method for the Navier--Stokes equations with pointwise divergence-free velocity field
We introduce a hybridizable discontinuous Galerkin method for the incompressible Navier--Stokes equations for which the approximate velocity field is pointwise divergence-free. The method builds on the method presented by Labeur and Wells [SIAM J. Sci. Comput., vol. 34 (2012), pp. A889--A913]. We show that with modif...
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Near Perfect Protein Multi-Label Classification with Deep Neural Networks
Artificial neural networks (ANNs) have gained a well-deserved popularity among machine learning tools upon their recent successful applications in image- and sound processing and classification problems. ANNs have also been applied for predicting the family or function of a protein, knowing its residue sequence. Here...
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Comparison of Decoding Strategies for CTC Acoustic Models
Connectionist Temporal Classification has recently attracted a lot of interest as it offers an elegant approach to building acoustic models (AMs) for speech recognition. The CTC loss function maps an input sequence of observable feature vectors to an output sequence of symbols. Output symbols are conditionally indepe...
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Battery Degradation Maps for Power System Optimization and as a Benchmark Reference
This paper presents a novel method to describe battery degradation. We use the concept of degradation maps to model the incremental charge capacity loss as a function of discrete battery control actions and state of charge. The maps can be scaled to represent any battery system in size and power. Their convex piece-w...
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Computer Assisted Localization of a Heart Arrhythmia
We consider the problem of locating a point-source heart arrhythmia using data from a standard diagnostic procedure, where a reference catheter is placed in the heart, and arrival times from a second diagnostic catheter are recorded as the diagnostic catheter moves around within the heart. We model this situation as ...
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Solving for high dimensional committor functions using artificial neural networks
In this note we propose a method based on artificial neural network to study the transition between states governed by stochastic processes. In particular, we aim for numerical schemes for the committor function, the central object of transition path theory, which satisfies a high-dimensional Fokker-Planck equation. ...
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The possibility of constructing a relativistic space of information states based on the theory of complexity and analogies with physical space-time
The possibility of calculation of the conditional and unconditional complexity of description of information objects in the algorithmic theory of information is connected with the limitations for the set of the used languages of programming (description). The results of calculation of the conditional complexity allow...
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Problems on Matchings and Independent Sets of a Graph
Let $G$ be a finite simple graph. For $X \subset V(G)$, the difference of $X$, $d(X) := |X| - |N (X)|$ where $N(X)$ is the neighborhood of $X$ and $\max \, \{d(X):X\subset V(G)\}$ is called the critical difference of $G$. $X$ is called a critical set if $d(X)$ equals the critical difference and ker$(G)$ is the inters...
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Nonsequential double ionization of helium in IR+XUV two-color laser fields II: Collision-excitation ionization process
The collision-ionization mechanism of nonsequential double ionization (NSDI) process in IR+XUV two-color laser fields [\PRA \textbf{93}, 043417 (2016)] has been investigated by us recently. Here we extend this work to study the collision-excitation-ionization (CEI) mechanism of NSDI processes in the two-color laser f...
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Chaos or Order?
What is chaos? Despite several decades of research on this ubiquitous and fundamental phenomenon there is yet no agreed-upon answer to this question. Recently, it was realized that all stochastic and deterministic differential equations, describing all natural and engineered dynamical systems, possess a topological s...
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Gaia Data Release 1: The archive visualisation service
Context: The first Gaia data release (DR1) delivered a catalogue of astrometry and photometry for over a billion astronomical sources. Within the panoply of methods used for data exploration, visualisation is often the starting point and even the guiding reference for scientific thought. However, this is a volume of ...
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Monte Carlo methods for massively parallel computers
Applications that require substantial computational resources today cannot avoid the use of heavily parallel machines. Embracing the opportunities of parallel computing and especially the possibilities provided by a new generation of massively parallel accelerator devices such as GPUs, Intel's Xeon Phi or even FPGAs ...
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A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform
Kiva is an online non-profit crowdsouring microfinance platform that raises funds for the poor in the third world. The borrowers on Kiva are small business owners and individuals in urgent need of money. To raise funds as fast as possible, they have the option to form groups and post loan requests in the name of thei...
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JADE - A Platform for Research on Cooperation of Physical and Virtual Agents
In the ICS, WUT a platform for simulation of cooperation of physical and virtual mobile agents is under development. The paper describes the motivation of the research, an organization of the platform, a model of agent, and the principles of design of the platform. Several experimental simulations are briefly describ...
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Analytic Expressions for the Inner-Rim Structure of Passively Heated Protoplanetary Disks
We analytically derive the expressions for the structure of the inner region of protoplanetary disks based on the results from the recent hydrodynamical simulations. The inner part of a disk can be divided into four regions: dust-free region with gas temperature in the optically thin limit, optically thin dust halo, ...
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X-ray Emission Spectrum of Liquid Ethanol : Origin of Split Peaks
The X-ray emission spectrum of liquid ethanol was calculated using density functional theory and a semi-classical approximation to the Kramers-Heisenberg formula including core-hole-induced dynamics. Our spectrum agrees well with the experimental spectrum. We found that the intensity ratio between the two peaks at 52...
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Activation Maximization Generative Adversarial Nets
Class labels have been empirically shown useful in improving the sample quality of generative adversarial nets (GANs). In this paper, we mathematically study the properties of the current variants of GANs that make use of class label information. With class aware gradient and cross-entropy decomposition, we reveal ho...
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Job Management and Task Bundling
High Performance Computing is often performed on scarce and shared computing resources. To ensure computers are used to their full capacity, administrators often incentivize large workloads that are not possible on smaller systems. Measurements in Lattice QCD frequently do not scale to machine-size workloads. By bund...
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Scintillation based search for off-pulse radio emission from pulsars
We propose a new method to detect off-pulse (unpulsed and/or continuous) emission from pulsars, using the intensity modulations associated with interstellar scintillation. Our technique involves obtaining the dynamic spectra, separately for on-pulse window and off-pulse region, with time and frequency resolutions to ...
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Machine learning for graph-based representations of three-dimensional discrete fracture networks
Structural and topological information play a key role in modeling flow and transport through fractured rock in the subsurface. Discrete fracture network (DFN) computational suites such as dfnWorks are designed to simulate flow and transport in such porous media. Flow and transport calculations reveal that a small ba...
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