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On the wave propagation analysis and supratransmission prediction of a metastable modular metastructure for adaptive non-reciprocal energy transmission
In this research, we investigate the nonlinear energy transmission phenomenon in a reconfigurable and adaptable metastable modular metastructure. Numerical studies on a 1D metastable chain uncover that when the driving frequency is within the stopband of the periodic structure, there exists a threshold input amplitud...
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Advances in Variational Inference
Many modern unsupervised or semi-supervised machine learning algorithms rely on Bayesian probabilistic models. These models are usually intractable and thus require approximate inference. Variational inference (VI) lets us approximate a high-dimensional Bayesian posterior with a simpler variational distribution by so...
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Security Against Impersonation Attacks in Distributed Systems
In a multi-agent system, transitioning from a centralized to a distributed decision-making strategy can introduce vulnerability to adversarial manipulation. We study the potential for adversarial manipulation in a class of graphical coordination games where the adversary can pose as a friendly agent in the game, ther...
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Large-Batch Training for LSTM and Beyond
Large-batch training approaches have enabled researchers to utilize large-scale distributed processing and greatly accelerate deep-neural net (DNN) training. For example, by scaling the batch size from 256 to 32K, researchers have been able to reduce the training time of ResNet50 on ImageNet from 29 hours to 2.2 minu...
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One-shot and few-shot learning of word embeddings
Standard deep learning systems require thousands or millions of examples to learn a concept, and cannot integrate new concepts easily. By contrast, humans have an incredible ability to do one-shot or few-shot learning. For instance, from just hearing a word used in a sentence, humans can infer a great deal about it, ...
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Exactly Robust Kernel Principal Component Analysis
We propose a novel method called robust kernel principal component analysis (RKPCA) to decompose a partially corrupted matrix as a sparse matrix plus a high or full-rank matrix whose columns are drawn from a nonlinear low-dimensional latent variable model. RKPCA can be applied to many problems such as noise removal a...
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Moderate deviation analysis for classical communication over quantum channels
We analyse families of codes for classical data transmission over quantum channels that have both a vanishing probability of error and a code rate approaching capacity as the code length increases. To characterise the fundamental tradeoff between decoding error, code rate and code length for such codes we introduce a...
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Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
We study the training process of Deep Neural Networks (DNNs) from the Fourier analysis perspective. Our starting point is a Frequency Principle (F-Principle) --- DNNs initialized with small parameters often fit target functions from low to high frequencies --- which was first proposed by Xu et al. (2018) and Rahaman ...
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Efficient, Safe, and Probably Approximately Complete Learning of Action Models
In this paper we explore the theoretical boundaries of planning in a setting where no model of the agent's actions is given. Instead of an action model, a set of successfully executed plans are given and the task is to generate a plan that is safe, i.e., guaranteed to achieve the goal without failing. To this end, we...
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Uniform cohomological expansion of uniformly quasiregular mappings
Let $f\colon M \to M$ be a uniformly quasiregular self-mapping of a compact, connected, and oriented Riemannian $n$-manifold $M$ without boundary, $n\ge 2$. We show that, for $k \in \{0,\ldots, n\}$, the induced homomorphism $f^* \colon H^k(M;\mathbb{R}) \to H^k(M;\mathbb{R})$, where $H^k(M;\mathbb{R})$ is the $k$:th...
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The logic of pseudo-uninorms and their residua
Our method of density elimination is generalized to the non-commutative substructural logic GpsUL*. Then the standard completeness of GpsUL* follows as a lemma by virtue of previous work by Metcalfe and Montagna. This result shows that GpsUL* is the logic of pseudo-uninorms and their residua and answered the question...
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Computation of Green's functions through algebraic decomposition of operators
In this article we use linear algebra to improve the computational time for the obtaining of Green's functions of linear differential equations with reflection (DER). This is achieved by decomposing both the `reduced' equation (the ODE associated to a given DER) and the corresponding two-point boundary conditions.
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Methods for finding leader--follower equilibria with multiple followers
The concept of leader--follower (or Stackelberg) equilibrium plays a central role in a number of real--world applications of game theory. While the case with a single follower has been thoroughly investigated, results with multiple followers are only sporadic and the problem of designing and evaluating computationall...
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Pressure Induced Superconductivity in the New Compound ScZrCo1-$δ$
It is widely perceived that the correlation effect may play an important role in several unconventional superconducting families, such as cuprate, iron-based and heavy-fermion superconductors. The application of high pressure can tune the ground state properties and balance the localization and itineracy of electrons...
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Universal Adversarial Perturbations Against Semantic Image Segmentation
While deep learning is remarkably successful on perceptual tasks, it was also shown to be vulnerable to adversarial perturbations of the input. These perturbations denote noise added to the input that was generated specifically to fool the system while being quasi-imperceptible for humans. More severely, there even e...
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Marginal sequential Monte Carlo for doubly intractable models
Bayesian inference for models that have an intractable partition function is known as a doubly intractable problem, where standard Monte Carlo methods are not applicable. The past decade has seen the development of auxiliary variable Monte Carlo techniques (M{\o}ller et al., 2006; Murray et al., 2006) for tackling th...
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The impact of neutral impurity concentration on charge drift mobility in n-type germanium
The impact of neutral impurity scattering of electrons on the charge drift mobility in high purity n-type germanium crystals at 77 Kelvin is investigated. We calculated the contributions from ionized impurity scattering, lattice scattering, and neutral impurity scattering to the total charge drift mobility using theo...
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Calabi-Yau hypersurfaces and SU-bordism
Batyrev constructed a family of Calabi-Yau hypersurfaces dual to the first Chern class in toric Fano varieties. Using this construction, we introduce a family of Calabi-Yau manifolds whose SU-bordism classes generate the special unitary bordism ring $\varOmega^{SU}\otimes\mathbb{Z}[\frac{1}{2}]\cong\mathbb{Z}[\frac{1...
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Distribution-Based Categorization of Classifier Transfer Learning
Transfer Learning (TL) aims to transfer knowledge acquired in one problem, the source problem, onto another problem, the target problem, dispensing with the bottom-up construction of the target model. Due to its relevance, TL has gained significant interest in the Machine Learning community since it paves the way to ...
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Alexander invariants of periodic virtual knots
We show that every periodic virtual knot can be realized as the closure of a periodic virtual braid and use this to study the Alexander invariants of periodic virtual knots. If $K$ is a $q$-periodic and almost classical knot, we show that its quotient knot $K_*$ is also almost classical, and in the case $q=p^r$ is a ...
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Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Computing optimal transport distances such as the earth mover's distance is a fundamental problem in machine learning, statistics, and computer vision. Despite the recent introduction of several algorithms with good empirical performance, it is unknown whether general optimal transport distances can be approximated i...
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Mathematical model of gender bias and homophily in professional hierarchies
Women have become better represented in business, academia, and government over time, yet a dearth of women at the highest levels of leadership remains. Sociologists have attributed the leaky progression of women through professional hierarchies to various cultural and psychological factors, such as self-segregation ...
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Monotonicity of non-pluripolar products and complex Monge-Ampère equations with prescribed singularity
We establish the monotonicity property for the mass of non-pluripolar products on compact Kahler manifolds, and we initiate the study of complex Monge-Ampere type equations with prescribed singularity type. Using the variational method of Berman-Boucksom-Guedj-Zeriahi we prove existence and uniqueness of solutions wi...
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Fast and high-quality tetrahedral mesh generation from neuroanatomical scans
Creating tetrahedral meshes with anatomically accurate surfaces is critically important for a wide range of model-based neuroimaging modalities. However, computationally efficient brain meshing algorithms and software are greatly lacking. Here, we report a fully automated open-source software to rapidly create high-q...
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Curriculum Dropout
Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability discourages over-specific co-adaptations of feature detectors, preventing overfitting and improving network generalization. Besides, Dropout can be interpreted as an approximate model aggreg...
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Self-dual and logarithmic representations of the twisted Heisenberg--Virasoro algebra at level zero
This paper is a continuation of arXiv:1405.1707. We present certain new applications and generalizations of the free field realization of the twisted Heisenberg-Virasoro algebra ${\mathcal H}$ at level zero. We find explicit formulas for singular vectors in certain Verma modules. A free field realization of self-dual...
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Distance weighted discrimination of face images for gender classification
We illustrate the advantages of distance weighted discrimination for classification and feature extraction in a High Dimension Low Sample Size (HDLSS) situation. The HDLSS context is a gender classification problem of face images in which the dimension of the data is several orders of magnitude larger than the sample...
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Partition-based Unscented Kalman Filter for Reconfigurable Battery Pack State Estimation using an Electrochemical Model
Accurate state estimation of large-scale lithium-ion battery packs is necessary for the advanced control of batteries, which could potentially increase their lifetime through e.g. reconfiguration. To tackle this problem, an enhanced reduced-order electrochemical model is used here. This model allows considering a wid...
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Towards Principled Methods for Training Generative Adversarial Networks
The goal of this paper is not to introduce a single algorithm or method, but to make theoretical steps towards fully understanding the training dynamics of generative adversarial networks. In order to substantiate our theoretical analysis, we perform targeted experiments to verify our assumptions, illustrate our clai...
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Co-Clustering for Multitask Learning
This paper presents a new multitask learning framework that learns a shared representation among the tasks, incorporating both task and feature clusters. The jointly-induced clusters yield a shared latent subspace where task relationships are learned more effectively and more generally than in state-of-the-art multit...
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Avoiding Communication in Proximal Methods for Convex Optimization Problems
The fast iterative soft thresholding algorithm (FISTA) is used to solve convex regularized optimization problems in machine learning. Distributed implementations of the algorithm have become popular since they enable the analysis of large datasets. However, existing formulations of FISTA communicate data at every ite...
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Stochastic Development Regression on Non-Linear Manifolds
We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables. The approach is based on stochastic development of Euclidean diffusion processes to the manifold....
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Prediction of Kidney Function from Biopsy Images Using Convolutional Neural Networks
A Convolutional Neural Network was used to predict kidney function in patients with chronic kidney disease from high-resolution digital pathology scans of their kidney biopsies. Kidney biopsies were taken from participants of the NEPTUNE study, a longitudinal cohort study whose goal is to set up infrastructure for ob...
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Weighing neutrinos in dynamical dark energy models
We briefly review the recent results of constraining neutrino mass in dynamical dark energy models using cosmological observations and summarize the findings. (i) In dynamical dark energy models, compared to $\Lambda$CDM, the upper limit of $\sum m_\nu$ can become larger and can also become smaller. In the cases of p...
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Can supersymmetry emerge at a quantum critical point?
Supersymmetry plays an important role in superstring theory and particle physics, but has never been observed in experiments. At certain quantum critical points of condensed matter systems, the fermionic excitations are gapless due to the special electronic structure whereas the bosonic order parameter is automatical...
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Five-parameter potential box with inverse square singular boundaries
Using the Tridiagonal Representation Approach, we obtain solutions (energy spectrum and corresponding wavefunctions) for a new five-parameter potential box with inverse square singularity at the boundaries.
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Succinctness in subsystems of the spatial mu-calculus
In this paper we systematically explore questions of succinctness in modal logics employed in spatial reasoning. We show that the closure operator, despite being less expressive, is exponentially more succinct than the limit-point operator, and that the $\mu$-calculus is exponentially more succinct than the equally-e...
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Evidence for electronically-driven ferroelectricity in the family of strongly correlated dimerized BEDT-TTF molecular conductors
By applying measurements of the dielectric constants and relative length changes to the dimerized molecular conductor $\kappa$-(BEDT-TTF)$_2$Hg(SCN)$_2$Cl, we provide evidence for order-disorder type electronic ferroelectricity which is driven by charge order within the (BEDT-TTF)$_2$ dimers and stabilized by a coupl...
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Testing FLUKA on neutron activation of Si and Ge at nuclear research reactor using gamma spectroscopy
Samples of two characteristic semiconductor sensor materials, silicon and germanium, have been irradiated with neutrons produced at the RP-10 Nuclear Research Reactor at 4.5 MW. Their radionuclides photon spectra have been measured with high resolution gamma spectroscopy, quantifying four radioisotopes ($^{28}$Al, $^...
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Probabilistic Search for Structured Data via Probabilistic Programming and Nonparametric Bayes
Databases are widespread, yet extracting relevant data can be difficult. Without substantial domain knowledge, multivariate search queries often return sparse or uninformative results. This paper introduces an approach for searching structured data based on probabilistic programming and nonparametric Bayes. Users spe...
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Superposition of p-superharmonic functions
The Dominative $p$-Laplace Operator is introduced. This operator is a relative to the $p$-Laplacian, but with the distinguishing property of being sublinear. It explains the superposition principle in the $p$-Laplace Equation.
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Ramsey properties and extending partial automorphisms for classes of finite structures
We show that every free amalgamation class of finite structures with relations and (symmetric) partial functions is a Ramsey class when enriched by a free linear ordering of vertices. This is a common strengthening of the Nešetřil-Rödl Theorem and the second and third authors' Ramsey theorem for finite models (that i...
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Estimation of the shape of the density contours of star-shaped distributions
Elliptically contoured distributions generalize the multivariate normal distributions in such a way that the density generators need not be exponential. However, as the name suggests, elliptically contoured distributions remain to be restricted in that the similar density contours ought to be elliptical. Kamiya, Take...
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Aggregated Pairwise Classification of Statistical Shapes
The classification of shapes is of great interest in diverse areas ranging from medical imaging to computer vision and beyond. While many statistical frameworks have been developed for the classification problem, most are strongly tied to early formulations of the problem - with an object to be classified described a...
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The MUSE-Wide survey: Detection of a clustering signal from Lyman-α-emitters at 3<z<6
We present a clustering analysis of a sample of 238 Ly{$\alpha$}-emitters at redshift 3<z<6 from the MUSE-Wide survey. This survey mosaics extragalactic legacy fields with 1h MUSE pointings to detect statistically relevant samples of emission line galaxies. We analysed the first year observations from MUSE-Wide makin...
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On Polymorphic Sessions and Functions: A Tale of Two (Fully Abstract) Encodings
This work exploits the logical foundation of session types to determine what kind of type discipline for the pi-calculus can exactly capture, and is captured by, lambda-calculus behaviours. Leveraging the proof theoretic content of the soundness and completeness of sequent calculus and natural deduction presentations...
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Effects of initial spatial phase in radiative neutrino pair emission
We study radiative neutrino pair emission in deexcitation process of atoms taking into account coherence effect in a macroscopic target system. In the course of preparing the coherent initial state to enhance the rate, a spatial phase factor is imprinted in the macroscopic target. It is shown that this initial spatia...
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Finite-sample risk bounds for maximum likelihood estimation with arbitrary penalties
The MDL two-part coding $ \textit{index of resolvability} $ provides a finite-sample upper bound on the statistical risk of penalized likelihood estimators over countable models. However, the bound does not apply to unpenalized maximum likelihood estimation or procedures with exceedingly small penalties. In this pape...
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Integrated Modeling of Second Phase Precipitation in Cold-Worked 316 Stainless Steels under Irradiation
The current work combines the Cluster Dynamics (CD) technique and CALPHAD-based precipitation modeling to address the second phase precipitation in cold-worked (CW) 316 stainless steels (SS) under irradiation at 300-400 C. CD provides the radiation enhanced diffusion and dislocation evolution as inputs for the precip...
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Emergent topological superconductivity at nematic domain wall of FeSe
One dimensional hybrid systems play an important role in the search for topological superconductivity. Nevertheless, all one dimensional hybrid systems so far have been externally defined. Here we show that one-dimensional domain wall in a nematic superconductor can serve as an emergent hybrid system in the presence ...
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Linear and nonlinear market correlations: characterizing financial crises and portfolio optimization
Pearson correlation and mutual information based complex networks of the day-to-day returns of US S&P500 stocks between 1985 and 2015 have been constructed in order to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recen...
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An explicit projective bimodule resolution of a Leavitt path algebra
We construct an explicit projective bimodule resolution for the Leavitt path algebra of a row-finite quiver. We prove that the Leavitt path algebra of a row-countable quiver has Hochschild cohomolgical dimension at most one, that is, it is quasi-free in the sense of Cuntz-Quillen. The construction of the resolution r...
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Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks
Modern deep neural networks (DNNs) spend a large amount of their execution time computing convolutions. Winograd's minimal algorithm for small convolutions can greatly reduce the number of arithmetic operations. However, a large reduction in floating point (FP) operations in these algorithms can result in poor numeri...
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Active Learning amidst Logical Knowledge
Structured prediction is ubiquitous in applications of machine learning such as knowledge extraction and natural language processing. Structure often can be formulated in terms of logical constraints. We consider the question of how to perform efficient active learning in the presence of logical constraints among var...
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On the Limiting Stokes' Wave of Extreme Height in Arbitrary Water Depth
As mentioned by Schwartz (1974) and Cokelet (1977), it was failed to gain convergent results of limiting Stokes' waves in extremely shallow water by means of perturbation methods even with the aid of extrapolation techniques such as Padé approximant. Especially, it is extremely difficult for traditional analytic/nume...
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Pressure impact on the stability and distortion of the crystal structure of CeScO3
The effects of high pressure on the crystal structure of orthorhombic (Pnma) perovskite type cerium scandate have been studied in situ under high pressure by means of synchrotron x-ray powder diffraction, using a diamond anvil cell. We have found that the perovskite type crystal structure remains stable up to 40 GPa,...
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The system of cloud oriented learning tools as an element of educational and scientific environment of high school
The aim of this research is to design and implementation of cloud based learning environment for separate division of the university. The analysis of existing approaches to the construction of cloud based learning environments, the formation of requirements cloud based learning tools, the selection on the basis of th...
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Chemical abundances of two extragalactic young massive clusters
We use integrated-light spectroscopic observations to measure metallicities and chemical abundances for two extragalactic young massive star clusters (NGC1313-379 and NGC1705-1). The spectra were obtained with the X-Shooter spectrograph on the ESO Very Large Telescope. We compute synthetic integrated-light spectra, b...
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Clingo goes Linear Constraints over Reals and Integers
The recent series 5 of the ASP system clingo provides generic means to enhance basic Answer Set Programming (ASP) with theory reasoning capabilities. We instantiate this framework with different forms of linear constraints, discuss the respective implementations, and present techniques of how to use these constraints...
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Dynamic Uplink/Downlink Resource Management in Flexible Duplex-Enabled Wireless Networks
Flexible duplex is proposed to adapt to the channel and traffic asymmetry for future wireless networks. In this paper, we propose two novel algorithms within the flexible duplex framework for joint uplink and downlink resource allocation in multi-cell scenario, named SAFP and RMDI, based on the awareness of interfere...
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Carleman estimates for forward and backward stochastic fourth order Schrödinger equations and their applications
In this paper, we establish the Carleman estimates for forward and backward stochastic fourth order Schrödinger equations, on basis of which, we can obtain the observability, unique continuation property and the exact controllability for the forward and backward stochastic fourth order Schrödinger equations.
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Reply to comment on `Poynting flux in the neighbourhood of a point charge in arbitrary motion and the radiative power losses'
Doubts have been expressed in a comment (Eur. J. Phys., 39, 018001, 2018), about the tenability of the formulation for radiative losses in our recent published work (Eur. J. Phys., 37, 045210, 2016). We provide our reply to the comment. In particular, it is pointed out that one need to clearly distinguish between the...
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Delegated Causality of Complex Systems
A notion of delegated causality is introduced. This subtle kind of causality is dual to interventional causality. Delegated causality elucidates the causal role of dynamical systems at the "edge of chaos", explicates evident cases of downward causation, and relates emergent phenomena to Godel's incompleteness theorem...
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Resonating Valence Bond Theory of Superconductivity: Beyond Cuprates
Resonating valence bond (RVB) theory of high Tc superconductivity, an electron correlation based mechanism, began as an insightful response by Anderson, to Bednorz and Muller's discovery of high Tc superconductivity in cuprates in late 1986. Shortly a theoretical framework for quantum spin liquids and superconductivi...
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Efficient and accurate numerical schemes for a hydrodynamically coupled phase field diblock copolymer model
In this paper, we consider numerical approximations of a hydrodynamically coupled phase field diblock copolymer model, in which the free energy contains a kinetic potential, a gradient entropy, a Ginzburg-Landau double well potential, and a long range nonlocal type potential. We develop a set of second order time mar...
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Brownian Motion of a Classical Particle in Quantum Environment
The Klein-Kramers equation, governing the Brownian motion of a classical particle in quantum environment under the action of an arbitrary external potential, is derived. Quantum temperature and friction operators are introduced and at large friction the corresponding Smoluchowski equation is obtained. Introducing the...
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Hierarchical Policy Search via Return-Weighted Density Estimation
Learning an optimal policy from a multi-modal reward function is a challenging problem in reinforcement learning (RL). Hierarchical RL (HRL) tackles this problem by learning a hierarchical policy, where multiple option policies are in charge of different strategies corresponding to modes of a reward function and a ga...
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Two-dimensional Fourier transformations and Mordell integrals
Several Fourier transformations of functions of one and two variables are evaluated and then used to derive some integral and series identities. It is shown that certain two- dimensional Mordell integrals factorize into product of two integrals and that the square of the absolute value of the Mordell integral can be ...
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Optimal Allocation of Static Var Compensator via Mixed Integer Conic Programming
Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally...
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Polarity tuning of spin-orbit-induced spin splitting in two-dimensional transition metal dichalcogenides semiconductors
The established spin splitting in monolayer (ML) of transition metal dichalcogenides (TMDs) that is caused by inversion symmetry breaking is dictated by mirror symmetry operations to exhibit fully out-of-plane direction of spin polarization. Through first-principles density functional theory calculations, we show tha...
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Some parametrized dynamic priority policies for 2-class M/G/1 queues: completeness and applications
Completeness of a dynamic priority scheduling scheme is of fundamental importance for the optimal control of queues in areas as diverse as computer communications, communication networks, supply chains and manufacturing systems. Our first main contribution is to identify the mean waiting time completeness as a unifyi...
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Vector bundles over classifying spaces of p-local finite groups and Benson-Carlson duality
In this paper we obtain a description of the Grothendieck group of complex vector bundles over the classifying space of a p-local finite group in terms of representation rings of subgroups of its Sylow. We also prove a stable elements formula for generalized cohomological invariants of p-local finite groups, which is...
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Identification of a complete YPT1 Rab GTPase sequence from the fungal pathogen Colletotrichum incanum
Colletotrichum represent a genus of fungal species primarily known as plant pathogens with severe economic impacts in temperate, subtropical and tropical climates Consensus taxonomy and classification systems for Colletotrichum species have been undergoing revision as high resolution genomic data becomes available. H...
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Multiplicative Structure in the Stable Splitting of $ΩSL_n(\mathbb{C})$
The space of based loops in $SL_n(\mathbb{C})$, also known as the affine Grassmannian of $SL_n(\mathbb{C})$, admits an $\mathbb{E}_2$ or fusion product. Work of Mitchell and Richter proves that this based loop space stably splits as an infinite wedge sum. We prove that the Mitchell--Richter splitting is coherently mu...
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Strange duality on rational surfaces II: higher rank cases
We study Le Potier's strange duality conjecture on a rational surface. We focus on the strange duality map $SD_{c_n^r,L}$ which involves the moduli space of rank $r$ sheaves with trivial first Chern class and second Chern class $n$, and the moduli space of 1-dimensional sheaves with determinant $L$ and Euler characte...
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Graph learning under sparsity priors
Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the application domain. If this is not possible, the data structure has to be inferred...
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Improving Trajectory Optimization using a Roadmap Framework
We present an evaluation of several representative sampling-based and optimization-based motion planners, and then introduce an integrated motion planning system which incorporates recent advances in trajectory optimization into a sparse roadmap framework. Through experiments in 4 common application scenarios with 50...
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Smooth and Efficient Policy Exploration for Robot Trajectory Learning
Many policy search algorithms have been proposed for robot learning and proved to be practical in real robot applications. However, there are still hyperparameters in the algorithms, such as the exploration rate, which requires manual tuning. The existing methods to design the exploration rate manually or automatical...
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Social Innovation and the Evolution of Creative, Sustainable Worldviews
The ideas that we forge creatively as individuals and groups build on one another in a manner that is cumulative and adaptive, forming open-ended lineages across space and time. Thus, human culture is believed to evolve. The pervasiveness of cross-domain creativity--as when a song inspires a painting--would appear in...
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Interaction between magnetic moments and itinerant carriers in d0 ferromagnetic SiC
Elucidating the interaction between magnetic moments and itinerant carriers is an important step to spintronic applications. Here, we investigate magnetic and transport properties in d0 ferromagnetic SiC single crystals prepared by postimplantation pulsed laser annealing. Magnetic moments are contributed by the p sta...
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Il Fattore di Sylvester
Sylvester factor, an essential part of the asymptotic formula of Hardy and Littlewood which is the extended Goldbach conjecture, regarded as strongly multiplicative arithmetic function, has several remarkable properties.
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Bright and Gap Solitons in Membrane-Type Acoustic Metamaterials
We study analytically and numerically envelope solitons (bright and gap solitons) in a one-dimensional, nonlinear acoustic metamaterial, composed of an air-filled waveguide periodically loaded by clamped elastic plates. Based on the transmission line approach, we derive a nonlinear dynamical lattice model which, in t...
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Local reservoir model for choice-based learning
Decision making based on behavioral and neural observations of living systems has been extensively studied in brain science, psychology, and other disciplines. Decision-making mechanisms have also been experimentally implemented in physical processes, such as single photons and chaotic lasers. The findings of these e...
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Weil-Petersson geometry on the space of Bridgeland stability conditions
Inspired by mirror symmetry, we investigate some differential geometric aspects of the space of Bridgeland stability conditions on a Calabi-Yau triangulated category. The aim is to develop theory of Weil-Petersson geometry on the stringy Kähler moduli space. A few basic examples are studied. In particular, we identif...
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Analysis of a Sputtered Si Surface for Ar Sputter Gas Supply Purity Monitoring
For sputter depth profiling often sample erosion by Ar+ ions is used. Only a high purity of the sputter gas and a low contamination level of the ion gun avoids misleading depth profile measurements results. Here a new measurement procedure is presented, which monitors these parameters. A Si sample is sputtered inside...
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Extracting spectroscopic molecular parameters from short pulse photo-electron angular distributions
Using a quantum wave packet simulation including the nuclear and electronic degrees of freedom, we investigate the femtosecond and picosecond energy- and angle-resolved photoelectron spectra of the E($^1\Sigma_g^+$) electronic state of Li$_2$. We find that the angular distributions of the emitted photoelectrons depen...
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A Generative Model for Score Normalization in Speaker Recognition
We propose a theoretical framework for thinking about score normalization, which confirms that normalization is not needed under (admittedly fragile) ideal conditions. If, however, these conditions are not met, e.g. under data-set shift between training and runtime, our theory reveals dependencies between scores that...
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Deep Networks tag the location of bird vocalisations on audio spectrograms
This work focuses on reliable detection and segmentation of bird vocalizations as recorded in the open field. Acoustic detection of avian sounds can be used for the automatized monitoring of multiple bird taxa and querying in long-term recordings for species of interest. These tasks are tackled in this work, by sugge...
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To Wait or Not to Wait: Two-way Functional Hazards Model for Understanding Waiting in Call Centers
Telephone call centers offer a convenient communication channel between businesses and their customers. Efficient management of call centers needs accurate modeling of customer waiting behavior, which contains important information about customer patience (how long a customer is willing to wait) and service quality (...
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Bayesian Gaussian models for interpolating large-dimensional data at misaligned areal units
Areal level spatial data are often large, sparse and may appear with geographical shapes that are regular or irregular (e.g., postcode). Moreover, sometimes it is important to obtain predictive inference in regular or irregular areal shapes that is misaligned with the observed spatial areal geographical boundary. For...
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Report on TBAS 2012: Workshop on Task-Based and Aggregated Search
The ECIR half-day workshop on Task-Based and Aggregated Search (TBAS) was held in Barcelona, Spain on 1 April 2012. The program included a keynote talk by Professor Jarvelin, six full paper presentations, two poster presentations, and an interactive discussion among the approximately 25 participants. This report over...
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Reliability of the measured velocity anisotropy of the Milky Way stellar halo
Determining the velocity distribution of halo stars is essential for estimating the mass of the Milky Way and for inferring its formation history. Since the stellar halo is a dynamically hot system, the velocity distribution of halo stars is well described by the 3-dimensional velocity dispersions $(\sigma_r, \sigma_...
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$H$-compactness of elliptic operators on weighted Riemannian Manifolds
In this paper we study the asymptotic behavior of second-order uniformly elliptic operators on weighted Riemannian manifolds. We appeal to the notion of \mbox{$H$-convergence} introduced by Murat and Tartar. In our main result we establish an \mbox{$H$-compactness} result that applies to elliptic operators with measu...
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$b$-symbol distance distribution of repeated-root cyclic codes
Symbol-pair codes, introduced by Cassuto and Blaum [1], have been raised for symbol-pair read channels. This new idea is motivated by the limitation of the reading process in high-density data storage technologies. Yaakobi et al. [8] introduced codes for $b$-symbol read channels, where the read operation is performed...
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Knowledge Fusion via Embeddings from Text, Knowledge Graphs, and Images
We present a baseline approach for cross-modal knowledge fusion. Different basic fusion methods are evaluated on existing embedding approaches to show the potential of joining knowledge about certain concepts across modalities in a fused concept representation.
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Observation of spin superfluidity: YIG magnetic films and beyond
From topology of the order parameter of the magnon condensate observed in yttrium-iron-garnet (YIG) magnetic films one must not expect energetic barriers making spin supercurrents metastable. But we show that some barriers of dynamical origin are possible nevertheless until the gradient of the phase (angle of spin pr...
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Tuning of Interlayer Coupling in Large-Area Graphene/WSe2 van der Waals Heterostructure via Ion Irradiation: Optical Evidences and Photonic Applications
Van der Waals (vdW) heterostructures are receiving great attentions due to their intriguing properties and potentials in many research fields. The flow of charge carriers in vdW heterostructures can be efficiently rectified by the inter-layer coupling between neighboring layers, offering a rich collection of function...
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Learning to Multi-Task by Active Sampling
One of the long-standing challenges in Artificial Intelligence for learning goal-directed behavior is to build a single agent which can solve multiple tasks. Recent progress in multi-task learning for goal-directed sequential problems has been in the form of distillation based learning wherein a student network learn...
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Sufficient Conditions for Idealised Models to Have No Adversarial Examples: a Theoretical and Empirical Study with Bayesian Neural Networks
We prove, under two sufficient conditions, that idealised models can have no adversarial examples. We discuss which idealised models satisfy our conditions, and show that idealised Bayesian neural networks (BNNs) satisfy these. We continue by studying near-idealised BNNs using HMC inference, demonstrating the theoret...
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Long term availability of raw experimental data in experimental fracture mechanics
Experimental data availability is a cornerstone for reproducibility in experimental fracture mechanics, which is crucial to the scientific method. This short communication focuses on the accessibility and long term availability of raw experimental data. The corresponding authors of the eleven most cited papers, relat...
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