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Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search
Inference in log-linear models scales linearly in the size of output space in the worst-case. This is often a bottleneck in natural language processing and computer vision tasks when the output space is feasibly enumerable but very large. We propose a method to perform inference in log-linear models with sublinear am...
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Temperature Dependence of Magnetic Excitations: Terahertz Magnons above the Curie Temperature
When an ordered spin system of a given dimensionality undergoes a second order phase transition the dependence of the order parameter i.e. magnetization on temperature can be well-described by thermal excitations of elementary collective spin excitations (magnons). However, the behavior of magnons themselves, as a fu...
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On stable solitons and interactions of the generalized Gross-Pitaevskii equation with PT-and non-PT-symmetric potentials
We report the bright solitons of the generalized Gross-Pitaevskii (GP) equation with some types of physically relevant parity-time-(PT-) and non-PT-symmetric potentials. We find that the constant momentum coefficient can modulate the linear stability and complicated transverse power-flows (not always from the gain to...
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Mechanical properties of borophene films: A reactive molecular dynamics investigation
The most recent experimental advances could provide ways for the fabrication of several atomic thick and planar forms of boron atoms. For the first time, we explore the mechanical properties of five types of boron films with various vacancy ratios ranging from 0.1 to 0.15, using molecular dynamics simulations with Re...
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Stronger selection can slow down evolution driven by recombination on a smooth fitness landscape
Stronger selection implies faster evolution---that is, the greater the force, the faster the change. This apparently self-evident proposition, however, is derived under the assumption that genetic variation within a population is primarily supplied by mutation (i.e.\ mutation-driven evolution). Here, we show that thi...
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Differences Among Noninformative Stopping Rules Are Often Relevant to Bayesian Decisions
L.J. Savage once hoped to show that "the superficially incompatible systems of ideas associated on the one hand with [subjective Bayesianism] and on the other hand with [classical statistics]...lend each other mutual support and clarification." By 1972, however, he had largely "lost faith in the devices" of classical...
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CNNs are Globally Optimal Given Multi-Layer Support
Stochastic Gradient Descent (SGD) is the central workhorse for training modern CNNs. Although giving impressive empirical performance it can be slow to converge. In this paper we explore a novel strategy for training a CNN using an alternation strategy that offers substantial speedups during training. We make the fol...
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The Kontsevich integral for bottom tangles in handlebodies
The Kontsevich integral is a powerful link invariant, taking values in spaces of Jacobi diagrams. In this paper, we extend the Kontsevich integral to construct a functor on the category of bottom tangles in handlebodies. This functor gives a universal finite type invariant of bottom tangles, and refines a functorial ...
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Commutativity theorems for groups and semigroups
In this note we prove a selection of commutativity theorems for various classes of semigroups. For instance, if in a separative or completely regular semigroup $S$ we have $x^p y^p = y^p x^p$ and $x^q y^q = y^q x^q$ for all $x,y\in S$ where $p$ and $q$ are relatively prime, then $S$ is commutative. In a separative or...
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Content-based Approach for Vietnamese Spam SMS Filtering
Short Message Service (SMS) spam is a serious problem in Vietnam because of the availability of very cheap pre-paid SMS packages. There are some systems to detect and filter spam messages for English, most of which use machine learning techniques to analyze the content of messages and classify them. For Vietnamese, t...
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Measuring Software Performance on Linux
Measuring and analyzing the performance of software has reached a high complexity, caused by more advanced processor designs and the intricate interaction between user programs, the operating system, and the processor's microarchitecture. In this report, we summarize our experience about how performance characteristi...
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A general method for calculating lattice Green functions on the branch cut
We present a method for calculating the complex Green function $G_{ij} (\omega)$ at any real frequency $\omega$ between any two sites $i$ and $j$ on a lattice. Starting from numbers of walks on square, cubic, honeycomb, triangular, bcc, fcc, and diamond lattices, we derive Chebyshev expansion coefficients for $G_{ij}...
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Towards A Novel Unified Framework for Developing Formal, Network and Validated Agent-Based Simulation Models of Complex Adaptive Systems
Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inher-ently interested in an interdisciplinary compariso...
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Recover Fine-Grained Spatial Data from Coarse Aggregation
In this paper, we study a new type of spatial sparse recovery problem, that is to infer the fine-grained spatial distribution of certain density data in a region only based on the aggregate observations recorded for each of its subregions. One typical example of this spatial sparse recovery problem is to infer spatia...
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The Power Allocation Game on Dynamic Networks: Subgame Perfection
In the game theory literature, there appears to be little research on equilibrium selection for normal-form games with an infinite strategy space and discontinuous utility functions. Moreover, many existing selection methods are not applicable to games involving both cooperative and noncooperative scenarios (e.g., "g...
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MIMO Graph Filters for Convolutional Neural Networks
Superior performance and ease of implementation have fostered the adoption of Convolutional Neural Networks (CNNs) for a wide array of inference and reconstruction tasks. CNNs implement three basic blocks: convolution, pooling and pointwise nonlinearity. Since the two first operations are well-defined only on regular...
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An Edge Driven Wavelet Frame Model for Image Restoration
Wavelet frame systems are known to be effective in capturing singularities from noisy and degraded images. In this paper, we introduce a new edge driven wavelet frame model for image restoration by approximating images as piecewise smooth functions. With an implicit representation of image singularities sets, the pro...
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An exact algorithm exhibiting RS-RSB/easy-hard correspondence for the maximum independent set problem
A recently proposed exact algorithm for the maximum independent set problem is analyzed. The typical running time is improved exponentially in some parameter regions compared to simple binary search. The algorithm also overcomes the core transition point, where the conventional leaf removal algorithm fails, and works...
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Flexible Support for Fast Parallel Commutative Updates
Privatizing data is a useful strategy for increasing parallelism in a shared memory multithreaded program. Independent cores can compute independently on duplicates of shared data, combining their results at the end of their computations. Conventional approaches to privatization, however, rely on explicit static or d...
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Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms
Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables analyzing the native structures of macromolecular complexes and their spatial organization inside single cells. However, due to the high degre...
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CNN-MERP: An FPGA-Based Memory-Efficient Reconfigurable Processor for Forward and Backward Propagation of Convolutional Neural Networks
Large-scale deep convolutional neural networks (CNNs) are widely used in machine learning applications. While CNNs involve huge complexity, VLSI (ASIC and FPGA) chips that deliver high-density integration of computational resources are regarded as a promising platform for CNN's implementation. At massive parallelism ...
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Enstrophy Cascade in Decaying Two-Dimensional Quantum Turbulence
We report evidence for an enstrophy cascade in large-scale point-vortex simulations of decaying two-dimensional quantum turbulence. Devising a method to generate quantum vortex configurations with kinetic energy narrowly localized near a single length scale, the dynamics are found to be well-characterised by a superf...
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Contextual Multi-armed Bandits under Feature Uncertainty
We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined {\em NLinRel}, having $O\left(T^{\frac{7}{8}} \left(\log{(dT)}+K\sqrt{d}\right)\right)$ regret bound...
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Asymmetric Variational Autoencoders
Variational inference for latent variable models is prevalent in various machine learning problems, typically solved by maximizing the Evidence Lower Bound (ELBO) of the true data likelihood with respect to a variational distribution. However, freely enriching the family of variational distribution is challenging sin...
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Dynamics of homogeneous shear turbulence: A key role of the nonlinear transverse cascade in the bypass concept
To understand the self-sustenance of subcritical turbulence in spectrally stable shear flows, we performed direct numerical simulations of homogeneous shear turbulence for different aspect ratios of the flow domain and analyzed the dynamical processes in Fourier space. There are no exponentially growing modes in such...
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A taxonomy of learning dynamics in 2 x 2 games
Learning would be a convincing method to achieve coordination on an equilibrium. But does learning converge, and to what? We answer this question in generic 2-player, 2-strategy games, using Experience-Weighted Attraction (EWA), which encompasses many extensively studied learning algorithms. We exhaustively character...
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Dynamic attitude planning for trajectory tracking in underactuated VTOL UAVs
This paper addresses the trajectory tracking control problem for underactuated VTOL UAVs. According to the different actuation mechanisms, the most common UAV platforms can achieve only a partial decoupling of attitude and position tasks. Since position tracking is of utmost importance for applications involving aeri...
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The JCMT Transient Survey: Data Reduction and Calibration Methods
Though there has been a significant amount of work investigating the early stages of low-mass star formation in recent years, the evolution of the mass assembly rate onto the central protostar remains largely unconstrained. Examining in depth the variation in this rate is critical to understanding the physics of star...
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Synchronization Strings: Explicit Constructions, Local Decoding, and Applications
This paper gives new results for synchronization strings, a powerful combinatorial object that allows to efficiently deal with insertions and deletions in various communication settings: $\bullet$ We give a deterministic, linear time synchronization string construction, improving over an $O(n^5)$ time randomized cons...
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Independent Component Analysis via Energy-based and Kernel-based Mutual Dependence Measures
We apply both distance-based (Jin and Matteson, 2017) and kernel-based (Pfister et al., 2016) mutual dependence measures to independent component analysis (ICA), and generalize dCovICA (Matteson and Tsay, 2017) to MDMICA, minimizing empirical dependence measures as an objective function in both deflation and parallel...
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The local geometry of testing in ellipses: Tight control via localized Kolmogorov widths
We study the local geometry of testing a mean vector within a high-dimensional ellipse against a compound alternative. Given samples of a Gaussian random vector, the goal is to distinguish whether the mean is equal to a known vector within an ellipse, or equal to some other unknown vector in the ellipse. Such ellipse...
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A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe
Two of the most fundamental prototypes of greedy optimization are the matching pursuit and Frank-Wolfe algorithms. In this paper, we take a unified view on both classes of methods, leading to the first explicit convergence rates of matching pursuit methods in an optimization sense, for general sets of atoms. We deriv...
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Subsampled Rényi Differential Privacy and Analytical Moments Accountant
We study the problem of subsampling in differential privacy (DP), a question that is the centerpiece behind many successful differentially private machine learning algorithms. Specifically, we provide a tight upper bound on the Rényi Differential Privacy (RDP) (Mironov, 2017) parameters for algorithms that: (1) subsa...
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Concurrency and Probability: Removing Confusion, Compositionally
Assigning a satisfactory truly concurrent semantics to Petri nets with confusion and distributed decisions is a long standing problem, especially if one wants to fully replace nondeterminism with probability distributions and no stochastic structure is desired/allowed. Here we propose a general solution based on a re...
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Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration
We propose a technique for multi-task learning from demonstration that trains the controller of a low-cost robotic arm to accomplish several complex picking and placing tasks, as well as non-prehensile manipulation. The controller is a recurrent neural network using raw images as input and generating robot arm trajec...
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Dynamic Word Embeddings
We present a probabilistic language model for time-stamped text data which tracks the semantic evolution of individual words over time. The model represents words and contexts by latent trajectories in an embedding space. At each moment in time, the embedding vectors are inferred from a probabilistic version of word2...
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Multiple scattering effect on angular distribution and polarization of radiation by relativistic electrons in a thin crystal
The multiple scattering of ultra relativistic electrons in an amorphous matter leads to the suppression of the soft part of radiation spectrum (the Landau-Pomeranchuk-Migdal effect), and also can change essentially the angular distribution of the emitted photons. A similar effect must take place in a crystal for the ...
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Branched coverings of $CP^2$ and other basic 4-manifolds
We give necessary and sufficient conditions for a 4-manifold to be a branched covering of $CP^2$, $S^2\times S^2$, $S^2 \mathbin{\tilde\times} S^2$ and $S^3 \times S^1$, which are expressed in terms of the Betti numbers and the intersection form of the 4-manifold.
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Instantaneous effects of photons on electrons in semiconductors
The photoelectric effect established by Einstein is well known, which indicates that electrons on lower energy levels can jump up to higher levels by absorbing photons, or jump down from higher levels to lower levels and give out photons1-3. However, how do photons act on electrons and further on atoms have kept unkn...
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Mitigating the Impact of Speech Recognition Errors on Chatbot using Sequence-to-Sequence Model
We apply sequence-to-sequence model to mitigate the impact of speech recognition errors on open domain end-to-end dialog generation. We cast the task as a domain adaptation problem where ASR transcriptions and original text are in two different domains. In this paper, our proposed model includes two individual encode...
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Simultaneous 183 GHz H2O Maser and SiO Observations Towards Evolved Stars Using APEX SEPIA Band 5
We investigate the use of 183 GHz H2O masers for characterization of the physical conditions and mass loss process in the circumstellar envelopes of evolved stars. We used APEX SEPIA Band 5 to observe the 183 GHz H2O line towards 2 Red Supergiant and 3 Asymptotic Giant Branch stars. Simultaneously, we observed lines ...
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What does the free energy principle tell us about the brain?
The free energy principle has been proposed as a unifying theory of brain function. It is closely related, and in some cases subsumes, earlier unifying ideas such as Bayesian inference, predictive coding, and active learning. This article clarifies these connections, teasing apart distinctive and shared predictions.
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Learning with Changing Features
In this paper we study the setting where features are added or change interpretation over time, which has applications in multiple domains such as retail, manufacturing, finance. In particular, we propose an approach to provably determine the time instant from which the new/changed features start becoming relevant wi...
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Estimation Considerations in Contextual Bandits
Contextual bandit algorithms are sensitive to the estimation method of the outcome model as well as the exploration method used, particularly in the presence of rich heterogeneity or complex outcome models, which can lead to difficult estimation problems along the path of learning. We study a consideration for the ex...
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Using solar and load predictions in battery scheduling at the residential level
Smart solar inverters can be used to store, monitor and manage a home's solar energy. We describe a smart solar inverter system with battery which can either operate in an automatic mode or receive commands over a network to charge and discharge at a given rate. In order to make battery storage financially viable and...
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Towards Large-Pose Face Frontalization in the Wild
Despite recent advances in face recognition using deep learning, severe accuracy drops are observed for large pose variations in unconstrained environments. Learning pose-invariant features is one solution, but needs expensively labeled large-scale data and carefully designed feature learning algorithms. In this work...
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Managing the Public to Manage Data: Citizen Science and Astronomy
Citizen science projects recruit members of the public as volunteers to process and produce datasets. These datasets must win the trust of the scientific community. The task of securing credibility involves, in part, applying standard scientific procedures to clean these datasets. However, effective management of vol...
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Modular representations in type A with a two-row nilpotent central character
We study the category of representations of $\mathfrak{sl}_{m+2n}$ in positive characteristic, whose p-character is a nilpotent whose Jordan type is the two-row partition (m+n,n). In a previous paper with Anno, we used Bezrukavnikov-Mirkovic-Rumynin's theory of positive characteristic localization and exotic t-struct...
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Knowledge Acquisition: A Complex Networks Approach
Complex networks have been found to provide a good representation of the structure of knowledge, as understood in terms of discoverable concepts and their relationships. In this context, the discovery process can be modeled as agents walking in a knowledge space. Recent studies proposed more realistic dynamics, inclu...
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Frequent flaring in the TRAPPIST-1 system - unsuited for life?
We analyze short cadence K2 light curve of the TRAPPIST-1 system. Fourier analysis of the data suggests $P_\mathrm{rot}=3.295\pm0.003$ days. The light curve shows several flares, of which we analyzed 42 events, these have integrated flare energies of $1.26\times10^{30}-1.24\times10^{33}$ ergs. Approximately 12% of th...
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Playing Pairs with Pepper
As robots become increasingly prevalent in almost all areas of society, the factors affecting humans trust in those robots becomes increasingly important. This paper is intended to investigate the factor of robot attributes, looking specifically at the relationship between anthropomorphism and human development of tr...
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Wild theories with o-minimal open core
Let $T$ be a consistent o-minimal theory extending the theory of densely ordered groups and let $T'$ be a consistent theory. Then there is a complete theory $T^*$ extending $T$ such that $T$ is an open core of $T^*$, but every model of $T^*$ interprets a model of $T'$. If $T'$ is NIP, $T^*$ can be chosen to be NIP as...
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Objective Bayesian inference with proper scoring rules
Standard Bayesian analyses can be difficult to perform when the full likelihood, and consequently the full posterior distribution, is too complex and difficult to specify or if robustness with respect to data or to model misspecifications is required. In these situations, we suggest to resort to a posterior distribut...
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Large Area X-ray Proportional Counter (LAXPC) Instrument on AstroSat
Large Area X-ray Proportional Counter (LAXPC) is one of the major AstroSat payloads. LAXPC instrument will provide high time resolution X-ray observations in 3 to 80 keV energy band with moderate energy resolution. A cluster of three co-aligned identical LAXPC detectors is used in AstroSat to provide large collection...
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A Counterexample to the Vector Generalization of Costa's EPI, and Partial Resolution
We give a counterexample to the vector generalization of Costa's entropy power inequality (EPI) due to Liu, Liu, Poor and Shamai. In particular, the claimed inequality can fail if the matix-valued parameter in the convex combination does not commute with the covariance of the additive Gaussian noise. Conversely, the ...
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Models for Predicting Community-Specific Interest in News Articles
In this work, we ask two questions: 1. Can we predict the type of community interested in a news article using only features from the article content? and 2. How well do these models generalize over time? To answer these questions, we compute well-studied content-based features on over 60K news articles from 4 commun...
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On subfiniteness of graded linear series
Hilbert's 14th problem studies the finite generation property of the intersection of an integral algebra of finite type with a subfield of the field of fractions of the algebra. It has a negative answer due to the counterexample of Nagata. We show that a subfinite version of Hilbert's 14th problem has a confirmative ...
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Natasha 2: Faster Non-Convex Optimization Than SGD
We design a stochastic algorithm to train any smooth neural network to $\varepsilon$-approximate local minima, using $O(\varepsilon^{-3.25})$ backpropagations. The best result was essentially $O(\varepsilon^{-4})$ by SGD. More broadly, it finds $\varepsilon$-approximate local minima of any smooth nonconvex function i...
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Evidence for a Dayside Thermal Inversion and High Metallicity for the Hot Jupiter WASP-18b
We find evidence for a strong thermal inversion in the dayside atmosphere of the highly irradiated hot Jupiter WASP-18b (T$_{eq}=2411K$, $M=10.3M_{J}$) based on emission spectroscopy from Hubble Space Telescope secondary eclipse observations and Spitzer eclipse photometry. We demonstrate a lack of water vapor in eith...
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$α$-$β$ and $β$-$γ$ phase boundaries of solid oxygen observed by adiabatic magnetocaloric effect
The magnetic-field-temperature phase diagram of solid oxygen is investigated by the adiabatic magnetocaloric effect (MCE) measurement with pulsed magnetic fields. Relatively large temperature decrease with hysteresis is observed at just below the $\beta$-$\gamma$ and $\alpha$-$\beta$ phase transition temperatures owi...
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Localization Algorithm with Circular Representation in 2D and its Similarity to Mammalian Brains
Extended Kalman filter (EKF) does not guarantee consistent mean and covariance under linearization, even though it is the main framework for robotic localization. While Lie group improves the modeling of the state space in localization, the EKF on Lie group still relies on the arbitrary Gaussian assumption in face of...
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Lusin-type approximation of Sobolev by Lipschitz functions, in Gaussian and $RCD(K,\infty)$ spaces
We establish new approximation results, in the sense of Lusin, of Sobolev functions by Lipschitz ones, in some classes of non-doubling metric measure structures. Our proof technique relies upon estimates for heat semigroups and applies to Gaussian and $RCD(K, \infty)$ spaces. As a consequence, we obtain quantitative ...
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Distributed Coordination for a Class of Nonlinear Multi-agent Systems with Regulation Constraints
In this paper, a multi-agent coordination problem with steady-state regulation constraints is investigated for a class of nonlinear systems. Unlike existing leader-following coordination formulations, the reference signal is not given by a dynamic autonomous leader but determined as the optimal solution of a distribu...
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Intermodulation distortion of actuated MEMS capacitive switches
For the first time, intermodulation distortion of micro-electromechanical capacitive switches in the actuated state was analyzed both theoretically and experimentally. The distortion, although higher than that of switches in the suspended state, was found to decrease with increasing bias voltage but to depend weakly ...
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Parasitic Bipolar Leakage in III-V FETs: Impact of Substrate Architecture
InGaAs-based Gate-all-Around (GAA) FETs with moderate to high In content are shown experimentally and theoretically to be unsuitable for low-leakage advanced CMOS nodes. The primary cause for this is the large leakage penalty induced by the Parasitic Bipolar Effect (PBE), which is seen to be particularly difficult to...
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Properties of Ultra Gamma Function
In this paper we study the integral of type \[_{\delta,a}\Gamma_{\rho,b}(x) =\Gamma(\delta,a;\rho,b)(x)=\int_{0}^{\infty}t^{x-1}e^{-\frac{t^{\delta}}{a}-\frac{t^{-\rho}}{b}}dt.\] Different authors called this integral by different names like ultra gamma function, generalized gamma function, Kratzel integral, inverse ...
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Further remarks on liftings of crossed modules
In this paper we define the notion of pullback lifting of a lifting crossed module over a crossed module morphism and interpret this notion in the category of group-groupoid actions as pullback action. Moreover, we give a criterion for the lifting of homotopic crossed module morphisms to be homotopic, which will be c...
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Submodular Maximization through the Lens of Linear Programming
The simplex algorithm for linear programming is based on the fact that any local optimum with respect to the polyhedral neighborhood is also a global optimum. We show that a similar result carries over to submodular maximization. In particular, every local optimum of a constrained monotone submodular maximization pro...
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Channel Estimation for Diffusive MIMO Molecular Communications
In diffusion-based communication, as for molecular systems, the achievable data rate is very low due to the slow nature of diffusion and the existence of severe inter-symbol interference (ISI). Multiple-input multiple-output (MIMO) technique can be used to improve the data rate. Knowledge of channel impulse response ...
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Multi-stage splitting integrators for sampling with modified Hamiltonian Monte Carlo methods
Modified Hamiltonian Monte Carlo (MHMC) methods combine the ideas behind two popular sampling approaches: Hamiltonian Monte Carlo (HMC) and importance sampling. As in the HMC case, the bulk of the computational cost of MHMC algorithms lies in the numerical integration of a Hamiltonian system of differential equations...
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Proposal for a High Precision Tensor Processing Unit
This whitepaper proposes the design and adoption of a new generation of Tensor Processing Unit which has the performance of Google's TPU, yet performs operations on wide precision data. The new generation TPU is made possible by implementing arithmetic circuits which compute using a new general purpose, fractional ar...
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DICOD: Distributed Convolutional Sparse Coding
In this paper, we introduce DICOD, a convolutional sparse coding algorithm which builds shift invariant representations for long signals. This algorithm is designed to run in a distributed setting, with local message passing, making it communication efficient. It is based on coordinate descent and uses locally greedy...
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On uniqueness results for Dirichlet problems of elliptic systems without DeGiorgi-Nash-Moser regularity
We study uniqueness of Dirichlet problems of second order divergence-form elliptic systems with transversally independent coefficients on the upper half-space in absence of regularity of solutions. To this end, we develop a substitute for the fundamental solution used to invert elliptic operators on the whole space b...
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(LaTiO$_3$)$_n$/(LaVO$_3$)$_n$ as a model system for unconventional charge transfer and polar metallicity
At interfaces between oxide materials, lattice and electronic reconstructions always play important roles in exotic phenomena. In this study, the density functional theory and maximally localized Wannier functions are employed to investigate the (LaTiO$_3$)$_n$/(LaVO$_3$)$_n$ magnetic superlattices. The electron tran...
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Modeling sorption of emerging contaminants in biofilms
A mathematical model for emerging contaminants sorption in multispecies biofilms, based on a continuum approach and mass conservation principles is presented. Diffusion of contaminants within the biofilm is described using a diffusion-reaction equation. Binding sites formation and occupation are modeled by two system...
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Stabilizing Training of Generative Adversarial Networks through Regularization
Deep generative models based on Generative Adversarial Networks (GANs) have demonstrated impressive sample quality but in order to work they require a careful choice of architecture, parameter initialization, and selection of hyper-parameters. This fragility is in part due to a dimensional mismatch or non-overlapping...
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Spurious Vanishing Problem in Approximate Vanishing Ideal
Approximate vanishing ideal, which is a new concept from computer algebra, is a set of polynomials that almost takes a zero value for a set of given data points. The introduction of approximation to exact vanishing ideal has played a critical role in capturing the nonlinear structures of noisy data by computing the a...
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Opportunities for Two-color Experiments at the SASE3 undulator line of the European XFEL
X-ray Free Electron Lasers (XFELs) have been proven to generate short and powerful radiation pulses allowing for a wide class of novel experiments. If an XFEL facility supports the generation of two X-ray pulses with different wavelengths and controllable delay, the range of possible experiments is broadened even fur...
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Braiding errors in interacting Majorana quantum wires
Avenues of Majorana bound states (MBSs) have become one of the primary directions towards a possible realization of topological quantum computation. For a Y-junction of Kitaev quantum wires, we numerically investigate the braiding of MBSs while considering the full quasi-particle background. The two central sources o...
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Machine Learning for Structured Clinical Data
Research is a tertiary priority in the EHR, where the priorities are patient care and billing. Because of this, the data is not standardized or formatted in a manner easily adapted to machine learning approaches. Data may be missing for a large variety of reasons ranging from individual input styles to differences in...
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Hidden order and symmetry protected topological states in quantum link ladders
We show that whereas spin-1/2 one-dimensional U(1) quantum-link models (QLMs) are topologically trivial, when implemented in ladder-like lattices these models may present an intriguing ground-state phase diagram, which includes a symmetry protected topological (SPT) phase that may be readily revealed by analyzing lon...
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The effect of prudence on the optimal allocation in possibilistic and mixed models
In this paper two portfolio choice models are studied: a purely possibilistic model, in which the return of a risky asset is a fuzzy number, and a mixed model in which a probabilistic background risk is added. For the two models an approximate formula of the optimal allocation is computed, with respect to the possibi...
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On universal operators and universal pairs
We study some basic properties of the class of universal operators on Hilbert space, and provide new examples of universal operators and universal pairs.
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Interleaving Lattice for the APS Linac
To realize and test advanced accelerator concepts and hardware, a beamline is being reconfigured in the Linac Extension Area (LEA) of APS linac. A photo-cathode RF gun installed at the beginning of the APS linac will provide a low emittance electron beam into the LEA beamline. The thermionic RF gun beam for the APS s...
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\textit{Ab Initio} Study of the Magnetic Behavior of Metal Hydrides: A Comparison with the Slater-Pauling Curve
We investigated the magnetic behavior of metal hydrides FeH$_{x}$, CoH$_{x}$ and NiH$_{x}$ for several concentrations of hydrogen ($x$) by using Density Functional Theory calculations. Several structural phases of the metallic host: bcc ($\alpha$), fcc ($\gamma$), hcp ($\varepsilon$), dhcp ($\varepsilon'$), tetragona...
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Secret Sharing for Cloud Data Security
Cloud computing helps reduce costs, increase business agility and deploy solutions with a high return on investment for many types of applications. However, data security is of premium importance to many users and often restrains their adoption of cloud technologies. Various approaches, i.e., data encryption, anonymi...
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Design and Analysis of a Secure Three Factor User Authentication Scheme Using Biometric and Smart Card
Password security can no longer provide enough security in the area of remote user authentication. Considering this security drawback, researchers are trying to find solution with multifactor remote user authentication system. Recently, three factor remote user authentication using biometric and smart card has drawn ...
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Real-World Modeling of a Pathfinding Robot Using Robot Operating System (ROS)
This paper presents a practical approach towards implementing pathfinding algorithms on real-world and low-cost non- commercial hardware platforms. While using robotics simulation platforms as a test-bed for our algorithms we easily overlook real- world exogenous problems that are developed by external factors. Such ...
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Understanding Convolution for Semantic Segmentation
Recent advances in deep learning, especially deep convolutional neural networks (CNNs), have led to significant improvement over previous semantic segmentation systems. Here we show how to improve pixel-wise semantic segmentation by manipulating convolution-related operations that are of both theoretical and practica...
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Mechanical Failure in Amorphous Solids: Scale Free Spinodal Criticality
The mechanical failure of amorphous media is a ubiquitous phenomenon from material engineering to geology. It has been noticed for a long time that the phenomenon is "scale-free", indicating some type of criticality. In spite of attempts to invoke "Self-Organized Criticality", the physical origin of this criticality,...
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Moment conditions in strong laws of large numbers for multiple sums and random measures
The validity of the strong law of large numbers for multiple sums $S_n$ of independent identically distributed random variables $Z_k$, $k\leq n$, with $r$-dimensional indices is equivalent to the integrability of $|Z|(\log^+|Z|)^{r-1}$, where $Z$ is the typical summand. We consider the strong law of large numbers for...
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Connecting Clump Sizes in Turbulent Disk Galaxies to Instability Theory
In this letter we study the mean sizes of Halpha clumps in turbulent disk galaxies relative to kinematics, gas fractions, and Toomre Q. We use 100~pc resolution HST images, IFU kinematics, and gas fractions of a sample of rare, nearby turbulent disks with properties closely matched to z~1.5-2 main-sequence galaxies (...
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Anomalous slowing down of individual human activity due to successive decision-making processes
Motivated by a host of empirical evidences revealing the bursty character of human dynamics, we develop a model of human activity based on successive switching between an hesitation state and a decision-realization state, with residency times in the hesitation state distributed according to a heavy-tailed Pareto dist...
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The spectrum, radiation conditions and the Fredholm property for the Dirichlet Laplacian in a perforated plane with semi-infinite inclusions
We consider the spectral Dirichlet problem for the Laplace operator in the plane $\Omega^{\circ}$ with double-periodic perforation but also in the domain $\Omega^{\bullet}$ with a semi-infinite foreign inclusion so that the Floquet-Bloch technique and the Gelfand transform do not apply directly. We describe waves whi...
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On the Semantics and Complexity of Probabilistic Logic Programs
We examine the meaning and the complexity of probabilistic logic programs that consist of a set of rules and a set of independent probabilistic facts (that is, programs based on Sato's distribution semantics). We focus on two semantics, respectively based on stable and on well-founded models. We show that the semanti...
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Fitting Probabilistic Index Models on Large Datasets
Recently, Thas et al. (2012) introduced a new statistical model for the probability index. This index is defined as $P(Y \leq Y^*|X, X^*)$ where Y and Y* are independent random response variables associated with covariates X and X* [...] Crucially to estimate the parameters of the model, a set of pseudo-observations ...
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BICEP2 / Keck Array IX: New Bounds on Anisotropies of CMB Polarization Rotation and Implications for Axion-Like Particles and Primordial Magnetic Fields
We present the strongest constraints to date on anisotropies of CMB polarization rotation derived from $150$ GHz data taken by the BICEP2 & Keck Array CMB experiments up to and including the 2014 observing season (BK14). The definition of polarization angle in BK14 maps has gone through self-calibration in which the ...
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Unsupervised Object Discovery and Segmentation of RGBD-images
In this paper we introduce a system for unsupervised object discovery and segmentation of RGBD-images. The system models the sensor noise directly from data, allowing accurate segmentation without sensor specific hand tuning of measurement noise models making use of the recently introduced Statistical Inlier Estimati...
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Enabling large-scale viscoelastic calculations via neural network acceleration
One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Computationally intensive viscoelastic codes must be evaluated thousands of times and locations, and as a result, ...
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Speaker identification from the sound of the human breath
This paper examines the speaker identification potential of breath sounds in continuous speech. Speech is largely produced during exhalation. In order to replenish air in the lungs, speakers must periodically inhale. When inhalation occurs in the midst of continuous speech, it is generally through the mouth. Intra-sp...
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