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Local Gradient Estimates for Second-Order Nonlinear Elliptic and Parabolic Equations by the Weak Bernstein's Method
In the theory of second-order, nonlinear elliptic and parabolic equations, obtaining local or global gradient bounds is often a key step for proving the existence of solutions but it may be even more useful in many applications, for example to singular perturbations problems. The classical Bernstein's method is the w...
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Dynamic patterns of knowledge flows across technological domains: empirical results and link prediction
The purpose of this study is to investigate the structure and evolution of knowledge spillovers across technological domains. Specifically, dynamic patterns of knowledge flow among 29 technological domains, measured by patent citations for eight distinct periods, are identified and link prediction is tested for capab...
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Accurate calculation of oblate spheroidal wave functions
Alternative expressions for calculating the oblate spheroidal radial functions of both kinds R1ml and R2ml are shown to provide accurate values over very large parameter ranges using 64 bit arithmetic, even where the traditional expressions fail. First is the expansion of the product of a radial function and the angu...
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Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach
Learning cooperative policies for multi-agent systems is often challenged by partial observability and a lack of coordination. In some settings, the structure of a problem allows a distributed solution with limited communication. Here, we consider a scenario where no communication is available, and instead we learn l...
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Ion distribution and ablation depth measurements of a fs-ps laser-irradiated solid tin target
The ablation of solid tin surfaces by an 800-nanometer-wavelength laser is studied for a pulse length range from 500 fs to 4.5 ps and a fluence range spanning 0.9 to 22 J/cm^2. The ablation depth and volume are obtained employing a high-numerical-aperture optical microscope, while the ion yield and energy distributio...
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Measuring the Hubble constant with Type Ia supernovae as near-infrared standard candles
The most precise local measurements of $H_0$ rely on observations of Type Ia supernovae (SNe Ia) coupled with Cepheid distances to SN Ia host galaxies. Recent results have shown tension comparing $H_0$ to the value inferred from CMB observations assuming $\Lambda$CDM, making it important to check for potential system...
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Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Deep learning thrives with large neural networks and large datasets. However, larger networks and larger datasets result in longer training times that impede research and development progress. Distributed synchronous SGD offers a potential solution to this problem by dividing SGD minibatches over a pool of parallel w...
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Universal Construction of Cheater-Identifiable Secret Sharing Against Rushing Cheaters Based on Message Authentication
For conventional secret sharing, if cheaters can submit possibly forged shares after observing shares of the honest users in the reconstruction phase then they cannot only disturb the protocol but also only they may reconstruct the true secret. To overcome the problem, secret sharing scheme with properties of cheater...
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Regrasp Planning Considering Bipedal Stability Constraints
This paper presents a Center of Mass (CoM) based manipulation and regrasp planner that implements stability constraints to preserve the robot balance. The planner provides a graph of IK-feasible, collision-free and stable motion sequences, constructed using an energy based motion planning algorithm. It assures that t...
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Unsaturated deformable porous media flow with phase transition
In the present paper, a continuum model is introduced for fluid flow in a deformable porous medium, where the fluid may undergo phase transitions. Typically, such problems arise in modeling liquid-solid phase transformations in groundwater flows. The system of equations is derived here from the conservation principle...
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Active Mini-Batch Sampling using Repulsive Point Processes
The convergence speed of stochastic gradient descent (SGD) can be improved by actively selecting mini-batches. We explore sampling schemes where similar data points are less likely to be selected in the same mini-batch. In particular, we prove that such repulsive sampling schemes lowers the variance of the gradient e...
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Customizing First Person Image Through Desired Actions
This paper studies a problem of inverse visual path planning: creating a visual scene from a first person action. Our conjecture is that the spatial arrangement of a first person visual scene is deployed to afford an action, and therefore, the action can be inversely used to synthesize a new scene such that the actio...
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Michell trusses in two dimensions as a Gamma-limit of optimal design problems in linear elasticity
We reconsider the minimization of the compliance of a two dimensional elastic body with traction boundary conditions for a given weight. It is well known how to rewrite this optimal design problem as a nonlinear variational problem. We take the limit of vanishing weight by sending a suitable Lagrange multiplier to in...
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Moment analysis of highway-traffic clearance distribution
To help with the planning of inter-vehicular communication networks, an accurate understanding of traffic behavior and traffic phase transition is required. We calculate inter-vehicle spacings from empirical data collected in a multi-lane highway in California, USA. We calculate the correlation coefficients for spaci...
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Single-image Tomography: 3D Volumes from 2D Cranial X-Rays
As many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of data created when extending the 2D image into a 3D volume, we s...
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Stochastic Methods for Composite and Weakly Convex Optimization Problems
We consider minimization of stochastic functionals that are compositions of a (potentially) non-smooth convex function $h$ and smooth function $c$ and, more generally, stochastic weakly-convex functionals. We develop a family of stochastic methods---including a stochastic prox-linear algorithm and a stochastic (gener...
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Thermal Expansion of the Heavy-fermion Superconductor PuCoGa$_{5}$
We have performed high-resolution powder x-ray diffraction measurements on a sample of $^{242}$PuCoGa$_{5}$, the heavy-fermion superconductor with the highest critical temperature $T_{c}$ = 18.7 K. The results show that the tetragonal symmetry of its crystallographic lattice is preserved down to 2 K. Marginal evidenc...
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Versatile Auxiliary Classifier with Generative Adversarial Network (VAC+GAN), Multi Class Scenarios
Conditional generators learn the data distribution for each class in a multi-class scenario and generate samples for a specific class given the right input from the latent space. In this work, a method known as "Versatile Auxiliary Classifier with Generative Adversarial Network" for multi-class scenarios is presented...
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A Lagrangian Model to Predict Microscallop Motion in non Newtonian Fluids
The need to develop models to predict the motion of microrobots, or robots of a much smaller scale, moving in fluids in a low Reynolds number regime, and in particular, in non Newtonian fluids, cannot be understated. The article develops a Lagrangian based model for one such mechanism - a two-link mechanism termed a ...
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Towards a Bootstrap approach to higher orders of epsilon expansion
We employ a hybrid approach in determining the anomalous dimension and OPE coefficient of higher spin operators in the Wilson-Fisher theory. First we do a large spin analysis for CFT data where we use results obtained from the usual and the Mellin Bootstrap and also from Feynman diagram literature. This gives new pre...
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Small-scale Effects of Thermal Inflation on Halo Abundance at High-$z$, Galaxy Substructure Abundance and 21-cm Power Spectrum
We study the impact of thermal inflation on the formation of cosmological structures and present astrophysical observables which can be used to constrain and possibly probe the thermal inflation scenario. These are dark matter halo abundance at high redshifts, satellite galaxy abundance in the Milky Way, and fluctuat...
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Finiteness theorems for holomorphic mappings from products of hyperbolic Riemann surfaces
We prove that the space of dominant/non-constant holomorphic mappings from a product of hyperbolic Riemann surfaces of finite type into certain hyperbolic manifolds with universal cover a bounded domain is a finite set.
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Time and media-use of Italian Generation Y: dimensions of leisure preferences
Time spent in leisure is not a minor research question as it is acknowledged as a key aspect of one's quality of life. The primary aim of this article is to qualify time and Internet use of Italian Generation Y beyond media hype and assumptions. To this aim, we apply a multidimensional extension of Item Response Theo...
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Recurrent Multimodal Interaction for Referring Image Segmentation
In this paper we are interested in the problem of image segmentation given natural language descriptions, i.e. referring expressions. Existing works tackle this problem by first modeling images and sentences independently and then segment images by combining these two types of representations. We argue that learning ...
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Motion of a thin elliptic plate under symmetric and asymmetric orthotropic friction forces
Anisotropy of friction force is proved to be an important factor in various contact problems. We study dynamical behavior of thin plates with respect to symmetric and asymmetric orthotropic friction. Terminal motion of plates with circular and elliptic contact areas is mainly analyzed. Evaluation of friction forces f...
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Combinatorial Auctions with Online XOS Bidders
In combinatorial auctions, a designer must decide how to allocate a set of indivisible items amongst a set of bidders. Each bidder has a valuation function which gives the utility they obtain from any subset of the items. Our focus is specifically on welfare maximization, where the objective is to maximize the sum of...
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Application of Convolutional Neural Network to Predict Airfoil Lift Coefficient
The adaptability of the convolutional neural network (CNN) technique for aerodynamic meta-modeling tasks is probed in this work. The primary objective is to develop suitable CNN architecture for variable flow conditions and object geometry, in addition to identifying a sufficient data preparation process. Multiple CN...
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Bayesian inference in Y-linked two-sex branching processes with mutations: ABC approach
A Y-linked two-sex branching process with mutations and blind choice of males is a suitable model for analyzing the evolution of the number of carriers of an allele and its mutations of a Y-linked gene. Considering a two-sex monogamous population, in this model each female chooses her partner from among the male popu...
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Effective Theories for 2+1 Dimensional Non-Abelian Topological Spin Liquids
In this work we propose an effective low-energy theory for a large class of 2+1 dimensional non-Abelian topological spin liquids whose edge states are conformal degrees of freedom with central charges corresponding to the coset structure $su(2)_k\oplus su(2)_{k'}/su(2)_{k+k'}$. For particular values of $k'$ it furnis...
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Coset space construction for the conformal group. II. Spontaneously broken phase and inverse Higgs phenomenon
A self-contained method of obtaining effective theories resulting from the spontaneous breakdown of conformal invariance is developed. It allows to demonstrate that the Nambu-Goldstone fields for special conformal transformations always represent non-dynamical degrees of freedom. The standard approach to the same que...
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The morphodynamics of 3D migrating cancer cells
Cell shape is an important biomarker. Previously extensive studies have established the relation between cell shape and cell function. However, the morphodynamics, namely the temporal fluctuation of cell shape is much less understood. We study the morphodynamics of MDA-MB-231 cells in type I collagen extracellular ma...
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Evolution Strategies as a Scalable Alternative to Reinforcement Learning
We explore the use of Evolution Strategies (ES), a class of black box optimization algorithms, as an alternative to popular MDP-based RL techniques such as Q-learning and Policy Gradients. Experiments on MuJoCo and Atari show that ES is a viable solution strategy that scales extremely well with the number of CPUs ava...
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IoT Localization for Bistatic Passive UHF RFID Systems with 3D Radiation Pattern
Passive Radio-Frequency IDentification (RFID) systems carry critical importance for Internet of Things (IoT) applications due to their energy harvesting capabilities. RFID based position estimation, in particular, is expected to facilitate a wide array of location based services for IoT applications with low-power re...
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Multidimensional upwind hydrodynamics on unstructured meshes using Graphics Processing Units I. Two-dimensional uniform meshes
We present a new method for numerical hydrodynamics which uses a multidimensional generalisation of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which commonly use one-dimensional flux estimates as building blocks for a multidime...
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Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders
An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- eve...
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Density matrix expansion based semi-local exchange hole applied to range separated density functional theory
Exchange hole is the principle constituent in density functional theory, which can be used to accurately design exchange energy functional and range separated hybrid functionals coupled with some appropriate correlation. Recently, density matrix expansion (DME) based semi-local exchange hole proposed by Tao-Mo gained...
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CANDELS Sheds Light on the Environmental Quenching of Low-mass Galaxies
We investigate the environmental quenching of galaxies, especially those with stellar masses (M*)$<10^{9.5} M_\odot$, beyond the local universe. Essentially all local low-mass quenched galaxies (QGs) are believed to live close to massive central galaxies, which is a demonstration of environmental quenching. We use CA...
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BP-homology of elementary abelian 2-groups: BP-module structure
We determine the BP-module structure, mod higher filtration, of the main part of the BP-homology of elementary abelian 2-groups. The action is related to symmetric polynomials and to Dickson invariants.
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Probabilistic Active Learning of Functions in Structural Causal Models
We consider the problem of learning the functions computing children from parents in a Structural Causal Model once the underlying causal graph has been identified. This is in some sense the second step after causal discovery. Taking a probabilistic approach to estimating these functions, we derive a natural myopic a...
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Neural Episodic Control
Deep reinforcement learning methods attain super-human performance in a wide range of environments. Such methods are grossly inefficient, often taking orders of magnitudes more data than humans to achieve reasonable performance. We propose Neural Episodic Control: a deep reinforcement learning agent that is able to r...
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School bus routing by maximizing trip compatibility
School bus planning is usually divided into routing and scheduling due to the complexity of solving them concurrently. However, the separation between these two steps may lead to worse solutions with higher overall costs than that from solving them together. When finding the minimal number of trips in the routing pro...
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Solvability of abstract semilinear equations by a global diffeomorphism theorem
In this work we proivied a new simpler proof of the global diffeomorphism theorem from [9] which we further apply to consider unique solvability of some abstract semilinear equations. Applications to the second order Dirichlet problem driven by the Laplace operator are given.
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Learning a Generative Model for Validity in Complex Discrete Structures
Deep generative models have been successfully used to learn representations for high-dimensional discrete spaces by representing discrete objects as sequences and employing powerful sequence-based deep models. Unfortunately, these sequence-based models often produce invalid sequences: sequences which do not represent...
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On discrete structures in finite Hilbert spaces
We present a brief review of discrete structures in a finite Hilbert space, relevant for the theory of quantum information. Unitary operator bases, mutually unbiased bases, Clifford group and stabilizer states, discrete Wigner function, symmetric informationally complete measurements, projective and unitary t--design...
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Selected topics on Toric Varieties
This article is based on a series of lectures on toric varieties given at RIMS, Kyoto. We start by introducing toric varieties, their basic properties and later pass to more advanced topics relating mostly to combinatorics.
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Control Capacity
Feedback control actively dissipates uncertainty from a dynamical system by means of actuation. We develop a notion of "control capacity" that gives a fundamental limit (in bits) on the rate at which a controller can dissipate the uncertainty from a system, i.e. stabilize to a known fixed point. We give a computable ...
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Benefits from Superposed Hawkes Processes
The superposition of temporal point processes has been studied for many years, although the usefulness of such models for practical applications has not be fully developed. We investigate superposed Hawkes process as an important class of such models, with properties studied in the framework of least squares estimati...
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Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
Since the invention of word2vec, the skip-gram model has significantly advanced the research of network embedding, such as the recent emergence of the DeepWalk, LINE, PTE, and node2vec approaches. In this work, we show that all of the aforementioned models with negative sampling can be unified into the matrix factori...
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Differentially Private Query Learning: from Data Publishing to Model Publishing
With the development of Big Data and cloud data sharing, privacy preserving data publishing becomes one of the most important topics in the past decade. As one of the most influential privacy definitions, differential privacy provides a rigorous and provable privacy guarantee for data publishing. Differentially priva...
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Flexible Level-1 Consensus Ensuring Stable Social Choice: Analysis and Algorithms
Level-1 Consensus is a property of a preference-profile. Intuitively, it means that there exists a preference relation which induces an ordering of all other preferences such that frequent preferences are those that are more similar to it. This is a desirable property, since it enhances the stability of social choice...
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Fracture imaging within a granitic rock aquifer using multiple-offset single-hole and cross-hole GPR reflection data
The sparsely spaced highly permeable fractures of the granitic rock aquifer at Stang-er-Brune (Brittany, France) form a well-connected fracture network of high permeability but unknown geometry. Previous work based on optical and acoustic logging together with single-hole and cross-hole flowmeter data acquired in 3 n...
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The asymptotic behavior of automorphism groups of function fields over finite fields
The purpose of this paper is to investigate the asymptotic behavior of automorphism groups of function fields when genus tends to infinity. Motivated by applications in coding and cryptography, we consider the maximum size of abelian subgroups of the automorphism group $\mbox{Aut}(F/\mathbb{F}_q)$ in terms of genus $...
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Bootstrap Robust Prescriptive Analytics
We address the problem of prescribing an optimal decision in a framework where its cost depends on uncertain problem parameters $Y$ that need to be learned from data. Earlier work by Bertsimas and Kallus (2014) transforms classical machine learning methods that merely predict $Y$ from supervised training data $[(x_1,...
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Tverberg type theorems for matroids
In this paper we show a variant of colorful Tverberg's theorem which is valid in any matroid: Let $S$ be a sequence of non-loops in a matroid $M$ of finite rank $m$ with closure operator cl. Suppose that $S$ is colored in such a way that the first color does not appear more than $r$-times and each other color appears...
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Dynamic Erdős-Rényi graphs
We propose two classes of dynamic versions of the classical Erdős-Rényi graph: one in which the transition rates are governed by an external regime process, and one in which the transition rates are periodically resampled. For both models we consider the evolution of the number of edges present, with explicit results...
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Mining Density Contrast Subgraphs
Dense subgraph discovery is a key primitive in many graph mining applications, such as detecting communities in social networks and mining gene correlation from biological data. Most studies on dense subgraph mining only deal with one graph. However, in many applications, we have more than one graph describing relati...
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Unsupervised Learning by Predicting Noise
Convolutional neural networks provide visual features that perform remarkably well in many computer vision applications. However, training these networks requires significant amounts of supervision. This paper introduces a generic framework to train deep networks, end-to-end, with no supervision. We propose to fix a ...
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Trajectory Generation for Millimeter Scale Ferromagnetic Swimmers: Theory and Experiments
Microrobots have the potential to impact many areas such as microsurgery, micromanipulation and minimally invasive sensing. Due to their small size, microrobots swim in a regime that is governed by low Reynolds number hydrodynamics. In this paper, we consider small scale artificial swimmers that are fabricated using ...
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Decoupled Block-Wise ILU(k) Preconditioner on GPU
This research investigates the implementation mechanism of block-wise ILU(k) preconditioner on GPU. The block-wise ILU(k) algorithm requires both the level k and the block size to be designed as variables. A decoupled ILU(k) algorithm consists of a symbolic phase and a factorization phase. In the symbolic phase, a IL...
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Multi-agent Economics and the Emergence of Critical Markets
The dual crises of the sub-prime mortgage crisis and the global financial crisis has prompted a call for explanations of non-equilibrium market dynamics. Recently a promising approach has been the use of agent based models (ABMs) to simulate aggregate market dynamics. A key aspect of these models is the endogenous em...
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Error-Correcting Neural Sequence Prediction
In this paper we propose a novel neural language modelling (NLM) method based on \textit{error-correcting output codes} (ECOC), abbreviated as ECOC-NLM. This latent variable based approach provides a principled way to choose a varying amount of latent output codes and avoids exact softmax normalization. Instead of mi...
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Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem
We study sampling as optimization in the space of measures. We focus on gradient flow-based optimization with the Langevin dynamics as a case study. We investigate the source of the bias of the unadjusted Langevin algorithm (ULA) in discrete time, and consider how to remove or reduce the bias. We point out the diffic...
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Deep laser cooling in optical trap: two-level quantum model
We study laser cooling of $^{24}$Mg atoms in dipole optical trap with pumping field resonant to narrow $(3s3s)\,^1S_0 \rightarrow \, (3s3p)\,^{3}P_1$ ($\lambda = 457$ nm) optical transition. For description of laser cooling of atoms in the optical trap with taking into account quantum recoil effects we consider two q...
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JADE: Joint Autoencoders for Dis-Entanglement
The problem of feature disentanglement has been explored in the literature, for the purpose of image and video processing and text analysis. State-of-the-art methods for disentangling feature representations rely on the presence of many labeled samples. In this work, we present a novel method for disentangling factor...
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Numerical Simulations of Collisional Cascades at the Roche Limits of White Dwarf Stars
We consider the long-term collisional and dynamical evolution of solid material orbiting in a narrow annulus near the Roche limit of a white dwarf. With orbital velocities of 300 km/sec, systems of solids with initial eccentricity $e \gtrsim 10^{-3}$ generate a collisional cascade where objects with radii $r \lesssim...
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Causal Effect Inference with Deep Latent-Variable Models
Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers. The most important aspect of inferring causal effects from observational data is the handling of confounders, factors that aff...
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Gamma-ray bursts and their relation to astroparticle physics and cosmology
This article gives an overview of gamma-ray bursts (GRBs) and their relation to astroparticle physics and cosmology. GRBs are the most powerful explosions in the universe that occur roughly once per day and are characterized by flashes of gamma-rays typically lasting from a fraction of a second to thousands of second...
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Discrete-time Risk-sensitive Mean-field Games
In this paper, we study a class of discrete-time mean-field games under the infinite-horizon risk-sensitive discounted-cost optimality criterion. Risk-sensitivity is introduced for each agent (player) via an exponential utility function. In this game model, each agent is coupled with the rest of the population throug...
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Glasner's problem for Polish groups with metrizable universal minimal flow
A problem of Glasner, now known as Glasner's problem, asks whether every minimally almost periodic, monothetic, Polish groups is extremely amenable. The purpose of this short note is to observe that a positive answer is obtained under the additional assumption that the universal minimal flow is metrizable.
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VAE with a VampPrior
Many different methods to train deep generative models have been introduced in the past. In this paper, we propose to extend the variational auto-encoder (VAE) framework with a new type of prior which we call "Variational Mixture of Posteriors" prior, or VampPrior for short. The VampPrior consists of a mixture distri...
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Fast and Strong Convergence of Online Learning Algorithms
In this paper, we study the online learning algorithm without explicit regularization terms. This algorithm is essentially a stochastic gradient descent scheme in a reproducing kernel Hilbert space (RKHS). The polynomially decaying step size in each iteration can play a role of regularization to ensure the generaliza...
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A new continuum theory for incompressible swelling materials
Swelling media (e.g. gels, tumors) are usually described by mechanical constitutive laws (e.g. Hooke or Darcy laws). However, constitutive relations of real swelling media are not well known. Here, we take an opposite route and consider a simple packing heuristics, i.e. the particles can't overlap. We deduce a formul...
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The Hidden Binary Search Tree:A Balanced Rotation-Free Search Tree in the AVL RAM Model
In this paper we generalize the definition of "Search Trees" (ST) to enable reference values other than the key of prior inserted nodes. The idea builds on the assumption an $n$-node AVL (or Red-Black) requires to assure $O(\log_2n)$ worst-case search time, namely, a single comparison between two keys takes constant ...
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The sdB pulsating star V391 Peg and its putative giant planet revisited after 13 years of time-series photometric data
V391 Peg (alias HS2201+2610) is a subdwarf B (sdB) pulsating star that shows both p- and g-modes. By studying the arrival times of the p-mode maxima and minima through the O-C method, in a previous article the presence of a planet was inferred with an orbital period of 3.2 yr and a minimum mass of 3.2 M_Jup. Here we ...
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Rates of convergence for inexact Krasnosel'skii-Mann iterations in Banach spaces
We study the convergence of an inexact version of the classical Krasnosel'skii-Mann iteration for computing fixed points of nonexpansive maps. Our main result establishes a new metric bound for the fixed-point residuals, from which we derive their rate of convergence as well as the convergence of the iterates towards...
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Automatic Estimation of Fetal Abdominal Circumference from Ultrasound Images
Ultrasound diagnosis is routinely used in obstetrics and gynecology for fetal biometry, and owing to its time-consuming process, there has been a great demand for automatic estimation. However, the automated analysis of ultrasound images is complicated because they are patient-specific, operator-dependent, and machin...
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Heavy fermion quantum criticality at dilute carrier limit in CeNi$_{2-δ}$(As$_{1-x}$P$_{x}$)$_{2}$
We study the quantum phase transitions in the nickel pnctides, CeNi$_{2-\delta}$(As$_{1-x}$P$_{x}$)$_{2}$ ($\delta$ $\approx$ 0.07-0.22). This series displays the distinct heavy fermion behavior in the rarely studied parameter regime of dilute carrier limit. We systematically investigate the magnetization, specific h...
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Invariant Gibbs measures for the 2-d defocusing nonlinear wave equations
We consider the defocusing nonlinear wave equations (NLW) on the two-dimensional torus. In particular, we construct invariant Gibbs measures for the renormalized so-called Wick ordered NLW. We then prove weak universality of the Wick ordered NLW, showing that the Wick ordered NLW naturally appears as a suitable scali...
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Topological Analysis and Synthesis of Structures related to Certain Classes of K-Geodetic Computer Networks
A fundamental characteristic of computer networks is their topological structure. The question of the description of the structural characteristics of computer networks represents a problem that is not completely solved. Search methods for structures of computer networks, for which the values of the selected paramete...
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A distributed-memory hierarchical solver for general sparse linear systems
We present a parallel hierarchical solver for general sparse linear systems on distributed-memory machines. For large-scale problems, this fully algebraic algorithm is faster and more memory-efficient than sparse direct solvers because it exploits the low-rank structure of fill-in blocks. Depending on the accuracy of...
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Quasar: Datasets for Question Answering by Search and Reading
We present two new large-scale datasets aimed at evaluating systems designed to comprehend a natural language query and extract its answer from a large corpus of text. The Quasar-S dataset consists of 37000 cloze-style (fill-in-the-gap) queries constructed from definitions of software entity tags on the popular websi...
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Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems
As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human...
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Development of verification system of socio-demographic data of virtual community member
The important task of developing verification system of data of virtual community member on the basis of computer-linguistic analysis of the content of a large sample of Ukrainian virtual communities is solved. The subject of research is methods and tools for verification of web-members socio-demographic characterist...
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Demonstration of an efficient, photonic-based astronomical spectrograph on an 8-m telescope
We demonstrate for the first time an efficient, photonic-based astronomical spectrograph on the 8-m Subaru Telescope. An extreme adaptive optics system is combined with pupil apodiziation optics to efficiently inject light directly into a single-mode fiber, which feeds a compact cross-dispersed spectrograph based on ...
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A Game of Random Variables
This paper analyzes a simple game with $n$ players. We fix a mean, $\mu$, in the interval $[0, 1]$ and let each player choose any random variable distributed on that interval with the given mean. The winner of the zero-sum game is the player whose random variable has the highest realization. We show that the position...
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Parallel Structure from Motion from Local Increment to Global Averaging
In this paper, we tackle the accurate and consistent Structure from Motion (SfM) problem, in particular camera registration, far exceeding the memory of a single computer in parallel. Different from the previous methods which drastically simplify the parameters of SfM and sacrifice the accuracy of the final reconstru...
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Proceedings 2nd Workshop on Models for Formal Analysis of Real Systems
This volume contains the proceedings of MARS 2017, the second workshop on Models for Formal Analysis of Real Systems, held on April 29, 2017 in Uppala, Sweden, as an affiliated workshop of ETAPS 2017, the European Joint Conferences on Theory and Practice of Software. The workshop emphasises modelling over verificatio...
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Negative electronic compressibility and nanoscale inhomogeneity in ionic-liquid gated two-dimensional superconductors
When the electron density of highly crystalline thin films is tuned by chemical doping or ionic liq- uid gating, interesting effects appear including unconventional superconductivity, sizeable spin-orbit coupling, competition with charge-density waves, and a debated low-temperature metallic state that seems to avoid ...
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Symbolic Music Genre Transfer with CycleGAN
Deep generative models such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) have recently been applied to style and domain transfer for images, and in the case of VAEs, music. GAN-based models employing several generators and some form of cycle consistency loss have been among the most s...
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Methodology for Multi-stage, Operations- and Uncertainty-Aware Placement and Sizing of FACTS Devices in a Large Power Transmission System
We develop new optimization methodology for planning installation of Flexible Alternating Current Transmission System (FACTS) devices of the parallel and shunt types into large power transmission systems, which allows to delay or avoid installations of generally much more expensive power lines. Methodology takes as a...
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PC Proxy: A New Method of Dynamical Tracer Reconstruction
A detailed development of the principal component proxy method of dynamical tracer reconstruction is presented, including error analysis. The method works by correlating the largest principal components of a matrix representation of the transport dynamics with a set of sparse measurements. The Lyapunov spectrum was m...
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Magnetic Correlations in the Two-dimensional Repulsive Fermi Hubbard Model
The repulsive Fermi Hubbard model on the square lattice has a rich phase diagram near half-filling (corresponding to the particle density per lattice site $n=1$): for $n=1$ the ground state is an antiferromagnetic insulator, at $0.6 < n \lesssim 0.8$, it is a $d_{x^2-y^2}$-wave superfluid (at least for moderately str...
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Bridge type classification: supervised learning on a modified NBI dataset
A key phase in the bridge design process is the selection of the structural system. Due to budget and time constraints, engineers typically rely on engineering judgment and prior experience when selecting a structural system, often considering a limited range of design alternatives. The objective of this study was to...
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Automatic Question-Answering Using A Deep Similarity Neural Network
Automatic question-answering is a classical problem in natural language processing, which aims at designing systems that can automatically answer a question, in the same way as human does. In this work, we propose a deep learning based model for automatic question-answering. First the questions and answers are embedd...
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Long ties accelerate noisy threshold-based contagions
Changes to network structure can substantially affect when and how widely new ideas, products, and conventions are adopted. In models of biological contagion, interventions that randomly rewire edges (making them "longer") accelerate spread. However, there are other models relevant to social contagion, such as those ...
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Detecting topological transitions in two dimensions by Hamiltonian evolution
We show that the evolution of two-component particles governed by a two-dimensional spin-orbit lattice Hamiltonian can reveal transitions between topological phases. A kink in the mean width of the particle distribution signals the closing of the band gap, a prerequisite for a quantum phase transition between topolog...
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A search for optical bursts from the repeating fast radio burst FRB 121102
We present a search for optical bursts from the repeating fast radio burst FRB 121102 using simultaneous observations with the high-speed optical camera ULTRASPEC on the 2.4-m Thai National Telescope and radio observations with the 100-m Effelsberg Radio Telescope. A total of 13 radio bursts were detected, but we fou...
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de Haas-van Alphen measurement of the antiferromagnet URhIn$_5$
We report on the results of a de Haas-van Alphen (dHvA) measurement performed on the recently discovered antiferromagnet URhIn$_5$ ($T_N$ = 98 K), a 5\textit{f}-analogue of the well studied heavy fermion antiferromagnet CeRhIn$_5$. The Fermi surface is found to consist of four surfaces: a roughly spherical pocket $\b...
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Indoor Frame Recovery from Refined Line Segments
An important yet challenging problem in understanding indoor scene is recovering indoor frame structure from a monocular image. It is more difficult when occlusions and illumination vary, and object boundaries are weak. To overcome these difficulties, a new approach based on line segment refinement with two constrain...
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Fairly Allocating Contiguous Blocks of Indivisible Items
In this paper, we study the classic problem of fairly allocating indivisible items with the extra feature that the items lie on a line. Our goal is to find a fair allocation that is contiguous, meaning that the bundle of each agent forms a contiguous block on the line. While allocations satisfying the classical fairn...
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