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601
Regrasping by Fixtureless Fixturing
This paper presents a fixturing strategy for regrasping that does not require a physical fixture. To regrasp an object in a gripper, a robot pushes the object against external contact/s in the environment such that the external contact keeps the object stationary while the fingers slide over the object. We call this ...
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602
Subset Labeled LDA for Large-Scale Multi-Label Classification
Labeled Latent Dirichlet Allocation (LLDA) is an extension of the standard unsupervised Latent Dirichlet Allocation (LDA) algorithm, to address multi-label learning tasks. Previous work has shown it to perform in par with other state-of-the-art multi-label methods. Nonetheless, with increasing label sets sizes LLDA e...
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603
A Hybrid Approach to Video Source Identification
Multimedia Forensics allows to determine whether videos or images have been captured with the same device, and thus, eventually, by the same person. Currently, the most promising technology to achieve this task, exploits the unique traces left by the camera sensor into the visual content. Anyway, image and video sour...
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604
Asymptotics of ABC
We present an informal review of recent work on the asymptotics of Approximate Bayesian Computation (ABC). In particular we focus on how does the ABC posterior, or point estimates obtained by ABC, behave in the limit as we have more data? The results we review show that ABC can perform well in terms of point estimati...
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605
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity
We consider the problem of learning sparse polymatrix games from observations of strategic interactions. We show that a polynomial time method based on $\ell_{1,2}$-group regularized logistic regression recovers a game, whose Nash equilibria are the $\epsilon$-Nash equilibria of the game from which the data was gener...
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606
Superposition solutions to the extended KdV equation for water surface waves
The KdV equation can be derived in the shallow water limit of the Euler equations. Over the last few decades, this equation has been extended to include higher order effects. Although this equation has only one conservation law, exact periodic and solitonic solutions exist. Khare and Saxena \cite{KhSa,KhSa14,KhSa15} ...
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607
Boosting the Actor with Dual Critic
This paper proposes a new actor-critic-style algorithm called Dual Actor-Critic or Dual-AC. It is derived in a principled way from the Lagrangian dual form of the Bellman optimality equation, which can be viewed as a two-player game between the actor and a critic-like function, which is named as dual critic. Compared...
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608
Counting Dominating Sets of Graphs
Counting dominating sets in a graph $G$ is closely related to the neighborhood complex of $G$. We exploit this relation to prove that the number of dominating sets $d(G)$ of a graph is determined by the number of complete bipartite subgraphs of its complement. More precisely, we state the following. Let $G$ be a simp...
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609
High SNR Consistent Compressive Sensing
High signal to noise ratio (SNR) consistency of model selection criteria in linear regression models has attracted a lot of attention recently. However, most of the existing literature on high SNR consistency deals with model order selection. Further, the limited literature available on the high SNR consistency of su...
1
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0
1
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610
Communication Reducing Algorithms for Distributed Hierarchical N-Body Problems with Boundary Distributions
Reduction of communication and efficient partitioning are key issues for achieving scalability in hierarchical $N$-Body algorithms like FMM. In the present work, we propose four independent strategies to improve partitioning and reduce communication. First of all, we show that the conventional wisdom of using space-f...
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611
Traffic Surveillance Camera Calibration by 3D Model Bounding Box Alignment for Accurate Vehicle Speed Measurement
In this paper, we focus on fully automatic traffic surveillance camera calibration, which we use for speed measurement of passing vehicles. We improve over a recent state-of-the-art camera calibration method for traffic surveillance based on two detected vanishing points. More importantly, we propose a novel automati...
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612
Technical Report for Real-Time Certified Probabilistic Pedestrian Forecasting
The success of autonomous systems will depend upon their ability to safely navigate human-centric environments. This motivates the need for a real-time, probabilistic forecasting algorithm for pedestrians, cyclists, and other agents since these predictions will form a necessary step in assessing the risk of any actio...
1
0
1
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613
Distance Measure Machines
This paper presents a distance-based discriminative framework for learning with probability distributions. Instead of using kernel mean embeddings or generalized radial basis kernels, we introduce embeddings based on dissimilarity of distributions to some reference distributions denoted as templates. Our framework ex...
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614
DSBGK Method to Incorporate the CLL Reflection Model and to Simulate Gas Mixtures
Molecular reflections on usual wall surfaces can be statistically described by the Maxwell diffuse reflection model, which has been successfully applied in the DSBGK simulations. We develop the DSBGK algorithm to implement the Cercignani-Lampis-Lord (CLL) reflection model, which is widely applied to polished surfaces...
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615
Tropical formulae for summation over a part of SL(2, Z)
Let $f(a,b,c,d)=\sqrt{a^2+b^2}+\sqrt{c^2+d^2}-\sqrt{(a+c)^2+(b+d)^2}$, let $(a,b,c,d)$ stand for $a,b,c,d\in\mathbb Z_{\geq 0}$ such that $ad-bc=1$. Define \begin{equation} \label{eq_main} F(s) = \sum_{(a,b,c,d)} f(a,b,c,d)^s. \end{equation} In other words, we consider the sum of the powers of the triangle inequality...
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616
Efficient sampling of conditioned Markov jump processes
We consider the task of generating draws from a Markov jump process (MJP) between two time points at which the process is known. Resulting draws are typically termed bridges and the generation of such bridges plays a key role in simulation-based inference algorithms for MJPs. The problem is challenging due to the int...
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617
Holography and thermalization in optical pump-probe spectroscopy
Using holography, we model experiments in which a 2+1D strange metal is pumped by a laser pulse into a highly excited state, after which the time evolution of the optical conductivity is probed. We consider a finite-density state with mildly broken translation invariance and excite it by oscillating electric field pu...
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618
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discards a large part of training data, we show provable guarantees on the accuracy of the predictive mean/variance and its generalization abilit...
1
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619
Representing Hybrid Automata by Action Language Modulo Theories
Both hybrid automata and action languages are formalisms for describing the evolution of dynamic systems. This paper establishes a formal relationship between them. We show how to succinctly represent hybrid automata in an action language which in turn is defined as a high-level notation for answer set programming mo...
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620
An enthalpy-based multiple-relaxation-time lattice Boltzmann method for solid-liquid phase change heat transfer in metal foams
In this paper, an enthalpy-based multiple-relaxation-time (MRT) lattice Boltzmann (LB) method is developed for solid-liquid phase change heat transfer in metal foams under local thermal non-equilibrium (LTNE) condition. The enthalpy-based MRT-LB method consists of three different MRT-LB models: one for flow field bas...
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621
Birth of a subaqueous barchan dune
Barchan dunes are crescentic shape dunes with horns pointing downstream. The present paper reports the formation of subaqueous barchan dunes from initially conical heaps in a rectangular channel. Because the most unique feature of a barchan dune is its horns, we associate the timescale for the appearance of horns to ...
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622
Uncoupled isotonic regression via minimum Wasserstein deconvolution
Isotonic regression is a standard problem in shape-constrained estimation where the goal is to estimate an unknown nondecreasing regression function $f$ from independent pairs $(x_i, y_i)$ where $\mathbb{E}[y_i]=f(x_i), i=1, \ldots n$. While this problem is well understood both statistically and computationally, much...
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623
Failure of Smooth Pasting Principle and Nonexistence of Equilibrium Stopping Rules under Time-Inconsistency
This paper considers a time-inconsistent stopping problem in which the inconsistency arises from non-constant time preference rates. We show that the smooth pasting principle, the main approach that has been used to construct explicit solutions for conventional time-consistent optimal stopping problems, may fail unde...
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624
Perils of Zero-Interaction Security in the Internet of Things
The Internet of Things (IoT) demands authentication systems which can provide both security and usability. Recent research utilizes the rich sensing capabilities of smart devices to build security schemes operating without human interaction, such as zero-interaction pairing (ZIP) and zero-interaction authentication (...
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625
Coarse-grained simulation of auxetic, two-dimensional crystal dynamics
The increasing number of protein-based metamaterials demands reliable and efficient methods to study the physicochemical properties they may display. In this regard, we develop a simulation strategy based on Molecular Dynamics (MD) that addresses the geometric degrees of freedom of an auxetic two-dimensional protein ...
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626
Core2Vec: A core-preserving feature learning framework for networks
Recent advances in the field of network representation learning are mostly attributed to the application of the skip-gram model in the context of graphs. State-of-the-art analogues of skip-gram model in graphs define a notion of neighbourhood and aim to find the vector representation for a node, which maximizes the l...
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627
Predicting wind pressures around circular cylinders using machine learning techniques
Numerous studies have been carried out to measure wind pressures around circular cylinders since the early 20th century due to its engineering significance. Consequently, a large amount of wind pressure data sets have accumulated, which presents an excellent opportunity for using machine learning (ML) techniques to t...
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628
Randomly coloring simple hypergraphs with fewer colors
We study the problem of constructing a (near) uniform random proper $q$-coloring of a simple $k$-uniform hypergraph with $n$ vertices and maximum degree $\Delta$. (Proper in that no edge is mono-colored and simple in that two edges have maximum intersection of size one). We show that if $q\geq \max\{C_k\log n,500k^3\...
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629
Contributed Discussion to Uncertainty Quantification for the Horseshoe by Stéphanie van der Pas, Botond Szabó and Aad van der Vaart
We begin by introducing the main ideas of the paper under discussion. We discuss some interesting issues regarding adaptive component-wise credible intervals. We then briefly touch upon the concepts of self-similarity and excessive bias restriction. This is then followed by some comments on the extensive simulation s...
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630
Channel masking for multivariate time series shapelets
Time series shapelets are discriminative sub-sequences and their similarity to time series can be used for time series classification. Initial shapelet extraction algorithms searched shapelets by complete enumeration of all possible data sub-sequences. Research on shapelets for univariate time series proposed a mecha...
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0
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631
Spin mediated enhanced negative magnetoresistance in Ni80Fe20 and p-silicon bilayer
In this work, we present an experimental study of spin mediated enhanced negative magnetoresistance in Ni80Fe20 (50 nm)/p-Si (350 nm) bilayer. The resistance measurement shows a reduction of ~2.5% for the bilayer specimen as compared to 1.3% for Ni80Fe20 (50 nm) on oxide specimen for an out-of-plane applied magnetic ...
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632
On the Limitations of Representing Functions on Sets
Recent work on the representation of functions on sets has considered the use of summation in a latent space to enforce permutation invariance. In particular, it has been conjectured that the dimension of this latent space may remain fixed as the cardinality of the sets under consideration increases. However, we demo...
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633
Learning Models from Data with Measurement Error: Tackling Underreporting
Measurement error in observational datasets can lead to systematic bias in inferences based on these datasets. As studies based on observational data are increasingly used to inform decisions with real-world impact, it is critical that we develop a robust set of techniques for analyzing and adjusting for these biases...
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634
A simple introduction to Karmarkar's Algorithm for Linear Programming
An extremely simple, description of Karmarkar's algorithm with very few technical terms is given.
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635
Magneto-inductive Passive Relaying in Arbitrarily Arranged Networks
We consider a wireless sensor network that uses inductive near-field coupling for wireless powering or communication, or for both. The severely limited range of an inductively coupled source-destination pair can be improved using resonant relay devices, which are purely passive in nature. Utilization of such magneto-...
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636
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
Transfer operators such as the Perron--Frobenius or Koopman operator play an important role in the global analysis of complex dynamical systems. The eigenfunctions of these operators can be used to detect metastable sets, to project the dynamics onto the dominant slow processes, or to separate superimposed signals. W...
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637
Asymptotics of the bound state induced by $δ$-interaction supported on a weakly deformed plane
In this paper we consider the three-dimensional Schrödinger operator with a $\delta$-interaction of strength $\alpha > 0$ supported on an unbounded surface parametrized by the mapping $\mathbb{R}^2\ni x\mapsto (x,\beta f(x))$, where $\beta \in [0,\infty)$ and $f\colon \mathbb{R}^2\rightarrow\mathbb{R}$, $f\not\equiv ...
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638
Análise comparativa de pesquisas de origens e destinos: uma abordagem baseada em Redes Complexas
In this paper, a comparative study was conducted between complex networks representing origin and destination survey data. Similarities were found between the characteristics of the networks of Brazilian cities with networks of foreign cities. Power laws were found in the distributions of edge weights and this scale ...
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639
Inverse Kinematics for Control of Tensegrity Soft Robots: Existence and Optimality of Solutions
Tension-network (`tensegrity') robots encounter many control challenges as articulated soft robots, due to the structures' high-dimensional nonlinear dynamics. Control approaches have been developed which use the inverse kinematics of tensegrity structures, either for open-loop control or as equilibrium inputs for cl...
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640
Smallest eigenvalue density for regular or fixed-trace complex Wishart-Laguerre ensemble and entanglement in coupled kicked tops
The statistical behaviour of the smallest eigenvalue has important implications for systems which can be modeled using a Wishart-Laguerre ensemble, the regular one or the fixed trace one. For example, the density of the smallest eigenvalue of the Wishart-Laguerre ensemble plays a crucial role in characterizing multip...
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641
Development of probabilistic dam breach model using Bayesian inference
Dam breach models are commonly used to predict outflow hydrographs of potentially failing dams and are key ingredients for evaluating flood risk. In this paper a new dam breach modeling framework is introduced that shall improve the reliability of hydrograph predictions of homogeneous earthen embankment dams. Strivin...
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642
Large Magellanic Cloud Near-Infrared Synoptic Survey. V. Period-Luminosity Relations of Miras
We study the near-infrared properties of 690 Mira candidates in the central region of the Large Magellanic Cloud, based on time-series observations at JHKs. We use densely-sampled I-band observations from the OGLE project to generate template light curves in the near infrared and derive robust mean magnitudes at thos...
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643
One-Step Time-Dependent Future Video Frame Prediction with a Convolutional Encoder-Decoder Neural Network
There is an inherent need for autonomous cars, drones, and other robots to have a notion of how their environment behaves and to anticipate changes in the near future. In this work, we focus on anticipating future appearance given the current frame of a video. Existing work focuses on either predicting the future app...
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644
Deep Multi-User Reinforcement Learning for Distributed Dynamic Spectrum Access
We consider the problem of dynamic spectrum access for network utility maximization in multichannel wireless networks. The shared bandwidth is divided into K orthogonal channels. In the beginning of each time slot, each user selects a channel and transmits a packet with a certain transmission probability. After each ...
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645
Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming
We design a new myopic strategy for a wide class of sequential design of experiment (DOE) problems, where the goal is to collect data in order to to fulfil a certain problem specific goal. Our approach, Myopic Posterior Sampling (MPS), is inspired by the classical posterior (Thompson) sampling algorithm for multi-arm...
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646
Data-Driven Sparse Structure Selection for Deep Neural Networks
Deep convolutional neural networks have liberated its extraordinary power on various tasks. However, it is still very challenging to deploy state-of-the-art models into real-world applications due to their high computational complexity. How can we design a compact and effective network without massive experiments and...
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647
Scaling laws and bounds for the turbulent G.O. Roberts dynamo
Numerical simulations of the G.O. Roberts dynamo are presented. Dynamos both with and without a significant mean field are obtained. Exact bounds are derived for the total energy which conform with the Kolmogorov phenomenology of turbulence. Best fits to numerical data show the same functional dependences as the ineq...
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648
Control Strategies for the Fokker-Planck Equation
Using a projection-based decoupling of the Fokker-Planck equation, control strategies that allow to speed up the convergence to the stationary distribution are investigated. By means of an operator theoretic framework for a bilinear control system, two different feedback control laws are proposed. Projected Riccati a...
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649
On Popov's formula involving the Von Mangoldt function
We offer a generalization of a formula of Popov involving the Von Mangoldt function. Some commentary on its relation to other results in analytic number theory is mentioned as well as an analogue involving the m$\ddot{o}$bius function.
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650
On fibering compact manifold over the circle
In this paper, we show that any compact manifold that carries a SL(n;R)-foliation is fibered on the circle S^1.
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651
Phonon-Induced Topological Transition to a Type-II Weyl Semimetal
Given the importance of crystal symmetry for the emergence of topological quantum states, we have studied, as exemplified in NbNiTe2, the interplay of crystal symmetry, atomic displacements (lattice vibration), band degeneracy, and band topology. For NbNiTe2 structure in space group 53 (Pmna) - having an inversion ce...
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652
Multi-hop assortativities for networks classification
Several social, medical, engineering and biological challenges rely on discovering the functionality of networks from their structure and node metadata, when it is available. For example, in chemoinformatics one might want to detect whether a molecule is toxic based on structure and atomic types, or discover the rese...
1
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0
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653
A Bayesian Nonparametrics based Robust Particle Filter Algorithm
This paper is concerned with the online estimation of a nonlinear dynamic system from a series of noisy measurements. The focus is on cases wherein outliers are present in-between normal noises. We assume that the outliers follow an unknown generating mechanism which deviates from that of normal noises, and then mode...
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654
Highly accurate model for prediction of lung nodule malignancy with CT scans
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a sy...
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655
Rotating Rayleigh-Taylor turbulence
The turbulent Rayleigh--Taylor system in a rotating reference frame is investigated by direct numerical simulations within the Oberbeck-Boussinesq approximation. On the basis of theoretical arguments, supported by our simulations, we show that the Rossby number decreases in time, and therefore the Coriolis force beco...
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656
Evolutionary dynamics of N-person Hawk-Dove games
In the animal world, the competition between individuals belonging to different species for a resource often requires the cooperation of several individuals in groups. This paper proposes a generalization of the Hawk-Dove Game for an arbitrary number of agents: the N-person Hawk-Dove Game. In this model, doves exempl...
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657
A global model for predicting the arrival of imported dengue infections
With approximately half of the world's population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue's rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent future outbreaks an...
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658
Contextually Customized Video Summaries via Natural Language
The best summary of a long video differs among different people due to its highly subjective nature. Even for the same person, the best summary may change with time or mood. In this paper, we introduce the task of generating customized video summaries through simple text. First, we train a deep architecture to effect...
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659
Observation of surface plasmon polaritons in 2D electron gas of surface electron accumulation in InN nanostructures
Recently, heavily doped semiconductors are emerging as an alternate for low loss plasmonic materials. InN, belonging to the group III nitrides, possesses the unique property of surface electron accumulation (SEA) which provides two dimensional electron gas (2DEG) system. In this report, we demonstrated the surface pl...
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660
Asymmetric Mach-Zehnder atom interferometers
It is shown that using beam splitters with non-equal wave vectors results in a new recoil diagram which is qualitatively different from the well-known diagram associated with the Mach-Zehnder atom interferometer. We predict a new asymmetric Mach-Zehnder atom interferometer (AMZAI) and study it when one uses a Raman b...
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661
Partial Information Stochastic Differential Games for Backward Stochastic Systems Driven By Lévy Processes
In this paper, we consider a partial information two-person zero-sum stochastic differential game problem where the system is governed by a backward stochastic differential equation driven by Teugels martingales associated with a Lévy process and an independent Brownian motion. One sufficient (a verification theorem)...
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662
Inter-Session Modeling for Session-Based Recommendation
In recent years, research has been done on applying Recurrent Neural Networks (RNNs) as recommender systems. Results have been promising, especially in the session-based setting where RNNs have been shown to outperform state-of-the-art models. In many of these experiments, the RNN could potentially improve the recomm...
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663
Multiscale Modeling of Shock Wave Localization in Porous Energetic Material
Shock wave interactions with defects, such as pores, are known to play a key role in the chemical initiation of energetic materials. The shock response of hexanitrostilbene is studied through a combination of large scale reactive molecular dynamics and mesoscale hydrodynamic simulations. In order to extend our simula...
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664
Cryptoasset Factor Models
We propose factor models for the cross-section of daily cryptoasset returns and provide source code for data downloads, computing risk factors and backtesting them out-of-sample. In "cryptoassets" we include all cryptocurrencies and a host of various other digital assets (coins and tokens) for which exchange market d...
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665
Multi-dimensional Graph Fourier Transform
Many signals on Cartesian product graphs appear in the real world, such as digital images, sensor observation time series, and movie ratings on Netflix. These signals are "multi-dimensional" and have directional characteristics along each factor graph. However, the existing graph Fourier transform does not distinguis...
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666
Criteria for the Application of Double Exponential Transformation
The double exponential formula was introduced for calculating definite integrals with singular point oscillation functions and Fourier-integrals. The double exponential transformation is not only useful for numerical computations but it is also used in different methods of Sinc theory. In this paper we use double exp...
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667
Ultra-high strain in epitaxial silicon carbide nanostructures utilizing residual stress amplification
Strain engineering has attracted great attention, particularly for epitaxial films grown on a different substrate. Residual strains of SiC have been widely employed to form ultra-high frequency and high Q factor resonators. However, to date the highest residual strain of SiC was reported to be limited to approximatel...
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668
The Diverse Club: The Integrative Core of Complex Networks
A complex system can be represented and analyzed as a network, where nodes represent the units of the network and edges represent connections between those units. For example, a brain network represents neurons as nodes and axons between neurons as edges. In many networks, some nodes have a disproportionately high nu...
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669
Bayesian Semisupervised Learning with Deep Generative Models
Neural network based generative models with discriminative components are a powerful approach for semi-supervised learning. However, these techniques a) cannot account for model uncertainty in the estimation of the model's discriminative component and b) lack flexibility to capture complex stochastic patterns in the ...
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670
Robust Detection of Covariate-Treatment Interactions in Clinical Trials
Detection of interactions between treatment effects and patient descriptors in clinical trials is critical for optimizing the drug development process. The increasing volume of data accumulated in clinical trials provides a unique opportunity to discover new biomarkers and further the goal of personalized medicine, b...
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671
The Future of RICH Detectors through the Light of the LHCb RICH
The limitations in performance of the present RICH system in the LHCb experiment are given by the natural chromatic dispersion of the gaseous Cherenkov radiator, the aberrations of the optical system and the pixel size of the photon detectors. Moreover, the overall PID performance can be affected by high detector occ...
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672
Stability of Valuations: Higher Rational Rank
Given a klt singularity $x\in (X, D)$, we show that a quasi-monomial valuation $v$ with a finitely generated associated graded ring is the minimizer of the normalized volume function $\widehat{\rm vol}_{(X,D),x}$, if and only if $v$ induces a degeneration to a K-semistable log Fano cone singularity. Moreover, such a ...
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673
Higgs mode and its decay in a two dimensional antiferromagnet
Condensed-matter analogs of the Higgs boson in particle physics allow insights into its behavior in different symmetries and dimensionalities. Evidence for the Higgs mode has been reported in a number of different settings, including ultracold atomic gases, disordered superconductors, and dimerized quantum magnets. H...
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674
Robust and Efficient Boosting Method using the Conditional Risk
Well-known for its simplicity and effectiveness in classification, AdaBoost, however, suffers from overfitting when class-conditional distributions have significant overlap. Moreover, it is very sensitive to noise that appears in the labels. This article tackles the above limitations simultaneously via optimizing a m...
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675
High Dimensional Robust Estimation of Sparse Models via Trimmed Hard Thresholding
We study the problem of sparsity constrained $M$-estimation with arbitrary corruptions to both {\em explanatory and response} variables in the high-dimensional regime, where the number of variables $d$ is larger than the sample size $n$. Our main contribution is a highly efficient gradient-based optimization algorith...
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676
Stop talking to me -- a communication-avoiding ADER-DG realisation
We present a communication- and data-sensitive formulation of ADER-DG for hyperbolic differential equation systems. Sensitive here has multiple flavours: First, the formulation reduces the persistent memory footprint. This reduces pressure on the memory subsystem. Second, the formulation realises the underlying predi...
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677
The effect of prior probabilities on quantification and propagation of imprecise probabilities resulting from small datasets
This paper outlines a methodology for Bayesian multimodel uncertainty quantification (UQ) and propagation and presents an investigation into the effect of prior probabilities on the resulting uncertainties. The UQ methodology is adapted from the information-theoretic method previously presented by the authors (Zhang ...
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678
Hierarchical loss for classification
Failing to distinguish between a sheepdog and a skyscraper should be worse and penalized more than failing to distinguish between a sheepdog and a poodle; after all, sheepdogs and poodles are both breeds of dogs. However, existing metrics of failure (so-called "loss" or "win") used in textual or visual classification...
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679
An efficient data structure for counting all linear extensions of a poset, calculating its jump number, and the likes
Achieving the goals in the title (and others) relies on a cardinality-wise scanning of the ideals of the poset. Specifically, the relevant numbers attached to the k+1 element ideals are inferred from the corresponding numbers of the k-element (order) ideals. Crucial in all of this is a compressed representation (usin...
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680
Perception-in-the-Loop Adversarial Examples
We present a scalable, black box, perception-in-the-loop technique to find adversarial examples for deep neural network classifiers. Black box means that our procedure only has input-output access to the classifier, and not to the internal structure, parameters, or intermediate confidence values. Perception-in-the-lo...
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681
Deep Fluids: A Generative Network for Parameterized Fluid Simulations
This paper presents a novel generative model to synthesize fluid simulations from a set of reduced parameters. A convolutional neural network is trained on a collection of discrete, parameterizable fluid simulation velocity fields. Due to the capability of deep learning architectures to learn representative features ...
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682
Bias Reduction in Instrumental Variable Estimation through First-Stage Shrinkage
The two-stage least-squares (2SLS) estimator is known to be biased when its first-stage fit is poor. I show that better first-stage prediction can alleviate this bias. In a two-stage linear regression model with Normal noise, I consider shrinkage in the estimation of the first-stage instrumental variable coefficients...
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683
An Unsupervised Learning Classifier with Competitive Error Performance
An unsupervised learning classification model is described. It achieves classification error probability competitive with that of popular supervised learning classifiers such as SVM or kNN. The model is based on the incremental execution of small step shift and rotation operations upon selected discriminative hyperpl...
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684
Exploring the predictability of range-based volatility estimators using RNNs
We investigate the predictability of several range-based stock volatility estimators, and compare them to the standard close-to-close estimator which is most commonly acknowledged as the volatility. The patterns of volatility changes are analyzed using LSTM recurrent neural networks, which are a state of the art meth...
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685
Mean squared displacement and sinuosity of three-dimensional random search movements
Correlated random walks (CRW) have been used for a long time as a null model for animal's random search movement in two dimensions (2D). An increasing number of studies focus on animals' movement in three dimensions (3D), but the key properties of CRW, such as the way the mean squared displacement is related to the p...
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686
Context-Aware Pedestrian Motion Prediction In Urban Intersections
This paper presents a novel context-based approach for pedestrian motion prediction in crowded, urban intersections, with the additional flexibility of prediction in similar, but new, environments. Previously, Chen et. al. combined Markovian-based and clustering-based approaches to learn motion primitives in a grid-b...
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687
EnergyNet: Energy-based Adaptive Structural Learning of Artificial Neural Network Architectures
We present E NERGY N ET , a new framework for analyzing and building artificial neural network architectures. Our approach adaptively learns the structure of the networks in an unsupervised manner. The methodology is based upon the theoretical guarantees of the energy function of restricted Boltzmann machines (RBM) o...
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688
Local Algorithms for Hierarchical Dense Subgraph Discovery
Finding the dense regions of a graph and relations among them is a fundamental problem in network analysis. Core and truss decompositions reveal dense subgraphs with hierarchical relations. The incremental nature of algorithms for computing these decompositions and the need for global information at each step of the ...
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689
Robust Gesture-Based Communication for Underwater Human-Robot Interaction in the context of Search and Rescue Diver Missions
We propose a robust gesture-based communication pipeline for divers to instruct an Autonomous Underwater Vehicle (AUV) to assist them in performing high-risk tasks and helping in case of emergency. A gesture communication language (CADDIAN) is developed, based on consolidated and standardized diver gestures, includin...
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690
High-$T_\textrm {C}$ superconductivity in Cs$_3$C$_{60}$ compounds governed by local Cs-C$_{60}$ Coulomb interactions
Unique among alkali-doped $\textit {A}$$_3$C$_{60}$ fullerene compounds, the A15 and fcc forms of Cs$_3$C$_{60}$ exhibit superconducting states varying under hydrostatic pressure with highest transition temperatures at $T_\textrm {C}$$^\textrm {meas}$ = 38.3 and 35.2 K, respectively. Herein it is argued that these tw...
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691
Analysis and mitigation of interface losses in trenched superconducting coplanar waveguide resonators
Improving the performance of superconducting qubits and resonators generally results from a combination of materials and fabrication process improvements and design modifications that reduce device sensitivity to residual losses. One instance of this approach is to use trenching into the device substrate in combinati...
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692
Recent Operation of the FNAL Magnetron $H^{-}$ Ion Source
This paper will detail changes in the operational paradigm of the Fermi National Accelerator Laboratory (FNAL) magnetron $H^{-}$ ion source due to upgrades in the accelerator system. Prior to November of 2012 the $H^{-}$ ions for High Energy Physics (HEP) experiments were extracted at ~18 keV vertically downward into...
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693
A Ball Breaking Away from a Fluid
We consider the withdrawal of a ball from a fluid reservoir to understand the longevity of the connection between that ball and the fluid it breaks away from, at intermediate Reynolds numbers. Scaling arguments based on the processes observed as the ball interacts with the fluid surface were applied to the `pinch-off...
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694
Unveiling the internal entanglement structure of the Kondo singlet
We disentangle all the individual degrees of freedom in the quantum impurity problem to deconstruct the Kondo singlet, both in real and energy space, by studying the contribution of each individual free electron eigenstate. This is a problem of two spins coupled to a bath, where the bath is formed by the remaining co...
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695
A parallel orbital-updating based plane-wave basis method for electronic structure calculations
Motivated by the recently proposed parallel orbital-updating approach in real space method, we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating ...
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696
Dynamics of the multi-soliton waves in the sine-Gordon model with two identical point impurities
The particular type of four-kink multi-solitons (or quadrons) adiabatic dynamics of the sine-Gordon equation in a model with two identical point attracting impurities has been studied. This model can be used for describing magnetization localized waves in multilayer ferromagnet. The quadrons structure and properties ...
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697
Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder
Estimates of the Hubble constant, $H_0$, from the distance ladder and the cosmic microwave background (CMB) differ at the $\sim$3-$\sigma$ level, indicating a potential issue with the standard $\Lambda$CDM cosmology. Interpreting this tension correctly requires a model comparison calculation depending on not only the...
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698
Multi-User Multi-Armed Bandits for Uncoordinated Spectrum Access
A multi-user multi-armed bandit (MAB) framework is used to develop algorithms for uncoordinated spectrum access. The number of users is assumed to be unknown to each user. A stochastic setting is first considered, where the rewards on a channel are the same for each user. In contrast to prior work, it is assumed that...
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699
A Comparative Analysis of Contact Models in Trajectory Optimization for Manipulation
In this paper, we analyze the effects of contact models on contact-implicit trajectory optimization for manipulation. We consider three different approaches: (1) a contact model that is based on complementarity constraints, (2) a smooth contact model, and our proposed method (3) a variable smooth contact model. We co...
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700
Computationally Efficient Measures of Internal Neuron Importance
The challenge of assigning importance to individual neurons in a network is of interest when interpreting deep learning models. In recent work, Dhamdhere et al. proposed Total Conductance, a "natural refinement of Integrated Gradients" for attributing importance to internal neurons. Unfortunately, the authors found t...
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