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J0906+6930: a radio-loud quasar in the early Universe
Radio-loud high-redshift quasars (HRQs), although only a few of them are known to date, are crucial for the studies of the growth of supermassive black holes (SMBHs) and the evolution of active galactic nuclei (AGN) at early cosmological epochs. Radio jets offer direct evidence of SMBHs, and their radio structures ca...
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Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields
This work investigates the training of conditional random fields (CRFs) via the stochastic dual coordinate ascent (SDCA) algorithm of Shalev-Shwartz and Zhang (2016). SDCA enjoys a linear convergence rate and a strong empirical performance for binary classification problems. However, it has never been used to train C...
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Accelerating Innovation Through Analogy Mining
The availability of large idea repositories (e.g., the U.S. patent database) could significantly accelerate innovation and discovery by providing people with inspiration from solutions to analogous problems. However, finding useful analogies in these large, messy, real-world repositories remains a persistent challeng...
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$η$-Ricci solitons in $(\varepsilon)$-almost paracontact metric manifolds
The object of this paper is to study $\eta$-Ricci solitons on $(\varepsilon)$-almost paracontact metric manifolds. We investigate $\eta$-Ricci solitons in the case when its potential vector field is exactly the characteristic vector field $\xi$ of the $(\varepsilon)$-almost paracontact metric manifold and when the po...
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Entropy facilitated active transport
We show how active transport of ions can be interpreted as an entropy facilitated process. In this interpretation, the pore geometry through which substrates are transported can give rise to a driving force. This gives a direct link between the geometry and the changes in Gibbs energy required. Quantifying the size o...
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Consistency of the Predicative Calculus of Cumulative Inductive Constructions (pCuIC)
In order to avoid well-know paradoxes associated with self-referential definitions, higher-order dependent type theories stratify the theory using a countably infinite hierarchy of universes (also known as sorts), Type$_0$ : Type$_1$ : $\cdots$ . Such type systems are called cumulative if for any type $A$ we have tha...
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Private Information Retrieval from MDS Coded Data with Colluding Servers: Settling a Conjecture by Freij-Hollanti et al.
A $(K, N, T, K_c)$ instance of the MDS-TPIR problem is comprised of $K$ messages and $N$ distributed servers. Each message is separately encoded through a $(K_c, N)$ MDS storage code. A user wishes to retrieve one message, as efficiently as possible, while revealing no information about the desired message index to a...
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ADaPTION: Toolbox and Benchmark for Training Convolutional Neural Networks with Reduced Numerical Precision Weights and Activation
Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) are useful for many practical tasks in machine learning. Synaptic weights, as well as neuron activation functions within the deep network are typically stored with high-precision formats, e.g. 32 bit floating point. However, since storage capacity i...
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Graph Attention Networks
We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their approximations. By stacking layers in which nodes are able to attend over th...
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Social Media Would Not Lie: Prediction of the 2016 Taiwan Election via Online Heterogeneous Data
The prevalence of online media has attracted researchers from various domains to explore human behavior and make interesting predictions. In this research, we leverage heterogeneous social media data collected from various online platforms to predict Taiwan's 2016 presidential election. In contrast to most existing r...
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The stratified micro-randomized trial design: sample size considerations for testing nested causal effects of time-varying treatments
Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Increasingly the delivery of these treatments is triggered by predictions of risk or engagement which may hav...
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Multiplicative Convolution of Real Asymmetric and Real Antisymmetric Matrices
The singular values of products of standard complex Gaussian random matrices, or sub-blocks of Haar distributed unitary matrices, have the property that their probability distribution has an explicit, structured form referred to as a polynomial ensemble. It is furthermore the case that the corresponding bi-orthogonal...
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An approach to Griffiths conjecture
The Griffiths conjecture asserts that every ample vector bundle $E$ over a compact complex manifold $S$ admits a hermitian metric with positive curvature in the sense of Griffiths. In this article we give a sufficient condition for a positive hermitian metric on $\mathcal{O}_{\mathbb{P}(E^*)}(1)$ to induce a Griffith...
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On Detecting Adversarial Perturbations
Machine learning and deep learning in particular has advanced tremendously on perceptual tasks in recent years. However, it remains vulnerable against adversarial perturbations of the input that have been crafted specifically to fool the system while being quasi-imperceptible to a human. In this work, we propose to a...
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It's Time to Consider "Time" when Evaluating Recommender-System Algorithms [Proposal]
In this position paper, we question the current practice of calculating evaluation metrics for recommender systems as single numbers (e.g. precision p=.28 or mean absolute error MAE = 1.21). We argue that single numbers express only average effectiveness over a usually rather long period (e.g. a year or even longer),...
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Anomalous metals -- failed superconductors
The observation of metallic ground states in a variety of two-dimensional electronic systems poses a fundamental challenge for the theory of electron fluids. Here, we analyze evidence for the existence of a regime, which we call the "anomalous metal regime," in diverse 2D superconducting systems driven through a quan...
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Energy Optimization of Automatic Hybrid Sailboat
Autonomous Surface Vehicles (ASVs) provide an effective way to actualize applications such as environment monitoring, search and rescue, and scientific researches. However, the conventional ASVs depends overly on the stored energy. Hybrid Sailboat, mainly powered by the wind, can solve this problem by using an auxili...
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Estimating the Operating Characteristics of Ensemble Methods
In this paper we present a technique for using the bootstrap to estimate the operating characteristics and their variability for certain types of ensemble methods. Bootstrapping a model can require a huge amount of work if the training data set is large. Fortunately in many cases the technique lets us determine the e...
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Plasma turbulence at ion scales: a comparison between PIC and Eulerian hybrid-kinetic approaches
Kinetic-range turbulence in magnetized plasmas and, in particular, in the context of solar-wind turbulence has been extensively investigated over the past decades via numerical simulations. Among others, one of the widely adopted reduced plasma model is the so-called hybrid-kinetic model, where the ions are fully kin...
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Computational determination of the largest lattice polytope diameter
A lattice (d, k)-polytope is the convex hull of a set of points in dimension d whose coordinates are integers between 0 and k. Let {\delta}(d, k) be the largest diameter over all lattice (d, k)-polytopes. We develop a computational framework to determine {\delta}(d, k) for small instances. We show that {\delta}(3, 4)...
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A high resolution ion microscope for cold atoms
We report on an ion-optical system that serves as a microscope for ultracold ground state and Rydberg atoms. The system is designed to achieve a magnification of up to 1000 and a spatial resolution in the 100 nm range, thereby surpassing many standard imaging techniques for cold atoms. The microscope consists of four...
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Lock-Free Parallel Perceptron for Graph-based Dependency Parsing
Dependency parsing is an important NLP task. A popular approach for dependency parsing is structured perceptron. Still, graph-based dependency parsing has the time complexity of $O(n^3)$, and it suffers from slow training. To deal with this problem, we propose a parallel algorithm called parallel perceptron. The para...
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Finite groups with systems of $K$-$\frak{F}$-subnormal subgroups
Let $\frak {F}$ be a class of group. A subgroup $A$ of a finite group $G$ is said to be $K$-$\mathfrak{F}$-subnormal in $G$ if there is a subgroup chain $$A=A_{0} \leq A_{1} \leq \cdots \leq A_{n}=G$$ such that either $A_{i-1} \trianglelefteq A_{i}$ or $A_{i}/(A_{i-1})_{A_{i}} \in \mathfrak{F}$ for all $i=1, \ldots ,...
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Actions Speak Louder Than Goals: Valuing Player Actions in Soccer
Assessing the impact of the individual actions performed by soccer players during games is a crucial aspect of the player recruitment process. Unfortunately, most traditional metrics fall short in addressing this task as they either focus on rare events like shots and goals alone or fail to account for the context in...
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Partitioning the Outburst Energy of a Low Eddington Accretion Rate AGN at the Center of an Elliptical Galaxy: the Recent 12 Myr History of the Supermassive Black Hole in M87
M87, the active galaxy at the center of the Virgo cluster, is ideal for studying the interaction of a supermassive black hole (SMBH) with a hot, gas-rich environment. A deep Chandra observation of M87 exhibits an approximately circular shock front (13 kpc radius, in projection) driven by the expansion of the central ...
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On the missing link between pressure drop, viscous dissipation, and the turbulent energy spectrum
After decades of experimental, theoretical, and numerical research in fluid dynamics, many aspects of turbulence remain poorly understood. The main reason for this is often attributed to the multiscale nature of turbulent flows, which poses a formidable challenge. There are, however, properties of these flows whose r...
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Discrete Local Induction Equation
The local induction equation, or the binormal flow on space curves is a well-known model of deformation of space curves as it describes the dynamics of vortex filaments, and the complex curvature is governed by the nonlinear Schrödinger equation. In this paper, we present its discrete analogue, namely, a model of def...
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A sharp lower bound for the lifespan of small solutions to the Schrödinger equation with a subcritical power nonlinearity
Let $T_{\epsilon}$ be the lifespan for the solution to the Schrödinger equation on $\mathbb{R}^d$ with a power nonlinearity $\lambda |u|^{2\theta/d}u$ ($\lambda \in \mathbb{C}$, $0<\theta<1$) and the initial data in the form $\epsilon \varphi(x)$. We provide a sharp lower bound estimate for $T_{\epsilon}$ as $\epsilo...
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State Space Reduction for Reachability Graph of CSM Automata
Classical CTL temporal logics are built over systems with interleaving model concurrency. Many attempts are made to fight a state space explosion problem (for instance, compositional model checking). There are some methods of reduction of a state space based on independence of actions. However, in CSM model, which is...
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Permission Inference for Array Programs
Information about the memory locations accessed by a program is, for instance, required for program parallelisation and program verification. Existing inference techniques for this information provide only partial solutions for the important class of array-manipulating programs. In this paper, we present a static ana...
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Generating Query Suggestions to Support Task-Based Search
We address the problem of generating query suggestions to support users in completing their underlying tasks (which motivated them to search in the first place). Given an initial query, these query suggestions should provide a coverage of possible subtasks the user might be looking for. We propose a probabilistic mod...
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Application of Spin-Exchange Relaxation-Free Magnetometry to the Cosmic Axion Spin Precession Experiment
The Cosmic Axion Spin Precession Experiment (CASPEr) seeks to measure oscillating torques on nuclear spins caused by axion or axion-like-particle (ALP) dark matter via nuclear magnetic resonance (NMR) techniques. A sample spin-polarized along a leading magnetic field experiences a resonance when the Larmor frequency ...
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Symmetry and the Geometric Phase in Ultracold Hydrogen-Exchange Reactions
Quantum reactive scattering calculations are reported for the ultracold hydrogen-exchange reaction and its non-reactive atom-exchange isotopic counterparts, proceeding from excited rotational states. It is shown that while the geometric phase (GP) does not necessarily control the reaction to all final states one can ...
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Characterization and Photometric Performance of the Hyper Suprime-Cam Software Pipeline
The Subaru Strategic Program (SSP) is an ambitious multi-band survey using the Hyper Suprime-Cam (HSC) on the Subaru telescope. The Wide layer of the SSP is both wide and deep, reaching a detection limit of i~26.0 mag. At these depths, it is challenging to achieve accurate, unbiased, and consistent photometry across ...
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Information Geometry Approach to Parameter Estimation in Hidden Markov Models
We consider the estimation of hidden Markovian process by using information geometry with respect to transition matrices. We consider the case when we use only the histogram of $k$-memory data. Firstly, we focus on a partial observation model with Markovian process and we show that the asymptotic estimation error of ...
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Parallel transport in principal 2-bundles
A nice differential-geometric framework for (non-abelian) higher gauge theory is provided by principal 2-bundles, i.e. categorified principal bundles. Their total spaces are Lie groupoids, local trivializations are kinds of Morita equivalences, and connections are Lie-2-algebra-valued 1-forms. In this article, we con...
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Gotta Learn Fast: A New Benchmark for Generalization in RL
In this report, we present a new reinforcement learning (RL) benchmark based on the Sonic the Hedgehog (TM) video game franchise. This benchmark is intended to measure the performance of transfer learning and few-shot learning algorithms in the RL domain. We also present and evaluate some baseline algorithms on the n...
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Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit
Observations of astrophysical objects such as galaxies are limited by various sources of random and systematic noise from the sky background, the optical system of the telescope and the detector used to record the data. Conventional deconvolution techniques are limited in their ability to recover features in imaging ...
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Trends in European flood risk over the past 150 years
Flood risk changes in time and is influenced by both natural and socio-economic trends and interactions. In Europe, previous studies of historical flood losses corrected for demographic and economic growth ("normalized") have been limited in temporal and spatial extent, leading to an incomplete representation in tren...
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Kinetic Trans-assembly of DNA Nanostructures
The central dogma of molecular biology is the principal framework for understanding how nucleic acid information is propagated and used by living systems to create complex biomolecules. Here, by integrating the structural and dynamic paradigms of DNA nanotechnology, we present a rationally designed synthetic platform...
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Synthesis and analysis in total variation regularization
We generalize the bridge between analysis and synthesis estimators by Elad, Milanfar and Rubinstein (2007) to rank deficient cases. This is a starting point for the study of the connection between analysis and synthesis for total variation regularized estimators. In particular, the case of first order total variation...
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The Leray transform: factorization, dual $CR$ structures and model hypersurfaces in $\mathbb{C}\mathbb{P}^2$
We compute the exact norms of the Leray transforms for a family $\mathcal{S}_{\beta}$ of unbounded hypersurfaces in two complex dimensions. The $\mathcal{S}_{\beta}$ generalize the Heisenberg group, and provide local projective approximations to any smooth, strongly $\mathbb{C}$-convex hypersurface $\mathcal{S}_{\bet...
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A Fast Quantum-safe Asymmetric Cryptosystem Using Extra Superincreasing Sequences
This paper gives the definitions of an extra superincreasing sequence and an anomalous subset sum, and proposes a fast quantum-safe asymmetric cryptosystem called JUOAN2. The new cryptosystem is based on an additive multivariate permutation problem (AMPP) and an anomalous subset sum problem (ASSP) which parallel a mu...
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Knowledge Transfer for Melanoma Screening with Deep Learning
Knowledge transfer impacts the performance of deep learning -- the state of the art for image classification tasks, including automated melanoma screening. Deep learning's greed for large amounts of training data poses a challenge for medical tasks, which we can alleviate by recycling knowledge from models trained on...
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Large odd order character sums and improvements of the Pólya-Vinogradov inequality
For a primitive Dirichlet character $\chi$ modulo $q$, we define $M(\chi)=\max_{t } |\sum_{n \leq t} \chi(n)|$. In this paper, we study this quantity for characters of a fixed odd order $g\geq 3$. Our main result provides a further improvement of the classical Pólya-Vinogradov inequality in this case. More specifical...
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Estimation under group actions: recovering orbits from invariants
Motivated by geometric problems in signal processing, computer vision, and structural biology, we study a class of orbit recovery problems where we observe very noisy copies of an unknown signal, each acted upon by a random element of some group (such as Z/p or SO(3)). The goal is to recover the orbit of the signal u...
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Crystal field excitations from $\mathrm{Yb^{3+}}$ ions at defective sites in highly stuffed $\rm Yb_2Ti_2O_7$
The pyrochlore magnet $\rm Yb_2Ti_2O_7$ has been proposed as a quantum spin ice candidate, a spin liquid state expected to display emergent quantum electrodynamics with gauge photons among its elementary excitations. However, $\rm Yb_2Ti_2O_7$'s ground state is known to be very sensitive to its precise stoichiometry....
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HOUDINI: Lifelong Learning as Program Synthesis
We present a neurosymbolic framework for the lifelong learning of algorithmic tasks that mix perception and procedural reasoning. Reusing high-level concepts across domains and learning complex procedures are key challenges in lifelong learning. We show that a program synthesis approach that combines gradient descent...
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Detecting Adversarial Examples via Key-based Network
Though deep neural networks have achieved state-of-the-art performance in visual classification, recent studies have shown that they are all vulnerable to the attack of adversarial examples. Small and often imperceptible perturbations to the input images are sufficient to fool the most powerful deep neural networks. ...
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Guessing Attacks on Distributed-Storage Systems
The secrecy of a distributed-storage system for passwords is studied. The encoder, Alice, observes a length-n password and describes it using two hints, which she stores in different locations. The legitimate receiver, Bob, observes both hints. In one scenario the requirement is that the expected number of guesses it...
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Numerical analysis of nonlocal fracture models in Hölder space
In this work, we calculate the convergence rate of the finite difference approximation for a class of nonlocal fracture models. We consider two point force interactions characterized by a double well potential. We show the existence of a evolving displacement field in Hölder space with Hölder exponent $\gamma \in (0,...
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Iterative Collaborative Filtering for Sparse Matrix Estimation
The sparse matrix estimation problem consists of estimating the distribution of an $n\times n$ matrix $Y$, from a sparsely observed single instance of this matrix where the entries of $Y$ are independent random variables. This captures a wide array of problems; special instances include matrix completion in the conte...
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Parameter Estimation in Finite Mixture Models by Regularized Optimal Transport: A Unified Framework for Hard and Soft Clustering
In this short paper, we formulate parameter estimation for finite mixture models in the context of discrete optimal transportation with convex regularization. The proposed framework unifies hard and soft clustering methods for general mixture models. It also generalizes the celebrated $k$\nobreakdash-means and expect...
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Robust parameter determination in epidemic models with analytical descriptions of uncertainties
Compartmental equations are primary tools in disease spreading studies. Their predictions are accurate for large populations but disagree with empirical and simulated data for finite populations, where uncertainties become a relevant factor. Starting from the agent-based approach, we investigate the role of uncertain...
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Direct observation of domain wall surface tension by deflating or inflating a magnetic bubble
The surface energy of a magnetic Domain Wall (DW) strongly affects its static and dynamic behaviours. However, this effect was seldom directly observed and many related phenomena have not been well understood. Moreover, a reliable method to quantify the DW surface energy is still missing. Here, we report a series of ...
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Unified Halo-Independent Formalism From Convex Hulls for Direct Dark Matter Searches
Using the Fenchel-Eggleston theorem for convex hulls (an extension of the Caratheodory theorem), we prove that any likelihood can be maximized by either a dark matter 1- speed distribution $F(v)$ in Earth's frame or 2- Galactic velocity distribution $f^{\rm gal}(\vec{u})$, consisting of a sum of delta functions. The ...
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Finite size effects for spiking neural networks with spatially dependent coupling
We study finite-size fluctuations in a network of spiking deterministic neurons coupled with non-uniform synaptic coupling. We generalize a previously developed theory of finite size effects for uniform globally coupled neurons. In the uniform case, mean field theory is well defined by averaging over the network as t...
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Shape and fission instabilities of ferrofluids in non-uniform magnetic fields
We study static distributions of ferrofluid submitted to non-uniform magnetic fields. We show how the normal-field instability is modified in the presence of a weak magnetic field gradient. Then we consider a ferrofluid droplet and show how the gradient affects its shape. A rich phase transitions phenomenology is fou...
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Encrypted accelerated least squares regression
Information that is stored in an encrypted format is, by definition, usually not amenable to statistical analysis or machine learning methods. In this paper we present detailed analysis of coordinate and accelerated gradient descent algorithms which are capable of fitting least squares and penalised ridge regression ...
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Unified Model of Chaotic Inflation and Dynamical Supersymmetry Breaking
The large hierarchy between the Planck scale and the weak scale can be explained by the dynamical breaking of supersymmetry in strongly coupled gauge theories. Similarly, the hierarchy between the Planck scale and the energy scale of inflation may also originate from strong dynamics, which dynamically generate the in...
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Tuplemax Loss for Language Identification
In many scenarios of a language identification task, the user will specify a small set of languages which he/she can speak instead of a large set of all possible languages. We want to model such prior knowledge into the way we train our neural networks, by replacing the commonly used softmax loss function with a nove...
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Sparse Data Driven Mesh Deformation
Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can lead to overfitting, i.e. using a overly complicated model to explain the user-specified deformation. This leads to implausible or unstable...
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Short Presburger arithmetic is hard
We study the computational complexity of short sentences in Presburger arithmetic (Short-PA). Here by "short" we mean sentences with a bounded number of variables, quantifiers, inequalities and Boolean operations; the input consists only of the integer coefficients involved in the linear inequalities. We prove that s...
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The Bias of the Log Power Spectrum for Discrete Surveys
A primary goal of galaxy surveys is to tighten constraints on cosmological parameters, and the power spectrum $P(k)$ is the standard means of doing so. However, at translinear scales $P(k)$ is blind to much of these surveys' information---information which the log density power spectrum recovers. For discrete fields ...
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Consistent nonparametric change point detection combining CUSUM and marked empirical processes
A weakly dependent time series regression model with multivariate covariates and univariate observations is considered, for which we develop a procedure to detect whether the nonparametric conditional mean function is stable in time against change point alternatives. Our proposal is based on a modified CUSUM type tes...
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Nonlinear electric field effect on perpendicular magnetic anisotropy in Fe/MgO interfaces
The electric field effect on magnetic anisotropy was studied in an ultrathin Fe(001) monocrystalline layer sandwiched between Cr buffer and MgO tunnel barrier layers, mainly through post-annealing temperature and measurement temperature dependences. A large coefficient of the electric field effect of more than 200 fJ...
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Local Symmetry and Global Structure in Adaptive Voter Models
"Coevolving" or "adaptive" voter models (AVMs) are natural systems for modeling the emergence of mesoscopic structure from local networked processes driven by conflict and homophily. Because of this, many methods for approximating the long-run behavior of AVMs have been proposed over the last decade. However, most su...
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A Weighted Model Confidence Set: Applications to Local and Mixture Model Confidence Sets
This article provides a weighted model confidence set, whenever underling model has been misspecified and some part of support of random variable $X$ conveys some important information about underling true model. Application of such weighted model confidence set for local and mixture model confidence sets have been g...
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Poverty Mapping Using Convolutional Neural Networks Trained on High and Medium Resolution Satellite Images, With an Application in Mexico
Mapping the spatial distribution of poverty in developing countries remains an important and costly challenge. These "poverty maps" are key inputs for poverty targeting, public goods provision, political accountability, and impact evaluation, that are all the more important given the geographic dispersion of the rema...
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Network of sensitive magnetometers for urban studies
The magnetic signature of an urban environment is investigated using a geographically distributed network of fluxgate magnetometers deployed in and around Berkeley, California. The system hardware and software are described and results from initial operation of the network are reported. The sensors sample the vector ...
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Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization
The cooperative hierarchical structure is a common and significant data structure observed in, or adopted by, many research areas, such as: text mining (author-paper-word) and multi-label classification (label-instance-feature). Renowned Bayesian approaches for cooperative hierarchical structure modeling are mostly b...
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The extended law of star formation: the combined role of gas and stars
We present a model for the origin of the extended law of star formation in which the surface density of star formation ($\Sigma_{\rm SFR}$) depends not only on the local surface density of the gas ($\Sigma_{g}$), but also on the stellar surface density ($\Sigma_{*}$), the velocity dispersion of the stars, and on the ...
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Local and global similarity of holomorphic matrices
R. Guralnick (Linear Algebra Appl. 99, 85-96, 1988) proved that two holomorphic matrices on a noncompact connected Riemann surface, which are locally holomorphically similar, are globally holomorphically similar. We generalize this to (possibly, non-smooth) one-dimensional Stein spaces. For Stein spaces of arbitrary ...
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WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
Learning sparse linear models with two-way interactions is desirable in many application domains such as genomics. l1-regularised linear models are popular to estimate sparse models, yet standard implementations fail to address specifically the quadratic explosion of candidate two-way interactions in high dimensions,...
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On the Limitation of Convolutional Neural Networks in Recognizing Negative Images
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance on a variety of computer vision tasks, particularly visual classification problems, where new algorithms reported to achieve or even surpass the human performance. In this paper, we examine whether CNNs are capable of learning the semanti...
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$\aleph_1$ and the modal $μ$-calculus
For a regular cardinal $\kappa$, a formula of the modal $\mu$-calculus is $\kappa$-continuous in a variable x if, on every model, its interpretation as a unary function of x is monotone and preserves unions of $\kappa$-directed sets. We define the fragment $C_{\aleph_1}(x)$ of the modal $\mu$-calculus and prove that ...
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Optimal Service Elasticity in Large-Scale Distributed Systems
A fundamental challenge in large-scale cloud networks and data centers is to achieve highly efficient server utilization and limit energy consumption, while providing excellent user-perceived performance in the presence of uncertain and time-varying demand patterns. Auto-scaling provides a popular paradigm for automa...
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Variational Monte Carlo study of spin dynamics in underdoped cuprates
The hour-glass-like dispersion of spin excitations is a common feature of underdoped cuprates. It was qualitatively explained by the random phase approximation based on various ordered states with some phenomenological parameters; however, its origin remains elusive. Here, we present a numerical study of spin dynamic...
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High brightness electron beam for radiation therapy: A new approach
I propose to use high brightness electron beam with 1 to 100 MeV energy as tool to combat tumor or cancerous tissues in deep part of body. The method is to directly deliver the electron beam to the tumor site via a small tube that connected to a high brightness electron beam accelerator that is commonly available aro...
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Parabolic equations with divergence-free drift in space $L_{t}^{l}L_{x}^{q}$
In this paper we study the fundamental solution $\varGamma(t,x;\tau,\xi)$ of the parabolic operator $L_{t}=\partial_{t}-\Delta+b(t,x)\cdot\nabla$, where for every $t$, $b(t,\cdot)$ is a divergence-free vector field, and we consider the case that $b$ belongs to the Lebesgue space $L^{l}\left(0,T;L^{q}\left(\mathbb{R}^...
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Translating Terminological Expressions in Knowledge Bases with Neural Machine Translation
Our work presented in this paper focuses on the translation of terminological expressions represented in semantically structured resources, like ontologies or knowledge graphs. The challenge of translating ontology labels or terminological expressions represented in knowledge bases lies in the highly specific vocabul...
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Detecting Arbitrary Attacks Using Continuous Secured Side Information in Wireless Networks
This paper focuses on Byzantine attack detection for Gaussian two-hop one-way relay network, where an amplify-and-forward relay may conduct Byzantine attacks by forwarding altered symbols to the destination. For facilitating attack detection, we utilize the openness of wireless medium to make the destination observe ...
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Phase Transitions in the Pooled Data Problem
In this paper, we study the pooled data problem of identifying the labels associated with a large collection of items, based on a sequence of pooled tests revealing the counts of each label within the pool. In the noiseless setting, we identify an exact asymptotic threshold on the required number of tests with optima...
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Graph Convolutional Networks for Classification with a Structured Label Space
It is a usual practice to ignore any structural information underlying classes in multi-class classification. In this paper, we propose a graph convolutional network (GCN) augmented neural network classifier to exploit a known, underlying graph structure of labels. The proposed approach resembles an (approximate) inf...
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Decoupling of graphene from Ni(111) via oxygen intercalation
The combination of the surface science techniques (STM, XPS, ARPES) and density-functional theory calculations was used to study the decoupling of graphene from Ni(111) by oxygen intercalation. The formation of the antiferromagnetic (AFM) NiO layer at the interface between graphene and ferromagnetic (FM) Ni is found,...
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Model Risk Measurement under Wasserstein Distance
The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability measures. It formulates the theoretical motivation resulting from the interpretation of fictitious adversary of robust risk management. The proposed approach accounts for all alternative models and in...
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Fast kNN mode seeking clustering applied to active learning
A significantly faster algorithm is presented for the original kNN mode seeking procedure. It has the advantages over the well-known mean shift algorithm that it is feasible in high-dimensional vector spaces and results in uniquely, well defined modes. Moreover, without any additional computational effort it may yiel...
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Towards a Flow- and Path-Sensitive Information Flow Analysis: Technical Report
This paper investigates a flow- and path-sensitive static information flow analysis. Compared with security type systems with fixed labels, it has been shown that flow-sensitive type systems accept more secure programs. We show that an information flow analysis with fixed labels can be both flow- and path-sensitive. ...
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Topic supervised non-negative matrix factorization
Topic models have been extensively used to organize and interpret the contents of large, unstructured corpora of text documents. Although topic models often perform well on traditional training vs. test set evaluations, it is often the case that the results of a topic model do not align with human interpretation. Thi...
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Low-temperature lattice effects in the spin-liquid candidate $κ$-(BEDT-TTF)$_2$Cu$_2$(CN)$_3$
The quasi-two-dimensional organic charge-transfer salt $\kappa$-(BEDT-TTF)$_2$Cu$_2$(CN)$_3$ is one of the prime candidates for a quantum spin-liquid due the strong spin frustration of its anisotropic triangular lattice in combination with its proximity to the Mott transition. Despite intensive investigations of the ...
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ECO-AMLP: A Decision Support System using an Enhanced Class Outlier with Automatic Multilayer Perceptron for Diabetes Prediction
With advanced data analytical techniques, efforts for more accurate decision support systems for disease prediction are on rise. Surveys by World Health Organization (WHO) indicate a great increase in number of diabetic patients and related deaths each year. Early diagnosis of diabetes is a major concern among resear...
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Local approximation of non-holomorphic discs in almost complex manifolds
We provide a local approximation result of non-holomorphic discs with small d-bar by pseudoholomorphic ones. As an application, we provide a certain gluing construction.
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A Tutorial on Deep Learning for Music Information Retrieval
Following their success in Computer Vision and other areas, deep learning techniques have recently become widely adopted in Music Information Retrieval (MIR) research. However, the majority of works aim to adopt and assess methods that have been shown to be effective in other domains, while there is still a great nee...
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Modeling and control of modern wind turbine systems: An introduction
This chapter provides an introduction to the modeling and control of power generation from wind turbine systems. In modeling, the focus is on the electrical components: electrical machine (e.g. permanent-magnet synchronous generators), back-to-back converter (consisting of machine-side and grid-side converter sharing...
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Linear algebraic analogues of the graph isomorphism problem and the Erdős-Rényi model
A classical difficult isomorphism testing problem is to test isomorphism of p-groups of class 2 and exponent p in time polynomial in the group order. It is known that this problem can be reduced to solving the alternating matrix space isometry problem over a finite field in time polynomial in the underlying vector sp...
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A Family of Metrics for Clustering Algorithms
We give the motivation for scoring clustering algorithms and a metric $M : A \rightarrow \mathbb{N}$ from the set of clustering algorithms to the natural numbers which we realize as \begin{equation} M(A) = \sum_i \alpha_i |f_i - \beta_i|^{w_i} \end{equation} where $\alpha_i,\beta_i,w_i$ are parameters used for scorin...
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A numerical scheme for an improved Green-Naghdi model in the Camassa-Holm regime for the propagation of internal waves
In this paper we introduce a new reformulation of the Green-Naghdi model in the Camassa-Holm regime for the propagation of internal waves over a flat topography derived by Duchêne, Israwi and Talhouk. These new Green-Naghdi systems are adapted to improve the frequency dispersion of the original model, they share the ...
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General Bayesian Updating and the Loss-Likelihood Bootstrap
In this paper we revisit the weighted likelihood bootstrap, a method that generates samples from an approximate Bayesian posterior of a parametric model. We show that the same method can be derived, without approximation, under a Bayesian nonparametric model with the parameter of interest defined as minimising an exp...
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Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles
For many applications, an ensemble of base classifiers is an effective solution. The tuning of its parameters(number of classes, amount of data on which each classifier is to be trained on, etc.) requires G, the generalization error of a given ensemble. The efficient estimation of G is the focus of this paper. The ke...
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Self-consistent calculation of the flux-flow conductivity in diffusive superconductors
In the framework of Keldysh-Usadel kinetic theory, we study the temperature dependence of flux-flow conductivity (FFC) in diffusive superconductors. By using self-consistent vortex solutions we find the exact values of dimensionless parameters that determine the diffusion-controlled FFC both in the limit of the low t...
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