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A Result of Uniqueness of Solutions of the Shigesada-Kawasaki-Teramoto Equations
We derive the uniqueness of weak solutions to the Shigesada-Kawasaki-Teramoto (SKT) systems using the adjoint problem argument. Combining with [PT17] we then derive the well-posedness for the SKT systems in space dimension $d\le 4$
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Mind the Gap: A Well Log Data Analysis
The main task in oil and gas exploration is to gain an understanding of the distribution and nature of rocks and fluids in the subsurface. Well logs are records of petro-physical data acquired along a borehole, providing direct information about what is in the subsurface. The data collected by logging wells can have ...
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Inconsistency of Template Estimation with the Fr{é}chet mean in Quotient Space
We tackle the problem of template estimation when data have been randomly transformed under an isometric group action in the presence of noise. In order to estimate the template, one often minimizes the variance when the influence of the transformations have been removed (computation of the Fr{é}chet mean in quotient...
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All-optical switching and unidirectional plasmon launching with electron-hole plasma driven silicon nanoantennas
High-index dielectric nanoparticles have become a powerful platform for modern light science, enabling various fascinating applications, especially in nonlinear nanophotonics for which they enable special types of optical nonlinearity, such as electron-hole plasma photoexcitation, which are not inherent to plasmonic ...
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Group chasing tactics: how to catch a faster prey?
We propose a bio-inspired, agent-based approach to describe the natural phenomenon of group chasing in both two and three dimensions. Using a set of local interaction rules we created a continuous-space and discrete-time model with time delay, external noise and limited acceleration. We implemented a unique collectiv...
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On solving a restricted linear congruence using generalized Ramanujan sums
Consider the linear congruence equation $x_1+\ldots+x_k \equiv b\,(\text{mod } n)$ for $b,n\in\mathbb{Z}$. By $(a,b)_s$, we mean the largest $l^s\in\mathbb{N}$ which divides $a$ and $b$ simultaneously. For each $d_j|n$, define $\mathcal{C}_{j,s} = \{1\leq x\leq n^s | (x,n^s)_s = d^s_j\}$. Bibak et al. gave a formula ...
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Magnetization spin dynamics in a (LuBi)3Fe5O12 (BLIG) epitaxial film
Bismuth substituted lutetium iron garnet (BLIG) films exhibit larger Faraday rotation, and have a higher Curie temperature than yttrium iron garnet. We have observed magnetic stripe domains and measured domain widths of 1.4 {\mu}{\mu}m using Fourier domain polarization microscopy, Faraday rotation experiments yield a...
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Probing for sparse and fast variable selection with model-based boosting
We present a new variable selection method based on model-based gradient boosting and randomly permuted variables. Model-based boosting is a tool to fit a statistical model while performing variable selection at the same time. A drawback of the fitting lies in the need of multiple model fits on slightly altered data ...
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A surface-hopping method for semiclassical calculations of cross sections for radiative association with electronic transitions
A semicalssical method based on surface-hopping techniques is developed to model the dynamics of radiative association with electronic transitions in arbitrary polyatomic systems. It can be proven that our method is an extension of the established semiclassical formula used in the characterization of diatomic molecul...
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Holographic coherent states from random tensor networks
Random tensor networks provide useful models that incorporate various important features of holographic duality. A tensor network is usually defined for a fixed graph geometry specified by the connection of tensors. In this paper, we generalize the random tensor network approach to allow quantum superposition of diff...
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Persistent Spread Measurement for Big Network Data Based on Register Intersection
Persistent spread measurement is to count the number of distinct elements that persist in each network flow for predefined time periods. It has many practical applications, including detecting long-term stealthy network activities in the background of normal-user activities, such as stealthy DDoS attack, stealthy net...
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High-dimensional Linear Regression for Dependent Observations with Application to Nowcasting
In the last few years, an extensive literature has been focused on the $\ell_1$ penalized least squares (Lasso) estimators of high dimensional linear regression when the number of covariates $p$ is considerably larger than the sample size $n$. However, there is limited attention paid to the properties of the estimato...
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Dynamic control of the optical emission from GaN/InGaN nanowire quantum dots by surface acoustic waves
The optical emission of InGaN quantum dots embedded in GaN nanowires is dynamically controlled by a surface acoustic wave (SAW). The emission energy of both the exciton and biexciton lines is modulated over a 1.5 meV range at ~330 MHz. A small but systematic difference in the exciton and biexciton spectral modulation...
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Robust Tracking and Behavioral Modeling of Movements of Biological Collectives from Ordinary Video Recordings
We propose a novel computational method to extract information about interactions among individuals with different behavioral states in a biological collective from ordinary video recordings. Assuming that individuals are acting as finite state machines, our method first detects discrete behavioral states of those in...
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Understanding Membership Inferences on Well-Generalized Learning Models
Membership Inference Attack (MIA) determines the presence of a record in a machine learning model's training data by querying the model. Prior work has shown that the attack is feasible when the model is overfitted to its training data or when the adversary controls the training algorithm. However, when the model is ...
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Identification of Near-Infrared [Se III] and [Kr VI] Emission Lines in Planetary Nebulae
We identify [Se III] 1.0994 micron in the planetary nebula (PN) NGC 5315 and [Kr VI] 1.2330 micron in three PNe, from spectra obtained with the FIRE spectrometer on the 6.5-m Baade Telescope. Se and Kr are the two most widely-detected neutron-capture elements in astrophysical nebulae, and can be enriched by s-process...
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On reduction of differential inclusions and Lyapunov stability
In this paper, locally Lipschitz regular functions are utilized to identify and remove infeasible directions from differential inclusions. The resulting reduced differential inclusion is point-wise smaller (in the sense of set containment) than the original differential inclusion. The reduced inclusion is utilized to...
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Deep Generative Networks For Sequence Prediction
This thesis investigates unsupervised time series representation learning for sequence prediction problems, i.e. generating nice-looking input samples given a previous history, for high dimensional input sequences by decoupling the static input representation from the recurrent sequence representation. We introduce t...
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Composite Behavioral Modeling for Identity Theft Detection in Online Social Networks
In this work, we aim at building a bridge from poor behavioral data to an effective, quick-response, and robust behavior model for online identity theft detection. We concentrate on this issue in online social networks (OSNs) where users usually have composite behavioral records, consisting of multi-dimensional low-q...
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Asymptotic properties of the set of systoles of arithmetic Riemann surfaces
The purpose this article is to try to understand the mysterious coincidence between the asymptotic behavior of the volumes of the Moduli Space of closed hyperbolic surfaces of genus $g$ with respect to the Weil-Petersson metric and the asymptotic behavior of the number of arithmetic closed hyperbolic surfaces of genu...
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Nonlinear elliptic equations on Carnot groups
This article concerns a class of elliptic equations on Carnot groups depending on one real positive parameter and involving a subcritical nonlinearity (for the critical case we refer to G. Molica Bisci and D. Repovš, Yamabe-type equations on Carnot groups, Potential Anal. 46:2 (2017), 369-383; arXiv:1705.10100 [math....
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Raptor Codes for Higher-Order Modulation Using a Multi-Edge Framework
In this paper, we represent Raptor codes as multi-edge type low-density parity-check (MET-LDPC) codes, which gives a general framework to design them for higher-order modulation using MET density evolution. We then propose an efficient Raptor code design method for higher-order modulation, where we design distinct de...
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A Tidy Data Model for Natural Language Processing using cleanNLP
The package cleanNLP provides a set of fast tools for converting a textual corpus into a set of normalized tables. The underlying natural language processing pipeline utilizes Stanford's CoreNLP library, exposing a number of annotation tasks for text written in English, French, German, and Spanish. Annotators include...
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Relaxation of the EM Algorithm via Quantum Annealing for Gaussian Mixture Models
We propose a modified expectation-maximization algorithm by introducing the concept of quantum annealing, which we call the deterministic quantum annealing expectation-maximization (DQAEM) algorithm. The expectation-maximization (EM) algorithm is an established algorithm to compute maximum likelihood estimates and ap...
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Multiband Superconductivity in the time reversal symmetry broken superconductor Re6Zr
We report point contact Andreev Reflection (PCAR) measurements on a high-quality single crystal of the non-centrosymmetric superconductor Re6Zr. We observe that the PCAR spectra can be fitted by taking two isotropic superconducting gaps with Delta_1 ~ 0.79 meV and Delta_2 ~ 0.22 meV respectively, suggesting that ther...
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Influence of broken-pair excitations on the exact pair wavefunction
Doubly occupied configuration interaction (DOCI), the exact diagonalization of the Hamiltonian in the paired (seniority zero) sector of the Hilbert space, is a combinatorial cost wave function that can be very efficiently approximated by pair coupled cluster doubles (pCCD) at mean-field computational cost. As such, i...
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Dynamical regularities of US equities opening and closing auctions
We first investigate the evolution of opening and closing auctions volumes of US equities along the years. We then report dynamical properties of pre-auction periods: the indicative match price is strongly mean-reverting because the imbalance is; the final auction price reacts to a single auction order placement or c...
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Comment on "Laser cooling of $^{173}$Yb for isotope separation and precision hyperfine spectroscopy"
We present measurements of the hyperfine splitting in the Yb-173 $6s6p~^1P_1^{\rm o} (F^{\prime}=3/2,7/2)$ states that disagree significantly with those measured previously by Das and Natarajan [Phys. Rev. A 76, 062505 (2007)]. We point out inconsistencies in their measurements and suggest that their error is due to ...
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Training GANs with Optimism
We address the issue of limit cycling behavior in training Generative Adversarial Networks and propose the use of Optimistic Mirror Decent (OMD) for training Wasserstein GANs. Recent theoretical results have shown that optimistic mirror decent (OMD) can enjoy faster regret rates in the context of zero-sum games. WGAN...
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New concepts of inertial measurements with multi-species atom interferometry
In the field of cold atom inertial sensors, we present and analyze innovative configurations for improving their measurement range and sensitivity, especially attracting for onboard applications. These configurations rely on multi-species atom interferometry, involving the simultaneous manipulation of different atomi...
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LAMN in a class of parametric models for null recurrent diffusion
We study statistical models for one-dimensional diffusions which are recurrent null. A first parameter in the drift is the principal one, and determines regular varying rates of convergence for the score and the information process. A finite number of other parameters, of secondary importance, introduces additional f...
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A recipe for topological observables of density matrices
Meaningful topological invariants for mixed quantum states are challenging to identify as there is no unique way to define them, and most choices do not directly relate to physical observables. Here, we propose a simple pragmatic approach to construct topological invariants of mixed states while preserving a connecti...
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Generalization Tower Network: A Novel Deep Neural Network Architecture for Multi-Task Learning
Deep learning (DL) advances state-of-the-art reinforcement learning (RL), by incorporating deep neural networks in learning representations from the input to RL. However, the conventional deep neural network architecture is limited in learning representations for multi-task RL (MT-RL), as multiple tasks can refer to ...
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On a class of infinitely differentiable functions in ${\mathbb R}^n$ admitting holomorphic extension in ${\mathbb C}^n$
A space $G(M, \varPhi)$ of infinitely differentiable functions in ${\mathbb R}^n$ constructed with a help of a family $\varPhi=\{\varphi_m\}_{m=1}^{\infty}$ of real-valued functions $\varphi_m \in~C({\mathbb R}^n)$ and a logarithmically convex sequence $M$ of positive numbers is considered in the article. In view of ...
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Spatially resolved, energy-filtered imaging of core level and valence band photoemission of highly p and n doped silicon patterns
An accurate description of spatial variations in the energy levels of patterned semiconductor substrates on the micron and sub-micron scale as a function of local doping is an important technological challenge for the microelectronics industry. Spatially resolved surface analysis by photoelectron spectromicroscopy ca...
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Effects of Degree Correlations in Interdependent Security: Good or Bad?
We study the influence of degree correlations or network mixing in interdependent security. We model the interdependence in security among agents using a dependence graph and employ a population game model to capture the interaction among many agents when they are strategic and have various security measures they can...
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Towards more Reliable Transfer Learning
Multi-source transfer learning has been proven effective when within-target labeled data is scarce. Previous work focuses primarily on exploiting domain similarities and assumes that source domains are richly or at least comparably labeled. While this strong assumption is never true in practice, this paper relaxes it...
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Forming short-period Wolf-Rayet X-ray binaries and double black holes through stable mass transfer
We show that black-hole High-Mass X-ray Binaries (HMXBs) with O- or B-type donor stars and relatively short orbital periods, of order one week to several months may survive spiral in, to then form Wolf-Rayet (WR) X-ray binaries with orbital periods of order a day to a few days; while in systems where the compact star...
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Syzygies of Cohen-Macaulay modules over one dimensional Cohen-Macaulay local rings
We study syzygies of (maximal) Cohen-Macaulay modules over one dimensional Cohen-Macaulay local rings. We compare these modules to Cohen-Macaulay modules over the endomorphism ring of the maximal ideal. After this comparison, we give several characterizations of almost Gorenstein rings in terms of syzygies of Cohen-M...
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Chirality provides a direct fitness advantage and facilitates intermixing in cellular aggregates
Chirality in shape and motility can evolve rapidly in microbes and cancer cells. To determine how chirality affects cell fitness, we developed a model of chiral growth in compact aggregates such as microbial colonies and solid tumors. Our model recapitulates previous experimental findings and shows that mutant cells ...
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Learning to Draw Samples with Amortized Stein Variational Gradient Descent
We propose a simple algorithm to train stochastic neural networks to draw samples from given target distributions for probabilistic inference. Our method is based on iteratively adjusting the neural network parameters so that the output changes along a Stein variational gradient direction (Liu & Wang, 2016) that maxi...
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Preconditioned dynamic mode decomposition and mode selection algorithms for large datasets using incremental proper orthogonal decomposition
This note proposes a simple and general framework of dynamic mode decomposition (DMD) and a mode selection for large datasets. The proposed framework explicitly introduces a preconditioning step using an incremental proper orthogonal decomposition to DMD and mode selection algorithms. By performing the preconditionin...
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A functional perspective on emergent supersymmetry
We investigate the emergence of ${\cal N}=1$ supersymmetry in the long-range behavior of three-dimensional parity-symmetric Yukawa systems. We discuss a renormalization approach that manifestly preserves supersymmetry whenever such symmetry is realized, and use it to prove that supersymmetry-breaking operators are ir...
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Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
Adaptive gradient methods have become recently very popular, in particular as they have been shown to be useful in the training of deep neural networks. In this paper we have analyzed RMSProp, originally proposed for the training of deep neural networks, in the context of online convex optimization and show $\sqrt{T}...
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Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions
We study connections between Dykstra's algorithm for projecting onto an intersection of convex sets, the augmented Lagrangian method of multipliers or ADMM, and block coordinate descent. We prove that coordinate descent for a regularized regression problem, in which the (separable) penalty functions are seminorms, is...
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A Topological Perspective on Interacting Algebraic Theories
Techniques from higher categories and higher-dimensional rewriting are becoming increasingly important for understanding the finer, computational properties of higher algebraic theories that arise, among other fields, in quantum computation. These theories have often the property of containing simpler sub-theories, w...
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Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation
We introduce dynamic nested sampling: a generalisation of the nested sampling algorithm in which the number of "live points" varies to allocate samples more efficiently. In empirical tests the new method significantly improves calculation accuracy compared to standard nested sampling with the same number of samples; ...
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Multistage Adaptive Testing of Sparse Signals
Multistage design has been used in a wide range of scientific fields. By allocating sensing resources adaptively, one can effectively eliminate null locations and localize signals with a smaller study budget. We formulate a decision-theoretic framework for simultaneous multi- stage adaptive testing and study how to m...
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On the commutativity of the powerspace constructions
We investigate powerspace constructions on topological spaces, with a particular focus on the category of quasi-Polish spaces. We show that the upper and lower powerspaces commute on all quasi-Polish spaces, and show more generally that this commutativity is equivalent to the topological property of consonance. We th...
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Bounds on poloidal kinetic energy in plane layer convection
A numerical method is presented which conveniently computes upper bounds on heat transport and poloidal energy in plane layer convection for infinite and finite Prandtl numbers. The bounds obtained for the heat transport coincide with earlier results. These bounds imply upper bounds for the poloidal energy which foll...
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Concentration of Multilinear Functions of the Ising Model with Applications to Network Data
We prove near-tight concentration of measure for polynomial functions of the Ising model under high temperature. For any degree $d$, we show that a degree-$d$ polynomial of a $n$-spin Ising model exhibits exponential tails that scale as $\exp(-r^{2/d})$ at radius $r=\tilde{\Omega}_d(n^{d/2})$. Our concentration radiu...
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Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning
This paper proposes an exploration method for deep reinforcement learning based on parameter space noise. Recent studies have experimentally shown that parameter space noise results in better exploration than the commonly used action space noise. Previous methods devised a way to update the diagonal covariance matrix...
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Fast and high-accuracy measuring technique for transmittance spectrum in VIS-NIR
In this paper, based on the framework of traditional spectrophotometry, we put forward a novel fast and high-accuracy technique for measuring transmittance spectrum in VIS-NIR wave range, its key feature is that during the measurement procedure, the output wavelength of the grating monochromator is kept increasing co...
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The solution to the initial value problem for the ultradiscrete Somos-4 and 5 equations
We propose a method to solve the initial value problem for the ultradiscrete Somos-4 and Somos-5 equations by expressing terms in the equations as convex polygons and regarding max-plus algebras as those on polygons.
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Width-tuned magnetic order oscillation on zigzag edges of honeycomb nanoribbons
Quantum confinement and interference often generate exotic properties in nanostructures. One recent highlight is the experimental indication of a magnetic phase transition in zigzag-edged graphene nanoribbons at the critical ribbon width of about 7 nm [G. Z. Magda et al., Nature \textbf{514}, 608 (2014)]. Here we sho...
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Fast and accurate approximation of the full conditional for gamma shape parameters
The gamma distribution arises frequently in Bayesian models, but there is not an easy-to-use conjugate prior for the shape parameter of a gamma. This inconvenience is usually dealt with by using either Metropolis-Hastings moves, rejection sampling methods, or numerical integration. However, in models with a large num...
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Two variants of the Froiduire-Pin Algorithm for finite semigroups
In this paper, we present two algorithms based on the Froidure-Pin Algorithm for computing the structure of a finite semigroup from a generating set. As was the case with the original algorithm of Froidure and Pin, the algorithms presented here produce the left and right Cayley graphs, a confluent terminating rewriti...
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Holon Wigner Crystal in a Lightly Doped Kagome Quantum Spin Liquid
We address the problem of a lightly doped spin-liquid through a large-scale density-matrix renormalization group (DMRG) study of the $t$-$J$ model on a Kagome lattice with a small but non-zero concentration, $\delta$, of doped holes. It is now widely accepted that the undoped ($\delta=0$) spin 1/2 Heisenberg antiferr...
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Accelerated Block Coordinate Proximal Gradients with Applications in High Dimensional Statistics
Nonconvex optimization problems arise in different research fields and arouse lots of attention in signal processing, statistics and machine learning. In this work, we explore the accelerated proximal gradient method and some of its variants which have been shown to converge under nonconvex context recently. We show ...
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Phase retrieval using alternating minimization in a batch setting
This paper considers the problem of phase retrieval, where the goal is to recover a signal $z\in C^n$ from the observations $y_i=|a_i^* z|$, $i=1,2,\cdots,m$. While many algorithms have been proposed, the alternating minimization algorithm has been one of the most commonly used methods, and it is very simple to imple...
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Inverse statistical problems: from the inverse Ising problem to data science
Inverse problems in statistical physics are motivated by the challenges of `big data' in different fields, in particular high-throughput experiments in biology. In inverse problems, the usual procedure of statistical physics needs to be reversed: Instead of calculating observables on the basis of model parameters, we...
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Static structure of chameleon dark Matter as an explanation of dwarf spheroidal galactic core
We propose a novel mechanism which explains cored dark matter density profile in recently observed dark matter rich dwarf spheroidal galaxies. In our scenario, dark matter particle mass decreases gradually as function of distance towards the center of a dwarf galaxy due to its interaction with a chameleon scalar. At ...
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Multi-Stakeholder Recommendation: Applications and Challenges
Recommender systems have been successfully applied to assist decision making by producing a list of item recommendations tailored to user preferences. Traditional recommender systems only focus on optimizing the utility of the end users who are the receiver of the recommendations. By contrast, multi-stakeholder recom...
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Unbalancing Sets and an Almost Quadratic Lower Bound for Syntactically Multilinear Arithmetic Circuits
We prove a lower bound of $\Omega(n^2/\log^2 n)$ on the size of any syntactically multilinear arithmetic circuit computing some explicit multilinear polynomial $f(x_1, \ldots, x_n)$. Our approach expands and improves upon a result of Raz, Shpilka and Yehudayoff ([RSY08]), who proved a lower bound of $\Omega(n^{4/3}/\...
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Saturated absorption competition microscopy
We introduce the concept of saturated absorption competition (SAC) microscopy as a means of providing sub-diffraction spatial resolution in fluorescence imaging. Unlike the post-competition process between stimulated and spontaneous emission that is used in stimulated emission depletion (STED) microscopy, SAC microsc...
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Topological and non inertial effects on the interbank light absorption
In this work, we investigate the combined influence of the nontrivial topology introduced by a disclination and non inertial effects due to rotation, in the energy levels and the wave functions of a noninteracting electron gas confined to a two-dimensional pseudoharmonic quantum dot, under the influence of an externa...
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Evolution of antiferromagnetic domains in the all-in-all-out ordered pyrochlore Nd$_2$Zr$_2$O$_7$
We report the observation of magnetic domains in the exotic, antiferromagnetically ordered all-in-all-out state of Nd$_2$Zr$_2$O$_7$, induced by spin canting. The all-in-all-out state can be realized by Ising-like spins on a pyrochlore lattice and is established in Nd$_2$Zr$_2$O$_7$ below 0.31 K for external magnetic...
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Phylogenetic networks that are their own fold-ups
Phylogenetic networks are becoming of increasing interest to evolutionary biologists due to their ability to capture complex non-treelike evolutionary processes. From a combinatorial point of view, such networks are certain types of rooted directed acyclic graphs whose leaves are labelled by, for example, species. A ...
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Hyperbolic inverse mean curvature flow
In this paper, we prove the short-time existence of hyperbolic inverse (mean) curvature flow (with or without the specified forcing term) under the assumption that the initial compact smooth hypersurface of $\mathbb{R}^{n+1}$ ($n\geqslant2$) is mean convex and star-shaped. Several interesting examples and some hyperb...
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Theoretically Principled Trade-off between Robustness and Accuracy
We identify a trade-off between robustness and accuracy that serves as a guiding principle in the design of defenses against adversarial examples. Although the problem has been widely studied empirically, much remains unknown concerning the theory underlying this trade-off. In this work, we quantify the trade-off in ...
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A new charge reconstruction algorithm for the DAMPE silicon microstrip detector
The DArk Matter Particle Explorer (DAMPE) is one of the four satellites within the Strategic Pioneer Research Program in Space Science of the Chinese Academy of Science (CAS). The Silicon-Tungsten Tracker (STK), which is composed of 768 singled-sided silicon microstrip detectors, is one of the four subdetectors in DA...
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The Structure Transfer Machine Theory and Applications
Representation learning is a fundamental but challenging problem, especially when the distribution of data is unknown. We propose a new representation learning method, termed Structure Transfer Machine (STM), which enables feature learning process to converge at the representation expectation in a probabilistic way. ...
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Inverse Fractional Knapsack Problem with Profits and Costs Modification
We address in this paper the problem of modifying both profits and costs of a fractional knapsack problem optimally such that a prespecified solution becomes an optimal solution with prespect to new parameters. This problem is called the inverse fractional knapsack problem. Concerning the $l_1$-norm, we first prove t...
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Large dimensional analysis of general margin based classification methods
Margin-based classifiers have been popular in both machine learning and statistics for classification problems. Since a large number of classifiers are available, one natural question is which type of classifiers should be used given a particular classification task. We aim to answering this question by investigating...
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Complete reducibility, Kulshammer's question, conjugacy classes: a D_4 example
Let $k$ be a nonperfect separably closed field. Let $G$ be a connected reductive algebraic group defined over $k$. We study rationality problems for Serre's notion of complete reducibility of subgroups of $G$. In particular, we present a new example of subgroup $H$ of $G$ of type $D_4$ in characteristic $2$ such that...
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Covariance structure associated with an equality between two general ridge estimators
In a general linear model, this paper derives a necessary and sufficient condition under which two general ridge estimators coincide with each other. The condition is given as a structure of the dispersion matrix of the error term. Since the class of estimators considered here contains linear unbiased estimators such...
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Three natural subgroups of the Brauer-Picard group of a Hopf algebra with applications
In this article we construct three explicit natural subgroups of the Brauer-Picard group of the category of representations of a finite-dimensional Hopf algebra. In examples the Brauer Picard group decomposes into an ordered product of these subgroups, somewhat similar to a Bruhat decomposition. Our construction retu...
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UAV Visual Teach and Repeat Using Only Semantic Object Features
We demonstrate the use of semantic object detections as robust features for Visual Teach and Repeat (VTR). Recent CNN-based object detectors are able to reliably detect objects of tens or hundreds of categories in a video at frame rates. We show that such detections are repeatable enough to use as landmarks for VTR, ...
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Towards a Deep Reinforcement Learning Approach for Tower Line Wars
There have been numerous breakthroughs with reinforcement learning in the recent years, perhaps most notably on Deep Reinforcement Learning successfully playing and winning relatively advanced computer games. There is undoubtedly an anticipation that Deep Reinforcement Learning will play a major role when the first A...
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A Case for an Atmosphere on Super-Earth 55 Cancri e
One of the primary questions when characterizing Earth-sized and super-Earth-sized exoplanets is whether they have a substantial atmosphere like Earth and Venus or a bare-rock surface like Mercury. Phase curves of the planets in thermal emission provide clues to this question, because a substantial atmosphere would t...
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From LiDAR to Underground Maps via 5G - Business Models Enabling a System-of-Systems Approach to Mapping the Kankberg Mine
With ever-increasing productivity targets in mining operations, there is a growing interest in mining automation. The PIMM project addresses the fundamental challenge of network communication by constructing a pilot 5G network in the underground mine Kankberg. In this report, we discuss how such a 5G network could co...
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The number of realizations of a Laman graph
Laman graphs model planar frameworks that are rigid for a general choice of distances between the vertices. There are finitely many ways, up to isometries, to realize a Laman graph in the plane. Such realizations can be seen as solutions of systems of quadratic equations prescribing the distances between pairs of poi...
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UV Detector based on InAlN/GaN-on-Si HEMT Stack with Photo-to-Dark Current Ratio > 107
We demonstrate an InAlN/GaN-on-Si HEMT based UV detector with photo to dark current ratio > 107. Ti/Al/Ni/Au metal stack was evaporated and rapid thermal annealed for Ohmic contacts to the 2D electron gas (2DEG) at the InAlN/GaN interface while the channel + barrier was recess etched to a depth of 20 nm to pinch-off ...
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Deep Reinforcement Learning for Inquiry Dialog Policies with Logical Formula Embeddings
This paper is the first attempt to learn the policy of an inquiry dialog system (IDS) by using deep reinforcement learning (DRL). Most IDS frameworks represent dialog states and dialog acts with logical formulae. In order to make learning inquiry dialog policies more effective, we introduce a logical formula embeddin...
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Proof of Time's Arrow with Perfectly Chaotic Superdiffusion
The problem of Time's Arrow is rigorously solved in a certain microscopic system associated with a Hamiltonian using only information about the microscopic system. This microscopic system obeys an equation with time reversal symmetry. In detail, we prove that a symplectic map with time reversal symmetry is an Anosov ...
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Using Phone Sensors and an Artificial Neural Network to Detect Gait Changes During Drinking Episodes in the Natural Environment
Phone sensors could be useful in assessing changes in gait that occur with alcohol consumption. This study determined (1) feasibility of collecting gait-related data during drinking occasions in the natural environment, and (2) how gait-related features measured by phone sensors relate to estimated blood alcohol conc...
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A Lattice Model of Charge-Pattern-Dependent Polyampholyte Phase Separation
In view of recent intense experimental and theoretical interests in the biophysics of liquid-liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs), heteropolymer models with chain molecules configured as self-avoiding walks on the simple cubic lattice are constructed to study how phase behaviors ...
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"Noiseless" thermal noise measurement of atomic force microscopy cantilevers
When measuring quadratic values representative of random fluctuations, such as the thermal noise of Atomic Force Microscopy (AFM) cantilevers, the background measurement noise cannot be averaged to zero. We present a signal processing method that allows to get rid of this limitation using the ubiquitous optical beam ...
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A Forward Model at Purkinje Cell Synapses Facilitates Cerebellar Anticipatory Control
How does our motor system solve the problem of anticipatory control in spite of a wide spectrum of response dynamics from different musculo-skeletal systems, transport delays as well as response latencies throughout the central nervous system? To a great extent, our highly-skilled motor responses are a result of a re...
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De Rham and twisted cohomology of Oeljeklaus-Toma manifolds
Oeljeklaus-Toma (OT) manifolds are complex non-Kähler manifolds whose construction arises from specific number fields. In this note, we compute their de Rham cohomology in terms of invariants associated to the background number field. This is done by two distinct approaches, one using invariant cohomology and the oth...
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Episode-Based Active Learning with Bayesian Neural Networks
We investigate different strategies for active learning with Bayesian deep neural networks. We focus our analysis on scenarios where new, unlabeled data is obtained episodically, such as commonly encountered in mobile robotics applications. An evaluation of different strategies for acquisition, updating, and final tr...
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Origin of X-ray and gamma-ray emission from the Galactic central region
We study a possible connection between different non-thermal emissions from the inner few parsecs of the Galaxy. We analyze the origin of the gamma-ray source 2FGL J1745.6-2858 (or 3FGL J1745.6-2859c) in the Galactic Center and the diffuse hard X-ray component recently found by NuSTAR, as well as the radio emission a...
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Freeness and The Partial Transposes of Wishart Random Matrices
We show that the partial transposes of complex Wishart random matrices are asymptotically free. We also investigate regimes where the number of blocks is fixed but the size of the blocks increases. This gives a example where the partial transpose produces freeness at the operator level. Finally we investigate the cas...
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Coset space construction for the conformal group. I. Unbroken phase
The technique for constructing conformally invariant theories within the coset space construction is developed. It reproduces all consequences of the conformal invariance and Lagrangians of widely-known conformal field theories. The method of induced representations, which plays the key role in the construction, allo...
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Fixed points of polarity type operators
A well-known result says that the Euclidean unit ball is the unique fixed point of the polarity operator. This result implies that if, in $\mathbb{R}^n$, the unit ball of some norm is equal to the unit ball of the dual norm, then the norm must be Euclidean. Motivated by these results and by relatively recent results ...
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Multiple Improvements of Multiple Imputation Likelihood Ratio Tests
Multiple imputation (MI) inference handles missing data by first properly imputing the missing values $m$ times, and then combining the $m$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects...
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Estimating the unseen from multiple populations
Given samples from a distribution, how many new elements should we expect to find if we continue sampling this distribution? This is an important and actively studied problem, with many applications ranging from unseen species estimation to genomics. We generalize this extrapolation and related unseen estimation prob...
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Continued Fractions and $q$-Series Generating Functions for the Generalized Sum-of-Divisors Functions
We construct new continued fraction expansions of Jacobi-type J-fractions in $z$ whose power series expansions generate the ratio of the $q$-Pochhamer symbols, $(a; q)_n / (b; q)_n$, for all integers $n \geq 0$ and where $a,b,q \in \mathbb{C}$ are non-zero and defined such that $|q| < 1$ and $|b/a| < |z| < 1$. If we ...
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Implications of a wavelength dependent PSF for weak lensing measurements
The convolution of galaxy images by the point-spread function (PSF) is the dominant source of bias for weak gravitational lensing studies, and an accurate estimate of the PSF is required to obtain unbiased shape measurements. The PSF estimate for a galaxy depends on its spectral energy distribution (SED), because the...
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Improving TSP tours using dynamic programming over tree decomposition
Given a traveling salesman problem (TSP) tour $H$ in graph $G$ a $k$-move is an operation which removes $k$ edges from $H$, and adds $k$ edges of $G$ so that a new tour $H'$ is formed. The popular $k$-OPT heuristics for TSP finds a local optimum by starting from an arbitrary tour $H$ and then improving it by a sequen...
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