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Stability analysis of a system coupled to a heat equation
As a first approach to the study of systems coupling finite and infinite dimensional natures, this article addresses the stability of a system of ordinary differential equations coupled with a classic heat equation using a Lyapunov functional technique. Inspired from recent developments in the area of time delay syst...
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Corral Framework: Trustworthy and Fully Functional Data Intensive Parallel Astronomical Pipelines
Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. In this work we present Corral, a Python framework for astronomical pipeline generation. Corral features a Mod...
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Radial orbit instability in systems of highly eccentric orbits: Antonov problem reviewed
Stationary stellar systems with radially elongated orbits are subject to radial orbit instability -- an important phenomenon that structures galaxies. Antonov (1973) presented a formal proof of the instability for spherical systems in the limit of purely radial orbits. However, such spheres have highly inhomogeneous ...
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Short-range wakefields generated in the blowout regime of plasma-wakefield acceleration
In the past, calculation of wakefields generated by an electron bunch propagating in a plasma has been carried out in linear approximation, where the plasma perturbation can be assumed small and plasma equations of motion linearized. This approximation breaks down in the blowout regime where a high-density electron d...
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Scaled Nuclear Norm Minimization for Low-Rank Tensor Completion
Minimizing the nuclear norm of a matrix has been shown to be very efficient in reconstructing a low-rank sampled matrix. Furthermore, minimizing the sum of nuclear norms of matricizations of a tensor has been shown to be very efficient in recovering a low-Tucker-rank sampled tensor. In this paper, we propose to recov...
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Stability and Transparency Analysis of a Bilateral Teleoperation in Presence of Data Loss
This paper presents a novel approach for stability and transparency analysis for bilateral teleoperation in the presence of data loss in communication media. A new model for data loss is proposed based on a set of periodic continuous pulses and its finite series representation. The passivity of the overall system is ...
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Quantum eigenstate tomography with qubit tunneling spectroscopy
Measurement of the energy eigenvalues (spectrum) of a multi-qubit system has recently become possible by qubit tunneling spectroscopy (QTS). In the standard QTS experiments, an incoherent probe qubit is strongly coupled to one of the qubits of the system in such a way that its incoherent tunneling rate provides infor...
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Binary hermitian forms and optimal embeddings
Fix a quadratic order over the ring of integers. An embedding of the quadratic order into a quaternionic order naturally gives an integral binary hermitian form over the quadratic order. We show that, in certain cases, this correspondence is a discriminant preserving bijection between the isomorphism classes of embed...
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An Improved Training Procedure for Neural Autoregressive Data Completion
Neural autoregressive models are explicit density estimators that achieve state-of-the-art likelihoods for generative modeling. The D-dimensional data distribution is factorized into an autoregressive product of one-dimensional conditional distributions according to the chain rule. Data completion is a more involved ...
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A Stochastic Formulation of the Resolution of Identity: Application to Second Order Møller-Plesset Perturbation Theory
A stochastic orbital approach to the resolution of identity (RI) approximation for 4-index 2-electron electron repulsion integrals (ERIs) is presented. The stochastic RI-ERIs are then applied to M\o ller-Plesset perturbation theory (MP2) utilizing a \textit{multiple stochastic orbital approach}. The introduction of m...
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Automatic Mapping of NES Games with Mappy
Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation. These maps are generally made by hand-assembling manually-created screenshots of game levels. Besides being tedious and error-prone, this approach requires additional effort for each new game and level ...
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Proportional Closeness Estimation of Probability of Contamination Under Group Testing
The paper is focused on the problem of estimating the probability $p$ of individual contaminated sample, under group testing. The precision of the estimator is given by the probability of proportional closeness, a concept defined in the Introduction. Two-stage and sequential sampling procedures are characterized. An ...
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Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research
Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of learning semantic meaning and similarity between words in an entirely unsupervised manner using a contextual window and doing so much faster ...
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The AKARI IRC asteroid flux catalogue: updated diameters and albedos
The AKARI IRC All-sky survey provided more than twenty thousand thermal infrared observations of over five thousand asteroids. Diameters and albedos were obtained by fitting an empirically calibrated version of the standard thermal model to these data. After the publication of the flux catalogue in October 2016, our ...
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Finite sample Bernstein - von Mises theorems for functionals and spectral projectors of covariance matrix
We demonstrate that a prior influence on the posterior distribution of covariance matrix vanishes as sample size grows. The assumptions on a prior are explicit and mild. The results are valid for a finite sample and admit the dimension $p$ growing with the sample size $n$. We exploit the described fact to derive the ...
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Low-temperature behavior of the multicomponent Widom-Rowlison model on finite square lattices
We consider the multicomponent Widom-Rowlison with Metropolis dynamics, which describes the evolution of a particle system where $M$ different types of particles interact subject to certain hard-core constraints. Focusing on the scenario where the spatial structure is modeled by finite square lattices, we study the a...
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Stream Graphs and Link Streams for the Modeling of Interactions over Time
Graph theory provides a language for studying the structure of relations, and it is often used to study interactions over time too. However, it poorly captures the both temporal and structural nature of interactions, that calls for a dedicated formalism. In this paper, we generalize graph concepts in order to cope wi...
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Supermetric Search
Metric search is concerned with the efficient evaluation of queries in metric spaces. In general,a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most mechanisms rely upon the triangle inequality p...
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Liouville-type theorems with finite Morse index for Δ_λ-Laplace operator
In this paper we study solutions, possibly unbounded and sign-changing, of the following problem: -\D_{\lambda} u=|x|_{\lambda}^a |u|^{p-1}u, in R^n,\;n\geq 1,\; p>1, and a \geq 0, where \D_{\lambda} is a strongly degenerate elliptic operator, the functions \lambda=(\lambda_1, ..., \lambda_k) : R^n \rightarrow R^k, s...
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Performance Impact of Base Station Antenna Heights in Dense Cellular Networks
In this paper, we present a new and significant theoretical discovery. If the absolute height difference between base station (BS) antenna and user equipment (UE) antenna is larger than zero, then the network performance in terms of both the coverage probability and the area spectral efficiency (ASE) will continuousl...
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An information-theoretic approach for selecting arms in clinical trials
The question of selecting the "best" amongst different choices is a common problem in statistics. In drug development, our motivating setting, the question becomes, for example: what is the dose that gives me a pre-specified risk of toxicity or which treatment gives the best response rate. Motivated by a recent devel...
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A watershed-based algorithm to segment and classify cells in fluorescence microscopy images
Imaging assays of cellular function, especially those using fluorescent stains, are ubiquitous in the biological and medical sciences. Despite advances in computer vision, such images are often analyzed using only manual or rudimentary automated processes. Watershed-based segmentation is an effective technique for id...
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On the restricted Chebyshev-Boubaker polynomials
Using the language of Riordan arrays, we study a one-parameter family of orthogonal polynomials that we call the restricted Chebyshev-Boubaker polynomials. We characterize these polynomials in terms of the three term recurrences that they satisfy, and we study certain central sequences defined by their coefficient ar...
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Band filling control of the Dzyaloshinskii-Moriya interaction in weakly ferromagnetic insulators
We observe and explain theoretically a dramatic evolution of the Dzyaloshinskii-Moriya interaction in the series of isostructural weak ferromagnets, MnCO$_3$, FeBO$_3$, CoCO$_3$ and NiCO$_3$. The sign of the interaction is encoded in the phase of x-ray magnetic diffraction amplitude, observed through interference wit...
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Reducing Estimation Risk in Mean-Variance Portfolios with Machine Learning
In portfolio analysis, the traditional approach of replacing population moments with sample counterparts may lead to suboptimal portfolio choices. I show that optimal portfolio weights can be estimated using a machine learning (ML) framework, where the outcome to be predicted is a constant and the vector of explanato...
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CutFEM topology optimization of 3D laminar incompressible flow problems
This paper studies the characteristics and applicability of the CutFEM approach as the core of a robust topology optimization framework for 3D laminar incompressible flow and species transport problems at low Reynolds number (Re < 200). CutFEM is a methodology for discretizing partial differential equations on comple...
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Network topology of neural systems supporting avalanche dynamics predicts stimulus propagation and recovery
Many neural systems display avalanche behavior characterized by uninterrupted sequences of neuronal firing whose distributions of size and durations are heavy-tailed. Theoretical models of such systems suggest that these dynamics support optimal information transmission and storage. However, the unknown role of netwo...
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Comparison of ontology alignment systems across single matching task via the McNemar's test
Ontology alignment is widely-used to find the correspondences between different ontologies in diverse fields.After discovering the alignments,several performance scores are available to evaluate them.The scores typically require the identified alignment and a reference containing the underlying actual correspondences...
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Polarizability Extraction for Waveguide-Fed Metasurfaces
We consider the design and modeling of metasurfaces that couple energy from guided waves to propagating wavefronts. This is a first step towards a comprehensive, multiscale modeling platform for metasurface antennas-large arrays of metamaterial elements embedded in a waveguide structure that radiates into free-space-...
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Connection Scan Algorithm
We introduce the Connection Scan Algorithm (CSA) to efficiently answer queries to timetable information systems. The input consists, in the simplest setting, of a source position and a desired target position. The output consist is a sequence of vehicles such as trains or buses that a traveler should take to get from...
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A Proof of Orthogonal Double Machine Learning with $Z$-Estimators
We consider two stage estimation with a non-parametric first stage and a generalized method of moments second stage, in a simpler setting than (Chernozhukov et al. 2016). We give an alternative proof of the theorem given in (Chernozhukov et al. 2016) that orthogonal second stage moments, sample splitting and $n^{1/4}...
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Quantile Treatment Effects in Difference in Differences Models under Dependence Restrictions and with only Two Time Periods
This paper shows that the Conditional Quantile Treatment Effect on the Treated can be identified using a combination of (i) a conditional Distributional Difference in Differences assumption and (ii) an assumption on the conditional dependence between the change in untreated potential outcomes and the initial level of...
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Coppersmith's lattices and "focus groups": an attack on small-exponent RSA
We present a principled technique for reducing the matrix size in some applications of Coppersmith's lattice method for finding roots of modular polynomial equations. It relies on an analysis of the actual performance of Coppersmith's attack for smaller parameter sizes, which can be thought of as "focus group" testin...
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Gas vs. solid phase deuterated chemistry: HDCO and D$_2$CO in massive star-forming regions
The formation of deuterated molecules is favoured at low temperatures and high densities. Therefore, the deuteration fraction D$_{frac}$ is expected to be enhanced in cold, dense prestellar cores and to decrease after protostellar birth. Previous studies have shown that the deuterated forms of species such as N2H+ (f...
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Improved stability of optimal traffic paths
Models involving branched structures are employed to describe several supply-demand systems such as the structure of the nerves of a leaf, the system of roots of a tree and the nervous or cardiovascular systems. Given a flow (traffic path) that transports a given measure $\mu^-$ onto a target measure $\mu^+$, along a...
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Neural Code Comprehension: A Learnable Representation of Code Semantics
With the recent success of embeddings in natural language processing, research has been conducted into applying similar methods to code analysis. Most works attempt to process the code directly or use a syntactic tree representation, treating it like sentences written in a natural language. However, none of the exist...
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Electron conduction in solid state via time varying wavevectors
In this paper, we study electron wavepacket dynamics in electric and magnetic fields. We rigorously derive the semiclassical equations of electron dynamics in electric and magnetic fields. We do it both for free electron and electron in a periodic potential. We do this by introducing time varying wavevectors $k(t)$. ...
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On blowup of co-rotational wave maps in odd space dimensions
We consider co-rotational wave maps from the $(1+d)$-dimensional Minkowski space into the $d$-sphere for $d\geq 3$ odd. This is an energy-supercritical model which is known to exhibit finite-time blowup via self-similar solutions. Based on a method developed by the second author and Schörkhuber, we prove the asymptot...
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The Young Substellar Companion ROXs 12 B: Near-Infrared Spectrum, System Architecture, and Spin-Orbit Misalignment
ROXs 12 (2MASS J16262803-2526477) is a young star hosting a directly imaged companion near the deuterium-burning limit. We present a suite of spectroscopic, imaging, and time-series observations to characterize the physical and environmental properties of this system. Moderate-resolution near-infrared spectroscopy of...
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Connecting dissipation and phase slips in a Josephson junction between fermionic superfluids
We study the emergence of dissipation in an atomic Josephson junction between weakly-coupled superfluid Fermi gases. We find that vortex-induced phase slippage is the dominant microscopic source of dissipation across the BEC-BCS crossover. We explore different dynamical regimes by tuning the bias chemical potential b...
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Satellite conjunction analysis and the false confidence theorem
Satellite conjunction analysis is the assessment of collision risk during a close encounter between a satellite and another object in orbit. A counterintuitive phenomenon has emerged in the conjunction analysis literature: probability dilution, in which lower quality data paradoxically appear to reduce the risk of co...
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A formula goes to court: Partisan gerrymandering and the efficiency gap
Recently, a proposal has been advanced to detect unconstitutional partisan gerrymandering with a simple formula called the efficiency gap. The efficiency gap is now working its way towards a possible landmark case in the Supreme Court. This note explores some of its mathematical properties in light of the fact that i...
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Quantitative aspects of linear and affine closed lambda terms
Affine $\lambda$-terms are $\lambda$-terms in which each bound variable occurs at most once and linear $\lambda$-terms are $\lambda$-terms in which each bound variables occurs once. and only once. In this paper we count the number of closed affine $\lambda$-terms of size $n$, closed linear $\lambda$-terms of size $n$...
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Drug response prediction by ensemble learning and drug-induced gene expression signatures
Chemotherapeutic response of cancer cells to a given compound is one of the most fundamental information one requires to design anti-cancer drugs. Recent advances in producing large drug screens against cancer cell lines provided an opportunity to apply machine learning methods for this purpose. In addition to cytoto...
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Eigenvalue approximation of sums of Hermitian matrices from eigenvector localization/delocalization
We propose a technique for calculating and understanding the eigenvalue distribution of sums of random matrices from the known distribution of the summands. The exact problem is formidably hard. One extreme approximation to the true density amounts to classical probability, in which the matrices are assumed to commut...
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Some Ultraspheroidal Monogenic Clifford Gegenbauer Jacobi Polynomials and Associated Wavelets
In the present paper, new classes of wavelet functions are presented in the framework of Clifford analysis. Firstly, some classes of orthogonal polynomials are provided based on 2-parameters weight functions. Such classes englobe the well known ones of Jacobi and Gegenbauer polynomials when relaxing one of the parame...
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Gait learning for soft microrobots controlled by light fields
Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize their locomotion performance in a given environment and used to adapt them to changing conditions. Albeit, because of the lack of accurat...
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Evolution of Nagaoka phase with kinetic energy frustrating hoppings
We investigate, using the density matrix renormalization group, the evolution of the Nagaoka state with $t'$ hoppings that frustrate the hole kinetic energy in the $U=\infty$ Hubbard model on the anisotropic triangular lattice and the square lattice with second-nearest neighbor hoppings. We find that the Nagaoka ferr...
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Blocking Transferability of Adversarial Examples in Black-Box Learning Systems
Advances in Machine Learning (ML) have led to its adoption as an integral component in many applications, including banking, medical diagnosis, and driverless cars. To further broaden the use of ML models, cloud-based services offered by Microsoft, Amazon, Google, and others have developed ML-as-a-service tools as bl...
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Analytic continuation of Wolynes theory into the Marcus inverted regime
The Wolynes theory of electronically nonadiabatic reaction rates [P. G. Wolynes, J. Chem. Phys. 87, 6559 (1987)] is based on a saddle point approximation to the time integral of a reactive flux autocorrelation function in the nonadiabatic (golden rule) limit. The dominant saddle point is on the imaginary time axis at...
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JDFTx: software for joint density-functional theory
Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- ...
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Experimental realization of purely excitonic lasing in ZnO microcrystals at room temperature: transition from exciton-exciton to exciton-electron scattering
Since the seminal observation of room-temperature laser emission from ZnO thin films and nanowires, numerous attempts have been carried out for detailed understanding of the lasing mechanism in ZnO. In spite of the extensive efforts performed over the last decades, the origin of optical gain at room temperature is st...
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Selective probing of hidden spin-polarized states in inversion-symmetric bulk MoS2
Spin- and angle-resolved photoemission spectroscopy is used to reveal that a large spin polarization is observable in the bulk centrosymmetric transition metal dichalcogenide MoS2. It is found that the measured spin polarization can be reversed by changing the handedness of incident circularly-polarized light. Calcul...
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Classification without labels: Learning from mixed samples in high energy physics
Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the simulation. In thi...
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Semantic Annotation for Microblog Topics Using Wikipedia Temporal Information
Trending topics in microblogs such as Twitter are valuable resources to understand social aspects of real-world events. To enable deep analyses of such trends, semantic annotation is an effective approach; yet the problem of annotating microblog trending topics is largely unexplored by the research community. In this...
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Twin-beam real-time position estimation of micro-objects in 3D
Various optical methods for measuring positions of micro-objects in 3D have been reported in the literature. Nevertheless, majority of them are not suitable for real-time operation, which is needed, for example, for feedback position control. In this paper, we present a method for real-time estimation of the position...
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Asymmetric metallicity patterns in the stellar velocity space with RAVE
We explore the correlations between velocity and metallicity and the possible distinct chemical signatures of the velocity over-densities of the local Galactic neighbourhood. We use the large spectroscopic survey RAVE and the Geneva Copenhagen Survey. We compare the metallicity distribution of regions in the velocity...
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End-to-End Attention based Text-Dependent Speaker Verification
A new type of End-to-End system for text-dependent speaker verification is presented in this paper. Previously, using the phonetically discriminative/speaker discriminative DNNs as feature extractors for speaker verification has shown promising results. The extracted frame-level (DNN bottleneck, posterior or d-vector...
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Automated Discovery of Process Models from Event Logs: Review and Benchmark
Process mining allows analysts to exploit logs of historical executions of business processes to extract insights regarding the actual performance of these processes. One of the most widely studied process mining operations is automated process discovery. An automated process discovery method takes as input an event ...
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Criteria for strict monotonicity of the mixed volume of convex polytopes
Let $P_1,\dots, P_n$ and $Q_1,\dots, Q_n$ be convex polytopes in $\mathbb{R}^n$ such that $P_i\subset Q_i$. It is well-known that the mixed volume has the monotonicity property: $V(P_1,\dots,P_n)\leq V(Q_1,\dots,Q_n)$. We give two criteria for when this inequality is strict in terms of essential collections of faces ...
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Colorings with Fractional Defect
Consider a coloring of a graph such that each vertex is assigned a fraction of each color, with the total amount of colors at each vertex summing to $1$. We define the fractional defect of a vertex $v$ to be the sum of the overlaps with each neighbor of $v$, and the fractional defect of the graph to be the maximum of...
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The new concepts of measurement error's regularities and effect characteristics
In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error's regularities and effect charac...
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The cavity approach for Steiner trees packing problems
The Belief Propagation approximation, or cavity method, has been recently applied to several combinatorial optimization problems in its zero-temperature implementation, the max-sum algorithm. In particular, recent developments to solve the edge-disjoint paths problem and the prize-collecting Steiner tree problem on g...
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Observational Learning by Reinforcement Learning
Observational learning is a type of learning that occurs as a function of observing, retaining and possibly replicating or imitating the behaviour of another agent. It is a core mechanism appearing in various instances of social learning and has been found to be employed in several intelligent species, including huma...
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P4-compatible High-level Synthesis of Low Latency 100 Gb/s Streaming Packet Parsers in FPGAs
Packet parsing is a key step in SDN-aware devices. Packet parsers in SDN networks need to be both reconfigurable and fast, to support the evolving network protocols and the increasing multi-gigabit data rates. The combination of packet processing languages with FPGAs seems to be the perfect match for these requiremen...
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Uniruledness of Strata of Holomorphic Differentials in Small Genus
We address the question concerning the birational geometry of the strata of holomorphic and quadratic differentials. We show strata of holomorphic and quadratic differentials to be uniruled in small genus by constructing rational curves via pencils on K3 and del Pezzo surfaces respectively. Restricting to genus $3\le...
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Conservation laws, vertex corrections, and screening in Raman spectroscopy
We present a microscopic theory for the Raman response of a clean multiband superconductor accounting for the effects of vertex corrections and long-range Coulomb interaction. The measured Raman intensity, $R(\Omega)$, is proportional to the imaginary part of the fully renormalized particle-hole correlator with Raman...
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The distribution of symmetry of a naturally reductive nilpotent Lie group
We show that the distribution of symmetry of a naturally reductive nilpotent Lie group coincides with the invariant distribution induced by the set of fixed vectors of the isotropy. This extends a known result on compact naturally reductive spaces. We also address the study of the quotient by the foliation of symmetr...
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Odd-integer quantum Hall states and giant spin susceptibility in p-type few-layer WSe2
We fabricate high-mobility p-type few-layer WSe2 field-effect transistors and surprisingly observe a series of quantum Hall (QH) states following an unconventional sequence predominated by odd-integer states under a moderate strength magnetic field. By tilting the magnetic field, we discover Landau level (LL) crossin...
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Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning
In the field of reinforcement learning there has been recent progress towards safety and high-confidence bounds on policy performance. However, to our knowledge, no practical methods exist for determining high-confidence policy performance bounds in the inverse reinforcement learning setting---where the true reward f...
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Face Identification and Clustering
In this thesis, we study two problems based on clustering algorithms. In the first problem, we study the role of visual attributes using an agglomerative clustering algorithm to whittle down the search area where the number of classes is high to improve the performance of clustering. We observe that as we add more at...
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Properties of Hydrogen Bonds in the Protic Ionic Liquid Ethylammonium Nitrate. DFT versus DFTB Molecular Dynamics
Comparative molecular dynamics simulations of a hexamer cluster of the protic ionic liquid ethylammonium nitrate are performed using density functional theory (DFT) and density functional-based tight binding (DFTB) methods. The focus is on assessing the performance of the DFTB approach to describe the dynamics and in...
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On Abruptly-Changing and Slowly-Varying Multiarmed Bandit Problems
We study the non-stationary stochastic multiarmed bandit (MAB) problem and propose two generic algorithms, namely, the limited memory deterministic sequencing of exploration and exploitation (LM-DSEE) and the Sliding-Window Upper Confidence Bound# (SW-UCB#). We rigorously analyze these algorithms in abruptly-changing...
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Validation of small Kepler transiting planet candidates in or near the habitable zone
A main goal of NASA's Kepler Mission is to establish the frequency of potentially habitable Earth-size planets (eta Earth). Relatively few such candidates identified by the mission can be confirmed to be rocky via dynamical measurement of their mass. Here we report an effort to validate 18 of them statistically using...
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CP-decomposition with Tensor Power Method for Convolutional Neural Networks Compression
Convolutional Neural Networks (CNNs) has shown a great success in many areas including complex image classification tasks. However, they need a lot of memory and computational cost, which hinders them from running in relatively low-end smart devices such as smart phones. We propose a CNN compression method based on C...
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Stoic Ethics for Artificial Agents
We present a position paper advocating the notion that Stoic philosophy and ethics can inform the development of ethical A.I. systems. This is in sharp contrast to most work on building ethical A.I., which has focused on Utilitarian or Deontological ethical theories. We relate ethical A.I. to several core Stoic notio...
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From quarks to nucleons in dark matter direct detection
We provide expressions for the nonperturbative matching of the effective field theory describing dark matter interactions with quarks and gluons to the effective theory of nonrelativistic dark matter interacting with nonrelativistic nucleons. We give the leading and subleading order expressions in chiral counting. In...
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Sharpened Strichartz estimates and bilinear restriction for the mass-critical quantum harmonic oscillator
We develop refined Strichartz estimates at $L^2$ regularity for a class of time-dependent Schrödinger operators. Such refinements begin to characterize the near-optimizers of the Strichartz estimate, and play a pivotal part in the global theory of mass-critical NLS. On one hand, the harmonic analysis is quite subtle ...
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A fast and stable test to check if a weakly diagonally dominant matrix is a nonsingular M-matrix
We present a test for determining if a substochastic matrix is convergent. By establishing a duality between weakly chained diagonally dominant (w.c.d.d.) L-matrices and convergent substochastic matrices, we show that this test can be trivially extended to determine whether a weakly diagonally dominant (w.d.d.) matri...
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Task-Oriented Query Reformulation with Reinforcement Learning
Search engines play an important role in our everyday lives by assisting us in finding the information we need. When we input a complex query, however, results are often far from satisfactory. In this work, we introduce a query reformulation system based on a neural network that rewrites a query to maximize the numbe...
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Inverse scattering transform for the nonlocal reverse space-time Sine-Gordon, Sinh-Gordon and nonlinear Schrödinger equations with nonzero boundary conditions
The reverse space-time (RST) Sine-Gordon, Sinh-Gordon and nonlinear Schrödinger equations were recently introduced and shown to be integrable infinite-dimensional dynamical systems. The inverse scattering transform (IST) for rapidly decaying data was also constructed. In this paper, IST for these equations with nonze...
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Relieving the frustration through Mn$^{3+}$ substitution in Holmium Gallium Garnet
We present a study on the impact of Mn$^{3+}$ substitution in the geometrically frustrated Ising garnet Ho$_3$Ga$_5$O$_{12}$ using bulk magnetic measurements and low temperature powder neutron diffraction. We find that the transition temperature, $T_N$ = 5.8 K, for Ho$_3$MnGa$_4$O$_{12}$ is raised by almost 20 when c...
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Inference on Auctions with Weak Assumptions on Information
Given a sample of bids from independent auctions, this paper examines the question of inference on auction fundamentals (e.g. valuation distributions, welfare measures) under weak assumptions on information structure. The question is important as it allows us to learn about the valuation distribution in a robust way,...
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Introduction to OXPath
Contemporary web pages with increasingly sophisticated interfaces rival traditional desktop applications for interface complexity and are often called web applications or RIA (Rich Internet Applications). They often require the execution of JavaScript in a web browser and can call AJAX requests to dynamically generat...
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Image Registration for the Alignment of Digitized Historical Documents
In this work, we conducted a survey on different registration algorithms and investigated their suitability for hyperspectral historical image registration applications. After the evaluation of different algorithms, we choose an intensity based registration algorithm with a curved transformation model. For the transf...
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Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification
Person Re-Identification (person re-id) is a crucial task as its applications in visual surveillance and human-computer interaction. In this work, we present a novel joint Spatial and Temporal Attention Pooling Network (ASTPN) for video-based person re-identification, which enables the feature extractor to be aware o...
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Inertia, positive definiteness and $\ell_p$ norm of GCD and LCM matrices and their unitary analogs
Let $S=\{x_1,x_2,\dots,x_n\}$ be a set of distinct positive integers, and let $f$ be an arithmetical function. The GCD matrix $(S)_f$ on $S$ associated with $f$ is defined as the $n\times n$ matrix having $f$ evaluated at the greatest common divisor of $x_i$ and $x_j$ as its $ij$ entry. The LCM matrix $[S]_f$ is defi...
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Low-Latency Millimeter-Wave Communications: Traffic Dispersion or Network Densification?
This paper investigates two strategies to reduce the communication delay in future wireless networks: traffic dispersion and network densification. A hybrid scheme that combines these two strategies is also considered. The probabilistic delay and effective capacity are used to evaluate performance. For probabilistic ...
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The structure of multiplicative tilings of the real line
Suppose $\Omega, A \subseteq \RR\setminus\Set{0}$ are two sets, both of mixed sign, that $\Omega$ is Lebesgue measurable and $A$ is a discrete set. We study the problem of when $A \cdot \Omega$ is a (multiplicative) tiling of the real line, that is when almost every real number can be uniquely written as a product $a...
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Supporting Crowd-Powered Science in Economics: FRACTI, a Conceptual Framework for Large-Scale Collaboration and Transparent Investigation in Financial Markets
Modern investigation in economics and in other sciences requires the ability to store, share, and replicate results and methods of experiments that are often multidisciplinary and yield a massive amount of data. Given the increasing complexity and growing interaction across diverse bodies of knowledge it is becoming ...
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The effect of temperature on generic stable periodic structures in the parameter space of dissipative relativistic standard map
In this work, we have characterized changes in the dynamics of a two-dimensional relativistic standard map in the presence of dissipation and specially when it is submitted to thermal effects modeled by a Gaussian noise reservoir. By the addition of thermal noise in the dissipative relativistic standard map (DRSM) it...
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The $u^n$-invariant and the Symbol Length of $H_2^n(F)$
Given a field $F$ of $\operatorname{char}(F)=2$, we define $u^n(F)$ to be the maximal dimension of an anisotropic form in $I_q^n F$. For $n=1$ it recaptures the definition of $u(F)$. We study the relations between this value and the symbol length of $H_2^n(F)$, denoted by $sl_2^n(F)$. We show for any $n \geq 2$ that ...
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An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario
Being able to recognize emotions in human users is considered a highly desirable trait in Human-Robot Interaction (HRI) scenarios. However, most contemporary approaches rarely attempt to apply recognized emotional features in an active manner to modulate robot decision-making and dialogue for the benefit of the user....
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Rao-Blackwellization to give Improved Estimates in Multi-List Studies
Sufficient statistics are derived for the population size and parameters of commonly used closed population mark-recapture models. Rao-Blackwellization details for improving estimators that are not functions of the statistics are presented. As Rao-Blackwellization entails enumerating all sample reorderings consistent...
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Bernstein Polynomial Model for Nonparametric Multivariate Density
In this paper, we study the Bernstein polynomial model for estimating the multivariate distribution functions and densities with bounded support. As a mixture model of multivariate beta distributions, the maximum (approximate) likelihood estimate can be obtained using EM algorithm. A change-point method of choosing o...
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Small-space encoding LCE data structure with constant-time queries
The \emph{longest common extension} (\emph{LCE}) problem is to preprocess a given string $w$ of length $n$ so that the length of the longest common prefix between suffixes of $w$ that start at any two given positions is answered quickly. In this paper, we present a data structure of $O(z \tau^2 + \frac{n}{\tau})$ wor...
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Machine learning application in the life time of materials
Materials design and development typically takes several decades from the initial discovery to commercialization with the traditional trial and error development approach. With the accumulation of data from both experimental and computational results, data based machine learning becomes an emerging field in materials...
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A Unified Framework for Stochastic Matrix Factorization via Variance Reduction
We propose a unified framework to speed up the existing stochastic matrix factorization (SMF) algorithms via variance reduction. Our framework is general and it subsumes several well-known SMF formulations in the literature. We perform a non-asymptotic convergence analysis of our framework and derive computational an...
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Short Term Power Demand Prediction Using Stochastic Gradient Boosting
Power prediction demand is vital in power system and delivery engineering fields. By efficiently predicting the power demand, we can forecast the total energy to be consumed in a certain city or district. Thus, exact resources required to produce the demand power can be allocated. In this paper, a Stochastic Gradient...
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Learning Qualitatively Diverse and Interpretable Rules for Classification
There has been growing interest in developing accurate models that can also be explained to humans. Unfortunately, if there exist multiple distinct but accurate models for some dataset, current machine learning methods are unlikely to find them: standard techniques will likely recover a complex model that combines th...
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