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Doubly autoparallel structure on the probability simplex
On the probability simplex, we can consider the standard information geometric structure with the e- and m-affine connections mutually dual with respect to the Fisher metric. The geometry naturally defines submanifolds simultaneously autoparallel for the both affine connections, which we call {\em doubly autoparallel...
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Probing Hidden Spin Order with Interpretable Machine Learning
The search of unconventional magnetic and non-magnetic states is a major topic in the study of frustrated magnetism. Canonical examples of those states include various spin liquids and spin nematics. However, discerning their existence and the correct characterization is usually challenging. Here we introduce a machi...
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Maximum a Posteriori Joint State Path and Parameter Estimation in Stochastic Differential Equations
A wide variety of phenomena of engineering and scientific interest are of a continuous-time nature and can be modeled by stochastic differential equations (SDEs), which represent the evolution of the uncertainty in the states of a system. For systems of this class, some parameters of the SDE might be unknown and the ...
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Spreading of an infectious disease between different locations
The endogenous adaptation of agents, that may adjust their local contact network in response to the risk of being infected, can have the perverse effect of increasing the overall systemic infectiveness of a disease. We study a dynamical model over two geographically distinct but interacting locations, to better under...
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Observation and calculation of the quasi-bound rovibrational levels of the electronic ground state of H$_2^+$
Although the existence of quasi-bound rotational levels of the $X^+ \ ^2\Sigma_g^+$ ground state of H$_2^+$ has been predicted a long time ago, these states have never been observed. Calculated positions and widths of quasi-bound rotational levels located close to the top of the centrifugal barriers have not been rep...
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A case study of hurdle and generalized additive models in astronomy: the escape of ionizing radiation
The dark ages of the Universe end with the formation of the first generation of stars residing in primeval galaxies. These objects were the first to produce ultraviolet ionizing photons in a period when the cosmic gas changed from a neutral state to an ionized one, known as Epoch of Reionization (EoR). A pivotal aspe...
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Out-of-focus: Learning Depth from Image Bokeh for Robotic Perception
In this project, we propose a novel approach for estimating depth from RGB images. Traditionally, most work uses a single RGB image to estimate depth, which is inherently difficult and generally results in poor performance, even with thousands of data examples. In this work, we alternatively use multiple RGB images t...
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Iterative Machine Teaching
In this paper, we consider the problem of machine teaching, the inverse problem of machine learning. Different from traditional machine teaching which views the learners as batch algorithms, we study a new paradigm where the learner uses an iterative algorithm and a teacher can feed examples sequentially and intellig...
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GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Directed latent variable models that formulate the joint distribution as $p(x,z) = p(z) p(x \mid z)$ have the advantage of fast and exact sampling. However, these models have the weakness of needing to specify $p(z)$, often with a simple fixed prior that limits the expressiveness of the model. Undirected latent varia...
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Characterization of 1-Tough Graphs using Factors
For a graph $G$, let $odd(G)$ and $\omega(G)$ denote the number of odd components and the number of components of $G$, respectively. Then it is well-known that $G$ has a 1-factor if and only if $odd(G-S)\le |S|$ for all $S\subset V(G)$. Also it is clear that $odd(G-S) \le \omega(G-S)$. In this paper we characterize a...
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Optimization by gradient boosting
Gradient boosting is a state-of-the-art prediction technique that sequentially produces a model in the form of linear combinations of simple predictors---typically decision trees---by solving an infinite-dimensional convex optimization problem. We provide in the present paper a thorough analysis of two widespread ver...
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RDV: Register, Deposit, Vote: Secure and Decentralized Consensus Mechanism for Blockchain Networks
A decentralized payment system is not secure if transactions are transferred directly between clients. In such a situation it is not possible to prevent a client from redeeming some coins twice in separate transactions that means a double-spending attack. Bitcoin uses a simple method to preventing this attack i.e. al...
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The Rees algebra of a two-Borel ideal is Koszul
Let $M$ and $N$ be two monomials of the same degree, and let $I$ be the smallest Borel ideal containing $M$ and $N$. We show that the toric ring of $I$ is Koszul by constructing a quadratic Gröbner basis for the associated toric ideal. Our proofs use the construction of graphs corresponding to fibers of the toric map...
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A forward--backward random process for the spectrum of 1D Anderson operators
We give a new expression for the law of the eigenvalues of the discrete Anderson model on the finite interval $[0,N]$, in terms of two random processes starting at both ends of the interval. Using this formula, we deduce that the tail of the eigenvectors behaves approximatelylike $\exp(\sigma B\_{|n-k|}-\gamma\frac{|...
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From Curves to Tropical Jacobians and Back
Given a curve defined over an algebraically closed field which is complete with respect to a nontrivial valuation, we study its tropical Jacobian. This is done by first tropicalizing the curve, and then computing the Jacobian of the resulting weighted metric graph. In general, it is not known how to find the abstract...
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Importance sampling the union of rare events with an application to power systems analysis
We consider importance sampling to estimate the probability $\mu$ of a union of $J$ rare events $H_j$ defined by a random variable $\boldsymbol{x}$. The sampler we study has been used in spatial statistics, genomics and combinatorics going back at least to Karp and Luby (1983). It works by sampling one event at rando...
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Estimating the sensitivity of centrality measures w.r.t. measurement errors
Most network studies rely on an observed network that differs from the underlying network which is obfuscated by measurement errors. It is well known that such errors can have a severe impact on the reliability of network metrics, especially on centrality measures: a more central node in the observed network might be...
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Matrix product moments in normal variables
Let ${\cal X }=XX^{\prime}$ be a random matrix associated with a centered $r$-column centered Gaussian vector $X$ with a covariance matrix $P$. In this article we compute expectations of matrix-products of the form $\prod_{1\leq i\leq n}({\cal X } P^{v_i})$ for any $n\geq 1$ and any multi-index parameters $v_i\in\mat...
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Asymptotics and Optimal Bandwidth Selection for Nonparametric Estimation of Density Level Sets
Bandwidth selection is crucial in the kernel estimation of density level sets. Risk based on the symmetric difference between the estimated and true level sets is usually used to measure their proximity. In this paper we provide an asymptotic $L^p$ approximation to this risk, where $p$ is characterized by the weight ...
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Population-specific design of de-immunized protein biotherapeutics
Immunogenicity is a major problem during the development of biotherapeutics since it can lead to rapid clearance of the drug and adverse reactions. The challenge for biotherapeutic design is therefore to identify mutants of the protein sequence that minimize immunogenicity in a target population whilst retaining phar...
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Linearized Binary Regression
Probit regression was first proposed by Bliss in 1934 to study mortality rates of insects. Since then, an extensive body of work has analyzed and used probit or related binary regression methods (such as logistic regression) in numerous applications and fields. This paper provides a fresh angle to such well-establish...
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Arithmetic properties of polynomials
In this paper, first, we prove that the Diophantine system \[f(z)=f(x)+f(y)=f(u)-f(v)=f(p)f(q)\] has infinitely many integer solutions for $f(X)=X(X+a)$ with nonzero integers $a\equiv 0,1,4\pmod{5}$. Second, we show that the above Diophantine system has an integer parametric solution for $f(X)=X(X+a)$ with nonzero in...
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A Graph Analytics Framework for Ranking Authors, Papers and Venues
A lot of scientific works are published in different areas of science, technology, engineering and mathematics. It is not easy, even for experts, to judge the quality of authors, papers and venues (conferences and journals). An objective measure to assign scores to these entities and to rank them is very useful. Alth...
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Inner Cohomology of the General Linear Group
The main theorem is incorrectly stated.
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Particle-hole symmetry and composite fermions in fractional quantum Hall states
We study fractional quantum Hall states at filling fractions in the Jain sequences using the framework of composite Dirac fermions. Synthesizing previous work, we write down an effective field theory consistent with all symmetry requirements, including Galilean invariance and particle-hole symmetry. Employing a Fermi...
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Large-type Artin groups are systolic
We prove that Artin groups from a class containing all large-type Artin groups are systolic. This provides a concise yet precise description of their geometry. Immediate consequences are new results concerning large-type Artin groups: biautomaticity; existence of $EZ$-boundaries; the Novikov conjecture; descriptions ...
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Gradient Sensing via Cell Communication
The chemotactic dynamics of cells and organisms that have no specialized gradient sensing organelles is not well understood. In fact, chemotaxis of this sort of organism is especially challenging to explain when the external chemical gradient is so small as to make variations of concentrations minute over the length ...
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Nichols Algebras and Quantum Principal Bundles
A general procedure for constructing Yetter-Drinfeld modules from quantum principal bundles is introduced. As an application a Yetter-Drinfeld structure is put on the cotangent space of the Heckenberger-Kolb calculi of the quantum Grassmannians. For the special case of quantum projective space the associated braiding...
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Inference of signals with unknown correlation structure from nonlinear measurements
We present a method to reconstruct autocorrelated signals together with their autocorrelation structure from nonlinear, noisy measurements for arbitrary monotonous nonlinear instrument response. In the presented formulation the algorithm provides a significant speedup compared to prior implementations, allowing for a...
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An optimization approach for dynamical Tucker tensor approximation
An optimization-based approach for the Tucker tensor approximation of parameter-dependent data tensors and solutions of tensor differential equations with low Tucker rank is presented. The problem of updating the tensor decomposition is reformulated as fitting problem subject to the tangent space without relying on a...
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Optical and structural study of the pressure-induced phase transition of CdWO$_4$
The optical absorption of CdWO$_4$ is reported at high pressures up to 23 GPa. The onset of a phase transition was detected at 19.5 GPa, in good agreement with a previous Raman spectroscopy study. The crystal structure of the high-pressure phase of CdWO$_4$ was solved at 22 GPa employing single-crystal synchrotron x-...
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Learning Context-Sensitive Convolutional Filters for Text Processing
Convolutional neural networks (CNNs) have recently emerged as a popular building block for natural language processing (NLP). Despite their success, most existing CNN models employed in NLP share the same learned (and static) set of filters for all input sentences. In this paper, we consider an approach of using a sm...
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On right $S$-Noetherian rings and $S$-Noetherian modules
In this paper we study right $S$-Noetherian rings and modules, extending of notions introduced by Anderson and Dumitrescu in commutative algebra to noncommutative rings. Two characterizations of right $S$-Noetherian rings are given in terms of completely prime right ideals and point annihilator sets. We also prove an...
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Reconfiguration of Brain Network between Resting-state and Oddball Paradigm
The oddball paradigm is widely applied to the investigation of multiple cognitive functions. Prior studies have explored the cortical oscillation and power spectral differing from the resting-state conduction to oddball paradigm, but whether brain networks existing the significant difference is still unclear. Our stu...
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Approximate Ranking from Pairwise Comparisons
A common problem in machine learning is to rank a set of n items based on pairwise comparisons. Here ranking refers to partitioning the items into sets of pre-specified sizes according to their scores, which includes identification of the top-k items as the most prominent special case. The score of a given item is de...
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Optimised information gathering in smartphone users
Human activities from hunting to emailing are performed in a fractal-like scale invariant pattern. These patterns are considered efficient for hunting or foraging, but are they efficient for gathering information? Here we link the scale invariant pattern of inter-touch intervals on the smartphone to optimal strategie...
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On Recoverable and Two-Stage Robust Selection Problems with Budgeted Uncertainty
In this paper the problem of selecting $p$ out of $n$ available items is discussed, such that their total cost is minimized. We assume that costs are not known exactly, but stem from a set of possible outcomes. Robust recoverable and two-stage models of this selection problem are analyzed. In the two-stage problem, u...
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Sparsity/Undersampling Tradeoffs in Anisotropic Undersampling, with Applications in MR Imaging/Spectroscopy
We study anisotropic undersampling schemes like those used in multi-dimensional NMR spectroscopy and MR imaging, which sample exhaustively in certain time dimensions and randomly in others. Our analysis shows that anisotropic undersampling schemes are equivalent to certain block-diagonal measurement systems. We devel...
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Multi-way sparsest cut problem on trees with a control on the number of parts and outliers
Given a graph, the sparsest cut problem asks for a subset of vertices whose edge expansion (the normalized cut given by the subset) is minimized. In this paper, we study a generalization of this problem seeking for $ k $ disjoint subsets of vertices (clusters) whose all edge expansions are small and furthermore, the ...
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Gallucci's axiom revisited
In this paper we propose a well-justified synthetic approach of the projective space. We define the concepts of plane and space of incidence and also the Gallucci's axiom as an axiom to our classical projective space. To this purpose we prove from our space axioms, the theorems of Desargues, Pappus, the fundamental t...
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Effect of the non-thermal Sunyaev-Zel'dovich Effect on the temperature determination of galaxy clusters
A recent stacking analysis of Planck HFI data of galaxy clusters (Hurier 2016) allowed to derive the cluster temperatures by using the relativistic corrections to the Sunyaev-Zel'dovich effect (SZE). However, the temperatures of high-temperature clusters, as derived from this analysis, resulted to be basically higher...
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ModelFactory: A Matlab/Octave based toolbox to create human body models
Background: Model-based analysis of movements can help better understand human motor control. Here, the models represent the human body as an articulated multi-body system that reflects the characteristics of the human being studied. Results: We present an open-source toolbox that allows for the creation of human mod...
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Dimensionality reduction with missing values imputation
In this study, we propose a new statical approach for high-dimensionality reduction of heterogenous data that limits the curse of dimensionality and deals with missing values. To handle these latter, we propose to use the Random Forest imputation's method. The main purpose here is to extract useful information and so...
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An effective formalism for testing extensions to General Relativity with gravitational waves
The recent direct observation of gravitational waves (GW) from merging black holes opens up the possibility of exploring the theory of gravity in the strong regime at an unprecedented level. It is therefore interesting to explore which extensions to General Relativity (GR) could be detected. We construct an Effective...
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On the Wiener-Hopf method for surface plasmons: Diffraction from semi-infinite metamaterial sheet
By formally invoking the Wiener-Hopf method, we explicitly solve a one-dimensional, singular integral equation for the excitation of a slowly decaying electromagnetic wave, called surface plasmon-polariton (SPP), of small wavelength on a semi-infinite, flat conducting sheet irradiated by a plane wave in two spatial d...
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Sim2Real View Invariant Visual Servoing by Recurrent Control
Humans are remarkably proficient at controlling their limbs and tools from a wide range of viewpoints and angles, even in the presence of optical distortions. In robotics, this ability is referred to as visual servoing: moving a tool or end-point to a desired location using primarily visual feedback. In this paper, w...
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The homotopy Lie algebra of symplectomorphism groups of 3-fold blow-ups of $(S^2 \times S^2, σ_{std} \oplus σ_{std}) $
We consider the 3-point blow-up of the manifold $ (S^2 \times S^2, \sigma \oplus \sigma)$ where $\sigma$ is the standard symplectic form which gives area 1 to the sphere $S^2$, and study its group of symplectomorphisms $\rm{Symp} ( S^2 \times S^2 \#\, 3\overline{\mathbb C\mathbb P}\,\!^2, \omega)$. So far, the monoto...
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Pressure Drop and Flow development in the Entrance Region of Micro-Channels with Second Order Slip Boundary Conditions and the Requirement for Development Length
In the present investigation, the development of axial velocity profile, the requirement for development length ($L^*_{fd}=L/D_{h}$) and the pressure drop in the entrance region of circular and parallel plate micro-channels have been critically analysed for a large range of operating conditions ($10^{-2}\le Re\le 10^...
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Household poverty classification in data-scarce environments: a machine learning approach
We describe a method to identify poor households in data-scarce countries by leveraging information contained in nationally representative household surveys. It employs standard statistical learning techniques---cross-validation and parameter regularization---which together reduce the extent to which the model is ove...
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Linguistic Matrix Theory
Recent research in computational linguistics has developed algorithms which associate matrices with adjectives and verbs, based on the distribution of words in a corpus of text. These matrices are linear operators on a vector space of context words. They are used to construct the meaning of composite expressions from...
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Dissecting Ponzi schemes on Ethereum: identification, analysis, and impact
Ponzi schemes are financial frauds where, under the promise of high profits, users put their money, recovering their investment and interests only if enough users after them continue to invest money. Originated in the offline world 150 years ago, Ponzi schemes have since then migrated to the digital world, approachin...
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On orthogonality and learning recurrent networks with long term dependencies
It is well known that it is challenging to train deep neural networks and recurrent neural networks for tasks that exhibit long term dependencies. The vanishing or exploding gradient problem is a well known issue associated with these challenges. One approach to addressing vanishing and exploding gradients is to use ...
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Chunk-Based Bi-Scale Decoder for Neural Machine Translation
In typical neural machine translation~(NMT), the decoder generates a sentence word by word, packing all linguistic granularities in the same time-scale of RNN. In this paper, we propose a new type of decoder for NMT, which splits the decode state into two parts and updates them in two different time-scales. Specifica...
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IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks
Deep neural networks (DNN) excel at extracting patterns. Through representation learning and automated feature engineering on large datasets, such models have been highly successful in computer vision and natural language applications. Designing optimal network architectures from a principled or rational approach how...
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Fast Spectral Clustering Using Autoencoders and Landmarks
In this paper, we introduce an algorithm for performing spectral clustering efficiently. Spectral clustering is a powerful clustering algorithm that suffers from high computational complexity, due to eigen decomposition. In this work, we first build the adjacency matrix of the corresponding graph of the dataset. To b...
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Sufficient Markov Decision Processes with Alternating Deep Neural Networks
Advances in mobile computing technologies have made it possible to monitor and apply data-driven interventions across complex systems in real time. Markov decision processes (MDPs) are the primary model for sequential decision problems with a large or indefinite time horizon. Choosing a representation of the underlyi...
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Gate-controlled magnonic-assisted switching of magnetization in ferroelectric/ferromagnetic junctions
Interfacing a ferromagnet with a polarized ferroelectric gate generates a non-uniform, interfacial spin density coupled to the ferroelectric polarization allowing so for an electric field control of effective transversal field to magnetization. Here we study the dynamic magnetization switching behavior of such a mult...
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Three-Dimensional Electronic Structure of type-II Weyl Semimetal WTe$_2$
By combining bulk sensitive soft-X-ray angular-resolved photoemission spectroscopy and accurate first-principles calculations we explored the bulk electronic properties of WTe$_2$, a candidate type-II Weyl semimetal featuring a large non-saturating magnetoresistance. Despite the layered geometry suggesting a two-dime...
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Decentralized Online Learning with Kernels
We consider multi-agent stochastic optimization problems over reproducing kernel Hilbert spaces (RKHS). In this setting, a network of interconnected agents aims to learn decision functions, i.e., nonlinear statistical models, that are optimal in terms of a global convex functional that aggregates data across the netw...
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Enumeration of complementary-dual cyclic $\mathbb{F}_{q}$-linear $\mathbb{F}_{q^t}$-codes
Let $\mathbb{F}_q$ denote the finite field of order $q,$ $n$ be a positive integer coprime to $q$ and $t \geq 2$ be an integer. In this paper, we enumerate all the complementary-dual cyclic $\mathbb{F}_q$-linear $\mathbb{F}_{q^t}$-codes of length $n$ by placing $\ast$, ordinary and Hermitian trace bilinear forms on $...
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MUTAN: Multimodal Tucker Fusion for Visual Question Answering
Bilinear models provide an appealing framework for mixing and merging information in Visual Question Answering (VQA) tasks. They help to learn high level associations between question meaning and visual concepts in the image, but they suffer from huge dimensionality issues. We introduce MUTAN, a multimodal tensor-bas...
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Nucleosynthesis Predictions and High-Precision Deuterium Measurements
Two new high-precision measurements of the deuterium abundance from absorbers along the line of sight to the quasar PKS1937--1009 were presented. The absorbers have lower neutral hydrogen column densities (N(HI) $\approx$ 18\,cm$^{-2}$) than for previous high-precision measurements, boding well for further extensions...
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Nearly-Linear Time Spectral Graph Reduction for Scalable Graph Partitioning and Data Visualization
This paper proposes a scalable algorithmic framework for spectral reduction of large undirected graphs. The proposed method allows computing much smaller graphs while preserving the key spectral (structural) properties of the original graph. Our framework is built upon the following two key components: a spectrum-pre...
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Text Indexing and Searching in Sublinear Time
We introduce the first index that can be built in $o(n)$ time for a text of length $n$, and also queried in $o(m)$ time for a pattern of length $m$. On a constant-size alphabet, for example, our index uses $O(n\log^{1/2+\varepsilon}n)$ bits, is built in $O(n/\log^{1/2-\varepsilon} n)$ deterministic time, and finds th...
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Temperature dependence of the bulk Rashba splitting in the bismuth tellurohalides
We study the temperature dependence of the Rashba-split bands in the bismuth tellurohalides BiTe$X$ $(X=$ I, Br, Cl) from first principles. We find that increasing temperature reduces the Rashba splitting, with the largest effect observed in BiTeI with a reduction of the Rashba parameter of $40$% when temperature inc...
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Viscosity solutions and the minimal surface system
We give a definition of viscosity solution for the minimal surface system and prove a version of Allard regularity theorem in this setting.
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Ray-tracing semiclassical low frequency acoustic modeling with local and extended reaction boundaries
The recently introduced acoustic ray-tracing semiclassical (RTS) method is validated for a set of practically relevant boundary conditions. RTS is a frequency domain geometrical method which directly reproduces the acoustic Green's function. As previously demonstrated for a rectangular room and weakly absorbing bound...
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Towards Understanding the Evolution of the WWW Conference
The World Wide Web conference is a well-established and mature venue with an already long history. Over the years it has been attracting papers reporting many important research achievements centered around the Web. In this work we aim at understanding the evolution of WWW conference series by detecting crucial years...
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Hierarchical State Abstractions for Decision-Making Problems with Computational Constraints
In this semi-tutorial paper, we first review the information-theoretic approach to account for the computational costs incurred during the search for optimal actions in a sequential decision-making problem. The traditional (MDP) framework ignores computational limitations while searching for optimal policies, essenti...
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The generalized Milne problem in gas-dusty atmosphere
We consider the generalized Milne problem in non-conservative plane-parallel optically thick atmosphere consisting of two components - the free electrons and small dust particles. Recall, that the traditional Milne problem describes the propagation of radiation through the conservative (without absorption) optically ...
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h-multigrid agglomeration based solution strategies for discontinuous Galerkin discretizations of incompressible flow problems
In this work we exploit agglomeration based $h$-multigrid preconditioners to speed-up the iterative solution of discontinuous Galerkin discretizations of the Stokes and Navier-Stokes equations. As a distinctive feature $h$-coarsened mesh sequences are generated by recursive agglomeration of a fine grid, admitting arb...
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The content correlation of multiple streaming edges
We study how to detect clusters in a graph defined by a stream of edges, without storing the entire graph. We extend the approach to dynamic graphs defined by the most recent edges of the stream and to several streams. The {\em content correlation }of two streams $\rho(t)$ is the Jaccard similarity of their clusters ...
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Fundamental solutions for second order parabolic systems with drift terms
We construct fundamental solutions of second-order parabolic systems of divergence form with bounded and measurable leading coefficients and divergence free first-order coefficients in the class of $BMO^{-1}_x$, under the assumption that weak solutions of the system satisfy a certain local boundedness estimate. We al...
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CMB in the river frame and gauge invariance at second order
GAUGE INVARIANCE: The Sachs-Wolfe formula describing the Cosmic Microwave Background (CMB) temperature anisotropies is one of the most important relations in cosmology. Despite its importance, the gauge invariance of this formula has only been discussed at first order. Here we discuss the subtle issue of second-order...
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Active matrix completion with uncertainty quantification
The noisy matrix completion problem, which aims to recover a low-rank matrix $\mathbf{X}$ from a partial, noisy observation of its entries, arises in many statistical, machine learning, and engineering applications. In this paper, we present a new, information-theoretic approach for active sampling (or designing) of ...
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Majoration du nombre de valeurs friables d'un polynôme
For $Q$ a polynomial with integer coefficients and $x, y \geq 2$, we prove upper bounds for the quantity $\Psi_Q(x, y) = |\{n\leq x: p\mid Q(n)\Rightarrow p\leq y\}|$. We apply our results to a problem of De Koninck, Doyon and Luca on integers divisible by the square of their largest prime factor. As a corollary to o...
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General analytical solution for the electromagnetic grating diffraction problem
Implementing the modal method in the electromagnetic grating diffraction problem delivered by the curvilinear coordinate transformation yields a general analytical solution to the 1D grating diffraction problem in a form of a T-matrix. Simultaneously it is shown that the validity of the Rayleigh expansion is defined ...
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Synthetic geometry of differential equations: I. Jets and comonad structure
We give an abstract formulation of the formal theory partial differential equations (PDEs) in synthetic differential geometry, one that would seamlessly generalize the traditional theory to a range of enhanced contexts, such as super-geometry, higher (stacky) differential geometry, or even a combination of both. A mo...
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Precision Prediction for the Cosmological Density Distribution
The distribution of matter in the universe is, to first order, lognormal. Improving this approximation requires characterization of the third moment (skewness) of the log density field. Thus, using Millennium Simulation phenomenology and building on previous work, we present analytic fits for the mean, variance, and ...
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Hamiltonian analogs of combustion engines: a systematic exception to adiabatic decoupling
Workhorse theories throughout all of physics derive effective Hamiltonians to describe slow time evolution, even though low-frequency modes are actually coupled to high-frequency modes. Such effective Hamiltonians are accurate because of \textit{adiabatic decoupling}: the high-frequency modes `dress' the low-frequenc...
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Towards Arbitrary Noise Augmentation - Deep Learning for Sampling from Arbitrary Probability Distributions
Accurate noise modelling is important for training of deep learning reconstruction algorithms. While noise models are well known for traditional imaging techniques, the noise distribution of a novel sensor may be difficult to determine a priori. Therefore, we propose learning arbitrary noise distributions. To do so, ...
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Unbiased Simulation for Optimizing Stochastic Function Compositions
In this paper, we introduce an unbiased gradient simulation algorithms for solving convex optimization problem with stochastic function compositions. We show that the unbiased gradient generated from the algorithm has finite variance and finite expected computation cost. We then combined the unbiased gradient simulat...
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Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context
A robot's ability to understand or ground natural language instructions is fundamentally tied to its knowledge about the surrounding world. We present an approach to grounding natural language utterances in the context of factual information gathered through natural-language interactions and past visual observations....
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Nonconvex generalizations of ADMM for nonlinear equality constrained problems
The growing demand on efficient and distributed optimization algorithms for large-scale data stimulates the popularity of Alternative Direction Methods of Multipliers (ADMM) in numerous areas, such as compressive sensing, matrix completion, and sparse feature learning. While linear equality constrained problems have ...
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Interpretable LSTMs For Whole-Brain Neuroimaging Analyses
The analysis of neuroimaging data poses several strong challenges, in particular, due to its high dimensionality, its strong spatio-temporal correlation and the comparably small sample sizes of the respective datasets. To address these challenges, conventional decoding approaches such as the searchlight reduce the co...
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Effect of Isopropanol on Gold Assisted Chemical Etching of Silicon Microstructures
Wet etching is an essential and complex step in semiconductor device processing. Metal-Assisted Chemical Etching (MacEtch) is fundamentally a wet but anisotropic etching method. In the MacEtch technique, there are still a number of unresolved challenges preventing the optimal fabrication of high-aspect-ratio semicond...
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Integrating Runtime Values with Source Code to Facilitate Program Comprehension
An inherently abstract nature of source code makes programs difficult to understand. In our research, we designed three techniques utilizing concrete values of variables and other expressions during program execution. RuntimeSearch is a debugger extension searching for a given string in all expressions at runtime. Dy...
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Nearest Embedded and Embedding Self-Nested Trees
Self-nested trees present a systematic form of redundancy in their subtrees and thus achieve optimal compression rates by DAG compression. A method for quantifying the degree of self-similarity of plants through self-nested trees has been introduced by Godin and Ferraro in 2010. The procedure consists in computing a ...
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Computing the Lusztig--Vogan Bijection
Let $G$ be a connected complex reductive algebraic group with Lie algebra $\mathfrak{g}$. The Lusztig--Vogan bijection relates two bases for the bounded derived category of $G$-equivariant coherent sheaves on the nilpotent cone $\mathcal{N}$ of $\mathfrak{g}$. One basis is indexed by $\Lambda^+$, the set of dominant ...
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Divide and Conquer: Variable Set Separation in Hybrid Systems Reachability Analysis
In this paper we propose an improvement for flowpipe-construction-based reachability analysis techniques for hybrid systems. Such methods apply iterative successor computations to pave the reachable region of the state space by state sets in an over-approximative manner. As the computational costs steeply increase wi...
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The bottom of the spectrum of time-changed processes and the maximum principle of Schrödinger operators
We give a necessary and sufficient condition for the maximum principle of Schrödinger operators in terms of the bottom of the spectrum of time-changed processes. As a corollary, we obtain a sufficient condition for the Liouville property of Schrödinger operators.
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Autocorrelation and Lower Bound on the 2-Adic Complexity of LSB Sequence of $p$-ary $m$-Sequence
In modern stream cipher, there are many algorithms, such as ZUC, LTE encryption algorithm and LTE integrity algorithm, using bit-component sequences of $p$-ary $m$-sequences as the input of the algorithm. Therefore, analyzing their statistical property (For example, autocorrelation, linear complexity and 2-adic compl...
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Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers
The telecommunications industry is highly competitive, which means that the mobile providers need a business intelligence model that can be used to achieve an optimal level of churners, as well as a minimal level of cost in marketing activities. Machine learning applications can be used to provide guidance on marketi...
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A Convex Cycle-based Degradation Model for Battery Energy Storage Planning and Operation
A vital aspect in energy storage planning and operation is to accurately model its operational cost, which mainly comes from the battery cell degradation. Battery degradation can be viewed as a complex material fatigue process that based on stress cycles. Rainflow algorithm is a popular way for cycle identification i...
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Demonstration of cascaded modulator-chicane micro-bunching of a relativistic electron beam
We present results of an experiment showing the first successful demonstration of a cascaded micro-bunching scheme. Two modulator-chicane pre-bunchers arranged in series and a high power mid-IR laser seed are used to modulate a 52 MeV electron beam into a train of sharp microbunches phase-locked to the external drive...
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Grothendieck rigidity of 3-manifold groups
We show that fundamental groups of compact, orientable, irreducible 3-manifolds with toroidal boundary are Grothendieck rigid.
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Sobczyk's simplicial calculus does not have a proper foundation
The pseudoscalars in Garret Sobczyk's paper \emph{Simplicial Calculus with Geometric Algebra} are not well defined. Therefore his calculus does not have a proper foundation.
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Hierarchy of Information Scrambling, Thermalization, and Hydrodynamic Flow in Graphene
We determine the information scrambling rate $\lambda_{L}$ due to electron-electron Coulomb interaction in graphene. $\lambda_{L}$ characterizes the growth of chaos and has been argued to give information about the thermalization and hydrodynamic transport coefficients of a many-body system. We demonstrate that $\lam...
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Neural Collaborative Autoencoder
In recent years, deep neural networks have yielded state-of-the-art performance on several tasks. Although some recent works have focused on combining deep learning with recommendation, we highlight three issues of existing models. First, these models cannot work on both explicit and implicit feedback, since the netw...
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Reexamination of Tolman's law and the Gibbs adsorption equation for curved interfaces
The influence of the surface curvature on the surface tension of small droplets in equilibrium with a surrounding vapour, or small bubbles in equilibrium with a surrounding liquid, can be expanded as $\gamma(R) = \gamma_0 + c_1\gamma_0/R + O(1/R^2)$, where $R = R_\gamma$ is the radius of the surface of tension and $\...
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