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Application of generative autoencoder in de novo molecular design
A major challenge in computational chemistry is the generation of novel molecular structures with desirable pharmacological and physiochemical properties. In this work, we investigate the potential use of autoencoder, a deep learning methodology, for de novo molecular design. Various generative autoencoders were used...
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Prospects for Measuring Cosmic Microwave Background Spectral Distortions in the Presence of Foregrounds
Measurements of cosmic microwave background spectral distortions have profound implications for our understanding of physical processes taking place over a vast window in cosmological history. Foreground contamination is unavoidable in such measurements and detailed signal-foreground separation will be necessary to e...
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The Fog of War: A Machine Learning Approach to Forecasting Weather on Mars
For over a decade, scientists at NASA's Jet Propulsion Laboratory (JPL) have been recording measurements from the Martian surface as a part of the Mars Exploration Rovers mission. One quantity of interest has been the opacity of Mars's atmosphere for its importance in day-to-day estimations of the amount of power ava...
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Substrate inhibition imposes fitness penalty at high protein stability
Proteins are only moderately stable. It has long been debated whether this narrow range of stabilities is solely a result of neutral drift towards lower stability or purifying selection against excess stability is also at work - for which no experimental evidence was found so far. Here we show that mutations outside ...
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Exact relativistic Toda chain eigenfunctions from Separation of Variables and gauge theory
We provide a proposal, motivated by Separation of Variables and gauge theory arguments, for constructing exact solutions to the quantum Baxter equation associated to the $N$-particle relativistic Toda chain and test our proposal against numerical results. Quantum Mechanical non-perturbative corrections, essential in ...
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Simple Compact Monotone Tree Drawings
A monotone drawing of a graph G is a straight-line drawing of G such that every pair of vertices is connected by a path that is monotone with respect to some direction. Trees, as a special class of graphs, have been the focus of several papers and, recently, He and He~\cite{mt:4} showed how to produce a monotone draw...
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Context-Free Path Querying by Matrix Multiplication
Graph data models are widely used in many areas, for example, bioinformatics, graph databases. In these areas, it is often required to process queries for large graphs. Some of the most common graph queries are navigational queries. The result of query evaluation is a set of implicit relations between nodes of the gr...
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Equivalence of sparse and Carleson coefficients for general sets
We remark that sparse and Carleson coefficients are equivalent for every countable collection of Borel sets and hence, in particular, for dyadic rectangles, the case relevant to the theory of bi-parameter singular integrals. The key observation is that a dual refomulation by I. E. Verbitsky for Carleson coefficients ...
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Discovering Business Rules from Business Process Models
Discovering business rules from business process models are of advantage to ensure the compliance of business processes with business rules. Furthermore it provides the agility of business processes in case of business rules evolution. Current approaches are limited on types of rules that can be discovered. This pape...
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Fast Learning and Prediction for Object Detection using Whitened CNN Features
We combine features extracted from pre-trained convolutional neural networks (CNNs) with the fast, linear Exemplar-LDA classifier to get the advantages of both: the high detection performance of CNNs, automatic feature engineering, fast model learning from few training samples and efficient sliding-window detection. ...
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N-body simulations of planet formation via pebble accretion I: First Results
Context. Planet formation with pebbles has been proposed to solve a couple of long-standing issues in the classical formation model. Some sophisticated simulations have been done to confirm the efficiency of pebble accretion. However, there has not been any global N-body simulations that compare the outcomes of plane...
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Local character of Kim-independence
We show that NSOP$_{1}$ theories are exactly the theories in which Kim-independence satisfies a form of local character. In particular, we show that if $T$ is NSOP$_{1}$, $M\models T$, and $p$ is a type over $M$, then the collection of elementary substructures of size $\left|T\right|$ over which $p$ does not Kim-fork...
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A Further Analysis of The Role of Heterogeneity in Coevolutionary Spatial Games
Heterogeneity has been studied as one of the most common explanations of the puzzle of cooperation in social dilemmas. A large number of papers have been published discussing the effects of increasing heterogeneity in structured populations of agents, where it has been established that heterogeneity may favour cooper...
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Transport properties of the Azimuthal Magnetorotational Instability
The magnetorotational instability (MRI) is thought to be a powerful source of turbulence in Keplerian accretion disks. Motivated by recent laboratory experiments, we study the MRI driven by an azimuthal magnetic field in an electrically conducting fluid sheared between two concentric rotating cylinders. By adjusting ...
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New bounds for the Probability of Causation in Mediation Analysis
An individual has been subjected to some exposure and has developed some outcome. Using data on similar individuals, we wish to evaluate, for this case, the probability that the outcome was in fact caused by the exposure. Even with the best possible experimental data on exposure and outcome, we typically can not iden...
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Searching for a cosmological preferred direction with 147 rotationally supported galaxies
It is well known that the Milgrom's MOND (modified Newtonian dynamics) explains well the mass discrepancy problem in galaxy rotation curves. The MOND predicts a universal acceleration scale below which the Newtonian dynamics is invalid yet. The universal acceleration scale we got from the SPARC dataset is $g_†=1.02\t...
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MultiFIT: A Multivariate Multiscale Framework for Independence Tests
We present a framework for testing independence between two random vectors that is scalable to massive data. We break down the multivariate test into univariate tests of independence on a collection of $2\times 2$ contingency tables, constructed by sequentially discretizing the sample space. This transforms a complex...
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Stability of algebraic varieties and Kahler geometry
This is a survey article, based on the author's lectures in the 2015 AMS Summer Research Institute in Algebraic Geometry, and to appear in the Proceedings.
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Scratch iridescence: Wave-optical rendering of diffractive surface structure
The surface of metal, glass and plastic objects is often characterized by microscopic scratches caused by manufacturing and/or wear. A closer look onto such scratches reveals iridescent colors with a complex dependency on viewing and lighting conditions. The physics behind this phenomenon is well understood; it is ca...
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An oscillation criterion for delay differential equations with several non-monotone arguments
The oscillatory behavior of the solutions to a differential equation with several non-monotone delay arguments and non-negative coefficients is studied. A new sufficient oscillation condition, involving lim sup, is obtained. An example illustrating the significance of the result is also given.
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Item Recommendation with Variational Autoencoders and Heterogenous Priors
In recent years, Variational Autoencoders (VAEs) have been shown to be highly effective in both standard collaborative filtering applications and extensions such as incorporation of implicit feedback. We extend VAEs to collaborative filtering with side information, for instance when ratings are combined with explicit...
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Boltzmann Exploration Done Right
Boltzmann exploration is a classic strategy for sequential decision-making under uncertainty, and is one of the most standard tools in Reinforcement Learning (RL). Despite its widespread use, there is virtually no theoretical understanding about the limitations or the actual benefits of this exploration scheme. Does ...
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Deep reinforcement learning from human preferences
For sophisticated reinforcement learning (RL) systems to interact usefully with real-world environments, we need to communicate complex goals to these systems. In this work, we explore goals defined in terms of (non-expert) human preferences between pairs of trajectory segments. We show that this approach can effecti...
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Entanglement spectroscopy on a quantum computer
We present a quantum algorithm to compute the entanglement spectrum of arbitrary quantum states. The interesting universal part of the entanglement spectrum is typically contained in the largest eigenvalues of the density matrix which can be obtained from the lower Renyi entropies through the Newton-Girard method. Ob...
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Light Attenuation Length of High Quality Linear Alkyl Benzene as Liquid Scintillator Solvent for the JUNO Experiment
The Jiangmen Underground Neutrino Observatory (JUNO) is a multipurpose neutrino experiment with a 20 kt liquid scintillator detector designed to determine the neutrino mass hierarchy, and measure the neutrino oscillation parameters. Linear alkyl benzene (LAB) will be used as the solvent for the liquid scintillation s...
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OIL: Observational Imitation Learning
Recent work has explored the problem of autonomous navigation by imitating a teacher and learning an end-to-end policy, which directly predicts controls from raw images. However, these approaches tend to be sensitive to mistakes by the teacher and do not scale well to other environments or vehicles. To this end, we p...
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A Multi-Scan Labeled Random Finite Set Model for Multi-object State Estimation
State space models in which the system state is a finite set--called the multi-object state--have generated considerable interest in recent years. Smoothing for state space models provides better estimation performance than filtering by using the full posterior rather than the filtering density. In multi-object state...
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On the Complexity of Sampling Nodes Uniformly from a Graph
We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed node; the algorithm, for an arbitrary node $v$ that it is aware of, can ask an oracle to return the set of the neighbors of $v$. (In social network analysis, a call to th...
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A structure theorem for almost low-degree functions on the slice
The Fourier-Walsh expansion of a Boolean function $f \colon \{0,1\}^n \rightarrow \{0,1\}$ is its unique representation as a multilinear polynomial. The Kindler-Safra theorem (2002) asserts that if in the expansion of $f$, the total weight on coefficients beyond degree $k$ is very small, then $f$ can be approximated ...
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Oxygen-vacancy driven electron localization and itinerancy in rutile-based TiO$_2$
Oxygen-deficient TiO$_2$ in the rutile structure as well as the Ti$_3$O$_5$ Magn{é}li phase is investigated within the charge self-consistent combination of density functional theory (DFT) with dynamical mean-field theory (DMFT). It is shown that an isolated oxygen vacancy (V$_{\rm O}$) in titanium dioxide is not suf...
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3D printable multimaterial cellular auxetics with tunable stiffness
Auxetic materials are a novel class of mechanical metamaterials which exhibit an interesting property of negative Poisson ratio by virtue of their architecture rather than composition. It has been well established that a wide range of negative Poisson ratio can be obtained by varying the geometry and architecture of ...
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MACS J0416.1-2403: Impact of line-of-sight structures on strong gravitational lensing modelling of galaxy clusters
Exploiting the powerful tool of strong gravitational lensing by galaxy clusters to study the highest-redshift Universe and cluster mass distributions relies on precise lens mass modelling. In this work, we present the first attempt at modelling line-of-sight mass distribution in addition to that of the cluster, exten...
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What can you do with a rock? Affordance extraction via word embeddings
Autonomous agents must often detect affordances: the set of behaviors enabled by a situation. Affordance detection is particularly helpful in domains with large action spaces, allowing the agent to prune its search space by avoiding futile behaviors. This paper presents a method for affordance extraction via word emb...
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On Generalized Gibbs Ensembles with an infinite set of conserved charges
We revisit the question of whether and how the steady states arising after non-equilibrium time evolution in integrable models (and in particular in the XXZ spin chain) can be described by the so-called Generalized Gibbs Ensemble (GGE). It is known that the micro-canonical ensemble built on a complete set of charges ...
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High resolution ion trap time-of-flight mass spectrometer for cold trapped ion experiments
Trapping molecular ions that have been sympathetically cooled with laser-cooled atomic ions is a useful platform for exploring cold ion chemistry. We designed and characterized a new experimental apparatus for probing chemical reaction dynamics between molecular cations and neutral radicals at temperatures below 1 K....
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The role of local-geometrical-orders on the growth of dynamic-length-scales in glass-forming liquids
The precise nature of complex structural relaxation as well as an explanation for the precipitous growth of relaxation time in cooling glass-forming liquids are essential to the understanding of vitrification of liquids. The dramatic increase of relaxation time is believed to be caused by the growth of one or more co...
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Snake: a Stochastic Proximal Gradient Algorithm for Regularized Problems over Large Graphs
A regularized optimization problem over a large unstructured graph is studied, where the regularization term is tied to the graph geometry. Typical regularization examples include the total variation and the Laplacian regularizations over the graph. When applying the proximal gradient algorithm to solve this problem,...
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Stability of the coexistent superconducting-nematic phase under the presence of intersite interactions
We analyze the effect of intersite-interaction terms on the stability of the coexisting superconucting-nematic phase (SC+N) within the extended Hubbard and $t$-$J$-$U$ models on the square lattice. In order to take into account the correlation effects with a proper precision, we use the approach based on the \textit{...
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Multi-Advisor Reinforcement Learning
We consider tackling a single-agent RL problem by distributing it to $n$ learners. These learners, called advisors, endeavour to solve the problem from a different focus. Their advice, taking the form of action values, is then communicated to an aggregator, which is in control of the system. We show that the local pl...
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Using CMB spectral distortions to distinguish between dark matter solutions to the small-scale crisis
The dissipation of small-scale perturbations in the early universe produces a distortion in the blackbody spectrum of cosmic microwave background photons. In this work, we propose to use these distortions as a probe of the microphysics of dark matter on scales $1\,\textrm{Mpc}^{-1}\lesssim k \lesssim 10^{4}\,\textrm{...
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Gradient Hyperalignment for multi-subject fMRI data alignment
Multi-subject fMRI data analysis is an interesting and challenging problem in human brain decoding studies. The inherent anatomical and functional variability across subjects make it necessary to do both anatomical and functional alignment before classification analysis. Besides, when it comes to big data, time compl...
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Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer
Knowledge transfer between tasks can improve the performance of learned models, but requires an accurate estimate of the inter-task relationships to identify the relevant knowledge to transfer. These inter-task relationships are typically estimated based on training data for each task, which is inefficient in lifelon...
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Giant Unification Theory of the Grand Unification and Gravitation Theories
Because the grand unification theory of gauge theories of strong, weak and electromagnetic interactions is based on principal bundle theory, and gravitational theory is based on the tangent vector bundle theory, so people cannot unify the these four basic interactions in principal bundle theory. This Letter discovers...
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Generalized Rich-Club Ordering in Networks
Rich-club ordering refers to the tendency of nodes with a high degree to be more interconnected than expected. In this paper we consider the concept of rich-club ordering when generalized to structural measures that differ from the node degree and to non-structural measures (i.e. to node metadata). The differences in...
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Integrating Proactive Mode Changes in Mixed Criticality Systems
In this work, we propose to integrate prediction algorithms to the scheduling of mode changes under the Earliest-Deadline-First and Fixed-priority scheduling in mixed-criticality real-time systems. The method proactively schedules a mode change in the system based on state variables such as laxity, to the percentage ...
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Leveraging Continuous Material Averaging for Inverse Electromagnetic Design
Inverse electromagnetic design has emerged as a way of efficiently designing active and passive electromagnetic devices. This maturing strategy involves optimizing the shape or topology of a device in order to improve a figure of merit--a process which is typically performed using some form of steepest descent algori...
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Robust Speech Recognition Using Generative Adversarial Networks
This paper describes a general, scalable, end-to-end framework that uses the generative adversarial network (GAN) objective to enable robust speech recognition. Encoders trained with the proposed approach enjoy improved invariance by learning to map noisy audio to the same embedding space as that of clean audio. Unli...
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Minimal inequalities for an infinite relaxation of integer programs
We show that maximal $S$-free convex sets are polyhedra when $S$ is the set of integral points in some rational polyhedron of $\mathbb{R}^n$. This result extends a theorem of Lovász characterizing maximal lattice-free convex sets. Our theorem has implications in integer programming. In particular, we show that maxima...
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The population of SNe/SNRs in the starburst galaxy Arp 220. A self-consistent analysis of 20 years of VLBI monitoring
The nearby ultra-luminous infrared galaxy (ULIRG) Arp 220 is an excellent laboratory for studies of extreme astrophysical environments. For 20 years, Very Long Baseline Interferometry (VLBI) has been used to monitor a population of compact sources thought to be supernovae (SNe), supernova remnants (SNRs) and possibly...
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Dirac and Chiral Quantum Spin Liquids on the Honeycomb Lattice in a Magnetic Field
Motivated by recent experimental observations in $\alpha$-RuCl$_3$, we study the $K$-$\Gamma$ model on the honeycomb lattice in an external magnetic field. By a slave-particle representation and Variational Monte Carlo calculations, we reproduce the phase transition from zigzag magnetic order to a field-induced disor...
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Secular Dynamics of an Exterior Test Particle: The Inverse Kozai and Other Eccentricity-Inclination Resonances
The behavior of an interior test particle in the secular 3-body problem has been studied extensively. A well-known feature is the Lidov-Kozai resonance in which the test particle's argument of periapse librates about $\pm 90^\circ$ and large oscillations in eccentricity and inclination are possible. Less explored is ...
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A pulsed, mono-energetic and angular-selective UV photo-electron source for the commissioning of the KATRIN experiment
The KATRIN experiment aims to determine the neutrino mass scale with a sensitivity of 200 meV/c^2 (90% C.L.) by a precision measurement of the shape of the tritium $\beta$-spectrum in the endpoint region. The energy analysis of the decay electrons is achieved by a MAC-E filter spectrometer. To determine the transmiss...
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Carrier frequency modulation of an acousto-optic modulator for laser stabilization
The stabilization of lasers to absolute frequency references is a fundamental requirement in several areas of atomic, molecular and optical physics. A range of techniques are available to produce a suitable reference onto which one can 'lock' the laser, many of which depend on the specific internal structure of the r...
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Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Method
In this paper, a new type of 3D bin packing problem (BPP) is proposed, in which a number of cuboid-shaped items must be put into a bin one by one orthogonally. The objective is to find a way to place these items that can minimize the surface area of the bin. This problem is based on the fact that there is no fixed-si...
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Entendendo o Pensamento Computacional
The goal of this article is to clarify the meaning of Computational Thinking. We differentiate logical from computational reasoning and discuss the importance of Computational Thinking in solving problems. The three pillars of Computational Thinking - Abstraction, Automation and Analysis - are outlined, highlighting ...
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Estimation of samples relevance by their histograms
The problem of the estimation of relevance to a set of histograms generated by samples of a discrete time process is discussed on the base of the variational principles proposed in the previous paper [1]. Some conditions for dimension reduction of corresponding linear programming problems are presented also.
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On the synthesis of acoustic sources with controllable near fields
In this paper we present a strategy for the the synthesis of acoustic sources with controllable near fields in free space and finite depth homogeneous ocean environments. We first present the theoretical results at the basis of our discussion and then, to illustrate our findings we focus on the following three partic...
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Inverse Protein Folding Problem via Quadratic Programming
This paper presents a method of reconstruction a primary structure of a protein that folds into a given geometrical shape. This method predicts the primary structure of a protein and restores its linear sequence of amino acids in the polypeptide chain using the tertiary structure of a molecule. Unknown amino acids ar...
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Spoken Language Understanding on the Edge
We consider the problem of performing Spoken Language Understanding (SLU) on small devices typical of IoT applications. Our contributions are twofold. First, we outline the design of an embedded, private-by-design SLU system and show that it has performance on par with cloud-based commercial solutions. Second, we rel...
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On the link between column density distribution and density scaling relation in star formation regions
We present a method to derive the density scaling relation $\langle n\rangle \propto L^{-\alpha}$ in regions of star formation or in their turbulent vicinities from straightforward binning of the column-density distribution ($N$-pdf). The outcome of the method is studied for three types of $N$-pdf: power law ($7/5\le...
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Measuring Effectiveness of Video Advertisements
Advertisements are unavoidable in modern society. Times Square is notorious for its incessant display of advertisements. Its popularity is worldwide and smaller cities possess miniature versions of the display, such as Pittsburgh and its digital works in Oakland on Forbes Avenue. Tokyo's Ginza district recently rose ...
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Multilinear compressive sensing and an application to convolutional linear networks
We study a deep linear network endowed with a structure. It takes the form of a matrix $X$ obtained by multiplying $K$ matrices (called factors and corresponding to the action of the layers). The action of each layer (i.e. a factor) is obtained by applying a fixed linear operator to a vector of parameters satisfying ...
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Normalization of closed Ekedahl-Oort strata
We apply our theory of partial flag spaces developed in previous articles to study a group-theoretical generalization of the canonical filtration of a truncated Barsotti-Tate group of level 1. As an application, we determine explicitly the normalization of the Zariski closures of Ekedahl-Oort strata of Shimura variet...
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Robustness of functional networks at criticality against structural defects
The robustness of dynamical properties of neuronal networks against structural damages is a central problem in computational and experimental neuroscience. Research has shown that the cortical network of a healthy brain works near a critical state, and moreover, that functional neuronal networks often have scale-free...
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Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning
Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced classification. So far, various supervised AUC optimization methods have been developed and they are also extended to semi-supervised scenarios to cope with small sample problems. However, existing semi-su...
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Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering
Motivated by problems in data clustering, we establish general conditions under which families of nonparametric mixture models are identifiable, by introducing a novel framework involving clustering overfitted \emph{parametric} (i.e. misspecified) mixture models. These identifiability conditions generalize existing c...
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The geometric classification of Leibniz algebras
We describe all rigid algebras and all irreducible components in the variety of four dimensional Leibniz algebras $\mathfrak{Leib}_4$ over $\mathbb{C}.$ In particular, we prove that the Grunewald--O'Halloran conjecture is not valid and the Vergne conjecture is valid for $\mathfrak{Leib}_4.$
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Discrete fundamental groups of Warped Cones and expanders
In this paper we compute the discrete fundamental groups of warped cones. As an immediate consequence, this allows us to show that there exist coarsely simply-connected expanders and superexpanders. This also provides a strong coarse invariant of warped cones and implies that many warped cones cannot be coarsely equi...
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Simulated Tempering Method in the Infinite Switch Limit with Adaptive Weight Learning
We investigate the theoretical foundations of the simulated tempering method and use our findings to design efficient algorithms. Employing a large deviation argument first used for replica exchange molecular dynamics [Plattner et al., J. Chem. Phys. 135:134111 (2011)], we demonstrate that the most efficient approach...
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Analysis and Modeling of 3D Indoor Scenes
We live in a 3D world, performing activities and interacting with objects in the indoor environments everyday. Indoor scenes are the most familiar and essential environments in everyone's life. In the virtual world, 3D indoor scenes are also ubiquitous in 3D games and interior design. With the fast development of VR/...
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Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy
Advances in astronomy are intimately linked to advances in digital signal processing (DSP). This special issue is focused upon advances in DSP within radio astronomy. The trend within that community is to use off-the-shelf digital hardware where possible and leverage advances in high performance computing. In particu...
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HPDedup: A Hybrid Prioritized Data Deduplication Mechanism for Primary Storage in the Cloud
Eliminating duplicate data in primary storage of clouds increases the cost-efficiency of cloud service providers as well as reduces the cost of users for using cloud services. Existing primary deduplication techniques either use inline caching to exploit locality in primary workloads or use post-processing deduplicat...
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Two-domain and three-domain limit cycles in a typical aeroelastic system with freeplay in pitch
Freeplay is a significant source of nonlinearity in aeroelastic systems and is strictly regulated by airworthiness authorities. It splits the phase plane of such systems into three piecewise linear subdomains. Depending on the location of the freeplay, limit cycle oscillations can result that span either two or three...
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Preference Modeling by Exploiting Latent Components of Ratings
Understanding user preference is essential to the optimization of recommender systems. As a feedback of user's taste, rating scores can directly reflect the preference of a given user to a given product. Uncovering the latent components of user ratings is thus of significant importance for learning user interests. In...
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Inductive Representation Learning on Large Graphs
Low-dimensional embeddings of nodes in large graphs have proved extremely useful in a variety of prediction tasks, from content recommendation to identifying protein functions. However, most existing approaches require that all nodes in the graph are present during training of the embeddings; these previous approache...
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Milnor and Tjurina numbers for a hypersurface germ with isolated singularity
Assume that $f:(\mathbb{C}^n,0) \to (\mathbb{C},0)$ is an analytic function germ at the origin with only isolated singularity. Let $\mu$ and $\tau$ be the corresponding Milnor and Tjurina numbers. We show that $\dfrac{\mu}{\tau} \leq n$. As an application, we give a lower bound for the Tjurina number in terms of $n$ ...
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Analysis of the Gibbs Sampler for Gaussian hierarchical models via multigrid decomposition
We study the convergence properties of the Gibbs Sampler in the context of posterior distributions arising from Bayesian analysis of Gaussian hierarchical models. We consider centred and non-centred parameterizations as well as their hybrids including the full family of partially non-centred parameterizations. We dev...
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A Cosmic Selection Rule for Glueball Dark Matter Relic Density
We point out a unique mechanism to produce the relic abundance for glueball dark matter from a gauged $SU(N)_d$ hidden sector which is bridged to the standard model sector through heavy vectorlike quarks colored under gauge interactions from both sides. A necessary ingredient of our assumption is that the vectorlike ...
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Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network
In this paper, we propose a method using a three dimensional convolutional neural network (3-D-CNN) to fuse together multispectral (MS) and hyperspectral (HS) images to obtain a high resolution hyperspectral image. Dimensionality reduction of the hyperspectral image is performed prior to fusion in order to significan...
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The fundamental Lepage form in variational theory for submanifolds
A setting for global variational geometry on Grassmann fibrations is presented. The integral variational functionals for finite dimensional immersed submanifolds are studied by means of the fundamental Lepage equivalent of a homogeneous Lagrangian, which can be regarded as a generalization of the well-known Hilbert f...
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Adding educational funcionalities to classic board games
In this paper we revisit some classic board games like Pachisi or the Game of Gosse. The main contribution of the paper is to design and add some functionalities to the games in order to transform them in serious games, that is, in games with learning and educational purposes. To do that, at the beginning of the game...
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Conceptual Frameworks for Building Online Citizen Science Projects
In recent years, citizen science has grown in popularity due to a number of reasons, including the emphasis on informal learning and creativity potential associated with these initiatives. Citizen science projects address research questions from various domains, ranging from Ecology to Astronomy. Due to the advanceme...
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SDN Architecture and Southbound APIs for IPv6 Segment Routing Enabled Wide Area Networks
The SRv6 architecture (Segment Routing based on IPv6 data plane) is a promising solution to support services like Traffic Engineering, Service Function Chaining and Virtual Private Networks in IPv6 backbones and datacenters. The SRv6 architecture has interesting scalability properties as it reduces the amount of stat...
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Topology-optimized Dual-Polarization Dirac Cones
We apply a large-scale computational technique, known as topology optimization, to the inverse design of photonic Dirac cones. In particular, we report on a variety of photonic crystal geometries, realizable in simple isotropic dielectric materials, which exhibit dual-polarization and dual-wavelength Dirac cones. We ...
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Reconstruction of Word Embeddings from Sub-Word Parameters
Pre-trained word embeddings improve the performance of a neural model at the cost of increasing the model size. We propose to benefit from this resource without paying the cost by operating strictly at the sub-lexical level. Our approach is quite simple: before task-specific training, we first optimize sub-word param...
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Deep Submodular Functions
We start with an overview of a class of submodular functions called SCMMs (sums of concave composed with non-negative modular functions plus a final arbitrary modular). We then define a new class of submodular functions we call {\em deep submodular functions} or DSFs. We show that DSFs are a flexible parametric famil...
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Inverse problems for the wave equation with under-determined data
We consider the inverse problems of determining the potential or the damping coefficient appearing in the wave equation. We will prove the unique determination of these coefficients from the one point measurement. Since our problem is under-determined, so some extra assumption on the coefficients is required to prove...
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Spatial interactions and oscillatory tragedies of the commons
A tragedy of the commons (TOC) occurs when individuals acting in their own self-interest deplete commonly-held resources, leading to a worse outcome than had they cooperated. Over time, the depletion of resources can change incentives for subsequent actions. Here, we investigate long-term feedback between game and en...
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An upper bound on transport
The linear growth of operators in local quantum systems leads to an effective lightcone even if the system is non-relativistic. We show that consistency of diffusive transport with this lightcone places an upper bound on the diffusivity: $D \lesssim v^2 \tau_\text{eq}$. The operator growth velocity $v$ defines the li...
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Taylor expansion in linear logic is invertible
Each Multiplicative Exponential Linear Logic (MELL) proof-net can be expanded into a differential net, which is its Taylor expansion. We prove that two different MELL proof-nets have two different Taylor expansions. As a corollary, we prove a completeness result for MELL: We show that the relational model is injectiv...
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Collision-Free Multi Robot Trajectory Optimization in Unknown Environments using Decentralized Trajectory Planning
Multi robot systems have the potential to be utilized in a variety of applications. In most of the previous works, the trajectory generation for multi robot systems is implemented in known environments. To overcome that we present an online trajectory optimization algorithm that utilizes communication of robots' curr...
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On the bottom of spectra under coverings
For a Riemannian covering $M_1\to M_0$ of complete Riemannian manifolds with boundary (possibly empty) and respective fundamental groups $\Gamma_1\subseteq\Gamma_0$, we show that the bottoms of the spectra of $M_0$ and $M_1$ coincide if the right action of $\Gamma_0$ on $\Gamma_1\backslash\Gamma_0$ is amenable.
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Theory of ground states for classical Heisenberg spin systems IV
We extend the theory of ground states of classical Heisenberg spin systems previously published to the case where the interaction with an external magnetic field is described by a Zeeman term. The ground state problem for the Heisenberg-Zeeman Hamiltonian can be reduced first to the relative ground state problem, and...
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Aggressive Deep Driving: Model Predictive Control with a CNN Cost Model
We present a framework for vision-based model predictive control (MPC) for the task of aggressive, high-speed autonomous driving. Our approach uses deep convolutional neural networks to predict cost functions from input video which are directly suitable for online trajectory optimization with MPC. We demonstrate the ...
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K-theory of line bundles and smooth varieties
We give a $K$-theoretic criterion for a quasi-projective variety to be smooth. If $\mathbb{L}$ is a line bundle corresponding to an ample invertible sheaf on $X$, it suffices that $K_q(X) = K_q(\mathbb{L})$ for all $q\le\dim(X)+1$.
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Local Two-Sample Testing: A New Tool for Analysing High-Dimensional Astronomical Data
Modern surveys have provided the astronomical community with a flood of high-dimensional data, but analyses of these data often occur after their projection to lower-dimensional spaces. In this work, we introduce a local two-sample hypothesis test framework that an analyst may directly apply to data in their native s...
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Are You Tampering With My Data?
We propose a novel approach towards adversarial attacks on neural networks (NN), focusing on tampering the data used for training instead of generating attacks on trained models. Our network-agnostic method creates a backdoor during training which can be exploited at test time to force a neural network to exhibit abn...
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Answering Spatial Multiple-Set Intersection Queries Using 2-3 Cuckoo Hash-Filters
We show how to answer spatial multiple-set intersection queries in O(n(log w)/w + kt) expected time, where n is the total size of the t sets involved in the query, w is the number of bits in a memory word, k is the output size, and c is any fixed constant. This improves the asymptotic performance over previous soluti...
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A framework for cascade size calculations on random networks
We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations and, in case of threshold mod...
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A Gaussian Process Regression Model for Distribution Inputs
Monge-Kantorovich distances, otherwise known as Wasserstein distances, have received a growing attention in statistics and machine learning as a powerful discrepancy measure for probability distributions. In this paper, we focus on forecasting a Gaussian process indexed by probability distributions. For this, we prov...
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