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A Decision Tree Based Approach Towards Adaptive Profiling of Distributed Applications
The adoption of the distributed paradigm has allowed applications to increase their scalability, robustness and fault tolerance, but it has also complicated their structure, leading to an exponential growth of the applications' configuration space and increased difficulty in predicting their performance. In this work...
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A Tractable Approach to Dynamic Network Dimensioning Based on the Best-cell Configuration
Spatial distributions of other cell interference (OCIF) and interference to own-cell power ratio (IOPR) with reference to the distance between a mobile and its serving base station (BS) are modeled for the down-link reception of cellular systems based on the best-cell configuration instead of the nearest-cell configu...
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Parametric uncertainty in complex environmental models: a cheap emulation approach for models with high-dimensional output
In order to understand underlying processes governing environmental and physical processes, and predict future outcomes, a complex computer model is frequently required to simulate these dynamics. However there is inevitably uncertainty related to the exact parametric form or the values of such parameters to be used ...
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Prediction and Control with Temporal Segment Models
We introduce a method for learning the dynamics of complex nonlinear systems based on deep generative models over temporal segments of states and actions. Unlike dynamics models that operate over individual discrete timesteps, we learn the distribution over future state trajectories conditioned on past state, past ac...
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Artificial Intelligence and Statistics
Artificial intelligence (AI) is intrinsically data-driven. It calls for the application of statistical concepts through human-machine collaboration during generation of data, development of algorithms, and evaluation of results. This paper discusses how such human-machine collaboration can be approached through the s...
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Shortcut Sequence Tagging
Deep stacked RNNs are usually hard to train. Adding shortcut connections across different layers is a common way to ease the training of stacked networks. However, extra shortcuts make the recurrent step more complicated. To simply the stacked architecture, we propose a framework called shortcut block, which is a mar...
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Distortions of the Cosmic Microwave Background through cooling lines during the epoch of Reionization
By using N-body hydrodynamical cosmological simulations in which the chemistry of major metals and molecules is consistently solved for, we study the interaction of metallic fine-structure lines with the CMB. Our analysis shows that the collisional induced emissions in the OI 145 $\mu$m and CII 158 $\mu$m lines durin...
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Improving brain computer interface performance by data augmentation with conditional Deep Convolutional Generative Adversarial Networks
One of the big restrictions in brain computer interface field is the very limited training samples, it is difficult to build a reliable and usable system with such limited data. Inspired by generative adversarial networks, we propose a conditional Deep Convolutional Generative Adversarial (cDCGAN) Networks method to ...
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From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood
Our goal is to learn a semantic parser that maps natural language utterances into executable programs when only indirect supervision is available: examples are labeled with the correct execution result, but not the program itself. Consequently, we must search the space of programs for those that output the correct re...
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GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data
Object Transfiguration replaces an object in an image with another object from a second image. For example it can perform tasks like "putting exactly those eyeglasses from image A on the nose of the person in image B". Usage of exemplar images allows more precise specification of desired modifications and improves th...
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Flow-free Video Object Segmentation
Segmenting foreground object from a video is a challenging task because of the large deformations of the objects, occlusions, and background clutter. In this paper, we propose a frame-by-frame but computationally efficient approach for video object segmentation by clustering visually similar generic object segments t...
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Finding Modes by Probabilistic Hypergraphs Shifting
In this paper, we develop a novel paradigm, namely hypergraph shift, to find robust graph modes by probabilistic voting strategy, which are semantically sound besides the self-cohesiveness requirement in forming graph modes. Unlike the existing techniques to seek graph modes by shifting vertices based on pair-wise ed...
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Bounding the size of an almost-equidistant set in Euclidean space
A set of points in d-dimensional Euclidean space is almost equidistant if among any three points of the set, some two are at distance 1. We show that an almost-equidistant set in $\mathbb{R}^d$ has cardinality $O(d^{4/3})$.
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Equipping weak equivalences with algebraic structure
We investigate the extent to which the weak equivalences in a model category can be equipped with algebraic structure. We prove, for instance, that there exists a monad T such that a morphism of topological spaces admits T-algebra structure if and only it is a weak homotopy equivalence. Likewise for quasi-isomorphism...
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An Experimental Study of the Treewidth of Real-World Graph Data (Extended Version)
Treewidth is a parameter that measures how tree-like a relational instance is, and whether it can reasonably be decomposed into a tree. Many computation tasks are known to be tractable on databases of small treewidth, but computing the treewidth of a given instance is intractable. This article is the first large-scal...
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A yield-cost tradeoff governs Escherichia coli's decision between fermentation and respiration in carbon-limited growth
Many microbial systems are known to actively reshape their proteomes in response to changes in growth conditions induced e.g. by nutritional stress or antibiotics. Part of the re-allocation accounts for the fact that, as the growth rate is limited by targeting specific metabolic activities, cells simply respond by fi...
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Towards a Unified Taxonomy of Biclustering Methods
Being an unsupervised machine learning and data mining technique, biclustering and its multimodal extensions are becoming popular tools for analysing object-attribute data in different domains. Apart from conventional clustering techniques, biclustering is searching for homogeneous groups of objects while keeping the...
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Global center stable manifold for the defocusing energy critical wave equation with potential
In this paper we consider the defocusing energy critical wave equation with a trapping potential in dimension $3$. We prove that the set of initial data for which solutions scatter to an unstable excited state $(\phi, 0)$ forms a finite co-dimensional path connected $C^1$ manifold in the energy space. This manifold i...
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Real-time convolutional networks for sonar image classification in low-power embedded systems
Deep Neural Networks have impressive classification performance, but this comes at the expense of significant computational resources at inference time. Autonomous Underwater Vehicles use low-power embedded systems for sonar image perception, and cannot execute large neural networks in real-time. We propose the use o...
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Mathematics in Caging of Robotics
It is a crucial problem in robotics field to cage an object using robots like multifingered hand. However the problem what is the caging for general geometrical objects and robots has not been well-described in mathematics though there were many rigorous studies on the methods how to cage an object by certain robots....
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Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces
Graph models are relevant in many fields, such as distributed computing, intelligent tutoring systems or social network analysis. In many cases, such models need to take changes in the graph structure into account, i.e. a varying number of nodes or edges. Predicting such changes within graphs can be expected to yield...
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Geometric comparison of phylogenetic trees with different leaf sets
The metric space of phylogenetic trees defined by Billera, Holmes, and Vogtmann, which we refer to as BHV space, provides a natural geometric setting for describing collections of trees on the same set of taxa. However, it is sometimes necessary to analyze collections of trees on non-identical taxa sets (i.e., with d...
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Automatic Detection of Cyberbullying in Social Media Text
While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful mes...
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Holographic Entanglement Entropy in Cyclic Cosmology
We discuss a cyclic cosmology in which the visible universe, or introverse, is all that is accessible to an observer while the extroverse represents the total spacetime originating from the time when the dark energy began to dominate. It is argued that entanglement entropy of the introverse is the more appropriate qu...
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Adversarial Training for Disease Prediction from Electronic Health Records with Missing Data
Electronic health records (EHRs) have contributed to the computerization of patient records and can thus be used not only for efficient and systematic medical services, but also for research on biomedical data science. However, there are many missing values in EHRs when provided in matrix form, which is an important ...
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Hydrodynamic stability in the presence of a stochastic forcing:a case study in convection
We investigate the stability of a statistically stationary conductive state for Rayleigh-Bénard convection between stress-free plates that arises due to a bulk stochastic internal heating. This setup may be seen as a generalization to a stochastic setting of the seminal 1916 study of Lord Rayleigh. Our results indica...
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Asset Price Bubbles: An Option-based Indicator
We construct a statistical indicator for the detection of short-term asset price bubbles based on the information content of bid and ask market quotes for plain vanilla put and call options. Our construction makes use of the martingale theory of asset price bubbles and the fact that such scenarios where the price for...
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Interleaving and Gromov-Hausdorff distance
One of the central notions to emerge from the study of persistent homology is that of interleaving distance. It has found recent applications in symplectic and contact geometry, sheaf theory, computational geometry, and phylogenetics. Here we present a general study of this topic. We define interleaving of functors w...
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Attainable Knowledge
The article investigates an evidence-based semantics for epistemic logics in which pieces of evidence are interpreted as equivalence relations on the epistemic worlds. It is shown that the properties of knowledge obtained from potentially infinitely many pieces of evidence are described by modal logic S5. At the same...
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Linear complementarity problems on extended second order cones
In this paper, we study the linear complementarity problems on extended second order cones. We convert a linear complementarity problem on an extended second order cone into a mixed complementarity problem on the non-negative orthant. We state necessary and sufficient conditions for a point to be a solution of the co...
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On the Bernstein-Von Mises Theorem for High Dimensional Nonlinear Bayesian Inverse Problems
We prove a Bernstein-von Mises theorem for a general class of high dimensional nonlinear Bayesian inverse problems in the vanishing noise limit. We propose a sufficient condition on the growth rate of the number of unknown parameters under which the posterior distribution is asymptotically normal. This growth conditi...
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Dynamic Word Embeddings for Evolving Semantic Discovery
Word evolution refers to the changing meanings and associations of words throughout time, as a byproduct of human language evolution. By studying word evolution, we can infer social trends and language constructs over different periods of human history. However, traditional techniques such as word representation lear...
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Constructing Words with High Distinct Square Densities
Fraenkel and Simpson showed that the number of distinct squares in a word of length n is bounded from above by 2n, since at most two distinct squares have their rightmost, or last, occurrence begin at each position. Improvements by Ilie to $2n-\Theta(\log n)$ and by Deza et al. to 11n/6 rely on the study of combinato...
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Annihilators of Koszul Homologies and Almost Complete Intersections
In this article, we propound a question on the annihilator of Koszul homologies of a system of parameters of an almost complete intersection $R$. The question can be stated in terms of the acyclicity of certain (finite) residual approximation complexes whose $0$-th homologies are the residue field of $R$. We show tha...
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Analyzing Knowledge Transfer in Deep Q-Networks for Autonomously Handling Multiple Intersections
We analyze how the knowledge to autonomously handle one type of intersection, represented as a Deep Q-Network, translates to other types of intersections (tasks). We view intersection handling as a deep reinforcement learning problem, which approximates the state action Q function as a deep neural network. Using a tr...
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From modelling of systems with constraints to generalized geometry and back to numerics
In this note we describe how some objects from generalized geometry appear in the qualitative analysis and numerical simulation of mechanical systems. In particular we discuss double vector bundles and Dirac structures. It turns out that those objects can be naturally associated to systems with constraints -- we reca...
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A Deeper Look at Experience Replay
Recently experience replay is widely used in various deep reinforcement learning (RL) algorithms, in this paper we rethink the utility of experience replay. It introduces a new hyper-parameter, the memory buffer size, which needs carefully tuning. However unfortunately the importance of this new hyper-parameter has b...
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Dirac operators with $W^{1,\infty}$-potential under codimension one collapse
We study the behavior of the spectrum of the Dirac operator together with a symmetric $W^{1, \infty}$-potential on spin manifolds under a collapse of codimension one with bounded sectional curvature and diameter. If there is an induced spin structure on the limit space $N$ then there are convergent eigenvalues which ...
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Tunable Superconducting Qubits with Flux-Independent Coherence
We have studied the impact of low-frequency magnetic flux noise upon superconducting transmon qubits with various levels of tunability. We find that qubits with weaker tunability exhibit dephasing that is less sensitive to flux noise. This insight was used to fabricate qubits where dephasing due to flux noise was sup...
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Kulish-Sklyanin type models: integrability and reductions
We start with a Riemann-Hilbert problem (RHP) related to a BD.I-type symmetric spaces $SO(2r+1)/S(O(2r-2s +1)\otimes O(2s))$, $s\geq 1$. We consider two Riemann-Hilbert problems: the first formulated on the real axis $\mathbb{R}$ in the complex $\lambda$-plane; the second one is formulated on $\mathbb{R} \oplus i\mat...
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Takiff algebras with polynomial rings of symmetric invariants
Extending results of Rais-Tauvel, Macedo-Savage, and Arakawa-Premet, we prove that under mild restrictions on the Lie algebra $\mathfrak q$ having the polynomial ring of symmetric invariants, the m-th Takiff algebra of $\mathfrak q$, $\mathfrak q\langle m\rangle$, also has a polynomial ring of symmetric invariants.
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Can We Prove Time Protection?
Timing channels are a significant and growing security threat in computer systems, with no established solution. We have recently argued that the OS must provide time protection, in analogy to the established memory protection, to protect applications from information leakage through timing channels. Based on a recen...
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On some Graphs with a Unique Perfect Matching
We show that deciding whether a given graph $G$ of size $m$ has a unique perfect matching as well as finding that matching, if it exists, can be done in time $O(m)$ if $G$ is either a cograph, or a split graph, or an interval graph, or claw-free. Furthermore, we provide a constructive characterization of the claw-fre...
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Trade-Offs in Stochastic Event-Triggered Control
This paper studies the optimal output-feedback control of a linear time-invariant system where a stochastic event-based scheduler triggers the communication between the sensor and the controller. The primary goal of the use of this type of scheduling strategy is to provide significant reductions in the usage of the s...
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Third Harmonic THz Generation from Graphene in a Parallel-Plate Waveguide
Graphene as a zero-bandgap two-dimensional semiconductor with a linear electron band dispersion near the Dirac points has the potential to exhibit very interesting nonlinear optical properties. In particular, third harmonic generation of terahertz radiation should occur due to the nonlinear relationship between the c...
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Taming the Signal-to-Noise Problem in Lattice QCD by Phase Reweighting
Path integrals describing quantum many-body systems can be calculated with Monte Carlo sampling techniques, but average quantities are often subject to signal-to-noise ratios that degrade exponentially with time. A phase-reweighting technique inspired by recent observations of random walk statistics in correlation fu...
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Description of radiation damage in diamond sensors using an effective defect model
The BCML system is a beam monitoring device in the CMS experiment at the LHC. As detectors poly-crystalline diamond sensors are used. Here high particle rates occur from the colliding beams scattering particles outside the beam pipe. These particles cause defects, which act as traps for the ionization, thus reducing ...
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Design and Analysis of Time-Invariant SC-LDPC Convolutional Codes With Small Constraint Length
In this paper, we deal with time-invariant spatially coupled low-density parity-check convolutional codes (SC-LDPC-CCs). Classic design approaches usually start from quasi-cyclic low-density parity-check (QC-LDPC) block codes and exploit suitable unwrapping procedures to obtain SC-LDPC-CCs. We show that the direct de...
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Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
The prediction of organic reaction outcomes is a fundamental problem in computational chemistry. Since a reaction may involve hundreds of atoms, fully exploring the space of possible transformations is intractable. The current solution utilizes reaction templates to limit the space, but it suffers from coverage and e...
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Legendre curves and singularities of a ruled surface according to rotation minimizing frame
In this paper, Legendre curves on unit tangent bundle are given using rotation minimizing (RM) vector fields. Ruled surfaces corresponding to these curves are represented. Singularities of these ruled surfaces are also analyzed and classifed.
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Field-free nucleation of antivortices and giant vortices in non-superconducting materials
Giant vortices with higher phase-winding than $2\pi$ are usually energetically unfavorable, but geometric symmetry constraints on a superconductor in a magnetic field are known to stabilize such objects. Here, we show via microscopic calculations that giant vortices can appear in intrinsically non-superconducting mat...
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Quantum criticality in photorefractive optics: vortices in laser beams and antiferromagnets
We study vortex patterns in a prototype nonlinear optical system: counterpropagating laser beams in a photorefractive crystal, with or without the background photonic lattice. The vortices are effectively planar and described by the winding number and the "flavor" index, stemming from the fact that we have two parall...
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Burn-In Demonstrations for Multi-Modal Imitation Learning
Recent work on imitation learning has generated policies that reproduce expert behavior from multi-modal data. However, past approaches have focused only on recreating a small number of distinct, expert maneuvers, or have relied on supervised learning techniques that produce unstable policies. This work extends InfoG...
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Elliptic Determinantal Processes and Elliptic Dyson Models
We introduce seven families of stochastic systems of interacting particles in one-dimension corresponding to the seven families of irreducible reduced affine root systems. We prove that they are determinantal in the sense that all spatio-temporal correlation functions are given by determinants controlled by a single ...
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Searching for chemical signatures of brown dwarf formation
Recent studies have shown that close-in brown dwarfs in the mass range 35-55 M$_{\rm Jup}$ are almost depleted as companions to stars, suggesting that objects with masses above and below this gap might have different formation mechanisms. We determine the fundamental stellar parameters, as well as individual abundanc...
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The Klein Paradox: A New Treatment
The Dirac equation requires a treatment of the step potential that differs fundamentally from the traditional treatment, because the Dirac plane waves, besides momentum and spin, are characterized by a quantum number with the physical meaning of sign of charge. Since the Hermitean operator corresponding to this quant...
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What are the most important factors that influence the changes in London Real Estate Prices? How to quantify them?
In recent years, real estate industry has captured government and public attention around the world. The factors influencing the prices of real estate are diversified and complex. However, due to the limitations and one-sidedness of their respective views, they did not provide enough theoretical basis for the fluctua...
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A Multi-Wavelength Analysis of Dust and Gas in the SR 24S Transition Disk
We present new Atacama Large Millimeter/sub-millimeter Array (ALMA) 1.3 mm continuum observations of the SR 24S transition disk with an angular resolution $\lesssim0.18"$ (12 au radius). We perform a multi-wavelength investigation by combining new data with previous ALMA data at 0.45 mm. The visibilities and images o...
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Step bunching with both directions of the current: Vicinal W(110) surfaces versus atomistic scale model
We report for the first time the observation of bunching of monoatomic steps on vicinal W(110) surfaces induced by step up or step down currents across the steps. Measurements reveal that the size scaling exponent {\gamma}, connecting the maximal slope of a bunch with its height, differs depending on the current dire...
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Causal Bandits with Propagating Inference
Bandit is a framework for designing sequential experiments. In each experiment, a learner selects an arm $A \in \mathcal{A}$ and obtains an observation corresponding to $A$. Theoretically, the tight regret lower-bound for the general bandit is polynomial with respect to the number of arms $|\mathcal{A}|$. This makes ...
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The 2D Tree Sliding Window Discrete Fourier Transform
We present a new algorithm for the 2D Sliding Window Discrete Fourier Transform (SWDFT). Our algorithm avoids repeating calculations in overlapping windows by storing them in a tree data-structure based on the ideas of the Cooley- Tukey Fast Fourier Transform (FFT). For an $N_0 \times N_1$ array and $n_0 \times n_1$ ...
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Towards security defect prediction with AI
In this study, we investigate the limits of the current state of the art AI system for detecting buffer overflows and compare it with current static analysis tools. To do so, we developed a code generator, s-bAbI, capable of producing an arbitrarily large number of code samples of controlled complexity. We found that...
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Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks
In general, neural networks are not currently capable of learning tasks in a sequential fashion. When a novel, unrelated task is learnt by a neural network, it substantially forgets how to solve previously learnt tasks. One of the original solutions to this problem is pseudo-rehearsal, which involves learning the new...
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Multivariate Hadamard self-similarity: testing fractal connectivity
While scale invariance is commonly observed in each component of real world multivariate signals, it is also often the case that the inter-component correlation structure is not fractally connected, i.e., its scaling behavior is not determined by that of the individual components. To model this situation in a versati...
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Efficient barycentric point sampling on meshes
We present an easy-to-implement and efficient analytical inversion algorithm for the unbiased random sampling of a set of points on a triangle mesh whose surface density is specified by barycentric interpolation of non-negative per-vertex weights. The correctness of the inversion algorithm is verified via statistical...
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Femtosecond Optical Superregular Breathers
Superregular (SR) breathers are nonlinear wave structures formed by a unique nonlinear superposition of pairs of quasi-Akhmediev breathers. They describe a complete scenario of modulation instability that develops from localized small perturbations as well as an unusual quasiannihilation of breather collision. Here, ...
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Diversity, Topology, and the Risk of Node Re-identification in Labeled Social Graphs
Real network datasets provide significant benefits for understanding phenomena such as information diffusion or network evolution. Yet the privacy risks raised from sharing real graph datasets, even when stripped of user identity information, are significant. When nodes have associated attributes, the privacy risks i...
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Braid group action and root vectors for the $q$-Onsager algebra
We define two algebra automorphisms $T_0$ and $T_1$ of the $q$-Onsager algebra $B_c$, which provide an analog of G. Lusztig's braid group action for quantum groups. These automorphisms are used to define root vectors which give rise to a PBW basis for $B_c$. We show that the root vectors satisfy $q$-analogs of Onsage...
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Underapproximation of Reach-Avoid Sets for Discrete-Time Stochastic Systems via Lagrangian Methods
We examine Lagrangian techniques for computing underapproximations of finite-time horizon, stochastic reach-avoid level-sets for discrete-time, nonlinear systems. We use the concept of reachability of a target tube in the control literature to define robust reach-avoid sets which are parameterized by the target set, ...
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A Domain-Specific Language and Editor for Parallel Particle Methods
Domain-specific languages (DSLs) are of increasing importance in scientific high-performance computing to reduce development costs, raise the level of abstraction and, thus, ease scientific programming. However, designing and implementing DSLs is not an easy task, as it requires knowledge of the application domain an...
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Manifold regularization based on Nystr{ö}m type subsampling
In this paper, we study the Nystr{ö}m type subsampling for large scale kernel methods to reduce the computational complexities of big data. We discuss the multi-penalty regularization scheme based on Nystr{ö}m type subsampling which is motivated from well-studied manifold regularization schemes. We develop a theoreti...
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Path integral molecular dynamics with surface hopping for thermal equilibrium sampling of nonadiabatic systems
In this work, a novel ring polymer representation for multi-level quantum system is proposed for thermal average calculations. The proposed presentation keeps the discreteness of the electronic states: besides position and momentum, each bead in the ring polymer is also characterized by a surface index indicating the...
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The interplay of the collisionless nonlinear thin-shell instability with the ion acoustic instability
The nonlinear thin-shell instability (NTSI) may explain some of the turbulent hydrodynamic structures that are observed close to the collision boundary of energetic astrophysical outflows. It develops in nonplanar shells that are bounded on either side by a hydrodynamic shock, provided that the amplitude of the seed ...
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Multiple Scaled Contaminated Normal Distribution and Its Application in Clustering
The multivariate contaminated normal (MCN) distribution represents a simple heavy-tailed generalization of the multivariate normal (MN) distribution to model elliptical contoured scatters in the presence of mild outliers, referred to as "bad" points. The MCN can also automatically detect bad points. The price of thes...
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The Galaxy-Halo Connection Over The Last 13.3 Gyrs
We present new determinations of the stellar-to-halo mass relation (SHMR) at $z=0-10$ that match the evolution of the galaxy stellar mass function, the SFR$-M_*$ relation,and the cosmic star formation rate. We utilize a compilation of 40 observational studies from the literature and correct them for potential biases....
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State of the art of Trust and Reputation Systems in E-Commerce Context
This article proposes in depth comparative study of the most popular, used and analyzed Trust and Reputation System (TRS) according to the trust and reputation literature and in terms of specific trustworthiness criteria. This survey is realized relying on a selection of trustworthiness criteria that analyze and eval...
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Placing your Coins on a Shelf
We consider the problem of packing a family of disks "on a shelf", that is, such that each disk touches the $x$-axis from above and such that no two disks overlap. We prove that the problem of minimizing the distance between the leftmost point and the rightmost point of any disk is NP-hard. On the positive side, we s...
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Randomized Rumor Spreading in Ad Hoc Networks with Buffers
The randomized rumor spreading problem generates a big interest in the area of distributed algorithms due to its simplicity, robustness and wide range of applications. The two most popular communication paradigms used for spreading the rumor are Push and Pull algorithms. The former protocol allows nodes to send the r...
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A simple and efficient feedback control strategy for wastewater denitrification
Due to severe mathematical modeling and calibration difficulties open-loop feedforward control is mainly employed today for wastewater denitrification, which is a key ecological issue. In order to improve the resulting poor performances a new model-free control setting and its corresponding "intelligent" controller a...
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The interaction of Airy waves and solitons in the three-wave system
We employ the generic three-wave system, with the $\chi ^{(2)}$ interaction between two components of the fundamental-frequency (FF) wave and second-harmonic (SH) one, to consider collisions of truncated Airy waves (TAWs) and three-wave solitons in a setting which is not available in other nonlinear systems. The adva...
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A penalty criterion for score forecasting in soccer
This note proposes a penalty criterion for assessing correct score forecasting in a soccer match. The penalty is based on hierarchical priorities for such a forecast i.e., i) Win, Draw and Loss exact prediction and ii) normalized Euclidian distance between actual and forecast scores. The procedure is illustrated on t...
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A robust RUV-testing procedure via gamma-divergence
Identification of differentially expressed genes (DE-genes) is commonly conducted in modern biomedical researches. However, unwanted variation inevitably arises during the data collection process, which could make the detection results heavily biased. It is suggested to remove the unwanted variation while keeping the...
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On the Distribution, Model Selection Properties and Uniqueness of the Lasso Estimator in Low and High Dimensions
We derive expressions for the finite-sample distribution of the Lasso estimator in the context of a linear regression model with normally distributed errors in low as well as in high dimensions by exploiting the structure of the optimization problem defining the estimator. In low dimensions we assume full rank of the...
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Transductive Boltzmann Machines
We present transductive Boltzmann machines (TBMs), which firstly achieve transductive learning of the Gibbs distribution. While exact learning of the Gibbs distribution is impossible by the family of existing Boltzmann machines due to combinatorial explosion of the sample space, TBMs overcome the problem by adaptivel...
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Human-Robot Trust Integrated Task Allocation and Symbolic Motion planning for Heterogeneous Multi-robot Systems
This paper presents a human-robot trust integrated task allocation and motion planning framework for multi-robot systems (MRS) in performing a set of tasks concurrently. A set of task specifications in parallel are conjuncted with MRS to synthesize a task allocation automaton. Each transition of the task allocation a...
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A five-decision testing procedure to infer on unidimensional parameter
A statistical test can be seen as a procedure to produce a decision based on observed data, where some decisions consist of rejecting a hypothesis (yielding a significant result) and some do not, and where one controls the probability to make a wrong rejection at some pre-specified significance level. Whereas traditi...
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PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts
We present PubMed 200k RCT, a new dataset based on PubMed for sequential sentence classification. The dataset consists of approximately 200,000 abstracts of randomized controlled trials, totaling 2.3 million sentences. Each sentence of each abstract is labeled with their role in the abstract using one of the followin...
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Convergence radius of perturbative Lindblad driven non-equilibrium steady states
We address the problem of analyzing the radius of convergence of perturbative expansion of non-equilibrium steady states of Lindblad driven spin chains. A simple formal approach is developed for systematically computing the perturbative expansion of small driven systems. We consider the paradigmatic model of an open ...
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A 2D metamaterial with auxetic out-of-plane behavior and non-auxetic in-plane behavior
Customarily, in-plane auxeticity and synclastic bending behavior (i.e. out-of-plane auxeticity) are not independent, being the latter a manifestation of the former. Basically, this is a feature of three-dimensional bodies. At variance, two-dimensional bodies have more freedom to deform than three-dimensional ones. He...
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Isolated Loops in Quantum Feedback Networks
A scheme making use of an isolated feedback loop was recently proposed in \cite{GP_} for creating an arbitrary bilinear Hamiltonian interaction between two multi-mode Linear Quantum Stochastic Systems (LQSSs). In this work we examine the presence of an isolated feedback loop in a general SLH network, and derive the m...
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Distance-based Depths for Directional Data
Directional data are constrained to lie on the unit sphere of~$\mathbb{R}^q$ for some~$q\geq 2$. To address the lack of a natural ordering for such data, depth functions have been defined on spheres. However, the depths available either lack flexibility or are so computationally expensive that they can only be used f...
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Two-dimensional Schrödinger symmetry and three-dimensional breathers and Kelvin-ripple complexes as quasi-massive-Nambu-Goldstone modes
Bose-Einstein condensates (BECs) confined in a two-dimensional (2D) harmonic trap are known to possess a hidden 2D Schrödinger symmetry, that is, the Schrödinger symmetry modified by a trapping potential. Spontaneous breaking of this symmetry gives rise to a breathing motion of the BEC, whose oscillation frequency is...
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Groupoid of morphisms of groupoids
In this paper we construct two groupoids from morphisms of groupoids, with one from a categorical viewpoint and the other from a geometric viewpoint. We show that for each pair of groupoids, the two kinds of groupoids of morphisms are equivalent. Then we study the automorphism groupoid of a groupoid.
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Spin alignment of stars in old open clusters
Stellar clusters form by gravitational collapse of turbulent molecular clouds, with up to several thousand stars per cluster. They are thought to be the birthplace of most stars and therefore play an important role in our understanding of star formation, a fundamental problem in astrophysics. The initial conditions o...
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Global well-posedness of critical surface quasigeostrophic equation on the sphere
In this paper we prove global well-posedness of the critical surface quasigeostrophic equation on the two dimensional sphere building on some earlier work of the authors. The proof relies on an improving of the previously known pointwise inequality for fractional laplacians as in the work of Constantin and Vicol for ...
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On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples
Understanding and characterizing the subspaces of adversarial examples aid in studying the robustness of deep neural networks (DNNs) to adversarial perturbations. Very recently, Ma et al. (ICLR 2018) proposed to use local intrinsic dimensionality (LID) in layer-wise hidden representations of DNNs to study adversarial...
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A properly embedded holomorphic disc in the ball with finite area and dense boundary curve
In this paper we construct a properly embedded holomorphic disc in the unit ball $\mathbb{B}^2$ of $\mathbb{C}^2$ having a surprising combination of properties: on the one hand, it has finite area and hence is the zero set of a bounded holomorphic function on $\mathbb{B}^2$; on the other hand, its boundary curve is e...
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Kähler differential algebras for 0-dimensional schemes
Given a 0-dimensional scheme in a projective space $\mathbb{P}^n$ over a field $K$, we study the Kähler differential algebra $\Omega_{R/K}$ of its homogeneous coordinate ring $R$. Using explicit presentations of the modules $\Omega^m_{R/K}$ of Kähler differential $m$-forms, we determine many values of their Hilbert f...
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Benchmarks and reliable DFT results for spin-crossover complexes
DFT is used throughout nanoscience, especially when modeling spin-dependent properties that are important in spintronics. But standard quantum chemical methods (both CCSD(T) and self-consistent semilocal density functional calculations) fail badly for the spin adiabatic energy difference in Fe(II) spin-crossover comp...
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The Road to Success: Assessing the Fate of Linguistic Innovations in Online Communities
We investigate the birth and diffusion of lexical innovations in a large dataset of online social communities. We build on sociolinguistic theories and focus on the relation between the spread of a novel term and the social role of the individuals who use it, uncovering characteristics of innovators and adopters. Fin...
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