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Dual Supervised Learning
Many supervised learning tasks are emerged in dual forms, e.g., English-to-French translation vs. French-to-English translation, speech recognition vs. text to speech, and image classification vs. image generation. Two dual tasks have intrinsic connections with each other due to the probabilistic correlation between ...
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Pentavalent symmetric graphs of order four times an odd square-free integer
A graph is said to be symmetric if its automorphism group is transitive on its arcs. Guo et al. (Electronic J. Combin. 18, \#P233, 2011) and Pan et al. (Electronic J. Combin. 20, \#P36, 2013) determined all pentavalent symmetric graphs of order $4pq$. In this paper, we shall generalize this result by determining all ...
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Applying the Polyhedral Model to Tile Time Loops in Devito
The run time of many scientific computation applications for numerical methods is heavily dependent on just a few multi-dimensional loop nests. Since these applications are often limited by memory bandwidth rather than computational resources they can benefit greatly from any optimizations which decrease the run time...
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Deictic Image Maps: An Abstraction For Learning Pose Invariant Manipulation Policies
In applications of deep reinforcement learning to robotics, it is often the case that we want to learn pose invariant policies: policies that are invariant to changes in the position and orientation of objects in the world. For example, consider a peg-in-hole insertion task. If the agent learns to insert a peg into o...
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Charged Vector Particles Tunneling From 5D Black Hole and Black Ring
In this paper, we investigate the Hawking radiation process as a semiclassical quantum tunneling phenomenon from black ring and Myers-Perry black holes in 5-dimensional (5D) spaces. Using Lagrangian of Glashow-Weinberg-Salam model with background electromagnetic field (for charged W-bosons) and the WKB approximation,...
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Implementing implicit OpenMP data sharing on GPUs
OpenMP is a shared memory programming model which supports the offloading of target regions to accelerators such as NVIDIA GPUs. The implementation in Clang/LLVM aims to deliver a generic GPU compilation toolchain that supports both the native CUDA C/C++ and the OpenMP device offloading models. There are situations w...
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Real-Time Impulse Noise Removal from MR Images for Radiosurgery Applications
In the recent years image processing techniques are used as a tool to improve detection and diagnostic capabilities in the medical applications. Medical applications have been so much affected by these techniques which some of them are embedded in medical instruments such as MRI, CT and other medical devices. Among t...
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Pitfalls of Graph Neural Network Evaluation
Semi-supervised node classification in graphs is a fundamental problem in graph mining, and the recently proposed graph neural networks (GNNs) have achieved unparalleled results on this task. Due to their massive success, GNNs have attracted a lot of attention, and many novel architectures have been put forward. In t...
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Randomized CP Tensor Decomposition
The CANDECOMP/PARAFAC (CP) tensor decomposition is a popular dimensionality-reduction method for multiway data. Dimensionality reduction is often sought since many high-dimensional tensors have low intrinsic rank relative to the dimension of the ambient measurement space. However, the emergence of `big data' poses si...
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App Store 2.0: From Crowd Information to Actionable Feedback in Mobile Ecosystems
Given the increasing competition in mobile app ecosystems, improving the experience of users has become a major goal for app vendors. This article introduces a visionary app store, called APP STORE 2.0, which exploits crowdsourced information about apps, devices and users to increase the overall quality of the delive...
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An Information Matrix Approach for State Secrecy
This paper studies the problem of remote state estimation in the presence of a passive eavesdropper. A sensor measures a linear plant's state and transmits it to an authorized user over a packet-dropping channel, which is susceptible to eavesdropping. Our goal is to design a coding scheme such that the eavesdropper c...
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Adversarial Attacks on Node Embeddings
The goal of network representation learning is to learn low-dimensional node embeddings that capture the graph structure and are useful for solving downstream tasks. However, despite the proliferation of such methods there is currently no study of their robustness to adversarial attacks. We provide the first adversar...
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Time-reversed magnetically controlled perturbation (TRMCP) optical focusing inside scattering media
Manipulating and focusing light deep inside biological tissue and tissue-like complex media has been desired for long yet considered challenging. One feasible strategy is through optical wavefront engineering, where the optical scattering-induced phase distortions are time reversed or pre-compensated so that photons ...
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Dimensionality-strain phase diagram of strontium iridates
The competition between spin-orbit coupling, bandwidth ($W$) and electron-electron interaction ($U$) makes iridates highly susceptible to small external perturbations, which can trigger the onset of novel types of electronic and magnetic states. Here we employ {\em first principles} calculations based on density func...
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Herschel survey and modelling of externally-illuminated photoevaporating protoplanetary disks
Protoplanetary disks undergo substantial mass-loss by photoevaporation, a mechanism which is crucial to their dynamical evolution. However, the processes regulating the gas energetics have not been well constrained by observations so far. We aim at studying the processes involved in disk photoevaporation when it is d...
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Observation of Spatio-temporal Instability of Femtosecond Pulses in Normal Dispersion Multimode Graded-Index Fiber
We study the spatio-temporal instability generated by a universal unstable attractor in normal dispersion graded-index multimode fiber (GRIN MMF) for femtosecond pulses. Our results present the generation of geometric parametric instability (GPI) sidebands with ultrashort input pulse for the first time. Observed GPI ...
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Spectral curves for the rogue waves
Here we find the spectral curves, corresponding to the known rational or quasi-rational solutions of AKNS hierarchy equations, ultimately connected with the modeling of the rogue waves events in the optical waveguides and in hydrodynamics. We also determine spectral curves for the multi-phase trigonometric, hyperboli...
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Volume functional of compact manifolds with a prescribed boundary metric
We prove that a critical metric of the volume functional on a four-dimensional compact manifold with boundary satisfying a second-order vanishing condition on the Weyl tensor must be isometric to a geodesic ball in a simply connected space form $\mathbb{R}^{4}$, $\mathbb{H}^{4}$ or $\mathbb{S}^{4}.$ Moreover, we prov...
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Deep Multitask Learning for Semantic Dependency Parsing
We present a deep neural architecture that parses sentences into three semantic dependency graph formalisms. By using efficient, nearly arc-factored inference and a bidirectional-LSTM composed with a multi-layer perceptron, our base system is able to significantly improve the state of the art for semantic dependency ...
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Chentsov's theorem for exponential families
Chentsov's theorem characterizes the Fisher information metric on statistical models as essentially the only Riemannian metric that is invariant under sufficient statistics. This implies that each statistical model is naturally equipped with a geometry, so Chentsov's theorem explains why many statistical properties c...
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Dark trions and biexcitons in WS2 and WSe2 made bright by e-e scattering
The direct band gap character and large spin-orbit splitting of the valence band edges (at the K and K' valleys) in monolayer transition metal dichalcogenides have put these two-dimensional materials under the spot-light of intense experimental and theoretical studies. In particular, for Tungsten dichalcogenides it h...
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SGDLibrary: A MATLAB library for stochastic gradient descent algorithms
We consider the problem of finding the minimizer of a function $f: \mathbb{R}^d \rightarrow \mathbb{R}$ of the finite-sum form $\min f(w) = 1/n\sum_{i}^n f_i(w)$. This problem has been studied intensively in recent years in the field of machine learning (ML). One promising approach for large-scale data is to use a st...
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Structured Uncertainty Prediction Networks
This paper is the first work to propose a network to predict a structured uncertainty distribution for a synthesized image. Previous approaches have been mostly limited to predicting diagonal covariance matrices. Our novel model learns to predict a full Gaussian covariance matrix for each reconstruction, which permit...
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Shannon's entropy and its Generalizations towards Statistics, Reliability and Information Science during 1948-2018
Starting from the pioneering works of Shannon and Weiner in 1948, a plethora of works have been reported on entropy in different directions. Entropy-related review work in the direction of statistics, reliability and information science, to the best of our knowledge, has not been reported so far. Here we have tried t...
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Understanding MIDI: A Painless Tutorial on Midi Format
A short overview demystifying the midi audio format is presented. The goal is to explain the file structure and how the instructions are used to produce a music signal, both in the case of monophonic signals as for polyphonic signals.
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Optimization, fast and slow: optimally switching between local and Bayesian optimization
We develop the first Bayesian Optimization algorithm, BLOSSOM, which selects between multiple alternative acquisition functions and traditional local optimization at each step. This is combined with a novel stopping condition based on expected regret. This pairing allows us to obtain the best characteristics of both ...
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Optimization of exposure time division for wide field observations
The optical observations of wide fields of view encounter the problem of selection of best exposure time. As there are usually plenty of objects observed simultaneously, the quality of photometry of the brightest ones is always better than of the dimmer ones. Frequently all of them are equally interesting for the ast...
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Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder
Multi-Entity Dependence Learning (MEDL) explores conditional correlations among multiple entities. The availability of rich contextual information requires a nimble learning scheme that tightly integrates with deep neural networks and has the ability to capture correlation structures among exponentially many outcomes...
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A recognition algorithm for simple-triangle graphs
A simple-triangle graph is the intersection graph of triangles that are defined by a point on a horizontal line and an interval on another horizontal line. The time complexity of the recognition problem for simple-triangle graphs was a longstanding open problem, which was recently settled. This paper provides a new r...
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A normalized gradient flow method with attractive-repulsive splitting for computing ground states of Bose-Einstein condensates with higher-order interaction
In this paper, we generalize the normalized gradient flow method to compute the ground states of Bose-Einstein condensates (BEC) with higher order interactions (HOI), which is modelled via the modified Gross-Pitaevskii equation (MGPE). Schemes constructed in naive ways suffer from severe stability problems due to the...
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Truncation in Hahn Fields is Undecidable and Wild
We show that in any nontrivial Hahn field with truncation as a primitive operation we can interpret the monadic second-order logic of the additive monoid of natural numbers and are thus undecidable. We also specify a definable binary relation on such a structure that has $\SOP$ and $\TP$.
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Direct measurement of laser aberration and ahead point from ARTEMIS satellite through strong clouds
Laser communication has advances in compared with radio frequency communication as result of much high carrier frequency from ultraviolet to near infrared. Very narrow laser beam is possible to form with very high power density. But laser beam has high destruction and attenuation on clouds, turbulence, scattering on ...
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DNN-Buddies: A Deep Neural Network-Based Estimation Metric for the Jigsaw Puzzle Problem
This paper introduces the first deep neural network-based estimation metric for the jigsaw puzzle problem. Given two puzzle piece edges, the neural network predicts whether or not they should be adjacent in the correct assembly of the puzzle, using nothing but the pixels of each piece. The proposed metric exhibits an...
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Attack Analysis for Distributed Control Systems: An Internal Model Principle Approach
Although adverse effects of attacks have been acknowledged in many cyber-physical systems, there is no system-theoretic comprehension of how a compromised agent can leverage communication capabilities to maximize the damage in distributed multi-agent systems. A rigorous analysis of cyber-physical attacks enables us t...
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A conservative scheme for electromagnetic simulation of magnetized plasmas with kinetic electrons
A conservative scheme has been formulated and verified for gyrokinetic particle simulations of electromagnetic waves and instabilities in magnetized plasmas. An electron continuity equation derived from drift kinetic equation is used to time advance electron density perturbation by using the perturbed mechanical flow...
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Corrupt Bandits for Preserving Local Privacy
We study a variant of the stochastic multi-armed bandit (MAB) problem in which the rewards are corrupted. In this framework, motivated by privacy preservation in online recommender systems, the goal is to maximize the sum of the (unobserved) rewards, based on the observation of transformation of these rewards through...
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Deep Reinforcement Learning based Optimal Control of Hot Water Systems
Energy consumption for hot water production is a major draw in high efficiency buildings. Optimizing this has typically been approached from a thermodynamics perspective, decoupled from occupant influence. Furthermore, optimization usually presupposes existence of a detailed dynamics model for the hot water system. T...
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A Model-Based Fuzzy Control Approach to Achieving Adaptation with Contextual Uncertainties
Self-adaptive system (SAS) is capable of adjusting its behavior in response to meaningful changes in the operational context and itself. Due to the inherent volatility of the open and changeable environment in which SAS is embedded, the ability of adaptation is highly demanded by many software-intensive systems. Two ...
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See the Near Future: A Short-Term Predictive Methodology to Traffic Load in ITS
The Intelligent Transportation System (ITS) targets to a coordinated traffic system by applying the advanced wireless communication technologies for road traffic scheduling. Towards an accurate road traffic control, the short-term traffic forecasting to predict the road traffic at the particular site in a short perio...
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Single-Crystal N-polar GaN p-n Diodes by Plasma-Assisted Molecular Beam Epitaxy
N-polar GaN p-n diodes are realized on single-crystal N-polar GaN bulk wafers by plasma-assisted molecular beam epitaxy growth. The current-voltage characteristics show high-quality rectification and electroluminescence characteristics with a high on/off current ratio and interband photon emission. The measured elect...
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Particle Identification with the TOP and ARICH detectors at Belle II
Particle identification at the Belle II experiment will be provided by two ring imaging Cherenkov devices, the time of propagation counters in the central region and the proximity focusing RICH with aerogel radiator in the forward end-cap region. The key features of these two detectors, the performance studies, and t...
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Face Detection and Face Recognition In the Wild Using Off-the-Shelf Freely Available Components
This paper presents an easy and efficient face detection and face recognition approach using free software components from the internet. Face detection and face recognition problems have wide applications in home and office security. Therefore this work will helpful for those searching for a free face off-the-shelf f...
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End-to-end Learning of Deterministic Decision Trees
Conventional decision trees have a number of favorable properties, including interpretability, a small computational footprint and the ability to learn from little training data. However, they lack a key quality that has helped fuel the deep learning revolution: that of being end-to-end trainable, and to learn from s...
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Conceptualization of Object Compositions Using Persistent Homology
A topological shape analysis is proposed and utilized to learn concepts that reflect shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud segment constellations within objects. Therein constellations are decomposed and described in an hierarchical manner - from single segments ...
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Long-term Blood Pressure Prediction with Deep Recurrent Neural Networks
Existing methods for arterial blood pressure (BP) estimation directly map the input physiological signals to output BP values without explicitly modeling the underlying temporal dependencies in BP dynamics. As a result, these models suffer from accuracy decay over a long time and thus require frequent calibration. In...
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Risks for life on habitable planets from superflares of their host stars
We explore some of the ramifications arising from superflares on the evolutionary history of Earth, other planets in the Solar system, and exoplanets. We propose that the most powerful superflares can serve as plausible drivers of extinction events, and that their periodicity could correspond to certain patterns in t...
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Thermodynamics of Spin-1/2 Kagomé Heisenberg Antiferromagnet: Algebraic Paramagnetic Liquid and Finite-Temperature Phase Diagram
Quantum fluctuations from frustration can trigger quantum spin liquids (QSLs) at zero temperature. However, it is unclear how thermal fluctuations affect a QSL. We employ state-of-the-art tensor network-based methods to explore the ground state and thermodynamic properties of the spin-1/2 kagome Heisenberg antiferrom...
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Fast Rigid 3D Registration Solution: A Simple Method Free of SVD and Eigen-Decomposition
A novel solution is obtained to solve the rigid 3D registration problem, motivated by previous eigen-decomposition approaches. Different from existing solvers, the proposed algorithm does not require sophisticated matrix operations e.g. singular value decomposition or eigenvalue decomposition. Instead, the optimal ei...
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Massive MIMO 5G Cellular Networks: mm-wave vs. μ-wave Frequencies
Enhanced mobile broadband (eMBB) is one of the key use-cases for the development of the new standard 5G New Radio for the next generation of mobile wireless networks. Large-scale antenna arrays, a.k.a. Massive MIMO, the usage of carrier frequencies in the range 10-100 GHz, the so-called millimeter wave (mm-wave) band...
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Independent Set Size Approximation in Graph Streams
We study the problem of estimating the size of independent sets in a graph $G$ defined by a stream of edges. Our approach relies on the Caro-Wei bound, which expresses the desired quantity in terms of a sum over nodes of the reciprocal of their degrees, denoted by $\beta(G)$. Our results show that $\beta(G)$ can be a...
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Two-Person Zero-Sum Games with Unbounded Payoff Functions and Uncertain Expected Payoffs
This paper provides sufficient conditions for the existence of values and solutions for two-person zero-sum one-step games with possibly noncompact action sets for both players and possibly unbounded payoff functions, which may be neither convex nor concave. For such games payoffs may not be defined for some pairs of...
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Scale relativistic formulation of non-differentiable mechanics II: The Schroedinger picture
This article is the second in a series of two presenting the Scale Relativistic approach to non-differentiability in mechanics and its relation to quantum mechanics. Here, we show Schroedinger's equation to be a reformulation of Newton's fundamental relation of dynamics as generalized to non-differentiable geometries...
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Compact arrangement for femtosecond laser induced generation of broadband hard x-ray pulses
We present a simple apparatus for femtosecond laser induced generation of X-rays. The apparatus consists of a vacuum chamber containing an off-axis parabolic focusing mirror, a reel system, a debris protection setup, a quartz window for the incoming laser beam, and an X-ray window. Before entering the vacuum chamber,...
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Hierarchical Summarization of Metric Changes
We study changes in metrics that are defined on a cartesian product of trees. Such metrics occur naturally in many practical applications, where a global metric (such as revenue) can be broken down along several hierarchical dimensions (such as location, gender, etc). Given a change in such a metric, our goal is to i...
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Manifold learning with bi-stochastic kernels
In this paper we answer the following question: what is the infinitesimal generator of the diffusion process defined by a kernel that is normalized such that it is bi-stochastic with respect to a specified measure? More precisely, under the assumption that data is sampled from a Riemannian manifold we determine how t...
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The importance of the weak: Interaction modifiers in artificial spin ices
The modification of geometry and interactions in two-dimensional magnetic nanosystems has enabled a range of studies addressing the magnetic order, collective low-energy dynamics, and emergent magnetic properties, in e.g. artificial spin ice structures. The common denominator of all these investigations is the use of...
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How To Extract Fashion Trends From Social Media? A Robust Object Detector With Support For Unsupervised Learning
With the proliferation of social media, fashion inspired from celebrities, reputed designers as well as fashion influencers has shortened the cycle of fashion design and manufacturing. However, with the explosion of fashion related content and large number of user generated fashion photos, it is an arduous task for f...
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Multi-Task Learning Using Neighborhood Kernels
This paper introduces a new and effective algorithm for learning kernels in a Multi-Task Learning (MTL) setting. Although, we consider a MTL scenario here, our approach can be easily applied to standard single task learning, as well. As shown by our empirical results, our algorithm consistently outperforms the tradit...
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Optimized Bucket Wheel Design for Asteroid Excavation
Current spacecraft need to launch with all of their required fuel for travel. This limits the system performance, payload capacity, and mission flexibility. One compelling alternative is to perform In-Situ Resource Utilization (ISRU) by extracting fuel from small bodies in local space such as asteroids or small satel...
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Fraction of the X-ray selected AGNs with optical emission lines in galaxy groups
Compared with numerous X-ray dominant active galactic nuclei (AGNs) without emission-line signatures in their optical spectra, the X-ray selected AGNs with optical emission lines are probably still in the high-accretion phase of black hole growth. This paper presents an investigation on the fraction of these X-ray de...
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A local search 2.917-approximation algorithm for duo-preservation string mapping
We study the {\em maximum duo-preservation string mapping} ({\sc Max-Duo}) problem, which is the complement of the well studied {\em minimum common string partition} ({\sc MCSP}) problem. Both problems have applications in many fields including text compression and bioinformatics. Motivated by an earlier local search...
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Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code
The current trends in next-generation exascale systems go towards integrating a wide range of specialized (co-)processors into traditional supercomputers. Due to the efficiency of heterogeneous systems in terms of Watts and FLOPS per surface unit, opening the access of heterogeneous platforms to a wider range of user...
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Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning
We propose a general approach to modeling semi-supervised learning (SSL) algorithms. Specifically, we present a declarative language for modeling both traditional supervised classification tasks and many SSL heuristics, including both well-known heuristics such as co-training and novel domain-specific heuristics. In ...
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Fabrication of a centimeter-long cavity on a nanofiber for cavity QED
We report the fabrication of a 1.2 cm long cavity directly on a nanofiber using femtosecond laser ablation. The cavity modes with finesse value in the range 200-400 can still maintain the transmission between 40-60%, which can enable "strong-coupling" regime of cavity QED for a single atom trapped 200 nm away from th...
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Optimized Deformed Laplacian for Spectrum-based Community Detection in Sparse Heterogeneous Graphs
Spectral clustering is one of the most popular, yet still incompletely understood, methods for community detection on graphs. In this article we study spectral clustering based on the deformed Laplacian matrix $D-rA$, for sparse heterogeneous graphs (following a two-class degree-corrected stochastic block model). For...
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High dimensional deformed rectangular matrices with applications in matrix denoising
We consider the recovery of a low rank $M \times N$ matrix $S$ from its noisy observation $\tilde{S}$ in two different regimes. Under the assumption that $M$ is comparable to $N$, we propose two consistent estimators for $S$. Our analysis relies on the local behavior of the large dimensional rectangular matrices with...
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Validation of the 3-under-2 principle of cell wall growth in Gram-positive bacteria by simulation of a simple coarse-grained model
The aim of this work is to propose a first coarse-grained model of Bacillus subtilis cell wall, handling explicitly the existence of multiple layers of peptidoglycans. In this first work, we aim at the validation of the recently proposed "three under two" principle.
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Self-bound quantum droplets in atomic mixtures
Self-bound quantum droplets are a newly discovered phase in the context of ultracold atoms. In this work we report their experimental realization following the original proposal by Petrov [Phys. Rev. Lett. 115, 155302 (2015)], using an attractive bosonic mixture. In this system spherical droplets form due to the bala...
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Control of Gene Regulatory Networks with Noisy Measurements and Uncertain Inputs
This paper is concerned with the problem of stochastic control of gene regulatory networks (GRNs) observed indirectly through noisy measurements and with uncertainty in the intervention inputs. The partial observability of the gene states and uncertainty in the intervention process are accounted for by modeling GRNs ...
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On Memory System Design for Stochastic Computing
Growing uncertainty in design parameters (and therefore, in design functionality) renders stochastic computing particularly promising, which represents and processes data as quantized probabilities. However, due to the difference in data representation, integrating conventional memory (designed and optimized for non-...
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Strongly convex stochastic online optimization on a unit simplex with application to the mixing least square regression
In this paper we propose a new approach to obtain mixing least square regression estimate by means of stochastic online mirror descent in non-euclidian set-up.
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Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos
Despite rapid advances in face recognition, there remains a clear gap between the performance of still image-based face recognition and video-based face recognition, due to the vast difference in visual quality between the domains and the difficulty of curating diverse large-scale video datasets. This paper addresses...
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Unifying DAGs and UGs
We introduce a new class of graphical models that generalizes Lauritzen-Wermuth-Frydenberg chain graphs by relaxing the semi-directed acyclity constraint so that only directed cycles are forbidden. Moreover, up to two edges are allowed between any pair of nodes. Specifically, we present local, pairwise and global Mar...
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Program Completionin the Input Language of GRINGO
We argue that turning a logic program into a set of completed definitions can be sometimes thought of as the "reverse engineering" process of generating a set of conditions that could serve as a specification for it. Accordingly, it may be useful to define completion for a large class of ASP programs and to automate ...
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Numerical modelling of surface water wave interaction with a moving wall
In the present manuscript, we consider the practical problem of wave interaction with a vertical wall. However, the novelty here consists in the fact that the wall can move horizontally due to a system of springs. The water wave evolution is described with the free surface potential flow model. Then, a semi-analytica...
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Dynamic Curriculum Learning for Imbalanced Data Classification
Human attribute analysis is a challenging task in the field of computer vision, since the data is largely imbalance-distributed. Common techniques such as re-sampling and cost-sensitive learning require prior-knowledge to train the system. To address this problem, we propose a unified framework called Dynamic Curricu...
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Causal Discovery in the Presence of Measurement Error: Identifiability Conditions
Measurement error in the observed values of the variables can greatly change the output of various causal discovery methods. This problem has received much attention in multiple fields, but it is not clear to what extent the causal model for the measurement-error-free variables can be identified in the presence of me...
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Elliptic fibrations on covers of the elliptic modular surface of level 5
We consider the K3 surfaces that arise as double covers of the elliptic modular surface of level 5, $R_{5,5}$. Such surfaces have a natural elliptic fibration induced by the fibration on $R_{5,5}$. Moreover, they admit several other elliptic fibrations. We describe such fibrations in terms of linear systems of curves...
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A wide field-of-view crossed Dragone optical system using the anamorphic aspherical surfaces
A side-fed crossed Dragone telescope provides a wide field-of-view. This type of a telescope is commonly employed in the measurement of cosmic microwave background (CMB) polarization, which requires an image-space telecentric telescope with a large focal plane over broadband coverage. We report the design of the wide...
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Searching for Biophysically Realistic Parameters for Dynamic Neuron Models by Genetic Algorithms from Calcium Imaging Recording
Individual Neurons in the nervous systems exploit various dynamics. To capture these dynamics for single neurons, we tune the parameters of an electrophysiological model of nerve cells, to fit experimental data obtained by calcium imaging. A search for the biophysical parameters of this model is performed by means of...
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Matrix elements of irreducible representations of $\mathrm{SU}(n+1)\times\mathrm{SU}(n+1)$ and multivariable matrix-valued orthogonal polynomials
In Part 1 we study the spherical functions on compact symmetric pairs of arbitrary rank under a suitable multiplicity freeness assumption and additional conditions on the branching rules. The spherical functions are taking values in the spaces of linear operators of a finite dimensional representation of the subgroup...
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On the variance of internode distance under the multispecies coalescent
We consider the problem of estimating species trees from unrooted gene tree topologies in the presence of incomplete lineage sorting, a common phenomenon that creates gene tree heterogeneity in multilocus datasets. One popular class of reconstruction methods in this setting is based on internode distances, i.e. the a...
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DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN
Recently, the introduction of the generative adversarial network (GAN) and its variants has enabled the generation of realistic synthetic samples, which has been used for enlarging training sets. Previous work primarily focused on data augmentation for semi-supervised and supervised tasks. In this paper, we instead f...
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Online Human Gesture Recognition using Recurrent Neural Networks and Wearable Sensors
Gestures are a natural communication modality for humans. The ability to interpret gestures is fundamental for robots aiming to naturally interact with humans. Wearable sensors are promising to monitor human activity, in particular the usage of triaxial accelerometers for gesture recognition have been explored. Despi...
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Conditional Variance Penalties and Domain Shift Robustness
When training a deep network for image classification, one can broadly distinguish between two types of latent features of images that will drive the classification. Following the notation of Gong et al. (2016), we can divide latent features into (i) "core" features $X^\text{core}$ whose distribution $X^\text{core}\v...
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The First Optical Spectra of Wolf Rayet Stars in M101 Revealed with Gemini/GMOS
Deep narrow-band HST imaging of the iconic spiral galaxy M101 has revealed over a thousand new Wolf Rayet (WR) candidates. We report spectrographic confirmation of 10 HeII emission line sources hosting 15 WR stars. We find WR stars present at both sub- and super-solar metalicities with WC stars favouring more metal-r...
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Machine Learning Topological Invariants with Neural Networks
In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accurac...
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Topics and Label Propagation: Best of Both Worlds for Weakly Supervised Text Classification
We propose a Label Propagation based algorithm for weakly supervised text classification. We construct a graph where each document is represented by a node and edge weights represent similarities among the documents. Additionally, we discover underlying topics using Latent Dirichlet Allocation (LDA) and enrich the do...
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Parallel Markov Chain Monte Carlo for the Indian Buffet Process
Indian Buffet Process based models are an elegant way for discovering underlying features within a data set, but inference in such models can be slow. Inferring underlying features using Markov chain Monte Carlo either relies on an uncollapsed representation, which leads to poor mixing, or on a collapsed representati...
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The Robot Routing Problem for Collecting Aggregate Stochastic Rewards
We propose a new model for formalizing reward collection problems on graphs with dynamically generated rewards which may appear and disappear based on a stochastic model. The *robot routing problem* is modeled as a graph whose nodes are stochastic processes generating potential rewards over discrete time. The rewards...
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Estimating occupation time functionals
We study the estimation of integral type functionals $\int_{0}^{t}f(X_{r})dr$ for a function $f$ and a $d$-dimensional càdlàg process $X$ with respect to discrete observations by a Riemann-sum estimator. Based on novel semimartingale approximations in the Fourier domain, central limit theorems are proved for $L^{2}$-...
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Bootstrapping a Lexicon for Emotional Arousal in Software Engineering
Emotional arousal increases activation and performance but may also lead to burnout in software development. We present the first version of a Software Engineering Arousal lexicon (SEA) that is specifically designed to address the problem of emotional arousal in the software developer ecosystem. SEA is built using a ...
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Early Solar System irradiation quantified by linked vanadium and beryllium isotope variations in meteorites
X-ray emission in young stellar objects (YSOs) is orders of magnitude more intense than in main sequence stars1,2, suggestive of cosmic ray irradiation of surrounding accretion disks. Protoplanetary disk irradiation has been detected around YSOs by HERSCHEL3. In our solar system, short-lived 10Be (half-life = 1.39 My...
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Two classes of nonlocal Evolution Equations related by a shared Traveling Wave Problem
We consider reaction-diffusion equations and Korteweg-de Vries-Burgers (KdVB) equations, i.e. scalar conservation laws with diffusive-dispersive regularization. We review the existence of traveling wave solutions for these two classes of evolution equations. For classical equations the traveling wave problem (TWP) fo...
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Analyzing IO Amplification in Linux File Systems
We present the first systematic analysis of read, write, and space amplification in Linux file systems. While many researchers are tackling write amplification in key-value stores, IO amplification in file systems has been largely unexplored. We analyze data and metadata operations on five widely-used Linux file syst...
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Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS
The features of collaboration patterns are often considered to be different from discipline to discipline. Meanwhile, collaborating among disciplines is an obvious feature emerged in modern scientific research, which incubates several interdisciplines. The features of collaborations in and among the disciplines of bi...
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Inflationary magneto-(non)genesis, increasing kinetic couplings, and the strong coupling problem
We study the generation of magnetic fields during inflation making use of a coupling of the inflaton and moduli fields to electromagnetism via the photon kinetic term, and assuming that the coupling is an increasing function of time. We demonstrate that the strong coupling problem of inflationary magnetogenesis can b...
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HornDroid: Practical and Sound Static Analysis of Android Applications by SMT Solving
We present HornDroid, a new tool for the static analysis of information flow properties in Android applications. The core idea underlying HornDroid is to use Horn clauses for soundly abstracting the semantics of Android applications and to express security properties as a set of proof obligations that are automatical...
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Assessing the reliability polynomial based on percolation theory
In this paper, we study the robustness of network topologies. We use the concept of percolation as measuring tool to assess the reliability polynomial of those systems which can be modeled as a general inhomogeneous random graph as well as scale-free random graph.
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Interval Exchange Transformations and Low-Discrepancy
In [Mas82] and [Vee78] it was proved independently that almost every interval exchange transformation is uniquely ergodic. The Birkhoff ergodic theorem implies that these maps mainly have uniformly distributed orbits. This raises the question under which conditions the orbits yield low-discrepancy sequences. The case...
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