Search results for "Hard"

showing 10 items of 2294 documents

A General Framework for Complex Network-Based Image Segmentation

2019

International audience; With the recent advances in complex networks theory, graph-based techniques for image segmentation has attracted great attention recently. In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection algorithms. If we consider regions as communities, using community detection algorithms directly can lead to an over-segmented image. To address this problem, we start by splitting the image into small regions using an initial segmentation. The obtained regions are used for building the complex network. To produce meaningful connected components and detect …

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Networks and CommunicationsComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMachine Learning (stat.ML)02 engineering and technologyMachine Learning (cs.LG)Statistics - Machine Learning0202 electrical engineering electronic engineering information engineeringMedia TechnologySegmentationConnected componentbusiness.industrySimilarity matrix[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentationComplex networkHardware and ArchitectureComputer Science::Computer Vision and Pattern RecognitionGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusinessSoftware
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A Relational Tsetlin Machine with Applications to Natural Language Understanding

2021

TMs are a pattern recognition approach that uses finite state machines for learning and propositional logic to represent patterns. In addition to being natively interpretable, they have provided competitive accuracy for various tasks. In this paper, we increase the computing power of TMs by proposing a first-order logic-based framework with Herbrand semantics. The resulting TM is relational and can take advantage of logical structures appearing in natural language, to learn rules that represent how actions and consequences are related in the real world. The outcome is a logic program of Horn clauses, bringing in a structured view of unstructured data. In closed-domain question-answering, th…

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Science - Logic in Computer ScienceComputer Science - Computation and LanguageI.2.4Computer Science - Artificial IntelligenceComputer Networks and CommunicationsI.2.7Machine Learning (cs.LG)Logic in Computer Science (cs.LO)Artificial Intelligence (cs.AI)Artificial IntelligenceHardware and ArchitectureComputation and Language (cs.CL)I.2.7; I.2.4SoftwareInformation Systems
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Adding Partial Functions to Constraint Logic Programming with Sets

2015

AbstractPartial functions are common abstractions in formal specification notations such as Z, B and Alloy. Conversely, executable programming languages usually provide little or no support for them. In this paper we propose to add partial functions as a primitive feature to a Constraint Logic Programming (CLP) language, namely {log}. Although partial functions could be programmed on top of {log}, providing them as first-class citizens adds valuable flexibility and generality to the form of set-theoretic formulas that the language can safely deal with. In particular, the paper shows how the {log} constraint solver is naturally extended in order to accommodate for the new primitive constrain…

FOS: Computer and information sciencesComputer Science - Programming LanguagesProgramming languageComputer scienceOrder (ring theory)computer.file_formatcomputer.software_genreNotationTheoretical Computer ScienceComputational Theory and MathematicsArtificial IntelligenceHardware and ArchitectureFormal specificationPartial functionConstraint logic programmingExecutableSet theorycomputerSoftwareConstraint satisfaction problemProgramming Languages (cs.PL)
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RationalizeRoots: Software Package for the Rationalization of Square Roots

2019

The computation of Feynman integrals often involves square roots. One way to obtain a solution in terms of multiple polylogarithms is to rationalize these square roots by a suitable variable change. We present a program that can be used to find such transformations. After an introduction to the theoretical background, we explain in detail how to use the program in practice.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryHigh energy particleFeynman integralComputationGeneral Physics and AstronomyFOS: Physical sciencesengineering.materialSymbolic Computation (cs.SC)Rationalization (economics)01 natural sciences010305 fluids & plasmasHigh Energy Physics - Phenomenology (hep-ph)Square root0103 physical sciencesComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONAlgebraic number010306 general physicsMathematical PhysicsVariable (mathematics)MapleMathematical Physics (math-ph)AlgebraHigh Energy Physics - PhenomenologyHigh Energy Physics - Theory (hep-th)Hardware and ArchitectureengineeringComputer Science - Mathematical SoftwareMathematical Software (cs.MS)
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Importance of the window function choice for the predictive modelling of memristors

2018

Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absence…

FOS: Computer and information sciencesComputer Science::Hardware ArchitectureEmerging Technologies (cs.ET)Computer Science::Emerging TechnologiesComputer Science - Emerging Technologies
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Improving table compression with combinatorial optimization

2002

We study the problem of compressing massive tables within the partition-training paradigm introduced by Buchsbaum et al. [SODA'00], in which a table is partitioned by an off-line training procedure into disjoint intervals of columns, each of which is compressed separately by a standard, on-line compressor like gzip. We provide a new theory that unifies previous experimental observations on partitioning and heuristic observations on column permutation, all of which are used to improve compression rates. Based on the theory, we devise the first on-line training algorithms for table compression, which can be applied to individual files, not just continuously operating sources; and also a new, …

FOS: Computer and information sciencesComputer scienceHeuristic (computer science)E.4G.2.1Data_CODINGANDINFORMATIONTHEORYDisjoint setsTravelling salesman problemPermutationArtificial IntelligenceCompression (functional analysis)Computer Science - Data Structures and AlgorithmsH.1.8H.2.7Data Structures and Algorithms (cs.DS)E.4; F.1.3; F.2.2; G.2.1; H.1.1; H.1.8; H.2.7H.1.1Dynamic programmingHardware and ArchitectureControl and Systems EngineeringCombinatorial optimizationTable (database)F.1.3F.2.2AlgorithmSoftwareInformation SystemsJournal of the ACM
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Multi-GPU Accelerated Multi-Spin Monte Carlo Simulations of the 2D Ising Model

2010

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468–4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message P…

FOS: Computer and information sciencesComputer scienceMonte Carlo methodGraphics processing unitFOS: Physical sciencesGeneral Physics and AstronomyMathematical Physics (math-ph)Parallel computingGPU clusterComputational Physics (physics.comp-ph)Graphics (cs.GR)Computational scienceCUDAComputer Science - GraphicsHardware and ArchitectureIsing modelCentral processing unitGeneral-purpose computing on graphics processing unitsMassively parallelPhysics - Computational PhysicsMathematical Physics
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A comprehensive study of automatic program repair on the QuixBugs benchmark

2021

Abstract Automatic program repair papers tend to repeatedly use the same benchmarks. This poses a threat to the external validity of the findings of the program repair research community. In this paper, we perform an empirical study of automatic repair on a benchmark of bugs called QuixBugs, which has been little studied. In this paper, (1) We report on the characteristics of QuixBugs; (2) We study the effectiveness of 10 program repair tools on it; (3) We apply three patch correctness assessment techniques to comprehensively study the presence of overfitting patches in QuixBugs. Our key results are: (1) 16/40 buggy programs in QuixBugs can be repaired with at least a test suite adequate pa…

FOS: Computer and information sciencesCorrectnessComputer science02 engineering and technologyOverfittingMachine learningcomputer.software_genreMaintenance engineeringExternal validityComputer Science - Software Engineering020204 information systems0202 electrical engineering electronic engineering information engineeringTest suite[INFO]Computer Science [cs]computer.programming_languagebusiness.industry020207 software engineeringSoftware maintenancePython (programming language)Software Engineering (cs.SE)Software bugHardware and ArchitectureBenchmark (computing)Artificial intelligencebusinesscomputerSoftwareInformation Systems
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Transient dynamics of pulse-driven memristors in the presence of a stable fixed point

2019

Abstract Some memristors are quite interesting from the point of view of dynamical systems. When driven by narrow pulses of alternating polarities, their dynamics has a stable fixed point, which may be useful for future applications. We study the transient dynamics of two types of memristors characterized by a stable fixed point using a time-averaged evolution equation. Time-averaged trajectories of the Biolek window function memristor and resistor-threshold type memristor circuit (an effective memristor) are determined analytically, and the times of relaxation to the stable fixed point are found. Our analytical results are in perfect agreement with the results of numerical simulations.

FOS: Computer and information sciencesDynamical systems theoryFOS: Physical sciencesComputer Science - Emerging TechnologiesMemristorFixed point01 natural sciencesWindow function010305 fluids & plasmaslaw.inventionMemristive systemComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologieslawStablefixed pointMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesAttractorStatistical physics010306 general physicsPhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsAttractorMemristorResistance switching memoryCondensed Matter PhysicsAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsPulse (physics)Emerging Technologies (cs.ET)Relaxation (physics)Transient (oscillation)Physica E-Low-Dimensional Systems & Nanostructures
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Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources

2020

This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a plethora of different sensors, measuring states, fluxes, processes and variables, at unprecedented spatial and temporal resolutions. Earth observation is well equipped with remote sensing systems, mounted on satellites and airborne platforms, but it also involves in-situ observations, numerical models and social media data streams, among other data sources. Data-driven approaches, and ML techniques in particular, are the natural choice to extract significant i…

FOS: Computer and information sciencesEarth observationComputer Science - Machine LearningComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition02 engineering and technologyMachine learningcomputer.software_genreField (computer science)Machine Learning (cs.LG)Set (abstract data type)0202 electrical engineering electronic engineering information engineeringbusiness.industryData stream mining020206 networking & telecommunicationsNumerical modelsSensor fusionInformation fusionHardware and ArchitectureSignal Processing020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerSoftwareInformation SystemsInformation Fusion
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