Search results for "CALL"

showing 10 items of 2320 documents

Subsumption-driven clause learning with DPLL+restarts

2019

We propose to use a DPLL+restart to solve SAT instances by successive simplifications based on the production of clauses that subsume the initial clauses. We show that this approach allows the refutation of pebbling formulae in polynomial time and linear space, as effectively as with a CDCL solver.

FOS: Computer and information sciencesComputer Science - Logic in Computer ScienceTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESArtificial Intelligence (cs.AI)Computer Science - Artificial IntelligenceLogic in Computer Science (cs.LO)
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Adding Path-Functional Dependencies to the Guarded Two-Variable Fragment with Counting

2017

The satisfiability and finite satisfiability problems for the two-variable guarded fragment of first-order logic with counting quantifiers, a database, and path-functional dependencies are both ExpTime-complete.

FOS: Computer and information sciencesComputer Science - Logic in Computer ScienceTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESintegrity constraintssatisfiabilitycounting quantifierspath-functional dependenciesComputer Science::Logic in Computer Scienceguarded fragmentkey constraintstwo-variable fragmetLogic in Computer Science (cs.LO)
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Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions

2022

The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…

FOS: Computer and information sciencesComputer Science - Machine LearningEarth observationAdvanced microwave scanning radiometer-2 (AMSR-2)moderate resolution imaging spectroradiometer (MODIS)Computer scienceleaf area index (LAI)0211 other engineering and technologiesExtrapolationMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreMachine Learning (cs.LG)Data-drivenConvolutionsymbols.namesakeadvanced scatterometer (ASCAT)Statistics - Machine Learningordinary differential equation (ODE)Electrical and Electronic EngineeringGaussian processsoil moisture and ocean salinity (SMOS)021101 geological & geomatics engineeringInterpretabilityForcing (recursion theory)machine learning (ML)soil moisture (SM)time series analysisgaussian process (GP)symbolsGeneral Earth and Planetary SciencesDomain knowledgeData mininggap fillingphysicscomputerfraction of absorbed photosynthetically active radiation (faPAR)IEEE Transactions on Geoscience and Remote Sensing
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Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications

2019

Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…

FOS: Computer and information sciencesComputer Science - Machine LearningGeneral Computer ScienceComputer sciencetext categorizationNatural language understandingDecision treeMachine Learning (stat.ML)02 engineering and technologyVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Annen informasjonsteknologi: 559Machine learningcomputer.software_genresupervised learningMachine Learning (cs.LG)Naive Bayes classifierText miningStatistics - Machine Learning0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceTsetlin machinehealth informaticsInterpretabilityPropositional variableClassification algorithmsArtificial neural networkbusiness.industryDeep learning020208 electrical & electronic engineeringGeneral EngineeringRandom forestSupport vector machinemachine learningCategorization020201 artificial intelligence & image processingArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringbusinessPrecision and recallcomputerlcsh:TK1-9971
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Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling

2020

Using logical clauses to represent patterns, Tsetlin Machines (TMs) have recently obtained competitive performance in terms of accuracy, memory footprint, energy, and learning speed on several benchmarks. Each TM clause votes for or against a particular class, with classification resolved using a majority vote. While the evaluation of clauses is fast, being based on binary operators, the voting makes it necessary to synchronize the clause evaluation, impeding parallelization. In this paper, we propose a novel scheme for desynchronizing the evaluation of clauses, eliminating the voting bottleneck. In brief, every clause runs in its own thread for massive native parallelism. For each training…

FOS: Computer and information sciencesComputer Science - Machine LearningTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESArtificial Intelligence (cs.AI)Computer Science - Artificial IntelligenceMachine Learning (cs.LG)
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Visibly pushdown modular games,

2014

Games on recursive game graphs can be used to reason about the control flow of sequential programs with recursion. In games over recursive game graphs, the most natural notion of strategy is the modular strategy, i.e., a strategy that is local to a module and is oblivious to previous module invocations, and thus does not depend on the context of invocation. In this work, we study for the first time modular strategies with respect to winning conditions that can be expressed by a pushdown automaton. We show that such games are undecidable in general, and become decidable for visibly pushdown automata specifications. Our solution relies on a reduction to modular games with finite-state automat…

FOS: Computer and information sciencesComputer Science::Computer Science and Game TheoryComputer Science - Logic in Computer ScienceTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESTheoretical computer scienceFormal Languages and Automata Theory (cs.FL)Computer scienceComputer Science - Formal Languages and Automata Theory0102 computer and information sciences02 engineering and technologyComputational Complexity (cs.CC)Pushdown01 natural scienceslcsh:QA75.5-76.95Theoretical Computer ScienceComputer Science - Computer Science and Game TheoryComputer Science::Logic in Computer Science0202 electrical engineering electronic engineering information engineeringTemporal logicRecursionbusiness.industrylcsh:MathematicsGames; Modular; Pushdown; Theoretical Computer Science; Information Systems; Computer Science Applications; Computational Theory and MathematicsPushdown automatonModular designDecision problemlcsh:QA1-939Logic in Computer Science (cs.LO)Computer Science ApplicationsUndecidable problemDecidabilityNondeterministic algorithmComputer Science - Computational ComplexityModularTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESComputational Theory and Mathematics010201 computation theory & mathematics020201 artificial intelligence & image processinglcsh:Electronic computers. Computer scienceGamesbusinessComputer Science::Formal Languages and Automata TheoryComputer Science and Game Theory (cs.GT)Information SystemsInformation and Computation
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Computational Limitations of Affine Automata

2019

We present two new results on the computational limitations of affine automata. First, we show that the computation of bounded-error rational-values affine automata is simulated in logarithmic space. Second, we give an impossibility result for algebraic-valued affine automata. As a result, we identify some unary languages (in logarithmic space) that are not recognized by algebraic-valued affine automata with cutpoints.

FOS: Computer and information sciencesDiscrete mathematics050101 languages & linguisticsTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESUnary operationFormal Languages and Automata Theory (cs.FL)Computer scienceComputation05 social sciencesComputer Science - Formal Languages and Automata Theory02 engineering and technology[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]Nonlinear Sciences::Cellular Automata and Lattice GasesLogarithmic spaceAutomatonTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0501 psychology and cognitive sciencesAffine transformationImpossibilityComputer Science::Formal Languages and Automata TheoryComputingMilieux_MISCELLANEOUS
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New Results on Vector and Homing Vector Automata

2019

We present several new results and connections between various extensions of finite automata through the study of vector automata and homing vector automata. We show that homing vector automata outperform extended finite automata when both are defined over $ 2 \times 2 $ integer matrices. We study the string separation problem for vector automata and demonstrate that generalized finite automata with rational entries can separate any pair of strings using only two states. Investigating stateless homing vector automata, we prove that a language is recognized by stateless blind deterministic real-time version of finite automata with multiplication iff it is commutative and its Parikh image is …

FOS: Computer and information sciencesFinite-state machineTheoretical computer scienceTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESFormal Languages and Automata Theory (cs.FL)Computer science010102 general mathematicsComputer Science - Formal Languages and Automata Theory0102 computer and information sciencesNonlinear Sciences::Cellular Automata and Lattice Gases01 natural sciencesAutomatonTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES010201 computation theory & mathematicsComputer Science (miscellaneous)0101 mathematicsComputer Science::Formal Languages and Automata TheoryHoming (hematopoietic)
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Classical automata on promise problems

2015

Promise problems were mainly studied in quantum automata theory. Here we focus on state complexity of classical automata for promise problems. First, it was known that there is a family of unary promise problems solvable by quantum automata by using a single qubit, but the number of states required by corresponding one-way deterministic automata cannot be bounded by a constant. For this family, we show that even two-way nondeterminism does not help to save a single state. By comparing this with the corresponding state complexity of alternating machines, we then get a tight exponential gap between two-way nondeterministic and one-way alternating automata solving unary promise problems. Secon…

FOS: Computer and information sciencesNested wordTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESUnary operationGeneral Computer ScienceFormal Languages and Automata Theory (cs.FL)nondeterministic automataComputer Science - Formal Languages and Automata Theoryω-automatonComputational Complexity (cs.CC)Theoretical Computer ScienceContinuous spatial automatonQuantum finite automataDiscrete Mathematics and Combinatoricsalternating automatapromise problemsMathematicsprobabilistic automataNonlinear Sciences::Cellular Automata and Lattice GasesMobile automatonNondeterministic algorithmAlgebra[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Computer Science - Computational ComplexityTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESAutomata theorydescriptional complexityComputer Science::Formal Languages and Automata Theory
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Exact quantum algorithms have advantage for almost all Boolean functions

2014

It has been proved that almost all $n$-bit Boolean functions have exact classical query complexity $n$. However, the situation seemed to be very different when we deal with exact quantum query complexity. In this paper, we prove that almost all $n$-bit Boolean functions can be computed by an exact quantum algorithm with less than $n$ queries. More exactly, we prove that ${AND}_n$ is the only $n$-bit Boolean function, up to isomorphism, that requires $n$ queries.

FOS: Computer and information sciencesNuclear and High Energy Physics81P68 03D15Parity functionBoolean circuitGeneral Physics and AstronomyFOS: Physical sciencesBoolean algebras canonically definedComputational Complexity (cs.CC)Theoretical Computer ScienceCombinatoricsBoolean expressionBoolean functionMathematical PhysicsComputer Science::DatabasesMathematicsDiscrete mathematicsSymmetric Boolean functionQuantum PhysicsProduct termComputer Science::Information RetrievalStatistical and Nonlinear PhysicsComputer Science - Computational ComplexityComputational Theory and MathematicsMaximum satisfiability problemQuantum Physics (quant-ph)
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