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UniversalApproximationTheoremforDeepQ-LearningviaFBsdESystem
The approximation capabilities of Deep Q-Networks (DQNs) are commonly justified by general Universal
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IRNN:Innovation-drivenRecurrentNeuralNetworkforTime-SeriesdataModelingandPrediction
Many real-world datasets are time series that are sequentially collected and contain rich temporal i
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Cost-Effective,LowLatencyVectorSearchwithAzureCosmosdB
Vector indexing enables semantic search over diverse corpora and has become an important interface t
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Hexagonalicedensitydependenceoninteratomicdistancechangesduetonuclearquantumeffects
Hexagonal ice ($\rm{I_h}$), the most common structure of ice, displays a variety of fascinating prop
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AIsdata-DrivenMaritimeMonitoringBasedonTransformer:AComprehensiveReview
With the increasing demands for safety, efficiency, and sustainability in global shipping, Automatic
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HeterogeneousdataGame:CharacterizingtheModelCompetitionAcrossMultipleDataSources
Data heterogeneity across multiple sources is common in real-world machine learning (ML) settings. A
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OnPrem.LLM:APrivacy-ConsciousdocumentIntelligenceToolkit
We present this http URL, a Python-based toolkit for applying large language models (LLMs) to sensit
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EnhancingFederatedLearningwithKolmogorov-ArnoldNetworks:AComparativeStudyAcrossdiverseAggregationStrategies
Multilayer Perceptron (MLP), as a simple yet powerful model, continues to be widely used in classifi
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Finite-Sample-BasedReachabilityforSafeControlwithGaussianProcessdynamics
Gaussian Process (GP) regression is shown to be effective for learning unknown dynamics, enabling ef
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NewsNet-sdF:StochasticDiscountFactorEstimationwithPretrainedLanguageModelNewsEmbeddingsviaAdversarialNetworks
Stochastic Discount Factor (SDF) models provide a unified framework for asset pricing and risk asses
