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Titlebook: Intelligence Science V; 6th IFIP TC 12 Inter Zhongzhi Shi,Michael Witbrock,Qi Tian Conference proceedings 2025 IFIP International Federatio

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楼主: radionuclides
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A Framework of Reinforcement Learning for Truncated Lévy Flight Exploratoryveloping better exploration strategies is still one of the important tasks in reinforcement learning. The paper introduces a new exploration strategy ATLF (Adjustment of Truncated Lévy Flight exploration framework, ATLF) which augments the existing exploration mode with Lévy flight, making action se
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Detection of Depression in EEG Signals Based on Convolutional Transformer and Adaptive Transfer Learof depression. However, the classification of EEG signals for depression is severely affected by individual differences among subjects, complex intrinsic properties, and low Signal-to-Noise Ratio (.), which limits the classification accuracy. Additionally, traditional convolutional neural networks e
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MLEE: Event Extraction as Multi-label Classification Task at Token Leveluments of specific roles, has attracted a lot of attention from industry and academia. The previous works failed to address some issues, including error propagation problem, overlap and nest problem, and high complexity of model. This work proposes a novel model MLEE, which models Event Extraction t
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Research on Improvement of Sweeping Learning Chain Algorithm Based on Factor Space Theoryone to classify samples in mixed domain, this paper proposes sweeping learning chain-K-Nearest Neighbor (SLC-KNN) algorithm. When SLC encounters the problem of undivisible data, KNN is used to classify the samples to be tested that fall into the mixed domain. It not only solves the problem of undivi
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Research on the Causal Forest Algorithm Based on Factor Space Theorydegree of determination of factor space theory, a causal tree algorithm is proposed; Ensemble multiple causal trees, provide a definition of factor importance, obtain advantage factors, set importance thresholds in numerical experiments to reduce the set of condition factors, randomly select factors
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