ScienceDirect Publication: Information Sciences rss.sciencedirect.com

Fast and scalable sliding-window-based algorithms for mining frequent weighted utility patterns over dynamic quantitative data streams

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An adaptive large neighborhood search with dynamic exit reassignment for guided multi-story hospital fire evacuation

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AiGAS-dEVL: An adaptive incremental neural gas model for drifting data streams under extreme verification latency

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Learning directed acyclic graphs via noising and denoising

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A post-quantum hierarchical and adaptive LWE-based secret image sharing scheme with verifiable reconstruction

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Patch-HGST: Hierarchical graph spatio-temporal networks with data-driven adaptive patch partition for traffic prediction

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GCA-DETR: Global-context-aware-based detection transformer

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DM-SynTraj: A dual-module trajectory synthesis framework via tri-dimensional fusion and multi-stage optimization

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Bayesian-inspired non-negative matrix factorization with label propagation for multi-view clustering

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Irrelevant feature filtering module for deep multi-view generative clustering

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PCA-GRF: A novel granular random forest algorithm for enhancing classification of small sample data

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A robust multi-label learning method based on missing label probability modeling

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A material-aware, multi-modal synthetic dataset for smart city applications: Design and construction

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Multi-view consensus graph subspace clustering via embedding spatial information of features

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A unified deep learning framework for multi-scale spatio-temporal forecasting on dynamic graphs

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MaTra4LS:Mamba-transformer dual-architecture for long and short-term interests fusion in sequential recommendation

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Dynamic control of discrete event systems with unreliable resources by petri nets

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NAFF-HNN: Node attention and feature fusion hypergraph neural network for remote sensing scene classification

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Navigating the influence spread in social network via an adaptive large neighborhood search optimization

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FPS:Frequency-aware polynomial spectral reconstruction for dual-domain learning in long-term time series forecasting

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