Cloud-based machine learning services offer significant advantages but also introduce the risk of tampering with cloud-deployed deep neural network (DNN) models. Black-box integrity verification (BIV) allows model own...
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Accurate analysis of Fetal Heart Rate (FHR) signal is often impeded by challenges such as data scarcity and label imbalance, which affect the reliability and robustness of deep learning models. To address these challe...
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This paper proposes a framework called GHVC-Net that uses the graph neural network (GNN) model to approximate each solution's hypervolume contribution (HVC). GHVC-Net is permutation invariant and can handle soluti...
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Multi-hop reasoning has been widely studied for its important application values in the domain of intelligent search and question answering. Real-world applications are often dominated by natural language input, and i...
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The emergence of large-scale dynamic sets in real applications brings severe challenges in approximate set representation structures. A dynamic set with changing cardinality requires an elastic capacity of the approxi...
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The scale of real-world graphs is constantly growing. To deal with large-scale graphs, distributed graph processing has attracted much research efforts. Existing distributed graph processing systems are commonly built...
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Semantic reasoning techniques based on knowledge graphs have been widely studied since they were proposed. Previous studies are mostly based on closed-world assumptions, which cannot reason about unknown facts. To thi...
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Commonsense knowledge (CSK) is the information that people use in daily life but do not often mention. It summarizes the practical knowledge about how the world works. Existing machines have knowledge but lack commons...
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Although cloud computing saves the cost of enterprises and individuals to manage data in various applications on public cloud servers, it also causes the problem of the leakage of critical personal information and sen...
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The huge amount of data enforces great pressure on the processing efficiency of database systems. By leveraging the in-situ computing ability of emerging nonvolatile memory, processing-in-memory (PIM) technology shows...
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