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    {
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      "extra_author": "Zhikun Zhang",
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    },
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      "extra_author": "Tianhao Wang",
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      "extra_author": "Tianhao Wang",
            
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    },
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      "extra_author": "Michael Backes",
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    },
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    {
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      "extra_author": "Mathias Humbert",
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      "extra_author": "Mathias Humbert",
            
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Yang Zhang",
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      "extra_author": "Yang Zhang",
            
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      "orcid": ""
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      "orcid": ""
            
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      "display_name": "Machine Learning",
            
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  "name": 
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"grapheraser--a-novel-machine-unlearning-framework-for-graph-data",
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"grapheraser--a-novel-machine-unlearning-framework-for-graph-data",
            
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  "notes": "GraphEraser is a novel machine unlearning framework 
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  "notes": "GraphEraser is a novel machine unlearning framework 
            
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tailored to graph data. It proposes two novel graph partition 
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tailored to graph data. It proposes two novel graph partition 
            
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algorithms and a learning-based aggregation method to improve the 
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algorithms and a learning-based aggregation method to improve the 
            
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unlearning efficiency and model utility.",
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unlearning efficiency and model utility.",
            
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  "title": "GraphEraser: A Novel Machine Unlearning Framework for 
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  "title": "GraphEraser: A Novel Machine Unlearning Framework for 
            
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Graph Data",
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Graph Data",
            
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}