开课单位--北京大学
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Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels[基于匿名走图核的图神经网络理论改进]
Qingqing Long(北京大学) Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels
热度:19
Qingqing Long(北京大学) Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels
热度:19
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HeavyGuardian: Separate and Guard Hot Items in Data Streams[HeavyGuardian:分离和保护数据流中的热点项目]
Junzhi Gong(北京大学) HeavyGuardian: Separate and Guard Hot Items in Data Streams
热度:20
Junzhi Gong(北京大学) HeavyGuardian: Separate and Guard Hot Items in Data Streams
热度:20
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Node Conductance: A Scalable Node Centrality Measure on Big Networks[节点电导:大网络上可扩展的节点中心性度量]
Tianshu Lyu(北京大学) Node Conductance: A Scalable Node Centrality Measure on Big Networks
热度:31
Tianshu Lyu(北京大学) Node Conductance: A Scalable Node Centrality Measure on Big Networks
热度:31
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Attribute-driven Capsule Network for Entity Relation Prediction[用于实体关系预测的属性驱动胶囊网络]
Jiayin Chen(北京大学) Attribute-driven Capsule Network for Entity Relation Prediction
热度:33
Jiayin Chen(北京大学) Attribute-driven Capsule Network for Entity Relation Prediction
热度:33
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Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data[描述联邦学习中异构性对大规模智能手机数据的影响]
Chengxu Yang(北京大学) Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
热度:24
Chengxu Yang(北京大学) Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
热度:24
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Completing Missing Prevalence Rates for Multiple Chronic Diseases by Jointly Leveraging Both Intra- and Inter-Disease Population Health Data Correlations[通过联合利用疾病内和疾病间人口健康数据相关性,完成多种慢性病的缺失患病率]
Yujie Feng(北京大学) Completing Missing Prevalence Rates for Multiple Chronic Diseases by Jointly Leveraging Both Intra- and Inter-Disease Population Health Data Correlati...
热度:30
Yujie Feng(北京大学) Completing Missing Prevalence Rates for Multiple Chronic Diseases by Jointly Leveraging Both Intra- and Inter-Disease Population Health Data Correlati...
热度:30
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Improving Graph Neural Networks with Structural Adaptive Receptive Fields[用结构自适应感受野改进图神经网络]
Xiaojun Ma(北京大学) Improving Graph Neural Networks with Structural Adaptive Receptive Fields
热度:22
Xiaojun Ma(北京大学) Improving Graph Neural Networks with Structural Adaptive Receptive Fields
热度:22
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A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning[针对并行数据中毒的黑箱神经机器翻译攻击]
Chang Xu(北京大学) A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning
热度:30
Chang Xu(北京大学) A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning
热度:30
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DistCare: Distilling Knowledge from Publicly Available Online EMR Data to Emerging Epidemic for Prognosis[DistCare:从公开的在线EMR数据中提取知识,用于预测新出现的流行病]
Liantao Ma(北京大学) DistCare: Distilling Knowledge from Publicly Available Online EMR Data to Emerging Epidemic for Prognosis
热度:66
Liantao Ma(北京大学) DistCare: Distilling Knowledge from Publicly Available Online EMR Data to Emerging Epidemic for Prognosis
热度:66
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ATJ-Net: Auto-Table-Join Network for Automatic Learning on Relational Databases[ATJ Net:用于关系数据库自动学习的自动表连接网络]
Jinze Bai(北京大学) ATJ-Net: Auto-Table-Join Network for Automatic Learning on Relational Databases
热度:60
Jinze Bai(北京大学) ATJ-Net: Auto-Table-Join Network for Automatic Learning on Relational Databases
热度:60