开课单位--上海交通大学
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QA4IE: A Question Answering based Framework for Information Extraction[QA4IE：一种基于问答的信息提取框架]
  Lin Qiu(上海交通大学) Information Extraction (IE) refers to automatically extracting structured relation tuples from unstructured texts. Common IE solutions, including Rela...
热度：26

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Attention-based Aggregation Graph Networks for Knowledge Graph Information Transfer[基于注意力的知识图信息传递聚合图网络]
  Ming Zhao(上海交通大学) Attention-based Aggregation Graph Networks for Knowledge Graph Information Transfer
热度：38

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Bridging the Gap between von Neumann Graph Entropy and Structural Information: Theory and Applications[架起冯·诺依曼图熵与结构信息之间的桥梁：理论与应用]
  Xuecheng Liu(上海交通大学) Bridging the Gap between von Neumann Graph Entropy and Structural Information: Theory and Applications
热度：52

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AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph[AutoSTG：时空图预测的神经结构搜索]
  Zheyi Pan(上海交通大学) AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph
热度：55

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GNEM: A Generic One-to-Set Neural Entity Matching Framework[GNEM：一种通用的神经实体匹配框架]
  Runjin Chen(上海交通大学) GNEM: A Generic One-to-Set Neural Entity Matching Framework
热度：39

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Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation[用于顺序推荐的对抗式和对比式变分自动编码器]
  Zhe Xie(上海交通大学) Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation
热度：35

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Weakly-Supervised Question Answering with Effective Rank and Weighted Loss over Candidates[基于有效秩和加权损失的弱监督问答]
  Haozhe Qin(上海交通大学) Weakly-Supervised Question Answering with Effective Rank and Weighted Loss over Candidates
热度：44

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A Generative Adversarial Click Model for Information Retrieval[信息检索的生成对抗点击模型]
  Xinyi Dai(上海交通大学) A Generative Adversarial Click Model for Information Retrieval
热度：34

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Activities of GMO analysis in China[转基因分析在中国的活动]
  Litao Yang(上海交通大学) As the rapid research and application of transgenic techniques in modern agriculture, more and more new GM crops were developed and commercialized in ...
热度：37

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Separated Trust Regions Policy Optimization Method[信任区分离策略优化方法]
  Luobao Zou(上海交通大学) In this work, we propose a moderate policy update method for reinforcement learning, which encourages the agent to explore more boldly in early episod...
热度：55
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