开课单位--南京大学
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HoORaYs: High­order Optimization of Rating Distance for Recommender Systems[HoORaYs：推荐系统评级距离的高阶优化]
   Yuan Yao(南京大学) Latent factor models have become a prevalent method in recommender systems, to predict users' preference on items based on the historical user fee...
热度：18

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Complex Object Classification: A Multi‑Modal Multi‑Instance Multi‑Label Deep Network with Optimal Transport[复杂对象分类：具有最优传输的多模态多实例多标签深度网络]
  Yang Yang(南京大学) Complex Object Classification: A Multi‑Modal Multi‑Instance Multi‑Label Deep Network with Optimal Transport
热度：48

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Strong Baselines for Author Name Disambiguation with and without Neural Networks[使用和不使用神经网络的作者姓名消歧的强基线]
  Zhen-Yu Zhang(南京大学) Strong Baselines for Author Name Disambiguation with and without Neural Networks
热度：39

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Data-Free Adversarial Perturbations for Practical Black-Box Attack[实际黑盒攻击的无数据对抗扰动]
  Zhaoxin Huan(南京大学) Data-Free Adversarial Perturbations for Practical Black-Box Attack
热度：42

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Bottom-Up and Top-Down Graph Pooling[自下而上和自顶向下的图形池]
  Jia-Qi Yang(南京大学) Bottom-Up and Top-Down Graph Pooling
热度：41

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Accelerating Hyperparameter Optimization of Deep Neural Network via Progressive Multi-Fidelity Evaluation[通过渐进多保真度评估加速深度神经网络超参数优化]
  Guanghui Zhu(南京大学) Accelerating Hyperparameter Optimization of Deep Neural Network via Progressive Multi-Fidelity Evaluation
热度：45

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Entity Summarization with User Feedback[具有用户反馈的实体摘要]
  Qingxia Liu(南京大学) Entity Summarization with User Feedback
热度：33

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ESBM: An Entity Summarization BenchMark[ESBM：实体摘要基准]
  Qingxia Liu(南京大学) ESBM: An Entity Summarization BenchMark
热度：68

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DAPter: Preventing User Data Abuse in Deep Learning Inference Services[DAPter：在深度学习推理服务中防止用户数据滥用]
  Hao Wu(南京大学) DAPter: Preventing User Data Abuse in Deep Learning Inference Services
热度：67

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Facilitating Human Intervention in Coreference Resolution with Comparative Entity Summaries[通过比较实体摘要促进人类干预共指消解]
   Gong Cheng(南京大学) A primary challenge to Web data integration is coreference resolution, namely identifying entity descriptions from different data sources that refer t...
热度：57
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