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SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition



Hangyu Mao , Chao Wang , Xiaotian Hao , Yihuan Mao , Yiming Lu , Chengjie Wu , Jianye Hao , Dong Li , Pingzhong Tang

* The winner solution of NeurIPS 2020 MineRL competition (https://www.aicrowd.com/challenges/neurips-2020-minerl-competition/leaderboards). The paper has been accepted by DAI 2021 (the third International Conference on Distributed Artificial Intelligence) 

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DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis



Chuheng Zhang , Yuanqi Li , Xi Chen , Yifei Jin , Pingzhong Tang , Jian Li

* ICDM 2020 

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Deterministic Value-Policy Gradients



Qingpeng Cai , Ling Pan , Pingzhong Tang


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Towards reliable and fair probabilistic predictions: field-aware calibration with neural networks



Feiyang Pan , Xiang Ao , Pingzhong Tang , Min Lu , Dapeng Liu , Qing He


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Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings



Feiyang Pan , Shuokai Li , Xiang Ao , Pingzhong Tang , Qing He

* Accepted at SIGIR 2019 

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Policy Optimization with Model-based Explorations



Feiyang Pan , Qingpeng Cai , An-Xiang Zeng , Chun-Xiang Pan , Qing Da , Hualin He , Qing He , Pingzhong Tang

* Accepted at AAAI-19 

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Deterministic Policy Gradients With General State Transitions



Qingpeng Cai , Ling Pan , Pingzhong Tang


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Rebalancing Dockless Bike Sharing Systems



Ling Pan , Qingpeng Cai , Zhixuan Fang , Pingzhong Tang , Longbo Huang


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Policy Gradients for General Contextual Bandits



Feiyang Pan , Qingpeng Cai , Pingzhong Tang , Fuzhen Zhuang , Qing He


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Computer-aided mechanism design: designing revenue-optimal mechanisms via neural networks



Weiran Shen , Pingzhong Tang , Song Zuo


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