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張恆汝檢視原始碼討論檢視歷史

事實揭露 揭密真相
前往： 導覽、 搜尋
張恆汝
西南石油大學

張恆汝，男， 西南石油大學教授。

人物簡歷

2016.09–2019.06 西南石油大學, 理學院，博士

1999.09–2002.03 電子科技大學, 機械電子工程學院，碩士

1994.09–1998.07 瀋陽航空航天大學, 航空工程系，學士

研究方向

推薦系統、網絡空間安全、聯邦學習、多標籤學習、油氣人工智能

學術成果

  • [1] Heng-Ru Zhang, Fan Min*, Bing Shi, Regression-based three-way recommendation. Information Sciences, 2017, 378:444-461.（ESI高倍引）
  • [2] Heng-Ru Zhang, Fan Min*. Three-way recommender systems based on random forests. Knowledge-Based Systems, 2016, 91: 275-286.（ESI高倍引）
  • [3] Zi-Feng Peng, Heng-Ru Zhang*, and Fan Min. IUG-CF: Neural collaborative filtering with ideal user group labels. Expert Systems with Applications 238 (2024): 121887.
  • [4] Xiang-Yu Liang, Heng-Ru Zhang*, Wei Tang and Fan Min. Robust federated learning with voting and scaling. Future Generation Computer Systems 153 (2024): 113-124.
  • [5] Heng-Ru Zhang*, Ying Qiu, Ke-Lin Zhu, Fan Min, Lower bound estimation of recommendation error through user uncertainty modeling, Pattern Recognition 136 (2023): 109171.
  • [6] Gui-Lin Li, Heng-Ru Zhang*, Fan Min, et al. Two-stage label distribution learning with label-independent prediction based on label-specific features. Knowledge-Based Systems, 2023, 267: 110426.
  • [7] Bai, Run-Ting, Heng-Ru Zhang*, and Fan Min. Label-dependent feature exploration for label distribution learning. International Journal of Machine Learning and Cybernetics (2023): 1-20.
  • [8] Heng-Ru Zhang, Jie Qian, Hui-Lin Qu, Fan Min*. A Mixture-of-Gaussians model for estimating the magic barrier of the recommender system. Applied Soft Computing, 2022:108162.
  • [9] Cao-Fan Pan, Xue-Yang Min, Heng-Ru Zhang, et al. Behavior imitation of individual board game players. Applied Intelligence, 2022: 1-15.
  • [10] Heng-Ru Zhang, Fan Min*, Zhi-Heng Zhang, Song Wang. Efficient collaborative filtering recommendations with multi-channel feature vectors. International Journal of Machine Learning & Cybernetics. 2019:1165–1172.
  • [11] Heng-Ru Zhang, Fan Min*, Yan-Xue Wu, Zhuo-Lin Fu, Lei Gao. Magic barrier estimation models for recommended systems under normal distribution. Applied Intelligence. 2018,48: 4678-4693.
  • [12] Rong-Ping Shen, Heng-Ru Zhang, Hong Yu, Fan Min*. Sentiment based matrix factorization with reliability for recommendation. Expert Systems with Applications. 2019:249-258.
  • [13] Heng-Ru Zhang, Run-Ting Bai, and Wen-Tao Tang. Label Distribution Learning with Discriminative Instance Mapping. Pacific-Asia Conference on Knowledge Discovery and Data Mining. Cham: Springer Nature Switzerland, 2023 (亞太知識發現和數據挖掘會議，會議地址：日本大阪).
  • [14] Yan-Wen Xiong, Heng-Ru Zhang, Fan Min, Peng-Cheng Li. Sample Topology Exploration for Label Distribution Learning. In 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-9). IEEE，2023, October (數據科學與高級分析國際會議, 會議地址：希臘塞薩洛尼基).
  • [15] Cao-Fan Pan, Fan Min*, Heng-Ru Zhang, et al. BRL: Learning behavior representations of Reversi players. 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2022: 1-10 (數據科學與高級分析國際會議，會議地址：中國深圳).
  • [16] Bin-Yuan Rong, Heng-Ru Zhang*, Li, Gui-Lin, et al. Label Distribution Learning with Data Augmentation using Generative Adversarial Networks. 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2022: 1-10 (數據科學與高級分析國際會議，會議地址：中國深圳).
  • [17] Gui-Lin Li, Heng-Ru Zhang, et al. Label Distribution Learning by Exploiting Feature-Label Correlations Locally. 2021 IEEE International Conference on Big Knowledge (ICBK). IEEE, 2021 (IEEE巨量知識國際會議，會議地址：新西蘭奧克蘭).
  • [18] Fu, Zhuo-Lin, Fan Min*, and Heng-Ru Zhang. Recommendation with generalized logistic transformation. 2018 IEEE International Conference on Big Knowledge (ICBK). IEEE, 2018 (IEEE巨量知識國際會議，會議地址：新加坡).
  • [19] Yuan-Yuan Xu, Heng-Ru Zhang, and Fan Min*. A three-way recommender system for popularity-based costs. International Joint Conference on Rough Sets. Springer, Cham, 2017 (粗糙集國際會議，會議地址：波蘭奧爾什丁olsztyn).
  • [20] Xin-Ling Dong, Shuang-Bo Sun, Fan Min*, and Heng-Ru Zhang. Hybrid similarities for dynamic interaction recommendation. 2016 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE (機器學習和控制論國際會議，會議地址：韓國濟州島).

主要項目

[1] 深井固井設計與分析軟件開發 國家科技重大專項

[2] 高密度地震數據的初至波自動拾取方法研究 國家自然科學基金

[3] 基於粒計算的抽油機參數優化方法研究 四川省科技廳

[4] 多粒度視角下的油氣田*** 南充市科技局

[5] 基於代價敏感粗糙集的油田*** 四川省教育廳

教學獲獎

[1] 2020屆本科畢業設計（論文）優秀畢業指導教師

[2] 2017年教師本科課堂教學質量考核評價優秀三級

[3] 2013-2014學年課堂教學優秀獎三等獎

[4] 2012-2013學年優秀生產實習隊三等獎

[5] 2012年校級教學成果二等獎《信息及網絡安全教學改革研究與實踐》

[6] 2012年課堂教學優秀獎三等獎

[7] 2006年校優秀教案《信息系統安全與保密》[1]

參考資料

  1. ↑ 西南石油大學
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