“Yi Zhang @ IIP, NJU-CS”的版本间的差异

2021年12月12日 (日) 20:32的最新版本

Supervisor

• Professor Chong-Jun Wang and Jun-Yuan Xie

Biography

• I received my B.Sc. degree from Huazhong University of Science and Technology in June 2017. In September 2017 and 2019, I was admitted to study for an M.Sc. degree and Ph.D. degree at Nanjing University under the supervision of Prof. Chong-Jun Wang without entrance examination, respectively. Currently, I am a second-year Ph.D. student of Department of Computer Science and Technology at Nanjing University and a member of IIP Group. I am also one of the members of the international branches of Hasso-Plattner-Institut from Germany (2020- ).
• Research Interest

My research interests include: Machine Learning, Multi-modal and Multi-label Learning

Publications

• Zhang, Y., Zeng, C., Cheng, H., Wang, C., & Zhang, L. (2019, July). Many could be better than all: A novel instance-oriented algorithm for Multi-modal Multi-label problem. In 2019 IEEE International Conference on Multimedia and Expo (ICME) (pp. 838-843). IEEE. (Oral presentation)
• Zhang, Y., Zhang, Z., Cheng, H., Lu, H., Zhang, L., Wang, C., & Xie, J. (2019, November). Win-win Cooperation: A Novel Dual-Modal Dual-Label Algorithm for Membrane Proteins Function Pre-screen. In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 102-106). IEEE.
• Zhang, Y., Shen, J., Zhang, Z., & Wang, C. (2020, August). Common and Discriminative Semantic Pursuit for Multi-modal Multi-label Learning. In Proceedings of 24th European Conference on Artificial Intelligence - ECAI 2020 (pp. 1666-1673). (Oral presentation)
• Zhang, Y., Shen, J., Zhang, Z., Zhang, L., & Wang, C. (2020, July). Rethinking Modal-oriented Label Correlations for Multi-modal Multi-label Learning. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE. (Oral presentation)
• Zhang, Y., Zhang, Z., Zhu, Y., Zhang, L., & Wang, C. (2020, August). Discriminative Multi-label Model Reuse for Multi-label Learning. In Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data (pp. 725-739). Springer, Cham. (Oral presentation)
• Zhang, Y., Shen, J., Zhang, Z., & Wang, C. (2021). Partial Modal Conditioned GANs for Multi-modal Multi-label Learning with Arbitrary Modal-Missing. In DASFAA (2) (pp. 413-428). (Oral presentation)
• Zhang, Y., Shen, J., Yu, C., & Wang, C. (2021). Relation-Aware Alignment Attention Network for Multi-view Multi-label Learning. In DASFAA (2) (pp. 465-482). (Oral presentation)
• Zhang, Y., Shen, J., Yu, C., & Wang, C. (2021, July). Label-Specific Alignment with Adversarial Multi-View Representation. In 2021 IEEE International Conference on Multimedia and Expo (ICME) (pp. 1-6). IEEE. (Oral presentation)
• Zhang, Y., Zhang, Z., Chen, M., Lu, H., & Wang, C. LAMB: A Novel Algorithm of Label Collaboration based Multi-Label Learning. Intelligent Data Analysis. Accepted
• Zhang, Y., Chen, M., Shen, J., & Wang, C. Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognition. In Proceedings of  AAAI 2022. Accepted
• Cheng, H., Zhang, L., Zhang, Y., Wu, J., & Wang, C. (2018, July). Optimal constraint collection for core-selecting path mechanism. In Proceedings of the 17th international conference on autonomous agents and multiagent systems (pp. 41-49).
• Zeng, C., Zhang, Y., Lu, H. Y., & Wang, C. J. (2019, July). GADGET: Using Gated GRU for Biomedical Event Trigger Detection. In 2019 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
• Cheng, H., Zhang, W., Zhang, Y., Zhang, L., Wu, J., & Wang, C. (2020). Fast core pricing algorithms for path auction. Autonomous Agents and Multi-Agent Systems, 34(1), 18.
• Du, Y., Tan, Z., Chen, Q., Zhang, Y., & Wang, C.(2020, August). Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization. In Proceedings of 24th European Conference on Artificial Intelligence - ECAI 2020 (pp. 1111-1118).
• Zhu, Y., & Zhang, Y. (2020, July). M3LA: A Novel Approach Based on Encoder-Decoder with Attention Framework for Multi-modal Multi-label Learning. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
• Chen, Q., Du, Y., Tan, Z., Zhang, Y., & Wang, C. (2020, September). Unsupervised domain adaptation with joint domain-adversarial reconstruction networks. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 640-656). Springer, Cham.
• Shen, J., Zhang, Y., Yu, C., & Wang, C. (2020, December). Multi-view Multi-label Learning with Dual-Attention Networks for Stroke Screen. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1124-1128). IEEE.
• Lu, H. Y., Zhang, Y., & Du, Y. (2021). SenU-PTM: a novel phrase-based topic model for short-text topic discovery by exploiting word embeddings. Data Technologies and Applications.
• Chen M., Du Y., Zhang, Y., Qian, S., & Wang, C.Semi-Supervised Learning with Multi-Head Co-Training. In Proceedings of  AAAI 2022. Accepted

Rewards or Honors

• Excellent Graduate Student of Nanjing University in 2020
• First Prize of Talent Scholarship, November 2020
• Zhonghui Information Scholarship, December 2019
• Excellent Graduate Student of Nanjing University in 2019
• Excellent Graduate Student of Nanjing University in 2018
• First-class Academic Scholarship, 2018-2019
• First-class Academic Scholarship, 2017-2018
• Outstanding Graduate of Huazhong University of Science and Technology. Wuhan, June 2017

Correspondence

Mail

Yi Zhang
National Key Laboratory for Novel Software Technology 
Nanjing University 
Nanjing 210023, China 

Laboratory

325, Building of Computer Science and Technology, Xianlin Campus of Nanjing University