杨翔宇
报告人:   日期:2022年07月14日 09:23  

教育背景:

2017.09-2022.07, 博士, 中国科学院大学,  通信与信息系统

2013.09-2017.07, 学士, 郑州大学, 通信工程


工作经历:

2022.07-至今, 河南大学,讲师


研究领域:

大规模非线性优化、稀疏优化、机器学习


学术论文:

1. X. Yang, H. Wang* and J. Wang, "Towards An Efficient Approach for the Nonconvex Lp-ball Projection: Algorithm and Analysis," Journal of Machine Learning Research (JMLR), vol. 23, no.1, pp. 1-31, 2022.

2. H. Wang, X. Yang*, Y. Shi and J. Lin, "A Proximal Iteratively Reweighted Approach for Efficient Network Sparsification," IEEE Transactions on Computers, vol. 70, no. 1, pp. 185-196, 2022.

3. X. Yang, S. Hua, Y. Shi*, H. Wang, J. Zhang and K. B. Letaief, "Sparse Optimization for Green Edge AI
Inference," Journal of Communications and Information Networks, vol. 5, no. 1, pp. 1–15, 2020.

4. Z. Zhao, H. Wang*, X. Yang and F. Xu, "CVaR-cardinality Enhanced Indexation Optimization with Tunable Short-selling Constraints," Applied Economics Letters, pp. 1–7, Mar. 2020.

5. T. Jiang, X. Yang, Y. Shi and H. Wang, "Layer-wise Deep Neural Network Pruning via Iteratively Reweighted Optimization," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019, pp. 5606-5610.

6. S. Hua, X. Yang, K. Yang, G. Yin, Y. Shi and H. Wang, "Deep Learning Tasks Processing in Fog RAN," IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, HI, USA, 2019, pp. 1–5.


科研项目:

面向现代深度学习模型的随机二阶优化算法及理论研究,国家自然科学基金青年基金,2024-2026,主持


主讲课程:

概率论与数理统计、高等数学


社会兼职:

中国工业与应用数学学会会员

中国运筹学会会员


学术交流:

2021年10月在“中国运筹学会数学规划分会第十三届数学优化大会”在线报告(青岛)

2019年9月在 “2019 IEEE 90th VTC-2019-Fall”报告(Hawaii, USA)

2019年5月在“2019 IEEE 44th ICASSP”报告(Brighton, UK)

2018年10月在“中国运筹学会第十四次学术年会”报告(重庆)


荣誉与奖励:


研究生培养: