天津大学计算机学院于强,吴华明-优快云博客

该博客综述了Huaming Wu教授在深度学习、移动云环境下的多项研究成果，包括通道剪枝、能量效率决策、延迟移动计算优化、特征学习与安全策略。重点探讨了卷积神经网络加速、深度区分性表示、能耗响应时间 tradeoff 以及多目标决策等问题。

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1.Congcong Liu and Huaming Wu, Channel Pruning Based on Mean Gradient for Accelerating Convolutional Neural Networks, Signal Processing, 2019, vol. 156, 84-91

2.Monica M.Y. Zhang, Kun Shang, and Huaming Wu. Learning Deep Discriminative Face Features by Customized Weighted Constraint, Neurocomputing, 2019, 332, 71-79

3.Huaming Wu, William J. Knottenbelt and Katinka Wolter. An Efficient Application Partitioning Algorithm in Mobile Environments, IEEE Transactions on Parallel and Distributed Systems

4.Monica M.Y. Zhang, Kun Shang, and Huaming Wu. Deep Compact Discriminative representation for unconstrained face recognition, Signal Processing: Image Communication, 2019

5.Wu, H., and Wolter, K., Stochastic Analysis of Delayed Mobile Offloading in Heterogeneous Networks, IEEE Transactions on Mobile Computing, 17(2), 461-474, 2018.

6.Wu, H., Yi, S., and Wolter, K., Energy-Efficient Decision Making for Mobile Cloud Offloading, IEEE Transactions on Cloud Computing, 2018. IF:7.928

7.Meng T., Wolter, K., Wu, H. and Wang, Q., A Secure and Cost-efficient Offloading Policy for Mobile Cloud Computing against Timing Attacks, Pervasive and Mobile Computing, 45, 4-18, 2018.

8.Chen, Z. L., Wang, J., Li, W. J., Li, N., Wu, Wu, H., & Wang, D. W. Convolutional neural network with nonlinear competitive units. Signal Processing: Image Communication. 60 ,193-198, 2018

9.Wu, H., Multi-Objective Decision-Making for Mobile Cloud Offloading: A Survey, IEEE Access, vol. 6, pp. 3962 - 3976, 2018.

10.Wu, B., Chen, Z., Wang, J., & Wu, H. (2018). Exponential discriminative metric embedding in deep learning. Neurocomputing, 290, 108-120.

11. Monica M.Y. Zhang, Yifang Xu and Wu, H. Orientation Truncated Center Learning for Deep Face Recognition,IET Electronics Letters, Vol. 54, No. 19, 1110–1112

12.Wu, H. Performance Modeling of Delayed Offloading in Mobile Wireless Environments with Failures, IEEE Communications Letters, vol.22, no.11, pp. 2334-2337

13.Zhang, M. M.Y., Shang, K.& Wu, H. (2018). Exponential discriminative metric embedding in deep learning. Neurocomputing, 290, 108-120.

14.Wu, H., Knottenbelt, W., Wolter, K., & Sun, Y. (2016). An Optimal Offloading Partitioning Algorithm in Mobile Cloud Computing. In International Conference on Quantitative Evaluation of Systems (pp. 311-328). Springer International Publishing.

15.Wu, H., Sun, Y., & Wolter, K. (2015) Analysis of the Energy-Response Time Tradeoff for Delayed Mobile Cloud Offloading. ACM SIGMETRICS Performance Evaluation Review, 43(2), 33-35.

16.Wu, H. (2015). Analysis of mHealth Systems with Multi-cloud Computing Offloading. In Mobile Health (pp. 589-608). Springer International Publishing.

17.Wu, H., Knottenbelt, W. J. & Wolter, K. (2015) Analysis of the Energy-Response Time Tradeoff for Mobile Cloud Offloading using Combined Metrics, Teletraffic Congress (ITC), 2015 27th International (pp. 134-142). IEEE.

18.Wu, H., Wang, Q., & Wolter, K. (2013). Tradeoff Between Performance Improvement and Energy Saving in Mobile Cloud Offloading Systems. In Communications (ICC), 2013 IEEE International Conference on (pp. 728-732). IEEE.

19.Wu, H., Wang, Q., & Wolter, K. (2012). Methods of cloud-path selection for offloading in mobile cloud computing systems. In Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on (pp. 443-448). IEEE.