Hui Ye
Computer Science- Education
M.A. Lehigh University
M.A. Huazhong University of Science and Technology
B.A. Huazhong University of Science and Technology
- Specializations
Deep Learning, Large-scale Machine Learning, Data Mining, Deep Generative Learning
- Biography
Hui Ye is a PhD student in the Department of Computer Science at Georgia State University. He has specialized in computer science during his career. When he worked as a software engineer in the industry, his main job was to design and develop software for processing data. His principal research interests lie in deep learning. He is interested in developing efficient algorithms to deal with large-scale classification problems and models to generate images from texts. He has published several research papers in these areas in leading journals and conference proceedings.
- Publications
Hui Ye, Xiulong Yang, Martin Takac, Raj Sunderraman, and Shihao Ji, “Improving Text-to-Image Synthesis Using Contrastive Learning,” The 32nd British Machine Vision Conference (BMVC, IF: 5.94), Virtual, Nov. 2021. [link]
Xiulong Yang, Hui Ye, Yang Ye, Xiang Li, Shihao Ji. Generative Max-Mahalanobis
Classifiers for Image Classification, Generation and More. arXiv:2101.00122. [link]
Youshan Zhang, Hui Ye, Brian D. Davison. Adversarial Reinforcement Learning for Unsupervised Domain Adaptation. WACV, 2021. [link]
Hui Ye, Zhiyu Chen, Da-Han Wang, Brian D. Davison. Pretrained Generalized
Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification. ICML, 2020. [link]
Kun He, Hui Ye, Zhengli Wang, Jingfa Liu. An efficient quasi-physical quasi-human algorithm for packing equal circles in a circular container. Computers and Operations Research, Volume 92, April 2018, Pages 26-36. [link]