"Alternating Minimization in Machine Learning with Provable Convergence"
Kai Liu is a Ph.D. candidate at Colorado School of Mines working with Dr. Hua Wang. Before he started pursuing his Ph.D., he did his Master and Bachelor studies in Control Sciences & Automation at Tsinghua University and Beijing Jiaotong University respectively. His research interest lies in Machine Learning and its applications in Data Mining, Computer Vision, Natural Language Processing and Bioinformatics. He aims at providing computationally efficient algorithms with provable theoretical guarantees. His work has been published in various top machine learning venues such as NIPS, ACL, CVPR, SDM, AAAI, IJCAI and RECOMB. During his internship, he worked on speech recognition and image/audio denoising with deep learning approaches.
Wednesday, March 6 at 2:30pm to 3:30pm
McAdams Hall, 107
821 McMillan Rd., Clemson, SC 29634, USA