
Zhewei Yao
position bias
retrieval-augmented generation
consistency
inference scaling
rank distillation
2
presentations
1
number of views
SHORT BIO
Zhewei Yao is a Ph.D. student in the BAIR, RISELab (former AMPLab), BDD, and Math Department at University of California at Berkeley. He is advised by Michael Mahoney, and he is also working very closely with Kurt Keutzer. His research interest lies in computing statistics, optimization, and machine learning. Currently, he is interested in leveraging tools from randomized linear algebra to provide efficient and scalable solutions for large-scale optimization and learning problems. He is also working on the theory and application of deep learning. Before joining UC Berkeley, he received his B.S. in Math from Zhiyuan Honor College at Shanghai Jiao Tong University.
Presentations

What’s Hidden in a One-layer Randomly Weighted Transformer?
Zhewei Yao and 1 other author

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Zhewei Yao and 5 other authors