Yujia Jin

I am a third-year PhD student in the Department of Management Science and Engineering at Stanford in the Operations Research group, advised by Aaron Sidford.

I am broadly interested in optimization problems, sometimes in the intersection with machine learning theory and graph applications. I enjoy understanding the theoretical ground of many algorithms that are of practical importance.

Prior to coming to Stanford, I received my Bachelor's degree in Applied Math at Fudan University, where I was fortunate to work with Prof. Zhongzhi Zhang. From 2016 to 2018, I also worked in Research Institute for Interdisciplinary Sciences (RIIS) at SHUFE, where I was fortunate to be advised by Prof. Dongdong Ge.

Email / Google Scholar

Selected Publications

Acceleration with a Ball Optimization Oracle
with Yair Carmon, Arun Jambulapati, Qijia Jiang, Yin Tat Lee, Aaron Sidford and Kevin Tian
Neural Information Processing Systems (NeurIPS, Oral), 2020
[pdf]

Coordinate Methods for Matrix Games
with Yair Carmon, Kevin Tian and Aaron Sidford
Symposium on Foundations of Computer Science (FOCS), 2020
[pdf]

Efficiently Solving MDPs with Stochastic Mirror Descent
with Aaron Sidford
International Conference on Machine Learning (ICML), 2020
[pdf][talk]

Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG
with Aaron Sidford
Neural Information Processing Systems (NeurIPS, Spotlight), 2019
[pdf][slides]

Variance Reduction for Matrix Games
with Yair Carmon, Aaron Sidford and Kevin Tian
Neural Information Processing Systems (NeurIPS, Oral), 2019
[pdf][poster]