Previously, I received my Ph.D. degree from IIE, CAS under the supervision of Associate Researcher Yong Liu and Researcher Weiping Wang. I received my Bachelor’s degree in Northeastern University in Shenyang, China, where I am a member of 2011 International class (English) in Software College.
My research interests mainly lie in efficient large scale machine learning with theoretical guarantee, but also include kernel methods, semi-supervised learning (SSL) and interpretability of neural networks.
Indeed, my works focus on generalization analysis of those areas and building effective and scalable optimization tools for them, to channel theory and algorithms into applications.
- Oct 4, 2022. A corresponding-author paper titled “Non-IID Federated Learning with Sharper Risk Bound” is accepted at IEEE Transactions on Neural Networks and Learning Systems (TNNLS, CCF-B Journal / JCR Q1), available at here.
- Sep 30, 2022. A first-author paper titled “Convolutional Spectral Kernel Learning with Generalization Guarantees” is accepted at Artificial Intelligence (AI, CCF-A Journal / JCR Q1), available at here / free access before 12/01/2022.
- Aug 1, 2022. A paper titled “Sharper Utility Bounds for Differentially Private Models: Smooth and Non-smooth” is accepted at CIKM 2022 (CCF-B conference).
- Jun 15, 2022. A first-author paper titled “Non-IID Distributed Learning with Optimal Mixture Weights” is accepted at ECML 2022 (CCF-B conference).
Projects and Awards
- Excellent Talents Program of Institute of Information Engineering, CAS.
- Special Research Assistant Project of CAS.
- National Natural Science Foundation of China (No. 62106257).
- PRICAI 2021 best student paper award.
- Outstanding Graduates of Beijing & UCAS. 2020.
- National Scholarship for Doctoral students. 2018 & 2019.