Xinyuan (Youki) Cao

Hi! I am Xinyuan Cao (曹馨元), a second-year PhD student in Machine Learning at Georgia Institute of Technology. I am fortunate to be advised by Prof. Santosh Vempala. Before joining Gatech, I received my Master's degree in Data Science from Columbia University, supervised by Prof. John Wright. I obtained my Bachelor's degree in Mathematics at Fudan University.

Email  /  Github

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I have broad interest in machine learning, optimization and graph. My research mainly focuses on developing efficient and provable machine learning algorithms and build theories that inspire the machine learning practicers!

Provable Lifelong Learning of Representations
Xinyuan Cao, Weiyang Liu, Santosh Vempala


We propose a lifelong learning algorithm that maintains and refines the internal feature representation and prove nearly matching upper and lower bounds on the total sample complexity. We also complement our analysis with an empirical study, where our method performs favorably on challenging realistic image datasets compared to state-of-the-art continual learning methods.

Graph Embedding via Diffusion-Wavelets-Based Node Feature Distribution Characterization
Lili Wang, Chenghan Huang, Weicheng Ma, Xinyuan Cao, Soroush Vosoughi

CIKM 2021

We propose a novel unsupervised whole graph embedding method. Our method uses spectral graph wavelets to capture topological similarities on each k-hop sub-graph between nodes and uses them to learn embeddings for the whole graph. We evaluate our method against 12 well-known baselines on 4 real-world datasets and show that our method achieves the best performance across all experiments, outperforming the current state-of-the-art by a considerable margin.