Yixin Chen

I am a PhD student in Computer Science at Texas A&M University, advised by Dr. Alan Kuhnle. Prior that, I received my Master of Science degree in Statistics at University of Wisconsin-Madison, and Bachelor of Science degree in Mathematics and Applied Mathematics at Nankai University.

Research Interests

• Submodular Optimization
• Approximation Theory
• Combinatorial Optimizaiton
• Machine Learning

Education

• Ph.D in Computer Science, Texas A&M University, 2022 – present
• Ph.D (Transfer out) in Computer Science, Florida State University, 2019 – 2022
• M.S. in Statistics, University of Wisconsin Madison, 2017 – 2019
• B.S. in Mathematics and Applied Mathematics, Nankai University, 2014 – 2018

Publications

Note: ^★ indicates equal contribution.

1. Discretely Beyond $1/e$: Guided Combinatorial Algorithms for Submodular Maximization
   Yixin Chen, Ankur Nath, Chunli Peng, Alan Kuhnle
   NeurIPS 2024
2. Scalable Distributed Algorithms for Size-Constrained Submodular Maximization in the MapReduce and Adaptive Complexity Models
   Yixin Chen^★, Tonmoy Dey^★, Alan Kuhnle
   JAIR 2024
3. Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint
   Yixin Chen, Alan Kuhnle
   JAIR 2024
4. Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time
   Yixin Chen, Alan Kuhnle
   KDD 2023
5. DASH: A Distributed and Parallelizable Algorithm for Size-Constrained Submodular Maximization
   Tonmoy Dey, Yixin Chen, Alan Kuhnle
   AAAI 2023
6. Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel
   Yixin Chen, Tonmoy Dey, Alan Kuhnle
   NeurIPS 2021
7. Graph neural lasso for dynamic network regression
   Yixin Chen, Lin Meng, Jiawei Zhang
   Preprint (arXiv) 2020