叶光昊 (Yè Guāng Hào) | Guanghao Ye

Papers

Following conventions of math and theoretical computer science, author names are listed alphabetically.

1. [ bib ] Faster Min-Cost Flow on Bounded Treewidth Graphs

   with Sally Dong

   @article{DBLP:journals/corr/abs-2308-14727,
     author = {Dong, Sally and Ye, Guanghao},
     title = {Faster Min-Cost Flow on Bounded Treewidth Graphs},
     journal = {CoRR},
     year = {2023},
     url = {https://doi.org/10.48550/arXiv.2308.14727},
     doi = {10.48550/arXiv.2308.14727},
     eprinttype = {arXiv},
     eprint = {2308.14727},
   }

1. [ bib ] Improving the Bit Complexity of Communication for Distributed Convex Optimization

   with Mehrdad Ghadiri, Yin Tat Lee, Swati Padmanabhan, William Swartworth, and David Woodruff

   Symposium on Theory of Computing (STOC), 2024 (to appear)

   @article{ghadiri2024improving,
     author = {Ghadiri, Mehrdad and Lee, Yin Tat and Padmanabhan, Swati and Swartworth, William and Woodruff, David and Ye, Guanghao},
     title = {Improving the Bit Complexity of Communication for Distributed Convex Optimization},
     year = {2024},
   }

2. [ bib ] Fast Algorithms for Separable Linear Programs

   with Sally Dong, Gramoz Goranci, Lawrence Li, and Sushant Sachdeva

   Symposium on Discrete Algorithms (SODA), 2024

   @inproceedings{dong2024fast,
     author = {Dong, Sally and Goranci, Gramoz and Li, Lawrence and Sachdeva, Sushant and Ye, Guanghao},
     title = {Fast Algorithms for Separable Linear Programs},
     booktitle = {Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)},
     year = {2024},
   }

3. [ bib ] A Gradient Sampling Method with Complexity Guarantees for Lipschitz Functions in High and Low Dimensions

   with Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, and Swati Padmanabhan

   Neural Information Processing Systems (NeurIPS), 2022 (oral presentation)

   @inproceedings{DBLP:conf/nips/DavisDLPY22,
     author = {Davis, Damek and Drusvyatskiy, Dmitriy and Lee, Yin Tat and Padmanabhan, Swati and Ye, Guanghao},
     title = {A Gradient Sampling Method with Complexity Guarantees for Lipschitz Functions in High and Low Dimensions},
     booktitle = {NeurIPS},
     year = {2022},
   }

4. [ bib ] Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity

   with Sally Dong, Haotian Jiang, Yin Tat Lee, and Swati Padmanabhan

   Neural Information Processing Systems (NeurIPS), 2022

   @inproceedings{DBLP:conf/nips/DongJLPY22,
     author = {Dong, Sally and Jiang, Haotian and Lee, Yin Tat and Padmanabhan, Swati and Ye, Guanghao},
     title = {Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient
                       Oracle Complexity},
     booktitle = {NeurIPS},
     year = {2022},
   }

5. [ bib ] Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time

   with Sally Dong, Yu Gao, Gramoz Goranci, Yin Tat Lee, Richard Peng, and Sushant Sachdeva

   Symposium on Discrete Algorithms (SODA), 2022

   @inproceedings{DBLP:conf/soda/DongGGLPSY22,
     author = {Dong, Sally and Gao, Yu and Goranci, Gramoz and Lee, Yin Tat and Peng, Richard and Sachdeva, Sushant and Ye, Guanghao},
     editor = {Naor, Joseph (Seffi) and Buchbinder, Niv},
     title = {Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear
                    Time},
     booktitle = {Proceedings of the 2022 {ACM-SIAM} Symposium on Discrete Algorithms,
                    {SODA} 2022, Virtual Conference / Alexandria, VA, USA, January 9 -
                    12, 2022},
     pages = {124--153},
     publisher = {{SIAM}},
     year = {2022},
     url = {https://doi.org/10.1137/1.9781611977073.7},
     doi = {10.1137/1.9781611977073.7},
   }

6. [ bib ] A Nearly-Linear Time Algorithm for Linear Programs with Small Treewidth: A Multiscale Representation of Robust Central Path

   with Sally Dong, and Yin Tat Lee

   Symposium on Theory of Computing (STOC), 2021
   Invited to SICOMP Special Issue.

   @inproceedings{DBLP:conf/stoc/DongLY21,
     author = {Dong, Sally and Lee, Yin Tat and Ye, Guanghao},
     editor = {Khuller, Samir and Williams, Virginia Vassilevska},
     title = {A Nearly-Linear Time Algorithm for Linear Programs with Small Treewidth: A Multiscale Representation of Robust Central Path},
     booktitle = {{STOC} '21: 53rd Annual {ACM} {SIGACT} Symposium on Theory of Computing,
                    Virtual Event, Italy, June 21-25, 2021},
     pages = {1784--1797},
     publisher = {{ACM}},
     year = {2021},
     url = {https://doi.org/10.1145/3406325.3451056},
     doi = {10.1145/3406325.3451056},
   }

7. [ bib ] Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time

   with Jerry Li

   Neural Information Processing Systems (NeurIPS), 2020

   @inproceedings{DBLP:conf/nips/0001Y20,
     author = {Li, Jerry and Ye, Guanghao},
     editor = {Larochelle, Hugo and Ranzato, Marc'Aurelio and Hadsell, Raia and Balcan, Maria{-}Florina and Lin, Hsuan{-}Tien},
     title = {Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication
                    Time},
     booktitle = {Advances in Neural Information Processing Systems 33: Annual Conference
                    on Neural Information Processing Systems 2020, NeurIPS 2020, December
                    6-12, 2020, virtual},
     year = {2020},
   }

8. [ bib ] Fast Algorithm for Solving Structured Convex Programs

   Undergraduate Thesis
   Best Senior Thesis Award Honorable Mention

   @article{ye2020fast,
     title = {Fast Algorithm for Solving Structured Convex Programs},
     author = {Ye, Guanghao},
     year = {2020},
   }