Xiangyu Guo's Homepage

Xiangyu Guo 郭翔宇

(also written as Xiang-Yu Guo)

I have successfully defended my PhD thesis. I will still maintain this website, though may not be so up-to-date. You can also see my new homepage

I was a PhD student (2017 -- 2022) at the Department of Computer Science and Engineering of SUNY Buffalo, and I am very fortunate to be advised by Prof. Shi Li.

Before coming to the United States, I obtained my bachelor degree (2014) in Electronic Engineering from Xidian University, and master degree (2017) in Computer Science from Nanjing University under the supervision of Prof. Wei Wang.

Contact

Postal Address

Department of Computer Science and Engineering
The State University of New York at Buffalo
Amherst, NY 14260-2500

Office

wu ke feng gao.

Email

[first name] + [first letter of last name]@buffalo.edu

Research Interests

Currently I am mainly interested in approximation algorithms and their application in machine learning.

Teaching

• CSE331 Algorithms and Complexity (Summer 2020)

• Reading group: Sum-of-Squares Method for Statistics (Summer 2020)

Publications

((α) means authors are listed in alphabetical order, and * means equal contribution)

Manuscripts:

Conferences:

• The Multi-vehicle Ride-sharing Problem. (WSDM'22) [code to release soon]

(α) Chaitanya Agarwal, Syamantak Das, X. Guo, Kelin Luo.

• Consistent k-Median: Simpler, Better and Robust. (AISTATS'21) [code]

(α) X. Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian.

• On the Facility Location Problem in Online and Dynamic Models. (APPROX'20)

(α) X. Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian.

• On Approximating Degree-Bounded Network Design Problems. (APPROX'20) [slides]

(α) X. Guo, Guy Kortsarz, Bundit Laekhanukit, Shi Li, Daniel Vaz, Jiayi Xian.

• Scalable Estimating Stochastic Linear Combination of Non-linear Regressions. (AAAI'20) [code]

*Di Wang, *X. Guo, Chaowen Guan, Shi Li, Jinhui Xu.

(Journal version accepted to Neurocomputing, 2020)

• Distributed k-Clustering for Data with Heavy Noise. (NeurIPS'18, Spotlight) [poster | code]

(α) X. Guo, Shi Li.

• Modal Consistency based Pre-trained Multi-Model Reuse.(IJCAI'17)

Yang Yang, De-Chuan Zhan, X.-Y. Guo, Yuan Jiang.

• Obtaining High-quality Label by Distinguishing between Easy and Hard Items in Crowdsourcing. (IJCAI'17)

Wei Wang, X.-Y. Guo, Shao-Yuan Li, Yuan Jiang, Zhi-Hua Zhou.

Journals:

• Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding. (Machine Learning, 2020) [code]

*Di Wang, *X. Guo, Shi Li, Jinhui Xu.

• Estimating stochastic linear combination of non-linear regressions efficiently and scalably. (Neurocomputing, 2020)

*Di Wang, *X. Guo, Chaowen Guan, Shi Li, Jinhui Xu.

(Conference version appeared in AAAI, 2020)

Some Notes

Extension Complexity via Lifting LP Hierarchy Lower Bounds

Professional Activities

Conference Reviewer: ISAAC'19, SoCG'20, SPAA'20, NeurIPS'20, AAAI'21, AISTATS'21, NeurIPS'21.

Journal Reviewer: Discrete Applied Mathematics, Journal of Combinatorial Optimization, Algorithmica, Theoretical Computer Science, Journal of Computer and System Science