Lunjia Hu
I am a fourth-year Ph.D. student at Computer Science Department, Stanford University. I am very fortunate to be co-advised by Moses Charikar and Omer Reingold. Before Stanford, I was an undergraduate in the Yao Class at Tsinghua University, where I received B.Eng. in computer science and B.S. in mathematics.
Publications
Conference Proceedings:
An Improved Local Search Algorithm for k-Median.
Vincent Cohen-Addad, Anupam Gupta, Lunjia Hu, Hoon Oh, David Saulpic
To appear in SODA 2022
Near-Optimal Explainable k-Means for All Dimensions.
Moses Charikar, Lunjia Hu
To appear in SODA 2022
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers. [arXiv]
Lunjia Hu, Omer Reingold
AISTATS 2021
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization. [arXiv]
Moses Charikar, Lunjia Hu
AISTATS 2021
The Power of Many Samples in Query Complexity. [conference version][arXiv]
Andrew Bassilakis, Andrew Drucker, Mika Göös, Lunjia Hu, Weiyun Ma, Li-Yang Tan
ICALP 2020
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation. [conference version][arXiv]
Liwei Wang, Lunjia Hu, Jiayuan Gu, Zhiqiang Hu, Yue Wu, Kun He, John Hopcroft
NeurIPS 2018 (Spotlight)
Active Tolerant Testing. [conference version][arXiv]
Avrim Blum, Lunjia Hu.
COLT 2018
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes. [conference version][arXiv]
Lunjia Hu, Ruihan Wu, Tianhong Li, Liwei Wang.
COLT 2017
Capacitated Center Problems with Two-Sided Bounds and Outliers. [conference version][arXiv]
Hu Ding, Lunjia Hu, Lingxiao Huang, Jian Li.
WADS 2017
Professional Services
Conference & Journal Reviewing: ALT 2019, NeurIPS 2019, NeurIPS 2020, SODA 2022, JMLR
TA'ing:
Randomized Algorithms and Probabilistic Analysis (CS265/CME309), Fall 2020-2021, Stanford
The Practice of Theory Research (CS163), Winter 2020-2021, Stanford
Other:
I wrote a blog post about the sunflower lemma.
Contact Information
Email: [first name] [at] stanford [dot] edu