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Luofeng Liao

Columbia University (from arXiv:2402.07322, 2024) · OpenAlex

7 papers in scope · 3 published · 4 on the econ.EM arXiv · 21 citations · h-index 2 (over the papers listed here)

Related authors

The 20 authors closest to this one in our weighted citation graph, most related first.

  1. Christian Kroer
  2. Yuan Gao
  3. Sergei Leonenkov
  4. Nicolás E. Stier-Moses
  5. Congshan Zhang
  6. Kroer Christian
  7. Nian Si
  8. Liang Shi
  9. Okke Schrijvers
  10. Zeyu Zheng
  11. X. Chen
  12. Xingyu Bai
  13. Kenichi Nagasawa
  14. Yu-Wei Hsieh
  15. Michael Jansson
  16. Matias D. Cattaneo
  17. Inessa Liskovich
  18. David Holtz
  19. Sinan Aral
  20. Gabriel Y. Weintraub

Proximity is measured over citations between two papers we both hold, weighted by how heavily one leans on the other, and is symmetric — it does not distinguish citing from being cited. Authors without a profile here are skipped, and a genuinely close colleague can be missing simply because their work is not in our arXiv corpus. Method: docs/06-citations-pipeline.md.

Papers

(4 of 7)

working paper2024 · arXiv
Greedy-Based Online Fair Allocation with Adversarial Input: Enabling Best-of-Many-Worlds Guarantees
published2024 · Proceedings of the AAAI Conference on Artificial Intelligence · 2 citations · first circulated 2023
with Zongjun Yang, Christian Kroer, Yuan Gao
working paper2024 · arXiv · 1 citations
working paper2024 · arXiv
Local AdaGrad-type algorithm for stochastic convex-concave optimization
published2022 · Machine Learning · 6 citations · first circulated 2021
with Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao
working paper2022 · arXiv
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach
published2020 · Neural Information Processing Systems · 12 citations
with You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang

Assembled from arXiv and OpenAlex. Duplicate records for the same paper are merged, and the published version is shown where we could identify one. Corrections welcome.