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Alexander Hanbo Li

University of California San Diego (from arXiv:1902.03327, 2019) · OpenAlex

5 papers in scope · 4 published · 1 on the econ.EM arXiv · 148 citations · h-index 5 (over the papers listed here)

Related authors

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

  1. Stefan Wager
  2. Susan Athey
  3. Guido W. Imbens
  4. Vasilis Syrgkanis
  5. Victor Chernozhukov
  6. Whitney K. Newey
  7. Rahul Ladhania
  8. Lyle Ungar
  9. Wenbo Wu
  10. Greg Lewis
  11. Christian Hansen
  12. Dmitry Arkhangelsky
  13. Pedro H. C. Sant’Anna
  14. Jann Spiess
  15. Paolo Verme
  16. Alessandro Baldi Antognini
  17. Yuan Qi
  18. Kevin Guo
  19. Xinkun Nie
  20. Mohsen Bayati

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

(1 of 5)

Generation-Focused Table-Based Intermediate Pre-training for Free-Form Question Answering
published2022 · Proceedings of the AAAI Conference on Artificial Intelligence · 9 citations
with Peng Shi, Patrick Ng, Nan Feng, Henghui Zhu, Jun Wang, Jiarong Jiang, Rishav Chakravarti, Donald J. Weidner, Bing Xiang, Zhiguo Wang
Proceedings of the AAAI Conference on Artificial Intelligence
Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
published2021 · Proceedings of the AAAI Conference on Artificial Intelligence · 75 citations · first circulated 2020
with Peng Shi, Patrick Ng, Zhiguo Wang, Henghui Zhu, Jun Wang, Cícero Nogueira dos Santos, Bing Xiang
Proceedings of the AAAI Conference on Artificial Intelligence
Censored Quantile Regression Forests
working paper2020 · arXiv · 8 citations · first circulated 2019
with Jelena Bradić
Paper profile arXiv arXiv:1902.03327
Forest-type Regression with General Losses and Robust Forest
published2017 · International Conference on Machine Learning · 21 citations
with Andrew Martin
no link
Boosting in the Presence of Outliers: Adaptive Classification With Nonconvex Loss Functions
published2017 · Journal of the American Statistical Association · 35 citations
with Jelena Bradić
Journal of the American Statistical Association

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.