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Fang Yao

5 papers hereh-index 14 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • stat.ME3
  • math.ST1
  • stat.ML1
same name
  • Fang Yao — 9 papers, h 27
  • Fang Yao — 4 papers, h 1
  • Fang Yao — 3 papers, h 2
  • Fang Yao — 3 papers, h 2
  • Fang Yao — 2 papers
  • Fang Yao — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedMatrix Completion via Residual Spectral Matching

1 citations · 1 across the 5 of their papers we have counts for

collaborators

4 papers

stat.ME2026

Functional linear regression from sparse to dense designs: a pooling-ridge method and minimax optimality

Shunxing Yan, Fang Yao

Functional data analysis is an important statistical field that treats data as random functions. In practice, the random functions are often not fully observed but instead measured…

stat.ME2025

Deep Semiparametric Partial Differential Equation Models

Ziyuan Chen, Shunxing Yan, Fang Yao

In many scientific fields, the generation and evolution of data are governed by partial differential equations (PDEs) which are typically informed by established physical laws at t…

math.ST2025

Semiparametric M-estimation with overparameterized neural networks

Shunxing Yan, Ziyuan Chen, Fang Yao

We focus on semiparametric regression that has played a central role in statistics, and exploit the powerful learning ability of deep neural networks (DNNs) while enabling statisti…

stat.ML2024★ 1 cited

Matrix Completion via Residual Spectral Matching

Ziyuan Chen, Fang Yao

Noisy matrix completion has attracted significant attention due to its applications in recommendation systems, signal processing and image restoration. Most existing works rely on…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.