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Tieliang Gong

4 papers hereh-index 7189 citations24 works total

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

author position
  • middle author4

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

fields
  • cs.CV1
  • cs.LG1
  • eess.IV1
  • stat.ME1
same name
  • Tieliang Gong — 9 papers, h 5
  • Tieliang Gong — 6 papers, h 15
  • Tieliang Gong — 3 papers

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
20212026
most citedA Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization

Xuelin Zhang, Hong Chen, Bin Gu +2

Stochastic bilevel optimization (SBO) has been integrated into many machine learning paradigms recently, including hyperparameter optimization, meta learning, and reinforcement lea…

stat.ME2022

Error-based Knockoffs Inference for Controlled Feature Selection

Xuebin Zhao, Hong Chen, Yingjie Wang +4

Recently, the scheme of model-X knockoffs was proposed as a promising solution to address controlled feature selection under high-dimensional finite-sample settings. However, the p…

cs.CV2021★ 1 cited

A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data

Jialun Wu, Zeyu Gao, Haichuan Zhang +4

Personalized diagnoses have not been possible due to sear amount of data pathologists have to bear during the day-to-day routine. This lead to the current generalized standards tha…

eess.IV2021

W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image

Anyu Mao, Jialun Wu, Xinrui Bao +3

Pathological diagnosis is the gold standard for cancer diagnosis, but it is labor-intensive, in which tasks such as cell detection, classification, and counting are particularly pr…

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