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Feifei Wang

9 papers hereh-index 5114 citations19 works total

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

author position
  • first author1
  • middle author8

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • stat.ME3
  • cs.LG2
  • stat.CO2
  • math.ST1
  • stat.AP1
same name
  • Feifei Wang — 9 papers, h 6
  • Feifei Wang — 6 papers, h 3
  • Feifei Wang — 5 papers, h 5
  • Feifei Wang — 3 papers, h 3
  • Feifei Wang — 3 papers, h 2
  • Feifei Wang — 3 papers, h 7

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
20202025
most citedA Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques

22 citations · 23 across the 9 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

stat.CO2023

Subnetwork Estimation for Spatial Autoregressive Models in Large-scale Networks

Xuetong Li, Feifei Wang, Wei Lan +1

Large-scale networks are commonly encountered in practice (e.g., Facebook and Twitter) by researchers. In order to study the network interaction between different nodes of large-sc…

stat.CO2023

Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator

Haobo Qi, Feifei Wang, Hansheng Wang

We study here a fixed mini-batch gradient decent (FMGD) algorithm to solve optimization problems with massive datasets. In FMGD, the whole sample is split into multiple non-overlap…

cs.LG2023

Improved Naive Bayes with Mislabeled Data

Qianhan Zeng, Yingqiu Zhu, Xuening Zhu +5

Labeling mistakes are frequently encountered in real-world applications. If not treated well, the labeling mistakes can deteriorate the classification performances of a model serio…

stat.ME2023

Testing Sufficiency for Transfer Learning

Ziqian Lin, Yuan Gao, Feifei Wang +1

Modern statistical analysis often encounters high dimensional models but with limited sample sizes. This makes the target data based statistical estimation very difficult. Then how…

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