◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

F. Chen

31 papers hereh-index 9344.7k citations1.5k works total

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

author position
  • first author3
  • middle author25
  • last author3

Across the 31 of 31 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • cs.LG7
  • cs.CL3
  • cond-mat.mes-hall1
  • cond-mat.str-el1
  • cs.DC1
same name
  • F. Chen — 9 papers, h 13
  • F. Chen — 8 papers, h 73
  • F. Chen — 5 papers, h 20
  • F. Chen — 5 papers, h 11
  • F. Chen — 5 papers, h 3
  • F. Chen — 3 papers, h 2

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
20152023
most citedExperimental comparison of single-pixel imaging algorithms

221 citations · 378 across the 26 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.LG2019

Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data

Xujiang Zhao, Feng Chen, Jin-Hee Cho

Subjective Logic (SL) is one of well-known belief models that can explicitly deal with uncertain opinions and infer unknown opinions based on a rich set of operators of fusing mult…

cs.LG2019★ 7 cited

Dual Averaging Method for Online Graph-structured Sparsity

Baojian Zhou, Feng Chen, Yiming Ying

Online learning algorithms update models via one sample per iteration, thus efficient to process large-scale datasets and useful to detect malicious events for social benefits, suc…

cs.LG2019★ 6 cited

Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization

Baojian Zhou, Feng Chen, Yiming Ying

Stochastic optimization algorithms update models with cheap per-iteration costs sequentially, which makes them amenable for large-scale data analysis. Such algorithms have been wid…

cs.CV2019★ 40 cited

Convolution with even-sized kernels and symmetric padding

Shuang Wu, Guanrui Wang, Pei Tang +2

Compact convolutional neural networks gain efficiency mainly through depthwise convolutions, expanded channels and complex topologies, which contrarily aggravate the training proce…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.