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Zehong Cao

21 papers hereh-index 303k citations75 works total

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

author position
  • first author7
  • middle author8
  • last author3

Across the 18 of 21 papers where every author was matched, so the position is known.

fields
  • eess.SP8
  • cs.LG4
  • cs.AI3
  • cs.HC2
  • cs.CL1
  • cs.CV1
same name
  • Zehong Cao — 2 papers, h 21
  • Zehong Cao — 2 papers, h 7
  • Zehong Cao — 1 paper
  • Zehong Cao — 1 paper, h 4

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
20182024
most citedMulti-channel EEG recordings during a sustained-attention driving task

270 citations · 722 across the 20 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024

A Self-Constructing Multi-Expert Fuzzy System for High-dimensional Data Classification

Yingtao Ren, Yu-Cheng Chang, Thomas Do +2

Fuzzy Neural Networks (FNNs) are effective machine learning models for classification tasks, commonly based on the Takagi-Sugeno-Kang (TSK) fuzzy system. However, when faced with h…

cs.LG2022★ 10 cited

Distributed Semi-supervised Fuzzy Regression with Interpolation Consistency Regularization

Ye Shi, Leijie Zhang, Zehong Cao +2

Recently, distributed semi-supervised learning (DSSL) algorithms have shown their effectiveness in leveraging unlabeled samples over interconnected networks, where agents cannot sh…

cs.LG2019

Reinforcement Learning from Hierarchical Critics

Zehong Cao, Chin-Teng Lin

In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of reinforcement learning (RL) in competition tasks…

cs.LG2018★ 57 cited

Semi-supervised Feature Learning For Improving Writer Identification

Shiming Chen, Yisong Wang, Chin-Teng Lin +2

Data augmentation is usually used by supervised learning approaches for offline writer identification, but such approaches require extra training data and potentially lead to overf…

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