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researcher

Yimin Yang

7 papers hereh-index 313.1k citations109 works total

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

author position
  • first author4
  • middle author2
  • last author1

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CV2
  • cs.NE1
same name
  • Yimin Yang — 2 papers, h 2
  • Yimin Yang — 1 paper, h 1
  • Yimin Yang — 1 paper, h 10
  • Yimin Yang — 1 paper, h 4
  • Yimin Yang — 1 paper, h 2
  • Yimin Yang — 1 paper, 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
20142022
most citedDeep Networks with Fast Retraining

3 citations · 7 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2022★ 1 cited

AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks

Yimin Yang, Siamak Mehrkanoon

Data driven modeling based approaches have recently gained a lot of attention in many challenging meteorological applications including weather element forecasting. This paper intr…

cs.LG2021

Multi-Model Least Squares-Based Recomputation Framework for Large Data Analysis

Wandong Zhang, QM Jonathan Wu, Yimin Yang +3

Most multilayer least squares (LS)-based neural networks are structured with two separate stages: unsupervised feature encoding and supervised pattern classification. Once the unsu…

cs.LG2020★ 3 cited

Deep Networks with Fast Retraining

Wandong Zhang, Yimin Yang, Jonathan Wu

Recent work [1] has utilized Moore-Penrose (MP) inverse in deep convolutional neural network (DCNN) learning, which achieves better generalization performance over the DCNN with a…

cs.LG2018★ 1 cited

Non-iterative recomputation of dense layers for performance improvement of DCNN

Yimin Yang, Q. M. Jonathan Wu, Xiexing Feng +1

An iterative method of learning has become a paradigm for training deep convolutional neural networks (DCNN). However, utilizing a non-iterative learning strategy can accelerate th…

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