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Jianmin Wang

74 papers hereh-index 8246k citations166 works total

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

author position
  • middle author64
  • last author7

Across the 71 of 74 papers where every author was matched, so the position is known.

fields
  • cs.LG56
  • cs.CV15
  • cs.IR1
  • cs.NE1
  • cs.PL1
same name
  • Jianmin Wang — 11 papers, h 5
  • Jianmin Wang — 10 papers, h 9
  • Jianmin Wang — 9 papers, h 6
  • Jianmin Wang — 7 papers, h 33
  • Jianmin Wang — 5 papers, h 3
  • Jianmin Wang — 4 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
20152025
most citedLearning Transferable Features with Deep Adaptation Networks

2.8k citations · 8.6k across the 72 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.LG2020★ 13 cited

Bi-tuning of Pre-trained Representations

Jincheng Zhong, Ximei Wang, Zhi Kou +2

It is common within the deep learning community to first pre-train a deep neural network from a large-scale dataset and then fine-tune the pre-trained model to a specific downstrea…

cs.LG2020★ 7 cited

Unsupervised Transfer Learning for Spatiotemporal Predictive Networks

Zhiyu Yao, Yunbo Wang, Mingsheng Long +1

This paper explores a new research problem of unsupervised transfer learning across multiple spatiotemporal prediction tasks. Unlike most existing transfer learning methods that fo…

cs.LG2020★ 4 cited

On Localized Discrepancy for Domain Adaptation

Yuchen Zhang, Mingsheng Long, Jianmin Wang +1

We propose the discrepancy-based generalization theories for unsupervised domain adaptation. Previous theories introduced distribution discrepancies defined as the supremum over co…

cs.LG2020★ 19 cited

Transferable Calibration with Lower Bias and Variance in Domain Adaptation

Ximei Wang, Mingsheng Long, Jianmin Wang +1

Domain Adaptation (DA) enables transferring a learning machine from a labeled source domain to an unlabeled target one. While remarkable advances have been made, most of the existi…

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