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researcher

Han Yu

20 papers hereh-index 386.2k citations141 works total

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

author position
  • sole author1
  • first author3
  • middle author13
  • last author3

Across the 20 of 20 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.CV3
  • cs.CR2
  • cs.MA2
  • cs.SE2
  • cs.AI1
same name
  • Han Yu — 36 papers, h 11
  • Han Yu — 29 papers, h 26
  • Han Yu — 15 papers, h 11
  • Han Yu — 12 papers, h 8
  • Han Yu — 11 papers, h 8
  • Han Yu — 11 papers, h 3

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
20142021
most citedTransfer Learning with Dynamic Distribution Adaptation

177 citations · 425 across the 19 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.LG2021★ 2 cited

Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering

Chang Liu, Han Yu, Boyang Li +6

Noisy labels are commonly found in real-world data, which cause performance degradation of deep neural networks. Cleaning data manually is labour-intensive and time-consuming. Prev…

cs.CV2021★ 6 cited

Noise-resistant Deep Metric Learning with Ranking-based Instance Selection

Chang Liu, Han Yu, Boyang Li +6

The existence of noisy labels in real-world data negatively impacts the performance of deep learning models. Although much research effort has been devoted to improving robustness…

cs.LG2021★ 6 cited

Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection

Xu Guo, Boyang Li, Han Yu +1

The existence of multiple datasets for sarcasm detection prompts us to apply transfer learning to exploit their commonality. The adversarial neural transfer (ANT) framework utilize…

cs.LG2021★ 25 cited

HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks

Yuanyuan Chen, Boyang Li, Han Yu +2

The behaviors of deep neural networks (DNNs) are notoriously resistant to human interpretations. In this paper, we propose Hypergradient Data Relevance Analysis, or HYDRA, which in…

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