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researcher

Yan Feng

27 papers hereh-index 201.9k citations51 works total

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

author position
  • middle author25

Across the 25 of 27 papers where every author was matched, so the position is known.

fields
  • cs.IR13
  • cs.LG10
  • cs.CV3
  • cs.AI1
same name
  • Yan Feng — 28 papers, h 19
  • Yan Feng — 13 papers, h 6
  • Yan Feng — 8 papers, h 13
  • Yan Feng — 7 papers, h 3
  • Yan Feng — 6 papers, h 9
  • Yan Feng — 6 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
20192025
most citedHow Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective

20 citations · 66 across the 26 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 1 cited

Accelerating Diffusion Sampling with Classifier-based Feature Distillation

Wujie Sun, Defang Chen, Can Wang +3

Although diffusion model has shown great potential for generating higher quality images than GANs, slow sampling speed hinders its wide application in practice. Progressive distill…

cs.IR2022

GReS: Graphical Cross-domain Recommendation for Supply Chain Platform

Zhiwen Jing, Ziliang Zhao, Yang Feng +6

Supply Chain Platforms (SCPs) provide downstream industries with numerous raw materials. Compared with traditional e-commerce platforms, data in SCPs is more sparse due to limited…

cs.LG2022

Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding

Yichen Liu, Jiawei Chen, Defang Chen +3

Knowledge Graph Embedding (KGE), which projects entities and relations into continuous vector spaces, has garnered significant attention. Although high-dimensional KGE methods offe…

cs.CV2022★ 14 cited

Knowledge Distillation with the Reused Teacher Classifier

Defang Chen, Jian-Ping Mei, Hailin Zhang +3

Knowledge distillation aims to compress a powerful yet cumbersome teacher model into a lightweight student model without much sacrifice of performance. For this purpose, various ap…

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