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Fuzhen Zhuang

60 papers hereh-index 5116.4k citations210 works total

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

author position
  • first author3
  • middle author51
  • last author3

Across the 57 of 60 papers where every author was matched, so the position is known.

fields
  • cs.LG20
  • cs.IR18
  • cs.CL11
  • cs.AI3
  • cs.CV3
  • cs.CR1
same name
  • Fuzhen Zhuang — 59 papers, h 7
  • Fuzhen Zhuang — 11 papers, h 6
  • Fuzhen Zhuang — 3 papers, h 15
  • Fuzhen Zhuang — 3 papers, h 17
  • Fuzhen Zhuang — 2 papers, h 3
  • Fuzhen Zhuang — 2 papers, 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
20182026
most citedDeep Subdomain Adaptation Network for Image Classification

1.2k citations · 2.8k across the 60 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CL2018★ 18 cited

Cross-Domain Labeled LDA for Cross-Domain Text Classification

Baoyu Jing, Chenwei Lu, Deqing Wang +2

Cross-domain text classification aims at building a classifier for a target domain which leverages data from both source and target domain. One promising idea is to minimize the fe…

cs.CV2018★ 2 cited

The Automatic Identification of Butterfly Species

Juanying Xie, Qi Hou, Yinghuan Shi +6

The available butterfly data sets comprise a few limited species, and the images in the data sets are always standard patterns without the images of butterflies in their living env…

cs.IR2018★ 6 cited

Cross-domain novelty seeking trait mining for sequential recommendation

Fuzhen Zhuang, Yingmin Zhou, Fuzheng Zhang +3

Transfer learning has attracted a large amount of interest and research in last decades, and some efforts have been made to build more precise recommendation systems. Most previous…

cs.LG2018★ 21 cited

Policy Gradients for Contextual Recommendations

Feiyang Pan, Qingpeng Cai, Pingzhong Tang +2

Decision making is a challenging task in online recommender systems. The decision maker often needs to choose a contextual item at each step from a set of candidates. Contextual ba…

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