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researcher

Jian Liu

7 papers hereh-index 9426 citations29 works total

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

author position
  • first author1
  • middle author5

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.LG2
  • math.GR1
same name
  • Jian Liu — 57 papers, h 28
  • Jian Liu — 31 papers, h 19
  • Jian Liu — 16 papers, h 10
  • Jian Liu — 15 papers, h 6
  • Jian Liu — 13 papers, h 4
  • Jian Liu — 12 papers, h 27

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
20202026
most citedFederBoost: Private Federated Learning for GBDT

41 citations · 52 across the 6 of their papers we have counts for

collaborators
Showing cs.CRShow all

4 papers · 1 filter

cs.CR2023★ 4 cited

False Claims against Model Ownership Resolution

Jian Liu, Rui Zhang, Sebastian Szyller +2

Deep neural network (DNN) models are valuable intellectual property of model owners, constituting a competitive advantage. Therefore, it is crucial to develop techniques to protect…

cs.CR2022★ 2 cited

Private Data Valuation and Fair Payment in Data Marketplaces

Zhihua Tian, Jian Liu, Jingyu Li +5

Data valuation is an essential task in a data marketplace. It aims at fairly compensating data owners for their contribution. There is increasing recognition in the machine learnin…

cs.CR2021★ 2 cited

"Adversarial Examples" for Proof-of-Learning

Rui Zhang, Jian Liu, Yuan Ding +3

In S&P '21, Jia et al. proposed a new concept/mechanism named proof-of-learning (PoL), which allows a prover to demonstrate ownership of a machine learning model by proving integri…

cs.CR2020★ 41 cited

FederBoost: Private Federated Learning for GBDT

Zhihua Tian, Rui Zhang, Xiaoyang Hou +4

Federated Learning (FL) has been an emerging trend in machine learning and artificial intelligence. It allows multiple participants to collaboratively train a better global model a…

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