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Xiwei Xu

49 papers hereh-index 449.1k citations208 works total

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

author position
  • first author2
  • middle author40
  • last author5

Across the 47 of 49 papers where every author was matched, so the position is known.

fields
  • cs.SE21
  • cs.CR8
  • cs.IR5
  • cs.LG4
  • cs.CY3
  • cs.HC2
same name
  • Xiwei Xu — 23 papers, h 11
  • Xiwei Xu — 13 papers, h 6
  • Xiwei Xu — 5 papers, h 2
  • Xiwei Xu — 4 papers
  • Xiwei Xu — 3 papers
  • Xiwei Xu — 2 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
20132026
most citedObject Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination?

143 citations · 358 across the 40 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2021★ 1 cited

Cycle-Balanced Representation Learning For Counterfactual Inference

Guanglin Zhou, Lina Yao, Xiwei Xu +2

With the widespread accumulation of observational data, researchers obtain a new direction to learn counterfactual effects in many domains (e.g., health care and computational adve…

cs.LG2021★ 15 cited

Blockchain-based Trustworthy Federated Learning Architecture

Sin Kit Lo, Yue Liu, Qinghua Lu +4

Federated learning is an emerging privacy-preserving AI technique where clients (i.e., organisations or devices) train models locally and formulate a global model based on the loca…

cs.LG2021★ 15 cited

Generating Informative CVE Description From ExploitDB Posts by Extractive Summarization

Jiamou Sun, Zhenchang Xing, Hao Guo +4

ExploitDB is one of the important public websites, which contributes a large number of vulnerabilities to official CVE database. Over 60\% of these vulnerabilities have high- or cr…

cs.LG2021

Architectural Patterns for the Design of Federated Learning Systems

Sin Kit Lo, Qinghua Lu, Liming Zhu +3

Federated learning has received fast-growing interests from academia and industry to tackle the challenges of data hungriness and privacy in machine learning. A federated learning…

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