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Longfei Li

20 papers hereh-index 191.7k citations72 works total

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

author position
  • first author2
  • middle author14
  • last author3

Across the 19 of 20 papers where every author was matched, so the position is known.

fields
  • cs.LG11
  • cs.IR7
  • stat.ME1
  • stat.ML1
same name
  • Longfei Li — 7 papers, h 9
  • Longfei Li — 6 papers, h 3
  • Longfei Li — 5 papers, h 10
  • Longfei Li — 3 papers, h 3
  • Longfei Li — 2 papers, h 6
  • Longfei Li — 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
20182025
most citedGeniePath: Graph Neural Networks with Adaptive Receptive Paths

47 citations · 154 across the 20 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.LG2018★ 1 cited

Distributed Collaborative Hashing and Its Applications in Ant Financial

Chaochao Chen, Ziqi Liu, Peilin Zhao +3

Collaborative filtering, especially latent factor model, has been popularly used in personalized recommendation. Latent factor model aims to learn user and item latent factors from…

cs.LG2018★ 19 cited

Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud

Ya-Lin Zhang, Jun Zhou, Wenhao Zheng +10

Internet companies are facing the need for handling large-scale machine learning applications on a daily basis and distributed implementation of machine learning algorithms which c…

cs.LG2018

A Boosting Framework of Factorization Machine

Longfei Li, Peilin Zhao, Jun Zhou +1

Recently, Factorization Machines (FM) has become more and more popular for recommendation systems, due to its effectiveness in finding informative interactions between features. Us…

cs.LG2018★ 47 cited

GeniePath: Graph Neural Networks with Adaptive Receptive Paths

Ziqi Liu, Chaochao Chen, Longfei Li +4

We present, GeniePath, a scalable approach for learning adaptive receptive fields of neural networks defined on permutation invariant graph data. In GeniePath, we propose an adapti…

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