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Ting Li

4 papers hereh-index 7250 citations13 works total

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.SI2
  • stat.ML2
same name
  • Ting Li — 10 papers, h 15
  • Ting Li — 7 papers, h 23
  • Ting Li — 5 papers
  • Ting Li — 4 papers, h 4
  • Ting Li — 2 papers
  • Ting Li — 1 paper, 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
20172020
most citedCommunity Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition

3 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

cs.SI2020★ 3 cited

Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition

Bing-Yi Jing, Ting Li, Zhongyuan Lyu +1

We study the problem of community detection in multi-layer networks, where pairs of nodes can be related in multiple modalities. We introduce a general framework, i.e., mixture mul…

cs.SI2019

Measuring the Clustering Strength of a Network via the Normalized Clustering Coefficient

Ting Li, Xianshi Yu, Bing-Yi Jing

In this paper, we propose a novel statistic of networks, the normalized clustering coefficient, which is a modified version of the clustering coefficient that is robust to network…

stat.ML2019

Semi-supervised learning in unbalanced and heterogeneous networks

Ting Li, Ningchen Ying, Xianshi Yu +1

Community detection was a hot topic on network analysis, where the main aim is to perform unsupervised learning or clustering in networks. Recently, semi-supervised learning has re…

stat.ML2017★ 2 cited

Adaptive Scaling

Ting Li, Bingyi Jing, Ningchen Ying +1

Preprocessing data is an important step before any data analysis. In this paper, we focus on one particular aspect, namely scaling or normalization. We analyze various scaling meth…

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