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researcher

Huan Liu

Arizona State University

42 papers hereh-index 10747.3k citations588 works total

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

author position
  • first author3
  • middle author7
  • last author32

Across the 42 of 42 papers where every author was matched, so the position is known.

fields
  • cs.SI20
  • cs.CL8
  • cs.LG4
  • cs.CR3
  • cond-mat.soft1
  • cs.AI1
affiliations
  • Arizona State University
Homepage
same name
  • Huan Liu — 46 papers, h 54
  • Huan Liu — 17 papers, h 14
  • Huan Liu — 17 papers, h 11
  • Huan Liu — 17 papers, h 6
  • Huan Liu — 15 papers, h 13
  • Huan Liu — 12 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
20152023
most citedNeuroRule: A Connectionist Approach to Data Mining

107 citations · 286 across the 29 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2019

A Novel Trend Symbolic Aggregate Approximation for Time Series

Yufeng Yu, Yuelong Zhu, Dingsheng Wan +2

Symbolic Aggregate approximation (SAX) is a classical symbolic approach in many time series data mining applications. However, SAX only reflects the segment mean value feature and…

cs.LG2018

Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects

Vineeth Rakesh, Ruocheng Guo, Raha Moraffah +2

Modeling spillover effects from observational data is an important problem in economics, business, and other fields of research. % It helps us infer the causality between two seemi…

cs.LG2017★ 107 cited

NeuroRule: A Connectionist Approach to Data Mining

Hongjun Lu, Rudy Setiono, Huan Liu

Classification, which involves finding rules that partition a given data set into disjoint groups, is one class of data mining problems. Approaches proposed so far for mining class…

cs.LG2016★ 1 cited

Challenges of Feature Selection for Big Data Analytics

Jundong Li, Huan Liu

We are surrounded by huge amounts of large-scale high dimensional data. It is desirable to reduce the dimensionality of data for many learning tasks due to the curse of dimensional…

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