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researcher

Jun He

24 papers hereh-index 263k citations121 works total

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

author position
  • sole author1
  • first author12
  • middle author4
  • last author7

Across the 24 of 24 papers where every author was matched, so the position is known.

fields
  • cs.NE21
  • cs.AI1
  • cs.DS1
  • math.OC1
same name
  • Jun He — 89 papers, h 26
  • Jun He — 40 papers, h 30
  • Jun He — 20 papers
  • Jun He — 18 papers, h 22
  • Jun He — 14 papers, h 7
  • Jun He — 11 papers, h 6

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
20112021
most citedAverage Convergence Rate of Evolutionary Algorithms

95 citations · 308 across the 24 of their papers we have counts for

collaborators
Showing 2013 · cs.NEShow all

4 papers · 2 filters

cs.NE2013

Average Drift Analysis and Population Scalability

Jun He, Xin Yao

This paper aims to study how the population size affects the computation time of evolutionary algorithms in a rigorous way. The computation time of an evolutionary algorithm can be…

cs.NE2013

Geiringer Theorems: From Population Genetics to Computational Intelligence, Memory Evolutive Systems and Hebbian Learning

Boris Mitavskiy, Elio Tuci, Chris Cannings +2

The classical Geiringer theorem addresses the limiting frequency of occurrence of various alleles after repeated application of crossover. It has been adopted to the setting of evo…

cs.NE2013

Combining Drift Analysis and Generalized Schema Theory to Design Efficient Hybrid and/or Mixed Strategy EAs

Boris Mitavskiy, Jun He

Hybrid and mixed strategy EAs have become rather popular for tackling various complex and NP-hard optimization problems. While empirical evidence suggests that such algorithms are…

cs.NE2013★ 11 cited

Mixed Strategy May Outperform Pure Strategy: An Initial Study

Jun He, Wei Hou, Hongbin Dong +1

In pure strategy meta-heuristics, only one search strategy is applied for all time. In mixed strategy meta-heuristics, each time one search strategy is chosen from a strategy pool…

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