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Heng Guo

35 papers hereh-index 201.1k citations76 works total

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

author position
  • first author14
  • middle author18
  • last author1

Across the 33 of 35 papers where every author was matched, so the position is known.

fields
  • cs.DS21
  • cs.CC11
  • math.PR2
  • cs.LG1
same name
  • Heng Guo — 14 papers, h 5
  • Heng Guo — 8 papers, h 3
  • Heng Guo — 7 papers, h 2
  • Heng Guo — 7 papers, h 2
  • Heng Guo — 6 papers, h 3
  • Heng Guo — 6 papers, h 4

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
20122026
most cited#BIS-Hardness for 2-Spin Systems on Bipartite Bounded Degree Graphs in the Tree Nonuniqueness Region

37 citations · 171 across the 30 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.DS2018★ 1 cited

Zeros of Holant problems: locations and algorithms

Heng Guo, Chao Liao, Pinyan Lu +1

We present fully polynomial-time (deterministic or randomised) approximation schemes for Holant problems, defined by a non-negative constraint function satisfying a generalised sec…

cs.DS2018★ 14 cited

Approximately counting bases of bicircular matroids

Heng Guo, Mark Jerrum

We give a fully polynomial-time randomised approximation scheme (FPRAS) for the number of bases in a bicircular matroids. This is a natural class of matroids for which counting bas…

cs.DS2018★ 3 cited

Tight bounds for popping algorithms

Heng Guo, Kun He

We sharpen run-time analysis for algorithms under the partial rejection sampling framework. Our method yields improved bounds for: the cluster-popping algorithm for approximating a…

math.PR2018★ 11 cited

Perfect simulation of the Hard Disks Model by Partial Rejection Sampling

Heng Guo, Mark Jerrum

We present a perfect simulation of the hard disks model via the partial rejection sampling method. Provided the density of disks is not too high, the method produces exact samples…

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