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Pan Peng

28 papers hereh-index 14450 citations41 works total

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

author position
  • sole author1
  • first author6
  • middle author7
  • last author14

Across the 28 of 28 papers where every author was matched, so the position is known.

fields
  • cs.DS22
  • cs.LG2
  • quant-ph2
  • cs.LO1
  • math.PR1
same name
  • Pan Peng — 9 papers, h 5
  • Pan Peng — 6 papers, h 4
  • Pan Peng — 6 papers, h 2
  • Pan Peng — 5 papers, h 2
  • Pan Peng — 3 papers, h 1
  • Pan Peng — 2 papers, h 1

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
20112026
most citedTestable Bounded Degree Graph Properties Are Random Order Streamable

8 citations · 24 across the 23 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.DS2017★ 6 cited

The Power of Vertex Sparsifiers in Dynamic Graph Algorithms

Gramoz Goranci, Monika Henzinger, Pan Peng

We introduce a new algorithmic framework for designing dynamic graph algorithms in minor-free graphs, by exploiting the structure of such graphs and a tool called vertex sparsifica…

cs.DS2017

Estimating Graph Parameters from Random Order Streams

Pan Peng, Christian Sohler

We develop a new algorithmic technique that allows to transfer some constant time approximation algorithms for general graphs into random order streaming algorithms. We illustrate…

cs.DS2017★ 8 cited

Testable Bounded Degree Graph Properties Are Random Order Streamable

Morteza Monemizadeh, S. Muthukrishnan, Pan Peng +1

We study which property testing and sublinear time algorithms can be transformed into graph streaming algorithms for random order streams. Our main result is that for bounded degre…

cs.DS2017★ 6 cited

Improved Guarantees for Vertex Sparsification in Planar Graphs

Gramoz Goranci, Monika Henzinger, Pan Peng

Graph Sparsification aims at compressing large graphs into smaller ones while preserving important characteristics of the input graph. In this work we study Vertex Sparsifiers, i.e…

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