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Wenzheng Li

8 papers hereh-index 11375 citations18 works total

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

author position
  • first author3
  • middle author5

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.GT4
  • cs.DC3
  • cs.DS1
same name
  • Wenzheng Li — 1 paper, h 1
  • Wenzheng Li — 1 paper, h 3
  • Wenzheng Li — 1 paper, h 4
  • Wenzheng Li — 1 paper, h 5

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
20172023
most citedDistributed Edge Coloring with Small Palettes and a Special Case of the Constructive Lovász Local Lemma

26 citations · 35 across the 7 of their papers we have counts for

collaborators
Showing cs.GTShow all

4 papers · 1 filter

cs.GT2023★ 2 cited

A constant factor approximation for Nash social welfare with subadditive valuations

Shahar Dobzinski, Wenzheng Li, Aviad Rubinstein +1

We present a constant-factor approximation algorithm for the Nash social welfare maximization problem with subadditive valuations accessible via demand queries. More generally, we…

cs.GT2022

Approximating Nash Social Welfare by Matching and Local Search

Jugal Garg, Edin Husić, Wenzheng Li +2

For any ε>0, we give a simple, deterministic (4+ε)-approximation algorithm for the Nash social welfare (NSW) problem under submodular valuations. We also co…

cs.GT2021★ 4 cited

A constant-factor approximation algorithm for Nash Social Welfare with submodular valuations

Wenzheng Li, Jan Vondrák

We present a 380-approximation algorithm for the Nash Social Welfare problem with submodular valuations. Our algorithm builds on and extends a recent constant-factor approximatio…

cs.GT2021★ 1 cited

Estimating the Nash Social Welfare for coverage and other submodular valuations

Wenzheng Li, Jan Vondrak

We study the Nash Social Welfare problem: Given n agents with valuation functions vi​:2[m]→R, partition [m] into S1​,…,Sn​ so as to maximize $…

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