APPROX 2022

Important dates

  • Submissions: May 4, 2022, 18:00 EST
  • Notifications: June 24, 2022
  • Camera ready: July 15, 2022

Scope

APPROX focuses on algorithmic and complexity theoretic issues relevant to the development of efficient approximate solutions to computationally difficult problems. Papers are solicited in all research areas related to approximation, including but not limited to:

  • approximation algorithms
  • hardness of approximation
  • small space, sub-linear time and streaming algorithms
  • online algorithms
  • approaches that go beyond worst-case analysis
  • distributed and parallel approximation
  • embeddings and metric space methods
  • mathematical programming methods
  • spectral methods
  • combinatorial optimization
  • algorithmic game theory, mechanism design and economics
  • computational geometric problems
  • approximate learning

Program Committee

  • Nikhil Bansal, University of Michigan
  • Deeparnab Chakrabarty, Dartmouth College
  • Parinya Chalermsook, Aalto University
  • Karthekeyan Chandrasekaran, UIUC
  • Moses Charikar, Stanford University
  • Zachary Friggstad, University of Alberta
  • Sungjin Im, UC, Merced
  • Thomas Kesselheim, University of Bonn
  • Ravishankar Krishnaswamy, Microsoft Research India
  • Pasin Manurangsi, Google Research
  • Neil Olver, London School of Economics and Political Science
  • Chaitanya Swamy (PC chair), University of Waterloo
  • Vera Traub, ETH Zurich
  • Seeun William Umboh, The University of Sydney
  • Jan Vondrák, Stanford University
  • Rico Zenklusen, ETH Zurich

Local Organisation

Karthekeyan Chandrasekaran, UIUC