Algorithms for Uncertain Environments: Going Beyond the Worst-Case (Invited Talk)

Author Anupam Gupta



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Author Details

Anupam Gupta
  • Carnegie Mellon University, Pittsburgh, PA, USA

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Anupam Gupta. Algorithms for Uncertain Environments: Going Beyond the Worst-Case (Invited Talk). In 42nd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 250, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.FSTTCS.2022.1

Abstract

Analyzing the performance of algorithms in both the worst case and the average case are cornerstones of computer science: these are two different ways to understand how well algorithms perform. Over the past two decades, there has been a concerted effort to understand the performance of algorithms in models that go beyond these two extremes. In this talk I will discuss some of the proposed models and approaches, particularly for problems related to online algorithms, where decisions must be made sequentially without knowing future portions of the input.

Subject Classification

ACM Subject Classification
  • Theory of computation → Online algorithms
Keywords
  • Optimization under Uncertainty
  • Online Algorithms
  • Beyond Worst Case Analysis

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