Book contents
- Frontmatter
- Contents
- Preface
- List of Contributors
- 1 Introduction
- Part One Refinements of Worst-Case Analysis
- Part Two Deterministic Models of Data
- 5 Perturbation Resilience
- 6 Approximation Stability and Proxy Objectives
- 7 Sparse Recovery
- Part Three Semirandom Models
- Part Four Smoothed Analysis
- Part Five Applications in Machine Learning and Statistics
- Part Six Further Applications
- Index
5 - Perturbation Resilience
from Part Two - Deterministic Models of Data
Published online by Cambridge University Press: 17 December 2020
Edited by
Book contents
- Frontmatter
- Contents
- Preface
- List of Contributors
- 1 Introduction
- Part One Refinements of Worst-Case Analysis
- Part Two Deterministic Models of Data
- 5 Perturbation Resilience
- 6 Approximation Stability and Proxy Objectives
- 7 Sparse Recovery
- Part Three Semirandom Models
- Part Four Smoothed Analysis
- Part Five Applications in Machine Learning and Statistics
- Part Six Further Applications
- Index
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- Beyond the Worst-Case Analysis of Algorithms , pp. 95 - 119Publisher: Cambridge University PressPrint publication year: 2021
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- Cited by