Everything about Generic-case complexity

🧭 Start here: a 6-step reading path

1. Read the overview: Generic-case complexityA 5-minute orientation
2. Pick up a classic book: Complex litigation and the adversary systemThe most-reprinted book on the subject
3. Read the landmark paper: Generic-case complexity, decision problems in group theory, and random walksCited 119 times
4. Go sideways: Distribution learning theoryA closely related topic
5. Go sideways: Locally decodable codeA closely related topic

🏆 Landmark papers (most cited)

• Generic-case complexity, decision problems in group theory, and random walks

  Ilya Kapovich, Alexei Myasnikov, Paul Schupp · 2003 · Journal of Algebra · 119 citations

• Conjugacy in Baumslag’s Group, Generic Case Complexity, and Division in Power Circuits

  Volker Diekert, Alexei G. Myasnikov, Armin Weiß · 2016 · Algorithmica · 5 citations

• Generic Case Complexity and One-Way Functions

  Alex D. Myasnikov · 2009 · Groups – Complexity – Cryptology · 0 citations

• Generic case complexity of the Graph Isomorphism Problem

  Gennady A. Noskov, Alexander N. Rybalov · 2016 · Groups Complexity Cryptology · 0 citations

• Generic case completeness

  Alexei Miasnikov, Alexander Ushakov · 2016 · Journal of Computer and System Sciences · 0 citations

📚 Books worth reading

• Complex litigation and the adversary systemJay Tidmarsh, Roger H. Transrud · 1998
• 📕Hochschild Cohomology for AlgebrasSarah J. Witherspoon · 2019

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics

• Distribution learning theory The distributional learning theory or learning of probability distribution is a framework in computational learning theory. It has been proposed from Michael…
• Locally decodable code A locally decodable code (LDC) is an error-correcting code that allows a single bit of the original message to be decoded with high probability by only…
• Smoothed analysis In theoretical computer science, smoothed analysis is a way of measuring the complexity of an algorithm. Since its introduction in 2001, smoothed analysis…
• Barron space In functional analysis, the Barron space is a function space. It is a Banach space. It originated from the study of universal approximation properties…
• Exponential polynomial In mathematics, exponential polynomials are functions on fields, rings, or abelian groups that take the form of polynomials in a variable and an exponential…
• Approximation algorithm In computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems…
• AKS primality test The Agrawal–Kayal–Saxena primality test (also known as the AKS primality test and the cyclotomic AKS test) is a deterministic primality-proving algorithm…
• Exponential tilting Exponential tilting (ET), exponential twisting, or exponential change of measure (ECM) is a distribution-shifting technique used in many parts of mathematics…