dogear

enter for all results · esc to close

Demaine, Gasarch & Hajiaghayi. Computers and Intractability: A Guide to Algorithmic Lower Bounds

hardness.mit.edusite

A sequel to Garey and Johnson's Computers and Intractability: A Guide to NP-Completeness. New topics include Parameterized Complexity, Lower bounds on approximation, Other hardness assumptions (ETH, 3SUM-conjecture, APSP-conjecture, UGC, Others), Online Algorithms, Streaming…

from
Theoretical Computer Science
added
2026-10-10
likes
0

similar

  1. Demaine. Algorithmic Lower Bounds: Fun with Hardness Proofs ocw.mit.edu

    A class taking a practical approach to proving problems can't be solved efficient.

  2. Goldreich. P, NP, and NP-Completeness: The Basics of Computational Complexity wisdom.weizmann.ac.il

    A very gentle introduction to some fundamental ideas of computational complexity like NP-completeness and P vs NP.

  3. Rudich & Wigderson. Computational Complexity Theory ams.org

    Three weeks of lectures from the IAS/Park City Mathematics Institute Summer School on computational complexity. Topics include reductions, lower-bounds, average-case complexity, randomness, interactive proof systems, probabilistically checkable proofs, quantum computing, and…

  4. Copeland, Posy & Shagrir (editors). Computability: Turing, Gödel, Church, and Beyond mitpress.mit.edu

    Computer scientists, mathematicians, and philosophers discuss the conceptual foundations of the notion of computability as well as recent theoretical developments.

  5. Papadimitriou. Computational Complexity pearson.com

    Body of knowledge for studying the performance and limitations of computer algorithms. Among topics covered are: reductions and NP-completeness, cryptography and protocols, randomized algorithms, and approximability of optimization problems, circuit complexity, the structural…

  6. Arora. Overcoming Intractability in Machine Learning cs.princeton.edu

    A seminar course that will focus on the following phenomenon: many problems in machine learning are formally intractable (e.g., NP-hard). Nevertheless they are solved in practice by heuristics. Can we design algorithms with provable guarantees (running time, solution quality)?

Theoretical Computer Science › Lower Bounds > Books: “A sequel to Garey and Johnson's Computers and Intractability: A Guide to NP-Completeness. New topics include Parameterized Complexity, Lower bounds on approximation, Other hardness assumptions (ETH, 3SUM-conjecture, APSP-conjecture, UGC, Others), Online Algorithms, Streaming…”