Approximation algorithms
Efficient algorithms with guarantees on how close their answers are to an optimum.
7 problemsMethods for efficient computation and organizing information.
Efficient algorithms with guarantees on how close their answers are to an optimum.
7 problemsAlgorithms, computational limits and the guarantees behind decisions.
49 problemsGraph structure, approximation, counting and coordination across a network.
11 problemsRearranging bases, choosing distinct symbols and listing minimal hitting sets.
4 problemsTwo graphs can look different because their vertices have different names. Can we always decide efficiently whether they have the same connections?
Multiplying two square matrices seems to require more work than writing their answer. Is the best possible asymptotic exponent actually two?
77 = 7 × 11 is easy to check. Can a classical computer find the complete prime factorization of every integer efficiently as its written length grows?
Can exact shortest-path distances between every pair of vertices in a general weighted graph be computed in truly subcubic time?
A splay tree reorganizes itself after searches. Is its total cost always within a constant factor of the best search tree that knows all requests in advance?
Can finding three integers with a specified additive relation be done faster than essentially quadratic time?