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Codeforces (Russian: Коудфорсес) is a website that hosts competitive programming contests. [1] It is maintained by a group of competitive programmers from ITMO University led by Mikhail Mirzayanov. [2] Since 2013, Codeforces claims to surpass Topcoder in terms of active contestants. [3] As of 2019, it has over 600,000 registered users ...
Codeforces peak rating 4009 (30 August 2024) Gennady Korotkevich ( Belarusian : Генадзь Караткевіч , Hienadź Karatkievič , Russian : Геннадий Короткевич ; born 25 September 1994) is a Belarusian competitive sport programmer who has won major international competitions since the age of 11, as well as numerous ...
Every solution submitted by a contestant is run on the judge against a set of (usually secret) test cases. Normally, contest problems have an all-or-none marking system, meaning that a solution is "Accepted" only if it produces satisfactory results on all test cases run by the judge, and is rejected otherwise.
However, a dynamic programming solution can readily be formed using the following approach: [1] Consider an optimal solution containing activity k. We now have non-overlapping activities on the left and right of k. We can recursively find solutions for these two sets because of optimal sub-structure. As we don't know k, we can try each of the ...
HackerRank was founded as InterviewStreet Inc. by two NIT Trichy alumni, Vivek Ravisankar and Hari Karunanidhi. [5] [6] HackerRank is a Y Combinator-backed company, and was the first Indian company accepted into Y Combinator. [1]
The coin of the highest value, less than the remaining change owed, is the local optimum. (In general, the change-making problem requires dynamic programming to find an optimal solution; however, most currency systems are special cases where the greedy strategy does find an optimal solution.)
The beam width bounds the memory required to perform the search. Since a goal state could potentially be pruned, beam search sacrifices completeness (the guarantee that an algorithm will terminate with a solution, if one exists). Beam search is not optimal (that is, there is no guarantee that it will find the best solution).
The approximation ratio is defined as the ratio of the computed solution length to the optimal length for a worst-case instance, one that maximizes this ratio. Because the NP-hardness reduction for the k-minimum spanning tree problem preserves the weight of all solutions, it also preserves the hardness of approximation of the problem.