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IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...
It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .
Richard M. Karp, Michael Held, Finite-State Processes and Dynamic Programming, SIAM Journal on Applied Mathematics, Vol. 15, No. 3 (May, 1967), pp. 693-718 ...
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