Dynamic programming is a method of solving problems that have two main characteristics: optimal substructure and overlapping subproblems. Optimal substructure means that the optimal solution of a ...

Dynamic programming and greedy algorithms are two powerful techniques that can help you solve complex coding problems efficiently. In this article, you will learn what they are, how they differ ...

One of the most important properties of distributed computing systems (e.g., Apache Spark, Apache Hadoop, etc) on clusters and computation clouds is the ability to scale out by adding more compute ...

This article proposes efficient parallel methods for an important class of dynamic programming problems that includes Viterbi, Needleman-Wunsch, Smith-Waterman, and Longest Common Subsequence. In ...

A broad class of efficient discrete Fourier transform algorithms is developed by partitioning short DFT algorithms into factors. The factored short DFT's are combined into longer DFT's using ...

Create divide and conquer, dynamic programming, and greedy algorithms. Understand intractable problems, P vs NP and the use of integer programming solvers to tackle some of these problems. Course ...

Graph algorithms are extremely important for programmers working on complex data structures. This includes breadth-first search, dynamic programming techniques, and the Floyd-Warshall algorithm. These ...

Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...