This course 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) ...

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

Dynamic programming algorithms are developed for optimal capital allocation subject to budget constraints. We extend the work of Weingartner [17] and Weingartner and Ness [19] by including multilevel ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

In this paper we develop a discretized version of the dynamic programming algorithm and study its convergence and stability properties. We show that the computed value function converges quadratically ...

Bio-inspired computational methods have gained popularity recently. These methods mimic the seemingly complex behavior of ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

With new DPX instructions, the NVIDIA Hopper GPU architecture introduced today at GTC will speed dynamic programming — a problem-solving approach utilized in algorithms for genomics, quantum computing ...