Learning Outcomes Describe basic algorithm design techniques. Create divide and conquer, dynamic programming, and greedy algorithms. Understand intractable problems, P vs NP and the use of integer ...

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

We propose a dynamic programming algorithm for the one-dimensional Fused Lasso Signal Approximator (FLSA). The proposed algorithm has a linear running time in the worst case. A similar approach is ...

View on Coursera Course Description This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving ...

Manuel S. Santos, , Analysis of a Numerical Dynamic Programming Algorithm Applied to Economic Models, Econometrica, Vol. 66, No. 2 (Mar., 1998), pp. 409-426 ...

CS 336 or Permission of Instructor Description This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...

Before BLAST, alignment programs used dynamic programming algorithms, such as the Needleman-Wunsch and Smith-Waterman algorithms, that required long processing times and the use of supercomputers ...