dynamic programming, network flows, reductions, and randomized algorithms. Important themes that will be developed in the course include the algorithmic abstraction-design-analysis process and ...

Algorithm design strategies such as divide and conquer. Elementary techniques for analysis; asymptotic analysis ... and in previous courses to solve a number of logically complex programming problems ...

Programming Background: The course involves solving programming assignments in Python. You must be comfortable with Python programming. This includes basic control structures in Python: conditional ...

including time and space complexity, sorting algorithms, recurrence relations, divide and conquer algorithms, greedy algorithms, dynamic programming, linear programming, graph algorithms, problems in ...

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 ...

The course includes models of computation, programming language paradigms, programming language design, algorithm analysis, processes, threads, synchronisation and parallel programming. The fourth ...

Mäkinen has focused on extending sequence analysis to different pan-genome representations such as directed acyclic graphs. Frequently used techniques include dynamic ... algorithms, Veli Mäkinen ...