This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal ...

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) .

Computers don’t simply "understand" code in the way humans do. They rely on a highly sophisticated series of steps to ...

Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

Ever wondered how computers multiply huge numbers with hundreds or even thousands of digits? The process may seem simple, but it gets incredibly complex as numbers grow. In this video, we explore the ...

MG4C6.2 Mathematical Programming: Introduction to theory and the solution of linear and nonlinear programming problems: basic solutions and the simplex method, convex programming and KKT conditions, ...

Algorithms are turning up in the most unlikely places, promising to assert mathematical probability into corners of our lives where intuition, instinct and hunches have long held sway.

The algorithm presented here overcomes all of these shortcomings. Most significantly, it exhibits only a linear growth in the solution times based on the number of connections between nodes.

Dynamic Programming Algorithms in Computational Biology Publication Trend The graph below shows the total number of publications each year in Dynamic Programming Algorithms in Computational Biology.