Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

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 ...

Computers can be used to help solve problems. However, before a problem can be tackled, it must first be understood. Computational thinking helps us to solve problems. Designing, creating and refining ...

Successive Linear Programming (SLP) algorithms solve nonlinear optimization problems via a sequence of linear programs. They have been widely used, particularly in the oil and chemical industries, ...

This course is available on the BSc in Business Mathematics and Statistics, BSc in Management, BSc in Mathematics and Economics, BSc in Mathematics with Economics and BSc in Mathematics, Statistics ...

There was a time when embedded system developers didn’t need to worry about graphics. When you have a PIC processor and two-line LCD, there isn’t much to learn. But if you are deploying Linux-based ...

As applied to mixed-integer programming, Benders' original work made two primary contributions: (1) development of a "pure integer" problem (Problem P) that is equivalent to the original mixed-integer ...

This course is available on the BSc in Business Mathematics and Statistics, BSc in Management, BSc in Mathematics and Economics, BSc in Mathematics with Economics, BSc in Mathematics, Statistics, and ...