Many sequential decision problems can be formulated as Markov decision processes (MDPs) where the optimal value function (or cost-to-go function) can be shown to satisfy a monotone structure in some ...

A natural optimization model that formulates many online resource allocation problems is the online linear programming (LP) problem in which the constraint matrix is revealed column by column along ...

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

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

Programming Systems & Software Engineering research at Drexel University's College of Computing & Informatics (CCI) focuses on improving the design, construction, and maintenance of software systems, ...

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 ...

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 ...

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 ...

DotNetExercises is a collection focused on programming techniques in C#/.NET/.NET Core, covering commonly used syntax, algorithms, techniques, middleware, libraries, and real-world case studies.