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 ...

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 ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

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 ...

This is a preview. Log in through your library . Abstract In an earlier paper [20] combinatorial programming procedures were presented for solving a class of integer programming problems in which all ...

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 ...

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 ...