The travelling salesman problem (TSP) remains one of the most challenging NP‐hard problems in combinatorial optimisation, with significant implications for logistics, network design and route planning ...

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...

Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on ...

The stochastic root-finding problem is that of finding a zero of a vector-valued function known only through a stochastic simulation. The simulation-optimization problem is that of locating a ...

Nash equilibria represent a cornerstone in game theory, defining strategy profiles wherein no player can benefit by unilaterally deviating. This concept underpins a myriad of applications, ranging ...

In this paper we introduce two general techniques for the design and analysis of approximation algorithms for NP-hard scheduling problems in which the objective is to minimize the weighted sum of the ...

Not long ago, a team of researchers from Stanford and McGill universities broke a 35-year record in computer science by an almost imperceptible margin — four hundredths of a trillionth of a trillionth ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

The Foundations of Data Structures and Algorithms specialization includes two optional preparation courses and a three-course pathway to earn admission to the Online MS in Computer Science. You must ...