where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

Ever since the turn of the century, the technological landscape associated with every industry has been ever-evolving. There are a wide variety of engineering disciplines which have surfaced and are ...

Global optimisation stands as a pivotal discipline in applied mathematics and engineering, providing robust methodologies for determining the absolute best solution among myriad local optima. Recent ...

Modern optimization theory, algorithms, and applications in process engineering. Topics include the fundamentals of linear programming, integer programming, nonlinear programming, mixed-integer ...

Computer-aided simulation and optimisation methods offer comprehensive possibilities for analysing and improving thermoelectric generators (TEG). Our technical expertise and access to extensive ...