Optimisation algorithms in Statistics I, 4 credits

Submitted by Frank Miller on May 24, 2020 - 16:57

We will discuss algorithms to compute minima or maxima which are frequently needed in statistics and machine learning. Topics of lectures on four occasions: gradient based algorithms, stochastic gradient based algorithms, gradient free algorithms (e.g. particle swarm optimisation), handling of restrictions during optimisation. Course homepage: http://www.adoptdesign.de/optimisation1.html

The course is intended for Ph.D. students from Statistics or a related field (e.g. Mathematical Statistics, Engineering Science, Quantitative Finance, Computer Science).

Lecturer: Frank Miller, Dept. of Statistics, Stockholm University. Questions or course registration can be sent to frank.miller@stat.su.se. 

Course Data
Type of schedule: 
Travel friendly schedule
University: 
Stockholm
Level: 
PhD
Credits (ECTS): 
4.00
Offered: 
2020:2