Lecturers:
Ayalvadi Ganesh (a.ganesh@bristol.ac.uk) and Vladislav Tadic (v.b.tadic@bristol.ac.uk)
Office hours (second half of unit): Thursday 11am-1pm, Fry Bldg, Room 1.40.
Texts (second half of unit):
Lecture notes will be provided. In addition, the following texts are recommended:
· S. Bubeck and N. Cesa-Bianchi, Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems, Foundations and Trends in Machine Learning, 2012.
· T. Lattimore and C. Szepesvari, Bandit Algorithms, Cambridge University Press.
Homework policy: Homework is an important part of learning the material on this course and you are strongly encouraged to attempt all the homework problems. You may discuss the problems, but you should write out the solutions on your own.
You will have two items of assessed coursework, which will each count for 10% of the final mark.
Lecture videos
Lectures will be in-person. In addition, you can find recorded video lectures here covering the second half of the unit. These may not map 1-1 onto the in-person lectures.
Lecture notes
Homework problems
Problem Sheet 1 Due Fri, 17 Nov Solutions
Problem Sheet 2 Due Wed, 29 Nov Solutions
Problem Sheet 3 Due
Mon, 11 Dec Solutions