Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and hel...
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...