Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
This paper describes an original method for evaluating peer review in online systems by calculating the helpfulness of an individual reviewer's response. We focus on the deve...
William Hart-Davidson, Michael McLeod, Christopher...
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
In this paper, we consider online prediction from expert advice in a situation where each expert observes its own loss at each time while the loss cannot be disclosed to others fo...
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...