This methodological note focuses on the edge density of real world examples of networks. The edge density is a parameter of interest typically when putting up user studies in an e...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
We study the properties of the Minimum Description Length principle for sequence prediction, considering a two-part MDL estimator which is chosen from a countable class of models....
Given a bipartite graph of collaborative ratings, the task of recommendation and rating prediction can be modeled with graph kernels. We interpret these graph kernels as the inver...
Stochastic local search algorithms can now successfully solve MAXSAT problems with thousands of variables or more. A key to this success is how effectively the search can navigate...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...