A variant of the multi-armed bandit problem was recently introduced by Dimitriu, Tetali and Winkler. For this model (and a mild generalization) we propose faster algorithms to compute the Gittins index. The indexability of such models follows from earlier work of Nash on generalized bandits.

Closing long-stay psychiatric beds remains contentious. The review by Winkler et al in this issue examines 23 studies of deinstitutionalisation for the outcomes of people discharged from psychiatric hospitals after an admission of 1 year or longer. The majority of these studies identified no cases of homelessness, incarceration or suicide after discharge from hospital.

This paper presents an alternative method to measuring word-word semantic relatedness in distributional semantics framework. The main idea is to represent target words as rankings of all co-occurring words in a text corpus, ordered by their tf – idf weight and use a metric between rankings (such as Jaro distance or Rank distance) to compute semantic relatedness. This method has several advantag...

A number of tricky problems in probability are discussed, having in common one or more infinite sequences of coin tosses, and a representation as a problem in dependent percolation. Three of these problems are of ‘Winkler’ type, that is, they are challenges for a clairvoyant demon.

A number of tricky problems in probability are discussed, having in common one or more infinite sequences of coin tosses, and a representation as a problem in dependent percolation. Three of these problems are of ‘Winkler’ type, that is, they ask about what can be achieved by a clairvoyant demon.

We compare variations of string comparators based on the Jaro-Winkler comparator and edit distance comparator. We apply the comparators to Census data to see which are better classifiers for matches and nonmatches, first by comparing their classification abilities using a ROC curve based analysis, then by considering a direct comparison between two candidate comparators in record linkage results.