The objective of this work is to interpret inductive results obtained by the unsupervised learning method OSHAM. We briefly introduce the learning process of OSHAM, that extracts ...
Electronic submission to a conference is a process that is known to evolve nonlinearly in time, with a dramatic increase when approaching the deadline. A model has recently been pr...
We present an EM-algorithm for the problem of learning preferences with Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data ...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Entering search terms on mobile phones is a time consuming and cumbersome task. In this paper, we explore the usage patterns of query entry interfaces that display suggestions. Ou...