Abstract The significant overhead related to frequent location updates from moving objects often results in poor performance. As most of the location updates do not affect the quer...
K is an executable semantic framework in which programming languages, calculi, as well as type systems or formal analysis tools can be defined making use of configurations, comput...
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Methods based on 1-relaxation, such as basis pursuit and the Lasso, are very popular for sparse regression in high dimensions. The conditions for success of these methods are now ...
We study losses for binary classification and class probability estimation and extend the understanding of them from margin losses to general composite losses which are the compos...