We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
Abstract Intelligent calendar assistants have many years ago attracted researchers from the areas of scheduling, machine learning and human computer interaction. However, all effor...
There are today several systems for predicting transmembrane domains in membrane protein sequences. As they are based on different classifiers as well as different pre- and post-p...
Abstract. Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to ...