Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. We approach this setting from a case-based perspective and propo...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
— Hybrid deliberative-reactive control architectures are a popular and effective approach to the control of robotic navigation applications. However, the design of said architect...
Power dissipation has become one of the most critical factors for the continued development of both high-end and low-end computer systems. The successful design and evaluation of ...
Sudhanva Gurumurthi, Anand Sivasubramaniam, Mary J...
Indicators help actors to organise, orientate and navigate through complex environments by providing contextual information relevant for the performance of learning tasks. In this ...