Both teaching and learning multithreaded ing are complex tasks, due to the abstraction of the concepts, the non-determinism of the scheduler, the impossibility of using classical s...
Giovanni Malnati, Caterina Maria Cuva, Claudia Bar...
Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution ...
An “active learning system” will sequentially decide which unlabeled instance to label, with the goal of efficiently gathering the information necessary to produce a good cla...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Brain-Computer Interfaces can suffer from a large variance of the subject conditions within and across sessions. For example vigilance fluctuations in the individual, variable ta...
Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomiok...