Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
We show how models for prediction with expert advice can be defined concisely and clearly using hidden Markov models (HMMs); standard HMM algorithms can then be used to efficientl...
Today, systems should react based on explicit demands from the learner or even proactively react based on changes in the working environment. The success of this type of systems de...
Autonomics or self-reorganization becomes pertinent for websites serving a large number of users with highly varying workloads. An important component of self-adaptation is to mod...
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...