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This paper is concerned with the question of how to online combine an ensemble of active learners so as to expedite the learning progress during a pool-based active learning session. We develop a powerful active learning master algorithm, based a known competitive algorithm for the multi-armed bandit problem and a novel semi-supervised performance(More)
The identification and modeling of dynamical systems in a practical situation, where the model set under consideration does not necessarily include the observed system, are treated. A measure of the relevant information in a sequence of observations is shown to possess useful properties, such as the metric property on the parameter set. It is then shown(More)
OBJECTIVES   To study the effects of gait training with visual and auditory feedback cues on the walking abilities of patients with gait disorders due to cerebral palsy. MATERIALS AND METHODS   Visual and auditory feedback cues were generated by a wearable device, driven by inertial sensors. Ten randomly selected patients with gait disorders due to(More)
An estimate of the probability density function of a random vector is obtained by maximizing the output entropy of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's optimization method, applied to the estimated(More)
OBJECTIVE To study the use of auditory feedback for gait management and rehabilitation in patients with Multiple Sclerosis (MS). METHODS An auditory feedback cue, responding to the patient's own steps in closed-loop, was produced by a wearable motion sensor and delivered to the patient through ear phones. On-line (device on) and residual short-term(More)
OBJECTIVE To study the effects of visual cues, provided through a portable visual-feedback virtual reality (VR) apparatus, on the walking abilities of patients with multiple sclerosis (MS). METHODS On-line (display-on) and residual short-term therapeutic effects on walking speed and stride length were measured in 16 randomly selected patients with gait(More)
We present a neural network employing Hebbian storage and sparse internal coding, which is capable of memorizing and correcting sequences of binary vectors by association. A ternary version of the Kanerva memory, folded into a feedback configuration, is shown to perform the basic sequence memorization and regeneration function. The inclusion of lateral(More)