We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic convex optimization procedure of which we establish convergence guarantees. The overall learning procedure has the nice properties that a) the learned conical combination is automatically designed to perform the regres...

OBJECTIVE To define the learning curve of robot-assisted laparoscopic surgery for prostatectomy (RALP) and upper tract procedures, and show the differences between the classical approach to training and the new concept of parallel learning. METHODS This mini-review is based on the results of a Medline search using the keywords 'da Vinci', 'robot-assisted laparoscopic surgery', 'training', 'te...

Much natural learning occurs by observation without explicit feedback or tutaring, yet few models of learning address this class of tasks. Further, many natural cases of observational learning are complex, ond efficient learning seems to demand strategic learning procedures. The present work adopts o design perspective and asks what learning mechanisms would be both useful and feasible for natu...

Supervised learning is conventionally performed with pairwise input-output labeled data. After the training procedure, the adaptive system's weights are fixed while the testing procedure with unlabeled data is performed. Recently, in an attempt to improve classification performance unlabeled data has been exploited in the machine learning community. In this paper, we present an information theo...

We describe a PAC algorithm for learning linear threshold functions when some fraction of the examples used for learning are generated and labeled by an omniscient malicious adversary. The algorithm has complexity bounds similar to the classical Perceptron algorithm but can tolerate a substantially higher level of malicious noise than Perceptron and thus may be of signiicant practical interest....

Modal verbs in English are challenging to learn by speakers of other languages. The purpose of thiswas to shed light on the use of gesture in learning English modal verbs by Persian-speaking children.To achieve this, 60 elementary Iranian learners, studying at some institutes in Karaj took part in thisstudy. The participants were randomly put into one experimental group and one control group. T...

This paper reports a study investigating the degree of dissociation between performance shown by children with or without Down’s syndrome (DS), matched on non-verbal MA-level, following an implicit or explicit learning procedure. Taskspecific factors were tightly controlled using the same task for both modes of learning. The implicit learning task was based on the manipulation of a graphic prod...

Detecting changes in data-streams is an important part of enhancing learning quality in dynamic environments. We devise a procedure for detecting concept drifts in data-streams that relies on analyzing the empirical loss of learning algorithms. Our method is based on obtaining statistics from the loss distribution by reusing the data multiple times via resampling. We present theoretical guarant...

Self-supervised backpropagation is an unsupervised learning procedure for feedforward networks , where the desired output vector is identical with the input vector. For backpropagation, we are able to use powerful simulators running on parallel machines. Topology-preserving maps, on the other hand, can be developed by a variant of the competitive learning procedure. However , in a degenerate ca...