Language production requires selection of the appropriate sentence structure to accommodate the communication goal of the speaker - the transmission of a particular meaning. Here we consider event meanings, in terms of predicates and thematic roles, ...
IEEE transactions on neural networks and learning systems
Aug 31, 2015
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular mode...
Computational intelligence and neuroscience
Aug 27, 2015
We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets). The aim is to find General-Purpose (GP) heterogeneous ensembles (requiring ...
Learning and inferring features that generate sensory input is a task continuously performed by cortex. In recent years, novel algorithms and learning rules have been proposed that allow neural network models to learn such features from natural image...
Neural networks : the official journal of the International Neural Network Society
Aug 18, 2015
The application of biologically inspired methods in design and control has a long tradition in robotics. Unlike previous approaches in this direction, the emerging field of neurorobotics not only mimics biological mechanisms at a relatively high leve...
Journal of neuroengineering and rehabilitation
Jul 23, 2015
BACKGROUND: Despite the functional impact of upper limb dysfunction in multiple sclerosis (MS), effects of intensive exercise programs and specifically robot-supported training have been rarely investigated in persons with advanced MS.
Neuroscience and biobehavioral reviews
Jul 17, 2015
The last several years have seen a number of approaches to robot assistance of motor learning. Experimental studies have produced a range of findings from beneficial effects through null-effects to detrimental effects of robot assistance. In this rev...
Newton methods can be applied in many supervised learning approaches. However, for large-scale data, the use of the whole Hessian matrix can be time-consuming. Recently, subsampled Newton methods have been proposed to reduce the computational time by...
Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though ...
OBJECTIVE: Assessment of medical trainee learning through pre-defined competencies is now commonplace in schools of medicine. We describe a novel electronic advisor system using natural language processing (NLP) to identify two geriatric medicine com...