Neural networks : the official journal of the International Neural Network Society
Mar 27, 2018
The embodied and situated view of cognition stresses the importance of real-time and nonlinear bodily interaction with the environment for developing concepts and structuring knowledge. In this article, populations of robots controlled by an artifici...
Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools...
Proceedings of the National Academy of Sciences of the United States of America
Mar 15, 2018
Network oscillations across and within brain areas are critical for learning and performance of memory tasks. While a large amount of work has focused on the generation of neural oscillations, their effect on neuronal populations' spiking activity an...
Methods for representing the meaning of words in vector spaces purely using the information distributed in text corpora have proved to be very valuable in various text mining and natural language processing (NLP) tasks. However, these methods still d...
IEEE transactions on neural networks and learning systems
Mar 9, 2018
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful application of these methods in motor imagery (MI) brain-compu...
Journal of chemical information and modeling
Feb 15, 2018
To develop a new ensemble learning method and construct highly predictive regression models in chemoinformatics and chemometrics, applicability domains (ADs) are introduced into the ensemble learning process of prediction. When estimating values of a...
Neural networks : the official journal of the International Neural Network Society
Feb 2, 2018
The scalability of low-rank representation (LRR) to large-scale data is still a major research issue, because it is extremely time-consuming to solve singular value decomposition (SVD) in each optimization iteration especially for large matrices. Sev...
Neural networks : the official journal of the International Neural Network Society
Feb 2, 2018
Parallel incremental learning is an effective approach for rapidly processing large scale data streams, where parallel and incremental learning are often treated as two separate problems and solved one after another. Incremental learning can be imple...
Neural networks : the official journal of the International Neural Network Society
Jan 31, 2018
Determining optimal activation function in artificial neural networks is an important issue because it is directly linked with obtained success rates. But, unfortunately, there is not any way to determine them analytically, optimal activation functio...
Neural networks : the official journal of the International Neural Network Society
Jan 10, 2018
The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the sid...