This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity...
In this paper, we propose a hierarchical classifier structure for gender classification based on facial images by reducing the complexity of the original problem. In the proposed f...
— Inspired by the universal laws governing different kinds of complex networks, we propose a scale-free highlyclustered echo state network (SHESN). Different from echo state netw...
This paper presents a novel method for the classification of images that combines information extracted from the images and contextual information. The main hypothesis is that con...