Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Human and non-human primates excel at visual recognition tasks. The primate visual
system exhibits a strong degree of selectivity while at the same time being robust to changes …

We present a method for learning a low-dimensional representation which is shared across
a set of multiple related tasks. The method builds upon the wellknown 1-norm regularization …

We present a method for learning sparse representations shared across multiple tasks. This
method is a generalization of the well-known single-task 1-norm regularization. It is based …

We introduce a new general framework for the recognition of complex visual scenes, which
is motivated by biology: We describe a hierarchical system that closely follows the …

This document discusses the derivation and implementation of convolutional neural
networks (CNNs)[3, 4], followed by a few straightforward extensions. Convolutional neural …

Spike timing dependent plasticity (STDP) is a learning rule that modifies synaptic strength as
a function of the relative timing of pre-and postsynaptic spikes. When a neuron is repeatedly …

Primarily motivated by some characteristics of the human visual cortex (HVC), we propose a
new facial expression recognition scheme, involving a statistical synthesis of hierarchical …

Most electrophysiology studies analyze the activity of each neuron separately. While such
studies have given much insight into properties of the visual system, they have also …

This paper presents an effective scene classification approach based on collaborative
representation fusion of local and global spatial features. First, a visual word codebook is …