We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...
Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Na...
CT Cellphones have the potential to improve education for the millions of underprivileged users in the developing world. However, mobile learning in developing countries remains un...
Abstract. We present an approach for knowledge-free and unsupervised recognition of compound nouns for languages that use one-wordcompounds such as Germanic and Scandinavian langua...