Textbook wisdom advocates for smooth function fits and implies that
inte...
Neuroscientific data analysis has traditionally relied on linear algebra...
Traditionally in regression one minimizes the number of fitting paramete...
We design a self size-estimating feed-forward network (SSFN) using a joi...
We consider a distributed learning setup where a sparse signal is estima...
Modern supervised learning techniques, particularly those using so calle...
We develop an algorithm for systematic design of a large artificial neur...
We investigate an existing distributed algorithm for learning sparse sig...