One way of introducing sparsity into deep networks is by attaching an
ex...
It is well established that increasing scale in deep transformer network...
Deep and wide neural networks successfully fit very complex functions to...
In this paper, we propose a dynamic cascaded encoder Automatic Speech
Re...
We propose a modular architecture for the lifelong learning of hierarchi...
Can deep learning solve multiple tasks simultaneously, even when they ar...
It is well established that training deep neural networks gives useful
r...
Large neural network models have been successful in learning functions o...
How we store information in our mind has been a major intriguing open
qu...
We present a mechanism to compute a sketch (succinct summary) of how a
c...
In this paper we study the learnability of deep random networks from bot...
Giving provable guarantees for learning neural networks is a core challe...
We investigate the problem of factorizing a matrix into several sparse
m...
Consider the classical problem of predicting the next bit in a sequence ...
There is a vast supply of prior art that study models for mental process...