2295 search results - page 29 / 459 » Learning Overcomplete Representations |
GECCO
2006
Springer
14 years 8 days ago
2006
Springer
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
ICML
2008
IEEE
14 years 9 months ago
2008
IEEE
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
JMLR
2012
11 years 11 months ago
2012
We study the problem of learning a group of principal tasks using a group of auxiliary tasks, unrelated to the principal ones. In many applications, joint learning of unrelated ta...
HYBRID
1998
Springer
14 years 25 days ago
1998
Springer
We look at distributed representation of structure with variable binding, that is natural for neural nets and allows traditional symbolic representation and processing. The repres...