2934 search results - page 146 / 587 » Hypothesis Spaces for Learning |
148
Voted
NIPS
2003
15 years 6 months ago
2003
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
136
click to vote
STOC
2006
ACM
16 years 4 months ago
2006
ACM
Producing a small DNF expression consistent with given data is a classical problem in computer science that occurs in a number of forms and has numerous applications. We consider ...
139
click to vote
NIPS
1997
15 years 6 months ago
1997
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
149
Voted
NN
1998
Springer
15 years 4 months ago
1998
Springer
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
153
click to vote
ITS
2010
Springer
15 years 9 months ago
2010
Springer
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...