14 search results - page 1 / 3 » Learning with Few Examples using a Constrained Gaussian Prio... |
VMV
2008
13 years 6 months ago
2008
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
DAGM
2009
Springer
13 years 11 months ago
2009
Springer
The human ability to learn difficult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
ISCI
2008
13 years 4 months ago
2008
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
ML
1998
ACM
13 years 4 months ago
1998
ACM
It is well known that prior knowledge or bias can speed up learning, at least in theory. It has proved di cult to make constructive use of prior knowledge, so that approximately c...