399 search results - page 2 / 80 » Robust Boosting for Learning from Few Examples |
ICRA
1998
IEEE
13 years 10 months ago
1998
IEEE
: Precise sensorimotor mappings between various motor, ensor, and abstract physical spaces are the basis for many robotics tasks. Their cheap construction is a challenge for adapti...
VMV
2008
13 years 7 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 ...
ICML
2000
IEEE
14 years 6 months ago
2000
IEEE
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
MM
2005
ACM
13 years 11 months ago
2005
ACM
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
CVPR
2010
IEEE
14 years 2 months ago
2010
IEEE
Learning models for recognizing objects with few or no training examples is important, due to the intrinsic longtailed distribution of objects in the real world. In this paper, we...