172 search results - page 12 / 35 » Scaling up Analogical Learning |
SIGMOD
2010
ACM
14 years 21 days ago
2010
ACM
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
NIPS
2007
13 years 9 months ago
2007
Recently, we have introduced a novel approach to dynamic programming and reinforcement learning that is based on maintaining explicit representations of stationary distributions i...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
ILP
2000
Springer
13 years 11 months ago
2000
Springer
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
MLDM
2009
Springer
14 years 2 months ago
2009
Springer
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...