919 search results - page 39 / 184 » Generalizing over Several Learning Settings |
ICDM
2005
IEEE
14 years 1 months ago
2005
IEEE
In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
MIR
2005
ACM
14 years 1 months ago
2005
ACM
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...
MLDM
2005
Springer
14 years 1 months ago
2005
Springer
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
Latent Variable Models (LVM), like the Shared-GPLVM
and the Spectral Latent Variable Model, help mitigate over-
fitting when learning discriminative methods from small or
modera...