2388 search results - page 1 / 478 » Kernel information embeddings |
97
Voted
ICML
2006
IEEE
16 years 4 months ago
2006
IEEE
152
Voted
SSPR
2010
Springer
15 years 1 months ago
2010
Springer
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
156
Voted
CVPR
2009
IEEE
16 years 10 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...
148
Voted
ICIP
2010
IEEE
15 years 1 months ago
2010
IEEE
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
123
click to vote
CIBCB
2005
IEEE
15 years 9 months ago
2005
IEEE
— Part of the challenge of modeling protein sequences is their discrete nature. Many of the most powerful statistical and learning techniques are applicable to points in a Euclid...