8970 search results - page 374 / 1794 » Learning to Learn Causal Models |
203
click to vote
ICMCS
2005
IEEE
16 years 13 days ago
2005
IEEE
Modeling visual concepts using supervised or unsupervised machine learning approaches are becoming increasing important for video semantic indexing, retrieval, and filtering appli...
194
click to vote
ECAI
2008
Springer
15 years 8 months ago
2008
Springer
Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution ...
236
click to vote
JMLR
2012
13 years 9 months ago
2012
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
190
click to vote
ECCV
2008
Springer
16 years 8 months ago
2008
Springer
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
161
click to vote
ICML
2009
IEEE
16 years 7 months ago
2009
IEEE
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...