995 search results - page 13 / 199 » Learning Useful Horn Approximations |
JMLR
2010
13 years 4 months ago
2010
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
CORR
2012
Springer
12 years 5 months ago
2012
Springer
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
AAMAS
2007
Springer
14 years 4 months ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...