8970 search results - page 81 / 1794 » Learning to Learn Causal Models |
107
click to vote
NIPS
2000
15 years 2 months ago
2000
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
104
click to vote
ICML
2010
IEEE
15 years 2 months ago
2010
IEEE
This paper develops a generalized apprenticeship learning protocol for reinforcementlearning agents with access to a teacher who provides policy traces (transition and reward obse...
127
click to vote
IANDC
2007
15 years 1 months ago
2007
The present study aims at insights into the nature of incremental learning in the context of Gold’s model of identification in the limit. With a focus on natural requirements s...
112
click to vote
ICRA
2010
IEEE
15 years 1 days ago
2010
IEEE
— We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using ...
102
click to vote
EMNLP
2009
14 years 11 months ago
2009
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...