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» Learning Mixtures of Gaussians
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ILP
2003
Springer
15 years 11 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
NIPS
2008
15 years 7 months ago
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn th...
Kian Ming Adam Chai, Christopher K. I. Williams, S...
ICA
2010
Springer
15 years 7 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio
TSP
2010
15 years 1 months ago
Learning Gaussian tree models: analysis of error exponents and extremal structures
The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
EVOW
2008
Springer
15 years 8 months ago
Learning Gaussian Graphical Models of Gene Networks with False Discovery Rate Control
In many cases what matters is not whether a false discovery is made or not but the expected proportion of false discoveries among all the discoveries made, i.e. the so-called false...
Jose M. Peña