99 search results - page 3 / 20 » Learning Taxonomies by Dependence Maximization |
93
Voted
NN
2006
Springer
14 years 10 months ago
2006
Springer
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
75
Voted
IJON
2007
14 years 10 months ago
2007
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
117
Voted
PR
2007
14 years 9 months ago
2007
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
84
Voted
UAI
2008
14 years 11 months ago
2008
A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...
74
Voted
NIPS
2000
14 years 11 months ago
2000
The paradigm of Hebbian learning has recently received a novel interpretation with the discovery of synaptic plasticity that depends on the relative timing of pre and post synapti...