113 search results - page 9 / 23 » Structural Machine Learning with Galois Lattice and Graphs |
82
Voted
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
ICML
2004
IEEE
15 years 2 months ago
2004
IEEE
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
ML
2011
ACM
14 years 4 months ago
2011
ACM
In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representa...
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of ...
115
click to vote
ESOP
2011
Springer
14 years 1 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...