1393 search results - page 105 / 279 » Machine Learning by Function Decomposition |
186
click to vote
ML
2012
ACM
14 years 1 months ago
2012
ACM
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
157
click to vote
GECCO
2006
Springer
15 years 10 months ago
2006
Springer
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
195
click to vote
ICML
2008
IEEE
16 years 7 months ago
2008
IEEE
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
167
click to vote
GECCO
2008
Springer
15 years 7 months ago
2008
Springer
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
169
click to vote
ECTEL
2007
Springer
16 years 16 days ago
2007
Springer
This paper presents a dissertation project on business-integrated, service-oriented learning architectures. The isolation of corporate learning management from core business functi...