1393 search results - page 105 / 279 » Machine Learning by Function Decomposition |
137
click to vote
ML
2012
ACM
13 years 9 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...
104
click to vote
GECCO
2006
Springer
15 years 5 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...
127
click to vote
ICML
2008
IEEE
16 years 2 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...
114
Voted
GECCO
2008
Springer
15 years 3 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...
119
click to vote
ECTEL
2007
Springer
15 years 8 months 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...