1419 search results - page 77 / 284 » Approximation Methods for Supervised Learning |
ICML
2005
IEEE
14 years 10 months ago
2005
IEEE
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
CVPR
2009
IEEE
15 years 5 months ago
2009
IEEE
Graph matching is an important problem in computer
vision. It is used in 2D and 3D object matching and recognition.
Despite its importance, there is little literature on
learnin...
AAAI
2008
14 years 11 days ago
2008
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
PAKDD
2011
ACM
13 years 26 days ago
2011
ACM
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
AAAI
2006
13 years 11 months ago
2006
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...