23 search results - page 1 / 5 » Application specific loss minimization using gradient boosti... |
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establ...
NIPS
2007
13 years 6 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
SDM
2012
SIAM
11 years 7 months ago
2012
SIAM
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
ICCV
2007
IEEE
14 years 6 months ago
2007
IEEE
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...