197 search results - page 21 / 40 » A regularization framework for multiple-instance learning |
ML
2010
ACM
13 years 2 months ago
2010
ACM
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
NIPS
2003
13 years 9 months ago
2003
We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
CVPR
2005
IEEE
14 years 9 months ago
2005
IEEE
We present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of our original data. The motivation is that since the learning algori...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper, we present a new interpretation of AdaBoost.ECC and AdaBoost.OC. We show that AdaBoost.ECC performs stage-wise functional gradient descent on a cost function, defin...