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» A Boosting Algorithm for Regression
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NIPS
2004
13 years 9 months ago
Online Bounds for Bayesian Algorithms
We present a competitive analysis of Bayesian learning algorithms in the online learning setting and show that many simple Bayesian algorithms (such as Gaussian linear regression ...
Sham M. Kakade, Andrew Y. Ng
CSDA
2008
122views more  CSDA 2008»
13 years 8 months ago
Time-adaptive quantile regression
An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regressio...
Jan Kloppenborg Møller, Henrik Aalborg Niel...
ICML
2001
IEEE
14 years 9 months ago
Multiple Instance Regression
This paper introduces multiple instance regression, a variant of multiple regression in which each data point may be described by more than one vector of values for the independen...
Soumya Ray, David Page
NIPS
2001
13 years 9 months ago
Boosting and Maximum Likelihood for Exponential Models
We derive an equivalence between AdaBoost and the dual of a convex optimization problem, showing that the only difference between minimizing the exponential loss used by AdaBoost ...
Guy Lebanon, John D. Lafferty