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JMLR
2006
107views more  JMLR 2006»
14 years 9 months ago
Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation
In many pattern recognition/classification problem the true class conditional model and class probabilities are approximated for reasons of reducing complexity and/or of statistic...
Magnus Ekdahl, Timo Koski
JMLR
2006
79views more  JMLR 2006»
14 years 9 months ago
Estimation of Gradients and Coordinate Covariation in Classification
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
Sayan Mukherjee, Qiang Wu
JMLR
2006
97views more  JMLR 2006»
14 years 9 months ago
Learning Coordinate Covariances via Gradients
We introduce an algorithm that learns gradients from samples in the supervised learning framework. An error analysis is given for the convergence of the gradient estimated by the ...
Sayan Mukherjee, Ding-Xuan Zhou
JMLR
2006
137views more  JMLR 2006»
14 years 9 months ago
Bounds for Linear Multi-Task Learning
Abstract. We give dimension-free and data-dependent bounds for linear multi-task learning where a common linear operator is chosen to preprocess data for a vector of task speci...c...
Andreas Maurer
JMLR
2006
105views more  JMLR 2006»
14 years 9 months ago
Some Theory for Generalized Boosting Algorithms
We give a review of various aspects of boosting, clarifying the issues through a few simple results, and relate our work and that of others to the minimax paradigm of statistics. ...
Peter J. Bickel, Yaacov Ritov, Alon Zakai