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» A Boosting Algorithm for Regression
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JMLR
2010
88views more  JMLR 2010»
14 years 10 months ago
Descent Methods for Tuning Parameter Refinement
This paper addresses multidimensional tuning parameter selection in the context of "train-validate-test" and K-fold cross validation. A coarse grid search over tuning pa...
Alexander Lorbert, Peter J. Ramadge
121
Voted
NIPS
2003
15 years 4 months ago
AUC Optimization vs. Error Rate Minimization
The area under an ROC curve (AUC) is a criterion used in many applications to measure the quality of a classification algorithm. However, the objective function optimized in most...
Corinna Cortes, Mehryar Mohri
UAI
2003
15 years 4 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
165
Voted
ICIP
2001
IEEE
16 years 5 months ago
Image retrieval with relevance feedback: from heuristic weight adjustment to optimal learning methods
Various relevance feedback algorithms have been proposed in recent years in the area of content-based image retrieval. This paper gives a brief review and analysis on existing tec...
Xiang Sean Zhou, Thomas S. Huang
ICML
2005
IEEE
16 years 4 months ago
Predictive low-rank decomposition for kernel methods
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...
Francis R. Bach, Michael I. Jordan