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PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
13 years 9 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
CVPR
2008
IEEE
14 years 6 months ago
Robust statistics on Riemannian manifolds via the geometric median
The geometric median is a classic robust estimator of centrality for data in Euclidean spaces. In this paper we formulate the geometric median of data on a Riemannian manifold as ...
P. Thomas Fletcher, Suresh Venkatasubramanian, Sar...
ISBI
2011
IEEE
12 years 8 months ago
Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm
We develop a new algorithm to segment the hippocampus from MR images. Our method uses a new classifier ensemble algorithm to correct segmentation errors produced by a multi-atlas...
Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, Mur...
AAAI
1998
13 years 6 months ago
Boosting Combinatorial Search Through Randomization
Unpredictability in the running time of complete search procedures can often be explained by the phenomenon of "heavy-tailed cost distributions", meaning that at any tim...
Carla P. Gomes, Bart Selman, Henry A. Kautz
CORR
2011
Springer
193views Education» more  CORR 2011»
12 years 8 months ago
The Rate of Convergence of AdaBoost
The AdaBoost algorithm was designed to combine many “weak” hypotheses that perform slightly better than random guessing into a “strong” hypothesis that has very low error....
Indraneel Mukherjee, Cynthia Rudin, Robert E. Scha...