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PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
13 years 11 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 8 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 10 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 7 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 10 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...