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STOC
1993
ACM
117views Algorithms» more  STOC 1993»
14 years 20 days ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns
FIMH
2009
Springer
13 years 6 months ago
Random Forest Classification for Automatic Delineation of Myocardium in Real-Time 3D Echocardiography
Automatic delineation of the myocardium in real-time 3D echocardiography may be used to aid the diagnosis of heart problems such as ischaemia, by enabling quantification of wall th...
Victor S. Lempitsky, Michael Verhoek, J. Alison No...
CVPR
2010
IEEE
14 years 4 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
WSC
2008
13 years 11 months ago
A modeling-based classification algorithm validated with simulated data
We present a Generalized Lotka-Volterra (GLV) based approach for modeling and simulation of supervised inductive learning, and construction of an efficient classification algorith...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
TIP
2002
179views more  TIP 2002»
13 years 8 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki