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NIPS
2003
13 years 8 months ago
Margin Maximizing Loss Functions
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
Saharon Rosset, Ji Zhu, Trevor Hastie
ENGL
2008
133views more  ENGL 2008»
13 years 6 months ago
Cycle Time Forecasting Models for Defect Inspection Process in TFT-LCD Module Assembly
Because most of the procedures in defect inspection process of TFT-LCD module assembly are examined manually through human vision, cycle time estimation for this particular process...
Chien-wen Shen
SIGPRO
2010
111views more  SIGPRO 2010»
13 years 1 months ago
Semi-supervised speaker identification under covariate shift
In this paper, we propose a novel semi-supervised speaker identification method that can alleviate the influence of non-stationarity such as session dependent variation, the recor...
Makoto Yamada, Masashi Sugiyama, Tomoko Matsui
ICML
2007
IEEE
14 years 7 months ago
Discriminative learning for differing training and test distributions
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
Michael Brückner, Steffen Bickel, Tobias Sche...
ICML
2005
IEEE
14 years 7 months ago
Large margin non-linear embedding
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
Alexander Zien, Joaquin Quiñonero Candela