159 search results - page 7 / 32 » Margin Maximizing Loss Functions |
AAAI
2000
15 years 1 months ago
2000
The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
JMLR
2010
14 years 6 months ago
2010
In this paper, we investigate the problem of binary classification with a reject option in which one can withhold the decision of classifying an observation at a cost lower than t...
104
click to vote
AAAI
2010
14 years 9 months ago
2010
Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
102
Voted
EPEW
2006
Springer
15 years 3 months ago
2006
Springer
This paper shows how to construct a Markovian arrival process of second order from information on the marginal distribution and on its autocorrelation function. More precisely, clo...
ECAI
2004
Springer
15 years 5 months ago
2004
Springer
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...