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» Approximation Methods for Supervised Learning
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ACL
2007
13 years 9 months ago
Guiding Semi-Supervision with Constraint-Driven Learning
Over the last few years, two of the main research directions in machine learning of natural language processing have been the study of semi-supervised learning algorithms as a way...
Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth
ICML
2008
IEEE
14 years 8 months ago
An empirical evaluation of supervised learning in high dimensions
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
Rich Caruana, Nikolaos Karampatziakis, Ainur Yesse...
TKDE
2008
112views more  TKDE 2008»
13 years 7 months ago
IDD: A Supervised Interval Distance-Based Method for Discretization
This paper introduces a new method for supervised discretization based on interval distances by using a novel concept of neighborhood in the target's space. The proposed metho...
Francisco J. Ruiz, Cecilio Angulo, Núria Ag...
HAIS
2010
Springer
13 years 5 months ago
Reducing Dimensionality in Multiple Instance Learning with a Filter Method
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...
ICANN
2001
Springer
13 years 12 months ago
Scalable Kernel Systems
Kernel-based systems are currently very popular approaches to supervised learning. Unfortunately, the computational load for training kernel-based systems increases drastically wit...
Volker Tresp, Anton Schwaighofer