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» On learning algorithm selection for classification
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ACL
2009
15 years 4 months ago
A Novel Discourse Parser Based on Support Vector Machine Classification
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
David duVerle, Helmut Prendinger
ICMCS
2008
IEEE
148views Multimedia» more  ICMCS 2008»
16 years 1 months ago
Audio tonality mode classification without tonic annotations
Traditional tonality mode (major or minor) classification or audio key finding algorithms often rely on tonic annotations (key names) of the training songs. However, unlike clas...
Zhiyao Duan, Lie Lu, Changshui Zhang
BVAI
2007
Springer
16 years 25 days ago
Classification with Positive and Negative Equivalence Constraints: Theory, Computation and Human Experiments
We tested the efficiency of category learning when participants are provided only with pairs of objects, known to belong either to the same class (Positive Equivalence Constraints ...
Rubi Hammer, Tomer Hertz, Shaul Hochstein, Daphna ...
UAI
2008
15 years 8 months ago
Small Sample Inference for Generalization Error in Classification Using the CUD Bound
Confidence measures for the generalization error are crucial when small training samples are used to construct classifiers. A common approach is to estimate the generalization err...
Eric Laber, Susan Murphy
PAMI
2011
15 years 1 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang