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ICML
2005
IEEE
15 years 10 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
ICML
2010
IEEE
14 years 10 months ago
Structured Output Learning with Indirect Supervision
We present a novel approach for structure prediction that addresses the difficulty of obtaining labeled structures for training. We observe that structured output problems often h...
Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Da...
ASUNAM
2010
IEEE
14 years 11 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
14 years 11 months ago
Semi-Supervised Learning Based on Semiparametric Regularization
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
FINTAL
2006
15 years 1 months ago
Paraphrase Identification on the Basis of Supervised Machine Learning Techniques
Abstract. This paper presents a machine learning approach for paraphrase identification which uses lexical and semantic similarity information. In the experimental studies, we exam...
Zornitsa Kozareva, Andrés Montoyo