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» Approximation Methods for Supervised Learning
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NAACL
2004
13 years 11 months ago
Ensemble-based Active Learning for Parse Selection
Supervised estimation methods are widely seen as being superior to semi and fully unsupervised methods. However, supervised methods crucially rely upon training sets that need to ...
Miles Osborne, Jason Baldridge
CVPR
2004
IEEE
15 years 3 hour ago
BoostMap: A Method for Efficient Approximate Similarity Rankings
This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, ...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
DIS
2009
Springer
14 years 4 months ago
MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Yasser El-Manzalawy, Vasant Honavar
ESSMAC
2003
Springer
14 years 3 months ago
Analysis of Some Methods for Reduced Rank Gaussian Process Regression
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
Joaquin Quiñonero Candela, Carl Edward Rasm...
SDM
2011
SIAM
269views Data Mining» more  SDM 2011»
13 years 24 days ago
Semi-Supervised Convolution Graph Kernels for Relation Extraction
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
Xia Ning, Yanjun Qi