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ICPR
2008
IEEE
15 years 4 months ago
A supervised learning approach for imbalanced data sets
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Discrete Regularization for Perceptual Image Segmentation via Semi-Supervised Learning and Optimal Control
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Hongwei Zheng, Olaf Hellwich
ICMCS
2006
IEEE
136views Multimedia» more  ICMCS 2006»
15 years 4 months ago
Enhanced Semi-Supervised Learning for Automatic Video Annotation
For automatic semantic annotation of large-scale video database, the insufficiency of labeled training samples is a major obstacle. General semi-supervised learning algorithms can...
Meng Wang, Xian-Sheng Hua, Li-Rong Dai, Yan Song
AAAI
2007
15 years 8 days ago
Semi-Supervised Learning with Very Few Labeled Training Examples
In semi-supervised learning, a number of labeled examples are usually required for training an initial weakly useful predictor which is in turn used for exploiting the unlabeled e...
Zhi-Hua Zhou, De-Chuan Zhan, Qiang Yang
NIPS
2007
14 years 11 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang