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FLAIRS
2004
13 years 9 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
COLING
2010
13 years 2 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang
NIPS
2004
13 years 9 months ago
On Semi-Supervised Classification
A graph-based prior is proposed for parametric semi-supervised classification. The prior utilizes both labelled and unlabelled data; it also integrates features from multiple view...
Balaji Krishnapuram, David Williams, Ya Xue, Alexa...
ICML
2010
IEEE
13 years 8 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
CVPR
2011
IEEE
13 years 3 months ago
Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...