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ICDAR
2009
IEEE
14 years 21 days ago
Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...
Volkmar Frinken, Horst Bunke
JMLR
2010
158views more  JMLR 2010»
13 years 23 days ago
Topology Selection in Graphical Models of Autoregressive Processes
An algorithm is presented for topology selection in graphical models of autoregressive Gaussian time series. The graph topology of the model represents the sparsity pattern of the...
Jitkomut Songsiri, Lieven Vandenberghe
CVPR
2012
IEEE
11 years 8 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
JMLR
2006
186views more  JMLR 2006»
13 years 6 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
ICDM
2010
IEEE
197views Data Mining» more  ICDM 2010»
13 years 4 months ago
D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-defined Classification
: D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi HP Labo...
Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yu...