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is formulated as an integer programming problem and we .... rate a suitable orthogonality constraint such that the r-th ..... 5.2 Visualization Capability of MME.

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separable samples, we can relax the inequality constraints by introducing a slack variable ξi for each point xi and aug- menting the objective function with a ...

Structured Learning for Cell Tracking. Xinghua Lou ... Machine learning for tracking: • Local learning: fail .... Comparison: a simple model with only distance and.

Department of Automation, Tsinghua University, Beijing, China. ‡Department of .... programming problem and we propose a cutting plane al- gorithm to ...

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we maintain a distribution over alternative weight vectors, rather than committing to ..... We implemented in matlab a Hildreth-like algorithm (Cen- sor and Zenios ...

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straints imposed by the training examples, expressed as a. Gaussian distribution over weight vectors, learned from the training data. The learning algorithm ...

efficient than existing supervised topic models, especially for classification. Keywords: supervised topic models, max-margin learning, maximum entropy discrimi- nation, latent Dirichlet allocation, support vector machines. 1. Introduction. Probabili

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can work well in a mismatched condition (i.e., clean training case) without using other noise robust technologies. Table 1 (all the tables are in the last page of this paper) lists the detailed test accuracies for MLE and DT methods. (MCE and SME wit

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