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» A New Discriminative Kernel From Probabilistic Models
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ICML
2004
IEEE
15 years 3 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
SSPR
2010
Springer
14 years 8 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
CVPR
2004
IEEE
15 years 11 months ago
Dual-Space Linear Discriminant Analysis for Face Recognition
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
Xiaogang Wang, Xiaoou Tang
PAMI
2008
190views more  PAMI 2008»
14 years 9 months ago
Scene Classification Using a Hybrid Generative/Discriminative Approach
We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail we are given a set ...
Anna Bosch, Andrew Zisserman, Xavier Muñoz
MICCAI
2009
Springer
15 years 7 months ago
Fast Automatic Segmentation of the Esophagus from 3D CT Data Using a Probabilistic Model
Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confu...
Johannes Feulner, Shaohua Kevin Zhou, Alexander Ca...