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» Combining Discriminant Models with New Multi-Class SVMs
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TSP
2008
180views more  TSP 2008»
13 years 7 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein
ICML
2005
IEEE
14 years 8 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
COLING
2010
13 years 2 months ago
Latent Mixture of Discriminative Experts for Multimodal Prediction Modeling
During face-to-face conversation, people naturally integrate speech, gestures and higher level language interpretations to predict the right time to start talking or to give backc...
Derya Ozkan, Kenji Sagae, Louis-Philippe Morency
CVPR
2008
IEEE
14 years 9 months ago
A discriminatively trained, multiscale, deformable part model
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
ICCV
2005
IEEE
14 years 9 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu