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» Discriminative Mixed-Membership Models
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153
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CVBIA
2005
Springer
15 years 10 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
134
Voted
AAAI
2000
15 years 6 months ago
Restricted Bayes Optimal Classifiers
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Simon Tong, Daphne Koller
BIOINFORMATICS
2005
109views more  BIOINFORMATICS 2005»
15 years 4 months ago
Prediction error estimation: a comparison of resampling methods
In genomic studies, thousands of features are collected on relatively few samples. One of the goals of these studies is to build classifiers to predict the outcome of future obser...
Annette M. Molinaro, Richard Simon, Ruth M. Pfeiff...
139
Voted
ICASSP
2011
IEEE
14 years 8 months ago
Online feature selection and classification
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...
Habil Kalkan, Bayram Cetisli
137
Voted
EMNLP
2007
15 years 6 months ago
A Sequence Alignment Model Based on the Averaged Perceptron
We describe a discriminatively trained sequence alignment model based on the averaged perceptron. In common with other approaches to sequence modeling using perceptrons, and in co...
Dayne Freitag, Shahram Khadivi