A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
Natural gradient works efficiently in learning
Neural Computation
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Deterministic annealing EM algorithm
Neural Networks
Making large-scale support vector machine learning practical
Advances in kernel methods
Exploiting generative models in discriminative classifiers
Proceedings of the 1998 conference on Advances in neural information processing systems II
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
The Journal of Machine Learning Research
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Modeling word burstiness using the Dirichlet distribution
ICML '05 Proceedings of the 22nd international conference on Machine learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Unsupervised Selection of a Finite Dirichlet Mixture Model: An MML-Based Approach
IEEE Transactions on Knowledge and Data Engineering
Information Sciences: an International Journal
Journal of Visual Communication and Image Representation
Clustering of Count Data Using Generalized Dirichlet Multinomial Distributions
IEEE Transactions on Knowledge and Data Engineering
Novel mixtures based on the dirichlet distribution: application to data and image classification
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Deriving TF-IDF as a fisher kernel
SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
Space-alternating generalized expectation-maximization algorithm
IEEE Transactions on Signal Processing
A Graphical Model for Context-Aware Visual Content Recommendation
IEEE Transactions on Multimedia
Paper: Modeling by shortest data description
Automatica (Journal of IFAC)
Penalized maximum-likelihood image reconstruction using space-alternating generalized EM algorithms
IEEE Transactions on Image Processing
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Deriving kernels from generalized Dirichlet mixture models and applications
Information Processing and Management: an International Journal
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In this paper, we investigate the problem of training support vector machines (SVMs) on count data. Multinomial Dirichlet mixture models allow us to model efficiently count data. On the other hand, SVMs permit good discrimination. We propose, then, a hybrid model that appropriately combines their advantages. Finite mixture models are introduced, as an SVM kernel, to incorporate prior knowledge about the nature of data involved in the problem at hand. For the learning of our mixture model, we propose a deterministic annealing component-wise EM algorithm mixed with a minimum description length type criterion. In the context of this model, we compare different kernels. Through some applications involving spam and image database categorization, we find that our data-driven kernel performs better.