We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
A directed generative model for binary data using a small number of hidden continuous units is investigated. A clipping nonlinearity distinguishes the model from conventional prin...
Topic modeling has been a key problem for document analysis. One of the canonical approaches for topic modeling is Probabilistic Latent Semantic Indexing, which maximizes the join...
Deng Cai, Qiaozhu Mei, Jiawei Han, Chengxiang Zhai
Building profiles for processes and for interactive users is a important task in intrusion detection. This paper presents the results obtained with a Hierarchical Hidden Markov Mo...