We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Given any generative classifier based on an inexact density model, we can define a discriminative counterpart that reduces its asymptotic error rate, while increasing the estima...
We develop a method for the estimation of articulated pose, such as that of the human body or the human hand, from a single (monocular) image. Pose estimation is formulated as a s...
Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capabilit...
Abdul Rahim Ahmad, Christian Viard-Gaudin, Marzuki...
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...