Monthly Archives: January 2014

Project : Sensing Aware SVM

Background: Designing kernels is important in supervised classification method such as in Support Vector Machine. However, there lacks in general guidelines for designing a proper kernel. In many applications, the observation data and the class label are linked through a latent state. Partial knowledge of the generative process, i.e., the likelihood of the observation given […]

Project : Topic Modeling through Data Dependent and Random Projection

Background: Topic Modeling is a popular statistic tool in modeling the latent semantic structure of, e.g., text corpora. In a typical topic model, each document is assumed to be generated from a small set of topics – each being a distribution over a vocabulary. An important goal in topic modeling is to estimate the latent […]