We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Uniform random sample is often useful in analyzing data. Usually taking a uniform sample is not a problem if the entire data resides in one location. However, if the data is distr...
State estimation in multiagent settings involves updating an agent’s belief over the physical states and the space of other agents’ models. Performance of the previous approac...