Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
In this paper, we propose a new technique, referred to as MultiWafer Virtual Probe (MVP) to efficiently model wafer-level spatial variations for nanoscale integrated circuits. Tow...
Wangyang Zhang, Xin Li, Emrah Acar, Frank Liu, Rob...
The problem of routing of sensor observations for optimal detection of a Markov random field (MRF) at a designated fusion center is analyzed. Assuming that the correlation structur...