We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
In bibliographies like DBLP and Citeseer, there are three kinds of entity-name problems that need to be solved. First, multiple entities share one name, which is called the name sh...