This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
While collaboration is a natural choice in many situations, there is a lack of specialized tools for collaboratively seeking information. We present design specifications and impl...
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
This paper reports on the evaluation of a digitallyaugmented exhibition on the history of modern media. We discuss visitors’ interaction with installations and corresponding int...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...