Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
We propose a flexible approach for the visualization of large, high-dimensional datasets. The raw, highdimensional data is mapped into an abstract 3D distance space using the Fast...
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Complex systems experience dramatic changes in behavior and can undergo transitions from functional to dysfunctional states. An unstable system is prone to dysfunctional collective...
Current data repositories include a variety of data types, including audio, images and time series. State of the art techniques for indexing such data and doing query processing r...