We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...
Categorical data appears in various places, and dealing with it has been a major concern in analysis fields. However, representing not only global trends but also local trends of d...
This paper develops a supervised dimensionality reduction method, Lorentzian Discriminant Projection (LDP), for discriminant analysis and classification. Our method represents the...
We present methods to answer two basic questions that arise when benchmarking optimization algorithms. The first one is: which algorithm is the `best' one? and the second one:...
We develop an information?theoretic analysis of dependencies between image wavelet coefficients. The dependencies are measured using mutual information, which has a direct link wi...