Within the field of pattern classification, the Fisher kernel is a powerful framework which combines the strengths of generative and discriminative approaches. The idea is to ch...
This paper presents a method to estimate the position of object using contextual information. Although convention methods used only shape contextual information, color contextual i...
We present a new parallel algorithm that extends and generalizes the traditional graph analysis metric of betweenness centrality to include additional non-shortest paths according...
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
A power estimation approach is presented in which blocks of consecutive vectors are selected at random from a user-supplied realistic input vector set and the circuit is simulated...