We present a minimax framework for classification that considers stochastic adversarial perturbations to the training data. We show that for binary classification it is equivale...
Current multimodal registration methods almost always rely on local gradient-descent type optimization strategies. Such registration methods often converge to an incorrect local o...
We recently introduced symbolic timing simulation (STS) using data-dependent delays as a tool for verifying the timing of fullcustom transistor-level circuit designs, and for the ...
In this paper we use Dijkstra’s algorithm as a challenging, hard to parallelize paradigm to test the efficacy of several parallelization techniques in a multicore architecture....
This paper reports on the results of a preliminary study conducted to evaluate genetic programming (GP) as a means of evolving finite state transducers. A genetic programming syste...