We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...
Temporal derivatives are computed by a wide variety of neural circuits, but the problem of performing this computation accurately has received little theoretical study. Here we sy...
Abstract. Tracking the provenance of application data is of key importance in the network environment due to the abundance of heterogeneous and controllable resources. We focus on ...
We study what the existence of a classical embedding between computable structures implies about the existence of computable embeddings. In particular, we consider the effect of fi...
The weakly random reals contain not only the Schnorr random reals as a subclass but also the weakly 1-generic reals and therefore the n-generic reals for every n. While the class o...
Van Lambalgen's Theorem plays an important role in algorithmic randomness, especially when studying relative randomness. In this paper we extend van Lambalgen's Theorem ...