We built a tool to visualize and explore program execution traces. Our goal was to help programmers without any prior knowledge of a program, quickly get enough knowledge about it...
This paper describes the architecture and implementation of a high-speed decompression engine for embedded processors. The engine is targeted to processors where embedded programs...
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...
Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...