We propose an approximate computation technique for inter-object distances for binary data sets. Our approach is based on the locality sensitive hashing, scales up with the number ...
Recently, we have introduced a novel approach to dynamic programming and reinforcement learning that is based on maintaining explicit representations of stationary distributions i...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction...
SIMD extensions are the most common technique used in current processors for multimedia computing. In order to obtain more performance for emerging applications SIMD extensions ne...
We present the design and implementation of new inexact Newton type Bundle Adjustment algorithms that exploit hardware parallelism for efficiently solving large scale 3D scene re...
Changchang Wu, Sameer Agarwal, Brian Curless, Stev...