This paper proposes a framework for distributed sequential parameter estimation in wireless sensor networks. In the proposed scheme, the estimator is updated sequentially at the c...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Using existing programming tools, writing high-performance image processing code requires sacrificing readability, portability, and modularity. We argue that this is a consequenc...
Jonathan Ragan-Kelley, Andrew Adams, Sylvain Paris...
Data parallel programs are sensitive to the distribution of data across processor nodes. We formulate the reduction of inter-node communication as an optimization on a colored gra...