We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...
Abstract. Algorithms dealing with massive data sets are usually designed for I/O-efficiency, often captured by the I/O model by Aggarwal and Vitter. Another aspect of dealing with ...
This paper introduces a Combinatory Optimization Problem (COP) which captures the performance in cooperation of a P2P Streaming Network, considered at the buffer level. A new famil...
We address the problem of finding parallel plans for SQL queries using the two-phase approach of join ordering followed by parallelization. We focus on the parallelization phase a...