We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on ...
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
We present an algorithm, Shared-State Sampling (S3 ), for the problem of detecting large flows in high-speed networks. While devised with different principles in mind, S3 turns ...
The existing decoupling capacitance optimization approaches meet constraints on input impedance for package. In this paper, we show that using impedance as constraints leads to la...