We study field-monitoring applications in which sensors are deployed in large numbers and the sensing process is expensive. In such applications, nodes should use the minimum poss...
Can we leverage learning techniques to build a fast nearest-neighbor (ANN) retrieval data structure? We present a general learning framework for the NN problem in which sample que...
— This paper considers scheduling divisible workloads from multiple sources in linear networks of processors. We propose a two phase scheduling strategy (TPSS) to minimize the ov...
In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reason...
We describe the application of plan recognition techniques to support human intelligence analysts in processing national security alert sets by automatically identifying the hosti...