We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
Tiny, low-cost sensor devices are expected to be failure-prone and hence in many realistic deployment scenarios for sensor networks these nodes are deployed in higher than necessa...
We consider the problem of monitoring spatial phenomena, such as road speeds on a highway, using wireless sensors with limited battery life. A central question is to decide where ...
Andreas Krause, Ram Rajagopal, Anupam Gupta, Carlo...
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...