The MapReduce programming model simplifies large-scale data processing on commodity clusters by having users specify a map function that processes input key/value pairs to generate...
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Mathematical modeling for gene regulative networks (GRNs) provides an effective tool for hypothesis testing in biology. A necessary step in setting up such models is the estimati...
The characteristics of ad hoc networks naturally encourage the deployment of distributed services. Although current networks implement group communication methods, they do not sup...