In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
We develop an adaptive load distribution protocol for logical volume I/O workload in clustered storage systems. It exploits data redundancy among decentralized storage servers to ...
In this paper we present a processor microarchitecture that can simultaneously execute multiple threads and has a clustered design for scalability purposes. A main feature of the ...
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...