Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
A novel framework shows the potential of FPGA-based systems for increasing fault-tolerance and flexibility by placing functionality onto free hardware (HW) or software (SW) resour...
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
We propose a new approach for I/O scheduling that performs on-line simulation of the underlying disk. When simulation is integrated within a system, three key challenges must be a...
Florentina I. Popovici, Andrea C. Arpaci-Dusseau, ...
This paper considers the diagnosis of large discrete-event systems consisting of many components. The problem is to determine, online, all failures and states that explain a given...