For two decades, reconfigurable computing systems have provided an attractive alternative to fixed hardware solutions. Reconfigurable computing systems have demonstrated the low c...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
Current application-sharing systems support a single architecture for all collaborations, though different systems support different architectures We have developed a system that s...
Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind ...