Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
We have developed a new statistical timing analysis approach that does not impose any assumptions on the nature of manufacturing variability and takes into account an arbitrary mo...
Jennifer L. Wong, Azadeh Davoodi, Vishal Khandelwa...
—This paper introduces the microarchitecture and logical implementation of SMT (Simultaneous Multithreading) improvement of Godson-2 processor which is a 64-bit, four-issue, out-...
Deterministic gate delay models have been widely used to find the transition probabilities at the nodes of a circuit for calculating the power dissipation. However, with progress...