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. The paper considers the problem of semi-supervised multiview classification, where each view corresponds to a Reproducing Kernel Hilbert Space. An algorithm based on co-...
This paper presents a new scheduling technique to improve the speed, power, and scalability of a dynamic scheduler. In a high-performance superscalar processor, the instruction sc...
Many commercially available embedded processors are capable of extending their base instruction set for a specific domain of applications. While steady progress has been made in t...
Modeling frequency-dependent nonlinear characteristics of complex analog blocks and subsystems is critical for enabling efficient verification of mixed-signal system designs. Rece...