—We investigate optimal resource allocation and power management in virtualized data centers with time-varying workloads and heterogeneous applications. Prior work in this area u...
Rahul Urgaonkar, Ulas C. Kozat, Ken Igarashi, Mich...
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
A tool that automates the floating-point to fixed-point conversion (FFC) process for digital signal processing systems is described. The tool automatically optimizes fixed-point d...
We address the problem of recovering shape, albedo, and illumination from a single grayscale image of an object, using shading as our primary cue. Because this problem is fundamen...