Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example ...
We introduce a framework for modeling spatial patterns of shapes formed by multiple objects in an image. Our approach is graph-based where each node denotes an object and attribut...
CT The traditional approach to worst-case static-timing analysis is becoming unacceptably conservative due to an ever-increasing number of circuit and process effects. We propose a...
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
— In this paper, we study the Dynamic Traveling Repairman Problem (DTRP) for dynamic systems. In the DTRP, customers are arising dynamically and randomly in a bounded region R, a...