—We propose a new method for online estimation of probabilistic discriminative models. The method is based on the recently proposed online Kernel Density Estimation (oKDE) framew...
—We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a...
Future high-performance billion-transistor processors are likely to employ partitioned architectures to achieve high clock speeds, high parallelism, low design complexity, and low...
This paper presents a scalable and self-optimizing architecture for Quality-of-Service (QoS) provisioning in the Differentiated Services (DiffServ) framework. The proposed archite...
We present a new approach to learning image metrics. The main advantage of our method lies in a formulation that requires only a few pairwise examples. Apparently, based on the li...