We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Constraint satisfaction has been applied with great success in closed-world scenarios, where all options and constraints are known from the beginning and fixed. With the internet,...
This paper presents an analytical model to compute the average service time and jitter experienced by a packet when transmitted in a saturated IEEE 802.11 ad hoc network. In contr...
— Retrieving similar images from large repository of heterogeneous biomedical images has been a difficult research task. In this paper, we develop a retrieval system that uses H...
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...