In this paper, we present two ensemble learning algorithms which make use of boostrapping and out-of-bag estimation in an attempt to inherit the robustness of bagging to overfitti...
Recent research has shown that using a mobile element to collect and carry data mechanically from a sensor network has many advantages over static multihop routing. We have an imp...
David Jea, Arun A. Somasundara, Mani B. Srivastava
This paper presents a novel approach for model-based realtime tracking of highly articulated structures such as humans. This approach is based on an algorithm which efficiently pr...
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs),...