Zhaoshi Meng, a doctoral student in the Electrical Engineering:Systems program, received 2nd place in the Student Paper Competition at the Fifth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2013). The paper, "Marginal Likelihoods for Distributed Estimation of Graphical Model Parameters," was co-authored by Zhaoshi Meng, Dr. Dennis Wei, Dr. Ami Wiesel and Prof. Alfred Hero.
Zhaoshi stated that this work is an extension of ongoing research that provides a way to efficiently reveal relationships between even distant entities in a network, whether it be a social network or a network of sensors. That work received a best paper award at the 16th Int. Conference on Artificial Intelligence and Statistics (AISTATS). [more info]
In this paper, stated Zhaoshi, "we derive novel information theoretic guarantees (i.e. lower bounds on the estimation error) for the proposed algorithm, which reconfirm our previous empirical results."
|Poster describing the research|
Zhaoshi Meng received his bachelor's degree, with honors, from Tsinghua University in China. He is interested in the theory, algorithms and applications of machine learning, mathematical optimization, and statistical signal processing. Mr. Meng is co-advised by Alfred Hero, R. Jamison and Betty Williams Professor of Engineering, and Prof. Long Nguyen (Dept. of Statistics and EECS).
This research was supported by the Army Research Office under the MURI, "Value-centered Information Theory for Adaptive Learning, Inference, Tracking, and Exploitation."