Zhaoshi Meng

Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models

Alfred O. Hero, Ami Wiesel, Zhaoshi Meng, 2014, IEEE Transactions on Signal Processing.

Learning Latent Variable Gaussian Graphical Models pdf

Alfred O. Hero, Brian Eriksson, Zhaoshi Meng, 2014, ICML.

Marginal likelihoods for distributed estimation of graphical model parameters

Alfred O. Hero, Ami Wiesel, Zhaoshi Meng, 2013, 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Multimodal Sensing for Pediatric Obesity Applications

Gaurav S. Sukhatme, Shrikanth Narayanan, Nenad Medvidovic, 2008 .

Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods pdf

Alfred O. Hero, Ami Wiesel, Zhaoshi Meng, 2013, AISTATS.

A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs

Bhaskara Marthi, Wolfgang Lehrach, Dileep George, 2017, Science.

Distributed principal component analysis on networks via directed graphical models

Alfred O. Hero, Ami Wiesel, Zhaoshi Meng, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis

Qiaozhu Mei, Ming Zhang, XuanLong Nguyen, 2014, ICML.

Distributed Learning, Prediction and Detection in Probabilistic Graphs.

Zhaoshi Meng, Zhaoshi Meng, 2014 .

THU and ICRC at TRECVID 2007

Dong Wang, Xiaolin Hu, Bo Zhang, 2007, TRECVID.