Aonan Zhang


Ph. D student at Columbia University
Office: Mudd 4th Floor (Columbia Data Science Institute)
Email: az2385@columbia.edu

I'm a 3rd-year Ph. D student in the Department of Electrical Engineering at Columbia University, working with Prof. John Paisley. Before that, I finished my BS and MS at Tsinghua University, where I was working with Prof. Jun Zhu. My research focus is on machine learning, including probabilistic models and inference methods. Here is my CV.

Working Papers

A. Zhang, J. Paisley:
Bayesian Latent Feature Models via Sequential Allocations

S. Gultekin, A. Zhang, J. Paisley:
Stochastic Annealing for Variational Inference

G. Fazelnia, S. Li, A. Zhang, J. Paisley:
Bayesian Nonparametric Latent Subspace Analysis


Publications

A. Zhang, J. Paisley:
Markov Latent Feature Models
International Conference on Machine Learning (ICML), New York, NY, 2016 [PDF]

A. Zhang, S. Gultekin, J. Paisley:
Stochastic Variational Inference for HDP-HMM
International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, 2016 [PDF]

A. Zhang, J. Paisley:
Markov Mixed Membership Models
International Conference on Machine Learning (ICML), Lille, France, 2015 [PDF]

A. Zhang, J. Zhu, B. Zhang:
Max-margin Infinite Hidden Markov Models
International Conference on Machine Learning (ICML), Beijing, China, 2014 [PDF]

F. Xia, N. Chen, J. Zhu, A. Zhang, X. Jin:
Max-margin Latent Feature Relational Models for Entity-Attribute Networks
International Joint Conference on Neural Networks (IJCNN), Beijing, China, 2014 [PDF]

A. Zhang, J. Zhu, B. Zhang:
Sparse Relational Topic Models for Document Networks
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Prague, Czech Republic, 2013. [PDF]

A. Zhang, J. Zhu, B. Zhang:
Sparse Online Topic Models
International World Wide Web Conference (WWW), Rio de Janeiro, Brazil, 2013 [PDF]


Last update: October 16, 2016