Welcome! I am a PhD student in the Machine Learning Department at the
Carnegie Mellon University, advised by Eric Xing and Pradeep Ravikumar.
I am interested in machine learning, especially graphical models, neural networks, and learning their structures.
- DAGs with NO TEARS: Continuous Optimization for Structure Learning. NIPS 2018. (Spotlight)
Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric Xing.
- State Space LSTM Models with Particle MCMC Inference. Preprint. 2017.
Xun Zheng, Manzil Zaheer, Amr Ahmed, Yuan Wang, Eric Xing, Alex Smola.
- Linear Time Samplers for Supervised Topic Models using Compositional Proposals. ACM KDD 2015.
Xun Zheng, Yaoliang Yu, Eric Xing.
- Minimizing Nonconvex Non-Separable Functions. AISTATS 2015.
Yaoliang Yu, Xun Zheng, Micol Marchetti-Bowick, Eric Xing.
- LightLDA: Big Topic Models on Modest Compute Clusters. WWW 2015.
Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric Xing, Tie-Yan Liu, Wei-Ying Ma.
- Scalable Inference for Logistic-Normal Topic Models. NIPS 2013.
Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang.