Xun Zheng

According to our database, Xun Zheng authored at least 25 papers between 2011 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Learning DAGs with Continuous Optimization.

Xun Zheng

PhD thesis, 2021

Role of the AlGaN Cap Layer on the Trapping Behaviour of N-Polar GaN MISHEMTs.

Francesca Chiocchetta, Claudia Calascione, Carlo De Santi, Chandan Sharma, Fabiana Rampazzo, Xun Zheng, Brian Romanczyk, Matthew Guidry, Haoran Li, Stacia Keller, Umesh K. Mishra, Gaudenzio Meneghesso, Matteo Meneghini, Enrico Zanoni

Proceedings of the IEEE International Reliability Physics Symposium, 2021

2020

SimClusters: Community-Based Representations for Heterogeneous Recommendations at Twitter.

Venu Satuluri, Yao Wu, Xun Zheng, Yilei Qian, Brian Wichers, Qieyun Dai, Gui Ming Tang, Jerry Jiang, Jimmy Lin

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Learning Sparse Nonparametric DAGs.

Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Virtual-Source Modeling of N-polar GaN MISHEMTS.

Rohit R. Karnaty, Umesh K. Mishra, James F. Buckwalter, Matthew Guidry, Pawana Shrestha, Brian Romanczyk, Nirupam Hatui, Xun Zheng, Christian Wurm, Haoran Li, Stacia Keller

Proceedings of the 2019 IEEE BiCMOS and Compound semiconductor Integrated Circuits and Technology Symposium (BCICTS), 2019

2018

Learning Tensor Latent Features.

Sung-En Chang, Xun Zheng, Ian En-Hsu Yen, Pradeep Ravikumar, Rose Yu

CoRR, 2018

DAGs with NO TEARS: Smooth Optimization for Structure Learning.

Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

CoRR, 2018

DAGs with NO TEARS: Continuous Optimization for Structure Learning.

Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

State Space LSTM Models with Particle MCMC Inference.

Xun Zheng, Manzil Zaheer, Amr Ahmed, Yuan Wang, Eric P. Xing, Alexander J. Smola

CoRR, 2017

2016

STRADS: a distributed framework for scheduled model parallel machine learning.

Jin Kyu Kim, Qirong Ho, Seunghak Lee, Xun Zheng, Wei Dai, Garth A. Gibson, Eric P. Xing

Proceedings of the Eleventh European Conference on Computer Systems, 2016

2015

Petuum: A New Platform for Distributed Machine Learning on Big Data.

Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu

IEEE Trans. Big Data, 2015

LightLDA: Big Topic Models on Modest Computer Clusters.

Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric Poe Xing, Tie-Yan Liu, Wei-Ying Ma

Proceedings of the 24th International Conference on World Wide Web, 2015

Linear Time Samplers for Supervised Topic Models using Compositional Proposals.

Xun Zheng, Yaoliang Yu, Eric P. Xing

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Minimizing Nonconvex Non-Separable Functions.

Yaoliang Yu, Xun Zheng, Micol Marchetti-Bowick, Eric P. Xing

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Model-Parallel Inference for Big Topic Models.

Xun Zheng, Jin Kyu Kim, Qirong Ho, Eric P. Xing

CoRR, 2014

LightLDA: Big Topic Models on Modest Compute Clusters.

Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma

CoRR, 2014

Primitives for Dynamic Big Model Parallelism.

Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing

CoRR, 2014

On Model Parallelization and Scheduling Strategies for Distributed Machine Learning.

Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Consistent Bounded-Asynchronous Parameter Servers for Distributed ML.

Jinliang Wei, Wei Dai, Abhimanu Kumar, Xun Zheng, Qirong Ho, Eric P. Xing

CoRR, 2013

Petuum: A Framework for Iterative-Convergent Distributed ML.

Wei Dai, Jinliang Wei, Xun Zheng, Jin Kyu Kim, Seunghak Lee, Junming Yin, Qirong Ho, Eric P. Xing

CoRR, 2013

Scalable Inference for Logistic-Normal Topic Models.

Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Scalable inference in max-margin topic models.

Jun Zhu, Xun Zheng, Li Zhou, Bo Zhang

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Improved Bayesian Logistic Supervised Topic Models with Data Augmentation.

Jun Zhu, Xun Zheng, Bo Zhang

Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, 2013

2012

China's railways energy saving: Current status and development trends.

Xiaoming Xu, Keping Li, Xun Zheng, Le Zhao

Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, 2012

2011

A Case Study on Design of Teacher Peer-Coaching Activities Supported by a Web 2.0 Community.

Shuang Li, Hongtao Sun, Xun Zheng

Proceedings of the Hybrid Learning - 4th International Conference, 2011