Research

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
Neural Information Processing Systems (NIPS 2014)

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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
International World Wide Web Conference (WWW 2015)

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Litz: An Elastic Framework for High-Performance Distributed Machine Learning

Aurick Qiao, Abutalib Aghayev, Weiren Yu, Haoyang Chen, Qirong Ho, Garth A. Gibson, Eric P. Xing
USENIX Annual Technical Conference (ATC 2018)

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Toward Understanding the Impact of Staleness in Distributed Machine Learning

Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric Xing
International Conference on Learning Representations (ICLR 2019)

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Fault Tolerance in Iterative-Convergent Machine Learning

Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing
International Conference on Machine Learning (ICML 2019)

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Cavs: An Efficient Runtime System for Dynamic Neural Networks

Shizhen Xu, Hao Zhang, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P Xing
2018 USENIX Annual Technical Conference (USENIX ATC 18)

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Science Question Answering using Instructional Materials

Mrinmaya Sachan and Eric P. Xing
Annual Meeting of the Association for Computational Linguistics (ACL 2016)

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Learning Concept Taxonomies from Multi-modal Data

Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan, Eric P. Xing
Annual Meeting of the Association for Computational Linguistics (ACL 2016)

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Grounding Topic Models with Knowledge Bases

Zhiting Hu, Gang Luo, Mrinmaya Sachan, Zaiqing Nie and Eric P. Xing
International Joint Conference on Artificial Intelligence (IJCAI 2016)

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A Constituent-Centric Neural Architecture for Reading Comprehension. 

Pengtao Xie and Eric P. Xing
Annual Meeting of the Association for Computational Linguistics (ACL 2017)

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Uncorrelation and Evenness: A New Diversity-Promoting Regularizer

Pengtao Xie, Aarti Singh and Eric P. Xing
International Conference on Machine Learning (ICML 2017)

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Learning Latent Space Models with Angular Constraints

Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou, Eric P. Xing
International Conference on Machine Learning (ICML 2017)

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Toward Controlled Generation of Text

Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing
International Conference on Machine Learning (ICML 2017)

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Improved Variational Autoencoders for Text Modeling using Dilated Convolutions

Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, Taylor Berg-Kirkpatrick
International Conference on Machine Learning (ICML 2017)

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Near-Orthogonality Regularization in Kernel Methods

Pengtao Xie, Barnabas Poczos, Eric P. Xing
Conference on Uncertainty in Artificial Intelligence (UAI 2017)

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Efficient Correlated Topic Modeling with Topic Embedding

Zhiting Hu, Junxian He, Taylor Berg-Kirkpatrick, Ying Huang, Eric P. Xing
SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017)

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Deep Determinantal Point Process for Large-Scale Multi-Label Classification

Pengtao Xie, Ruslan Salakhutdinov, Luntian Mou and Eric P. Xing
International Conference on Computer Vision (ICCV 2017)

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Recurrent Topic-Transition GAN for Visual Paragraph Generation

Xiaodan Liang, Zhiting Hu, Hao Zhang, Chuang Gan, Eric P. Xing
International Conference on Computer Vision (ICCV 2017)

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Nonparametric Variational Auto-encoders for Hierarchical Representation Learning

Prasoon Goyal, Zhiting Hu, Xiaodan Liang, Chenyu Wang, Eric P. Xing
International Conference on Computer Vision (ICCV 2017)

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Structured Generative Adversarial Networks

Hao Zhang, Zhijie Deng, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, and Eric P. Xing
Conference on Neural Information Processing Systems (NeurIPS 2017)

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Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis

Pengtao Xie, Wei Wu, Yichen Zhu, Eric P. Xing
International Conference on Machine Learning (ICML 2018)

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Nonoverlap-Promoting Variable Selection

Pengtao Xie, Hongbao Zhang, Yichen Zhu, Eric P. Xing
International Conference on Machine Learning (ICML 2018)

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Generative Semantic Manipulation with Mask-Contrasting GAN

Xiaodan Liang, Hao Zhang, Eric P. Xing
European Conference on Computer Vision (ECCV 2018)

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Symbolic Graph Reasoning Meets Convolutions

Xiadon Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P. Xing
Conference on Neural Information Processing Systems (NeurIPS 2018)

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Deep Generative Models with Learnable Knowledge Constraints

Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric P. Xing
Conference on Neural Information Processing Systems (NeurIPS 2018)

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Unsupervised Text Style Transfer using Language Models as Discriminators

Zichao Yang, Zhiting Hu, Chris Dyer, Eric P. Xing, Taylor Berg-Kirkpatrick
Conference on Neural Information Processing Systems (NeurIPS 2018)

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AutoLoss: Learning Discrete Schedules for Alternate Optimization

Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing
International Conference on Learning Representations (ICLR 2019)

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Connecting the Dots Between MLE and RL for Sequence Generation

Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
International Conference on Machine Learning (ICML 2019)

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Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation

Zhiting Hu, Haoran Shi, Zichao Yang, Bowen Tan, Tiancheng Zhao, Junxian He, Wentao Wang, Xingjiang Yu, Lianhui Qin, Di Wang, Xuezhe Ma, Hector Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing

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Toward Unsupervised Text Content Manipulation

Zhiting Hu, Wentao Wang, Zichao Yang, Haoran Shi, Frank Xu, Eric Xing 

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