Linli Xu

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Shuheng Shen, Yifei Cheng, Jingchang Liu, Linli Xu. STL-SGD: Speeding Up Local SGD with Stagewise Communication Period. To appear in Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21). [pdf]

Junliang Guo, Zhirui Zhang, Linli Xu, Hao-Ran Wei, Boxing Chen, Enhong Chen. Incorporating BERT into Parallel Sequence Decoding with Adapters. In Advances in Neural Information Processing Systems 33 (NeurIPS-20). [pdf]

Junliang Guo, Linli Xu, Enhong Chen. Jointly Masked Sequence-to-Sequence Model for Non-Autoregressive Neural Machine Translation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020). [pdf]

Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhng Chen, Tieyan Liu. Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20). [pdf]

Xin Sheng, Linli Xu, Junliang Guo, Jingchang Liu, Ruoyu Zhao, Yinlong Xu. IntroVNMT: An Introspective Model for Variational Neural Machine Translation. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20). [pdf]

Junliang Guo, Linli Xu, Jingchang Liu. SPINE: Structural Identity Preserved Inductive Network Embedding. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-2019). [pdf]

Shuheng Shen, Linli Xu, Jingchang Liu, Xianfeng Liang and Yifei Cheng. Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-2019). [pdf]

Jingchang Liu, Linli Xu, Junliang Guo, Xin Sheng. Adaptive Proximal Average based Variance Reducing Stochastic Methods for Optimization with Composite Regularization. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19). [pdf]

Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tieyan Liu. Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19). [pdf]

Jingchang Liu, Linli Xu, Shuheng Shen, Qing Ling. An Accelerated Variance Reducing Stochastic Method with Douglas-Rachford Splitting. In Machine Learning. [pdf]

Xiaoying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, Enhong Chen. Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach. In Proceedings of the 18th IEEE International Conference on Data Mining (ICDM-2018). [pdf]

Linli Xu, Wenjun Ouyang, Yang Wang, Xiaoying Ren, Liang Jiang. Enhancing Semantic Representations of Bilingual Word Embeddings with Syntactic Dependencies. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-2018). [pdf]

Junliang Guo, Linli Xu, Xunpeng Huang, Enhong Chen. Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective. In Proceedings of the 23rd International Conference on Database Systems for Advanced Applications (DASFAA-2018). [pdf]

Linli Xu, Liang Jiang, Chuan Qin, Zhe Wang, Dongfang Du. How Images Inspire Poems: Generating Classical Chinese Poetry from Images with Memory Networks. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-2018). [pdf]

Linli Xu, Chao Zhang. Bridging Video Content and Comments: Synchronized Video Description with Temporal Summarization of Crowdsourced Time-sync Comments. In Proceedings ofthe 31th AAAI Conference on Artificial Intelligence (AAAI-2017). [pdf]

Linli Xu, Zaiyi Chen, Qi Zhou, Enhong Chen, Nicholas Jing Yuan, Xing Xie. Aligned Matrix Completion: Integrating Consistency and Independency in Multiple Domains. In Proceedings ofthe 16th IEEE International Conference on Data Mining (ICDM-2016). [pdf]

Linli Xu, Qi Zhou, Aiqing Huang, Wenjun Ouyang, Enhong Chen. Feature Selection with Integrated Relevance and Redundancy Optimization. In Proceedings of the 15th IEEE International Conference on Data Mining (ICDM-2015). [pdf]

Liyuan Liu, Linli Xu, Zhen Wang and Enhong Chen. Community Detection Based on Structure and Content: A Content Propagation Perspective. In Proceedings of the 15th IEEE International Conference on Data Mining (ICDM-2015). [pdf]

Yingzi Wang, Nicholas Jing Yuan, Defu Lian, Linli Xu, Xing Xie, Enhong Chen, Yong Rui. Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data. In Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2015). [pdf]

Yitan Li, Linli Xu, Fei Tian, Liang Jiang, Xiaowei Zhong and Enhong Chen. Word Embedding Revisited: A New Representation Learning and Explicit Matrix Factorization Perspective. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI-15). [pdf]

Zaiyi Chen, Linli Xu and Enhong Chen. Selecting Social Media Responses to News: A Convex Framework Based On Data Reconstruction. In Proceedings of the 2015 SIAM International Conference on Data Mining (SDM-15). [pdf]

Linli Xu, Aiqing Huang, Jianhui Chen and Enhong Chen. Exploiting Task-Feature Co-Clusters in Multi-Task Learning. In Proceedings of the 29th National Conference on Artificial Intelligence (AAAI-15). [pdf]

Xiaowei Zhong, Linli Xu, Yitan Li, Zhiyuan Liu and Enhong Chen. A Nonconvex Relaxation Approach for Rank Minimization Problems. In Proceedings of the 29th National Conference on Artificial Intelligence (AAAI-15). [pdf]

Linli Xu, Yitan Li, Yubo Wang and Enhong Chen. Temporally Adaptive Restricted Boltzmann Machine for Background Modeling. In Proceedings of the 29th National Conference on Artificial Intelligence (AAAI-15). [pdf]

Linli Xu, Zhen Wang, Zefan Shen, Yubo Wang and Enhong Chen. Learning Low-Rank Label Correlations for Multi-label Classification with Missing Labels. In Proceedings of the 14th IEEE Conference on Data Mining (ICDM-14). [pdf]

Aiqing Huang, Linli Xu, Yitan Li and Enhong Chen. Robust Dynamic Trajectory Regression on Road Networks: A Multi-Task Learning Framework. In Proceedings of the 14th IEEE Conference on Data Mining (ICDM-14). [pdf]

Yubo Wang, Linli Xu, Yucheng Chen and Hao Wang. A Scalable Approach for General Correlation Clustering. In Proceedings of the 9th International Conference on Advanced Data Mining and Applications (ADMA-13). [pdf]

Tianbao Yang, Prakash Mandaym Comar and Linli Xu. Community Detection by Popularity Based Models for Authored Networked Data. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM-13). [pdf]

Linli Xu, Bo Li and Enhong Chen. Ensemble Pruning via Constrained Eigen-Optimization. In Proceedings of the 12th IEEE Conference on Data Mining (ICDM-12). [pdf]

Junyuan Xie, Linli Xu and Enhong Chen. Image Denoising and Inpainting with Deep Neural Networks. In Advances in Neural Information Processing Systems (NIPS-12). [pdf]

Le Wu, Enhong Chen, Qi Liu, Linli Xu, Tengfei Bao and Lei Zhang. Leveraging Tagging for Neighborhood-aware Probabilistic Matrix Factorization. In Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM-12). [pdf]

Haiping Ma, Enhong Chen, Hui Xiong and Linli Xu. Capturing Correlations of Multiple Labels: A Generative Probabilistic Model for Multi-label Text Data. In Neurocomputing 2012.

Jiming Peng, Lopamudra Mukherjee, Vikas Singh, Dale Schuurmans. and Linli Xu. An Efficient Algorithm for Maximal Margin Clustering. In Journal of Global Optimization. [pdf]

Yaoliang Yu, Min Yang, Linli Xu, Martha White and Dale Schuurmans. Relaxed Clipping: A Global Training Method for Robust Regression and Classification. In Advances in Neural Information Processing Systems (NIPS) 23. [pdf]

Linli Xu, Martha White and Dale Schuurmans. Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning. In Proceedings of the 26th International Conference on Machine Learning (ICML-09). Best Overall Paper Honorable Mention [pdf]

Linli Xu, Wenye Li and Dale Schuurmans. Fast Normalized Cut with Linear Constraints. In Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR-09). [pdf]

Linli Xu (2007). Convex Large Margin Training Techniques for Unsupervised, Semi-supervised and Robust Support Vector Machines. Ph.D. Thesis, School of Computer Science, University of Waterloo.

Linli Xu, Koby Crammer and Dale Schuurmans (2006). Robust Support Vector Machine Training via Convex Outlier Ablation. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-06). [pdf]

Linli Xu, Dana Wilkinson, Finnegan Southey and Dale Schuurmans (2006). Discriminative Unsupervised Learning of Structured Predictors. In Proceedings of the 23rd International Conference on Machine Learning (ICML-06). [pdf]

Linli Xu, Dale Schuurmans (2005). Unsupervised and Semi-supervised Multi-class Support Vector Machines. In Proceedings of the 20th National Conference on Artificial Intelligence (AAAI-05). [pdf]

Linli Xu, James Neufeld, Bryce Larson and Dale Schuurmans (2004). Maximum Margin Clustering. In Advances in Neural Information Processing Systems (NIPS) 17. [pdf]