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Does Head Label Help for Long-Tailed Multi-Label Text Classification


Jan 24, 2021
Lin Xiao, Xiangliang Zhang, Liping Jing, Chi Huang, Mingyang Song

* Accepted by AAAI2021 

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Improving Self-supervised Pre-training via a Fully-Explored Masked Language Model


Oct 14, 2020
Mingzhi Zheng, Dinghan Shen, Yelong Shen, Weizhu Chen, Lin Xiao


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Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation


May 30, 2020
Shoujin Wang, Longbing Cao, Liang Hu, Shlomo Berkovsky, Xiaoshui Huang, Lin Xiao, Wenpeng Lu

* Accepted by IEEE Intelligent Systems 

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Statistical Adaptive Stochastic Gradient Methods


Feb 25, 2020
Pengchuan Zhang, Hunter Lang, Qiang Liu, Lin Xiao


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Understanding the Role of Momentum in Stochastic Gradient Methods


Oct 30, 2019
Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao

* 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada 

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Using Statistics to Automate Stochastic Optimization


Sep 21, 2019
Hunter Lang, Pengchuan Zhang, Lin Xiao


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Multi-Level Composite Stochastic Optimization via Nested Variance Reduction


Aug 29, 2019
Junyu Zhang, Lin Xiao


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A Stochastic Composite Gradient Method with Incremental Variance Reduction


Jun 24, 2019
Junyu Zhang, Lin Xiao


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Hyperbolic Interaction Model For Hierarchical Multi-Label Classification


May 26, 2019
Boli Chen, Xin Huang, Lin Xiao, Zixin Cai, Liping Jing


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Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification


May 24, 2019
Xin Huang, Boli Chen, Lin Xiao, Liping Jing


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SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation


Jun 05, 2018
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song

* 28 pages, 13 figures. To appear at the 35th International Conference on Machine Learning (ICML 2018) 

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Learning SMaLL Predictors


Mar 06, 2018
Vikas K. Garg, Ofer Dekel, Lin Xiao


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DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization


Oct 13, 2017
Lin Xiao, Adams Wei Yu, Qihang Lin, Weizhu Chen


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Stochastic Variance Reduction Methods for Policy Evaluation


Jun 09, 2017
Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou

* Accepted by ICML 2017 

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Variational Gram Functions: Convex Analysis and Optimization


Apr 12, 2017
Amin Jalali, Maryam Fazel, Lin Xiao

* 26 pages, 5 figures, additional revisions to text, under revision in SIOPT, An earlier version of this work has appeared as Chapter 3 in reference [21] 

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Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms


Mar 07, 2017
Jialei Wang, Lin Xiao


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End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture


Nov 01, 2015
Jianshu Chen, Ji He, Yelong Shen, Lin Xiao, Xiaodong He, Jianfeng Gao, Xinying Song, Li Deng

* Proc. NIPS 2015 

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Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization


Sep 09, 2015
Yuchen Zhang, Lin Xiao


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A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming


Mar 21, 2015
Zhaosong Lu, Lin Xiao

* The previous title was "Randomized Block Coordinate Non-Monotone Gradient Method for a Class of Nonlinear Programming" 

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Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss


Jan 01, 2015
Yuchen Zhang, Lin Xiao


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A Proximal Stochastic Gradient Method with Progressive Variance Reduction


Mar 19, 2014
Lin Xiao, Tong Zhang


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Online Classification Using a Voted RDA Method


Oct 17, 2013
Tianbing Xu, Jianfeng Gao, Lin Xiao, Amelia Regan

* 23 pages, 5 figures 

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On the Complexity Analysis of Randomized Block-Coordinate Descent Methods


May 21, 2013
Zhaosong Lu, Lin Xiao

* 26 pages (submitted) 

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A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem


Mar 14, 2012
Lin Xiao, Tong Zhang


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Optimal Distributed Online Prediction using Mini-Batches


Jan 31, 2012
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao

* Final version of paper to appear in Journal of Machine Learning Research (JMLR) 

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Robust Distributed Online Prediction


Dec 07, 2010
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao


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