Xiang Li

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 29

Top Topics

Data Sparseness

Kernel Learning

Top Venues

Publications

Ganyu Wang, Qingsong Zhang, Xiang Li, Boyu Wang, Bin Gu, Charles X. Ling
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization. Mach. Learn. 113 (9) (2024)
Bin Gu, Ziran Xiong, Xiang Li, Zhou Zhai, Guansheng Zheng
Kernel Path for ν-Support Vector Classification. IEEE Trans. Neural Networks Learn. Syst. 34 (1) (2023)
Zhiyuan Dang, Xiang Li, Bin Gu, Cheng Deng, Heng Huang
Large-Scale Nonlinear AUC Maximization via Triply Stochastic Gradients. IEEE Trans. Pattern Anal. Mach. Intell. 44 (3) (2022)
Bin Gu, Zhou Zhai, Xiang Li, Heng Huang
Towards Fairer Classifier via True Fairness Score Path. CIKM (2022)
Wanli Shi, Bin Gu, Xiang Li, Cheng Deng, Heng Huang
Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification. Mach. Learn. 110 (8) (2021)
Bin Gu, Zhou Zhai, Xiang Li, Heng Huang
Finding Age Path of Self-Paced Learning. ICDM (2021)
Bin Gu, Xiang Geng, Xiang Li, Wanli Shi, Guansheng Zheng, Cheng Deng, Heng Huang
Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients. IEEE Trans. Neural Networks Learn. Syst. 32 (8) (2021)
Wanli Shi, Victor S. Sheng, Xiang Li, Bin Gu
Semi-Supervised Multi-Label Learning from Crowds via Deep Sequential Generative Model. KDD (2020)
Zhou Zhai, Bin Gu, Xiang Li, Heng Huang
Safe Sample Screening for Robust Support Vector Machine. AAAI (2020)
Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data. KDD (2020)
Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data. CoRR (2020)
Wanli Shi, Bin Gu, Xiang Li, Heng Huang
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization. AAAI (2020)
Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang
Scalable Semi-Supervised SVM via Triply Stochastic Gradients. IJCAI (2019)
Zhou Zhai, Bin Gu, Xiang Li, Heng Huang
Safe Sample Screening for Robust Support Vector Machine. CoRR (2019)
Wanli Shi, Bin Gu, Xiang Li, Heng Huang
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization. CoRR (2019)
Bin Gu, Xiang Geng, Xiang Li, Guansheng Zheng
Efficient inexact proximal gradient algorithms for structured sparsity-inducing norm. Neural Networks 118 (2019)
Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization. IJCAI (2019)
Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization. CoRR (2019)
Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang
Scalable Semi-Supervised SVM via Triply Stochastic Gradients. CoRR (2019)
Robert J. Wang, Xiang Li, Shuang Ao, Charles X. Ling
Pelee: A Real-Time Object Detection System on Mobile Devices. ICLR (Workshop) (2018)
Robert J. Wang, Xiang Li, Shuang Ao, Charles X. Ling
Pelee: A Real-Time Object Detection System on Mobile Devices. CoRR (2018)
Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling
The convergence of linear classifiers on large sparse data. Neurocomputing 273 (2018)
Bin Gu, Xingwang Ju, Xiang Li, Guansheng Zheng
Faster Training Algorithms for Structured Sparsity-Inducing Norm. IJCAI (2018)
Shuang Ao, Xiang Li, Charles X. Ling
Fast Generalized Distillation for Semi-Supervised Domain Adaptation. AAAI (2017)
Shuang Ao, Xiang Li, Charles X. Ling
Effective Multiclass Transfer for Hypothesis Transfer Learning. PAKDD (2) (2017)
Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling
Triply Stochastic Gradients on Multiple Kernel Learning. UAI (2017)
Xiang Li, Charles X. Ling, Huaimin Wang
The Convergence Behavior of Naive Bayes on Large Sparse Datasets. ACM Trans. Knowl. Discov. Data 11 (1) (2016)
Xiang Li, Charles X. Ling, Huaimin Wang
The Convergence Behavior of Naive Bayes on Large Sparse Datasets. ICDM (2015)
Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling
Data Sparseness in Linear SVM. IJCAI (2015)
Tao Wang, Huaimin Wang, Gang Yin, Cheng Yang, Xiang Li, Peng Zou
Hierarchical Categorization of Open Source Software by Online Profiles. IEICE Trans. Inf. Syst. (9) (2014)
Yue Yu, Huaimin Wang, Gang Yin, Xiang Li, Cheng Yang
HESA: The Construction and Evaluation of Hierarchical Software Feature Repository. SEKE (2013)
Tao Wang, Huaimin Wang, Gang Yin, Charles X. Ling, Xiang Li, Peng Zou
Mining Software Profile across Multiple Repositories for Hierarchical Categorization. ICSM (2013)
Tao Wang, Gang Yin, Xiang Li, Huaimin Wang
Labeled topic detection of open source software from mining mass textual project profiles. Software Mining (2012)
Xiang Li, Huaimin Wang, Gang Yin, Tao Wang, Cheng Yang, Yue Yu, Dengqing Tang
Inducing Taxonomy from Tags: An Agglomerative Hierarchical Clustering Framework. ADMA (2012)
Xiang Li, Yanxu Zhu, Gang Yin, Tao Wang, Huaimin Wang
Exploiting Attribute Redundancy in Extracting Open Source Forge Websites. CyberC (2012)
Yanxu Zhu, Gang Yin, Xiang Li, Huaimin Wang, Dianxi Shi, Lin Yuan
Exploiting Attribute Redundancy for Web Entity Data Extraction. ICADL (2011)
Yanxu Zhu, Gang Yin, Huaimin Wang, Dianxi Shi, Xiang Li, Lin Yuan
An Indent Shape Based Approach for Web Lists Mining. WISM (2) (2011)
Lin Yuan, Huaimin Wang, Gang Yin, Dianxi Shi, Xiang Li, Bixin Liu
Mining Frequent Development Patterns of roles in Open Source Software. UIC/ATC Workshops (2010)