Analysis of Graph-Based Semi-supervised Regression. - Jin Luo; Hong Chen 004; Yi Tang 003 (FSKD (2), 2008)

Analysis of Classification with a Reject Option. - Hong Chen 004; Luoqing Li; Yuan Yan Tang (Int. J. Wavelets Multiresolution Inf. Process., 2009)

Error bounds of multi-graph regularized semi-supervised classification. - Hong Chen 004; Luoqing Li; Jiangtao Peng (Inf. Sci., 2009)

Semisupervised Multicategory Classification With Imperfect Model. - Hong Chen 004; Luoqing Li (IEEE Trans. Neural Networks, 2009)

Semi-supervised learning based on high density region estimation. - Hong Chen 004; Luoqing Li; Jiangtao Peng (Neural Networks, 2010)

Least Square Regression with coefficient Regularization by Gradient Descent. - Juan Huang; Hong Chen 004; Luoqing Li (Int. J. Wavelets Multiresolution Inf. Process., 2012)

Approximation Analysis of Gradient Descent Algorithm for Bipartite Ranking. - Hong Chen 004; Fangchao He; Zhibin Pan (J. Appl. Math., 2012)

Generalization performance of support vector classifiers for density level detection. - Hong Chen 004; Yicong Zhou; Yi Tang 003; Yuan Yan Tang; Zhibin Pan (Neurocomputing, 2013)

Generalization performance of magnitude-preserving semi-supervised ranking with graph-based regularization. - Zhibin Pan; Xinge You; Hong Chen 004; Dacheng Tao; Baochuan Pang (Inf. Sci., 2013)

Error Analysis of Coefficient-Based Regularized Algorithm for Density-Level Detection. - Hong Chen 004; Zhibin Pan; Luoqing Li; Yuan Yan Tang (Neural Comput., 2013)

Convergence rate of the semi-supervised greedy algorithm. - Hong Chen 004; Yicong Zhou; Yuan Yan Tang; Luoqing Li; Zhibin Pan (Neural Networks, 2013)

Error Analysis of Stochastic Gradient Descent Ranking. - Hong Chen 004; Yi Tang 003; Luoqing Li; Yuan Yuan 001; Xuelong Li 001; Yuan Yan Tang (IEEE Trans. Cybern., 2013)

Learning performance of coefficient-based regularized ranking. - Hong Chen 004; Zhibin Pan; Luoqing Li (Neurocomputing, 2014)

Statistical analysis of the moving least-squares method with unbounded sampling. - Fangchao He; Hong Chen 004; Luoqing Li (Inf. Sci., 2014)

Extreme learning machine for ranking: Generalization analysis and applications. - Hong Chen 004; Jiangtao Peng; Yicong Zhou; Luoqing Li; Zhibin Pan (Neural Networks, 2014)

Generalization ability of extreme learning machine with uniformly ergodic Markov chains. - Peipei Yuan; Hong Chen 004; Yicong Zhou; Xiaoyan Deng; Bin Zou 002 (Neurocomputing, 2015)

Error Analysis of Generalized Nyström Kernel Regression. - Hong Chen 004; Haifeng Xia; Heng Huang; Weidong Cai 001 (NIPS, 2016)

Stability analysis for ranking with stationary φ-mixing samples. - Fangchao He; Ling Zuo; Hong Chen 004 (Neurocomputing, 2016)

Example-based super-resolution via social images. - Yi Tang 003; Hong Chen 004; Zhanwen Liu; Biqin Song; Qi Wang 009 (Neurocomputing, 2016)

Generalization Performance of Regularized Ranking With Multiscale Kernels. - Yicong Zhou; Hong Chen 004; Rushi Lan; Zhibin Pan (IEEE Trans. Neural Networks Learn. Syst., 2016)

Group Sparse Additive Machine. - Hong Chen 004; Xiaoqian Wang 001; Cheng Deng; Heng Huang (NIPS, 2017)

Regularized Modal Regression with Applications in Cognitive Impairment Prediction. - Xiaoqian Wang 001; Hong Chen 004; Weidong Cai 001; Dinggang Shen; Heng Huang (NIPS, 2017)

Modal Regression based Atomic Representation for Robust Face Recognition. - Yulong Wang 002; Yuan Yan Tang; Luoqing Li; Hong Chen 004 (CoRR, 2017)

Generalization Analysis of Fredholm Kernel Regularized Classifiers. - Tieliang Gong; Zongben Xu; Hong Chen 004 (Neural Comput., 2017)

Ideal Regularized Composite Kernel for Hyperspectral Image Classification. - Jiangtao Peng; Hong Chen 004; Yicong Zhou; Luoqing Li (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017)

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks. - Xiaoqian Wang 001; Hong Chen 004; Jingwen Yan; Kwangsik Nho; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Heng Huang (Bioinform., 2018)

Robust Variable Selection and Estimation Based on Kernel Modal Regression. - Changying Guo; Biqin Song; Yingjie Wang 007; Hong Chen 004; Huijuan Xiong (Entropy, 2019)

Error analysis of distributed least squares ranking. - Hong Chen 004; Han Li; Zhibin Pan (Neurocomputing, 2019)

Regularized modal regression with data-dependent hypothesis spaces. - Yingjie Wang 007; Hong Chen 004; Biqin Song; Han Li (Int. J. Wavelets Multiresolution Inf. Process., 2019)

Atomic Representation-Based Classification: Theory, Algorithm, and Applications. - Yulong Wang 002; Yuan Yan Tang; Luoqing Li; Hong Chen 004; Jianjia Pan (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Sparse Shrunk Additive Models. - Guodong Liu; Hong Chen 004; Heng Huang (ICML, 2020)

Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery. - Yingjie Wang 007; Hong Chen 004; Feng Zheng; Chen Xu 007; Tieliang Gong; Yanhong Chen (NeurIPS, 2020)

Optimal Margin Distribution Additive Machine. - Changying Guo; Hao Deng; Hong Chen 004 (IEEE Access, 2020)

Modal regression based greedy algorithm for robust sparse signal recovery, clustering and classification. - Yulong Wang 002; Yuan Yan Tang; Cuiming Zou; Luoqing Li; Hong Chen 004 (Neurocomputing, 2020)

Group sparse additive machine with average top-k loss. - Peipei Yuan; Xinge You; Hong Chen 004; Qinmu Peng; Yue Zhao; Zhou Xu 003; Xiao-Yuan Jing; Zhenyu He 001 (Neurocomputing, 2020)

Modal additive models with data-driven structure identification. - Tieliang Gong; Chen Xu 007; Hong Chen 004 (Math. Found. Comput., 2020)

Modal Regression-Based Atomic Representation for Robust Face Recognition and Reconstruction. - Yulong Wang 002; Yuan Yan Tang; Luoqing Li; Hong Chen 004 (IEEE Trans. Cybern., 2020)

Distributed Ranking with Communications: Approximation Analysis and Applications. - Hong Chen 004; Yingjie Wang 007; Yulong Wang 002; Feng Zheng (AAAI, 2021)

Computationally Efficient Approximations for Matrix-based Renyi's Entropy. - Tieliang Gong; Yuxin Dong; Shujian Yu; Hong Chen 004; Bo Dong 001; Chen Li 011; Qinghua Zheng (CoRR, 2021)

Learning performance of LapSVM based on Markov subsampling. - Tieliang Gong; Hong Chen 004; Chen Xu 007 (Neurocomputing, 2021)

Sparse additive machine with pinball loss. - Yingjie Wang 007; Xin Tang; Hong Chen 004; Tianjiao Yuan; Yanhong Chen; Han Li (Neurocomputing, 2021)

Sparse Modal Additive Model. - Hong Chen 004; Yingjie Wang 007; Feng Zheng; Cheng Deng; Heng Huang (IEEE Trans. Neural Networks Learn. Syst., 2021)

Regularized Modal Regression on Markov-Dependent Observations: A Theoretical Assessment. - Tieliang Gong; Yuxin Dong; Hong Chen 004; Wei Feng 010; Bo Dong 001; Chen Li 011 (AAAI, 2022)

Error-Based Knockoffs Inference for Controlled Feature Selection. - Xuebin Zhao; Hong Chen 004; Yingjie Wang 007; Weifu Li; Tieliang Gong; Yulong Wang 002; Feng Zheng (AAAI, 2022)

Huber Additive Models for Non-stationary Time Series Analysis. - Yingjie Wang 007; Xianrui Zhong; Fengxiang He; Hong Chen 004; Dacheng Tao (ICLR, 2022)

Distribution-dependent feature selection for deep neural networks. - Xuebin Zhao; Weifu Li; Hong Chen 004; Yingjie Wang 007; Yanhong Chen; Vijay John (Appl. Intell., 2022)

Global Weighted Tensor Nuclear Norm for Tensor Robust Principal Component Analysis. - Libin Wang; Yulong Wang 002; Shiyuan Wang; Youheng Liu; Yutao Hu; Longlong Chen; Hong Chen 004 (CoRR, 2022)

A General Loss-Based Nonnegative Matrix Factorization for Hyperspectral Unmixing. - Jiangtao Peng; Weiwei Sun 005; Fan Jiang; Hong Chen 004; Yicong Zhou; Qian Du 001 (IEEE Geosci. Remote. Sens. Lett., 2022)

Generalized and Discriminative Collaborative Representation for Multiclass Classification. - Yulong Wang 002; Yap-Peng Tan; Yuan Yan Tang; Hong Chen 004; Cuiming Zou; Luoqing Li (IEEE Trans. Cybern., 2022)

On the Stability and Generalization of Triplet Learning. - Jun Chen; Hong Chen 004; Xue Jiang; Bin Gu 001; Weifu Li; Tieliang Gong; Feng Zheng (AAAI, 2023)

Robust and Fast Measure of Information via Low-Rank Representation. - Yuxin Dong; Tieliang Gong; Shujian Yu; Hong Chen 004; Chen Li 011 (AAAI, 2023)

Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning. - Jiahuan Wang; Jun Chen; Hong Chen 004; Bin Gu 001; Weifu Li; Xin Tang (AAAI, 2023)

Tilted Sparse Additive Models. - Yingjie Wang 007; Hong Chen 004; Weifeng Liu 001; Fengxiang He; Tieliang Gong; Youcheng Fu; Dacheng Tao (ICML, 2023)

Detecting Out-of-distribution Data through In-distribution Class Prior. - Xue Jiang; Feng Liu 003; Zhen Fang 001; Hong Chen 004; Tongliang Liu; Feng Zheng; Bo Han 003 (ICML, 2023)

Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Rényi's Entropy Perspective. - Yuxin Dong; Tieliang Gong; Hong Chen 004; Chen Li 011 (IJCAI, 2023)

Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization. - Jun Chen; Hong Chen 004; Bin Gu 001; Hao Deng (NeurIPS, 2023)

Simultaneous Robust Matching Pursuit for Multi-view Learning. - Yulong Wang 002; Kit Ian Kou; Hong Chen 004; Yuan Yan Tang; Luoqing Li (Pattern Recognit., 2023)

Double Auto-Weighted Tensor Robust Principal Component Analysis. - Yulong Wang 002; Kit Ian Kou; Hong Chen 004; Yuan Yan Tang; Luoqing Li (IEEE Trans. Image Process., 2023)

Robust partially linear models for automatic structure discovery. - Yuxiang Han; Hong Chen 004; Tieliang Gong; Jia Cai; Hao Deng (Expert Syst. Appl., 2023)

Robust variable structure discovery based on tilted empirical risk minimization. - Xuelin Zhang; Yingjie Wang 007; Liangxuan Zhu; Hong Chen 004; Han Li; Lingjuan Wu (Appl. Intell., 2023)

Attention reweighted sparse subspace clustering. - Libin Wang; Yulong Wang 002; Hao Deng; Hong Chen 004 (Pattern Recognit., 2023)

PTQ4SAM: Post-Training Quantization for Segment Anything. - Chengtao Lv; Hong Chen 004; Jinyang Guo; Yifu Ding; Xianglong Liu 001 (CVPR, 2024)

Generalized Sparse Additive Model with Unknown Link Function. - Peipei Yuan; Xinge You; Hong Chen 004; Xuelin Zhang; Qinmu Peng (ICDM, 2024)

Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds. - Yuxin Dong; Tieliang Gong; Hong Chen 004; Shujian Yu; Chen Li 011 (ICLR, 2024)

Negative Label Guided OOD Detection with Pretrained Vision-Language Models. - Xue Jiang; Feng Liu 003; Zhen Fang 001; Hong Chen 004; Tongliang Liu; Feng Zheng; Bo Han 003 (ICLR, 2024)

General Stability Analysis for Zeroth-Order Optimization Algorithms. - Xinyue Liu; Hualin Zhang; Bin Gu 001; Hong Chen 004 (ICLR, 2024)

Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective. - Yuxin Dong; Tieliang Gong; Hong Chen 004; Zhongjiang He; Mengxiang Li; Shuangyong Song; Chen Li 011 (ICML, 2024)

Towards Sharper Generalization Bounds for Adversarial Contrastive Learning. - Wen Wen; Han Li; Tieliang Gong; Hong Chen 004 (IJCAI, 2024)

Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization. - Xuelin Zhang; Hong Chen 004; Bin Gu 001; Tieliang Gong; Feng Zheng (IJCAI, 2024)

Asynchronous Vertical Federated Learning for Kernelized AUC Maximization. - Ke Zhang; Ganyu Wang; Han Li; Yulong Wang 002; Hong Chen 004; Bin Gu 001 (KDD, 2024)

How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization? - Jun Chen; Hong Chen 004; Bin Gu 001 (NeurIPS, 2024)

Error Density-dependent Empirical Risk Minimization. - Hong Chen 004; Xuelin Zhang; Tieliang Gong; Bin Gu 001; Feng Zheng (Expert Syst. Appl., 2024)

Robust multi-view learning via M-estimator joint sparse representation. - Yutao Hu; Yulong Wang 002; Han Li; Hong Chen 004 (Pattern Recognit., 2024)

A Bayesian Federated Learning Framework With Online Laplace Approximation. - Liangxi Liu; Xi Jiang 009; Feng Zheng; Hong Chen 004; Guo-Jun Qi; Heng Huang; Ling Shao 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Markov Subsampling Based on Huber Criterion. - Tieliang Gong; Yuxin Dong; Hong Chen 004; Bo Dong 001; Chen Li 011 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Gradient Learning With the Mode-Induced Loss: Consistency Analysis and Applications. - Hong Chen 004; Youcheng Fu; Xue Jiang; Yanhong Chen; Weifu Li; Yicong Zhou; Feng Zheng (IEEE Trans. Neural Networks Learn. Syst., 2024)

Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent. - Jun Chen; Hong Chen 004; Bin Gu 001; Guodong Liu; Yingjie Wang 007; Weifu Li (AAAI, 2025)

Towards Generalization Bounds of GCNs for Adversarially Robust Node Classification. - Wen Wen; Han Li; Tieliang Gong; Hong Chen 004 (ICLR, 2025)

TSGaussian: Semantic and depth-guided Target-Specific Gaussian Splatting from sparse views. - Liang Zhao; Zehan Bao; Yi Xie; Hong Chen 004; Yaohui Chen 002; Weifu Li (Image Vis. Comput., 2025)

Tensor Nuclear Norm-Based Multi-Channel Atomic Representation for Robust Face Recognition. - Yutao Hu; Yulong Wang 002; Libin Wang; Han Li; Hong Chen 004; Yuan Yan Tang (IEEE Trans. Image Process., 2025)

Efficient Approximations for Matrix-Based Rényi's Entropy on Sequential Data. - Yuxin Dong; Tieliang Gong; Hong Chen 004; Chen Li 011 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Sparse Additive Machine With the Correntropy-Induced Loss. - Peipei Yuan; Xinge You; Hong Chen 004; Yingjie Wang 007; Qinmu Peng; Bin Zou 002 (IEEE Trans. Neural Networks Learn. Syst., 2025)

How Does Distribution Matching Help Domain Generalization: An Information-Theoretic Analysis. - Yuxin Dong; Tieliang Gong; Hong Chen 004; Shuangyong Song; Weizhan Zhang; Chen Li 011 (IEEE Trans. Inf. Theory, 2025)

Clustering-Guided Multi-Layer Contrastive Representation Learning for Citrus Disease Classification. - Jun Chen; Yonghua Yu; Weifu Li; Yaohui Chen 002; Hong Chen 004 (CoRR, 2025)

Generalization Bounds of Deep Neural Networks With τ-Mixing Samples. - Liyuan Liu; Yaohui Chen 002; Weifu Li; Yingjie Wang 007; Bin Gu 001; Feng Zheng; Hong Chen 004 (IEEE Trans. Neural Networks Learn. Syst., 2025)