Multiple Gaussian graphical estimation with jointly sparse penalty. - Qinghua Tao; Xiaolin Huang; Shuning Wang; Xiangming Xi; Li Li 013 (Signal Process., 2016)

Adaptive block coordinate DIRECT algorithm. - Qinghua Tao; Xiaolin Huang; Shuning Wang; Li Li 013 (J. Glob. Optim., 2017)

Fast Adaptive Hinging Hyperplanes. - Qinghua Tao; Jun Xu 008; Johan A. K. Suykens; Shuning Wang (CDC, 2018)

An Improved Coordinate Update Method for the Identification of Adaptive Hinging Hyperplanes Model. - Qinghua Tao; Jun Xu 008; Shuning Wang; Li Li 013 (ICCAE, 2018)

Tensor-based Cooperative Control for Large Scale Multi-intersection Traffic Signal Using Deep Reinforcement Learning and Imitation Learning. - Yusen Huo; Qinghua Tao; Jianming Hu (CoRR, 2019)

Cooperative Control for Multi-Intersection Traffic Signal Based on Deep Reinforcement Learning and Imitation Learning. - Yusen Huo; Qinghua Tao; Jianming Hu (IEEE Access, 2020)

Efficient hinging hyperplanes neural network and its application in nonlinear system identification. - Jun Xu 008; Qinghua Tao; Zhen Li 032; Xiangming Xi; Johan A. K. Suykens; Shuning Wang (Autom., 2020)

Noncyclic Scheduling of Multi-cluster Tools with Multi-type Wafers Based on Pareto Optimization. - Yuanyuan Yan; Qinghua Tao; Huangang Wang; Wenhui Fan (ICCAE, 2021)

Going Far Boosts Attack Transferability, but Do Not Do It. - Sizhe Chen; Qinghua Tao; Zhixing Ye; Xiaolin Huang (CoRR, 2021)

Train Deep Neural Networks in 40-D Subspaces. - Tao Li 054; Lei Tan; Qinghua Tao; Yipeng Liu 001; Xiaolin Huang (CoRR, 2021)

QueryNet: An Efficient Attack Framework with Surrogates Carrying Multiple Identities. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Xiaolin Huang (CoRR, 2021)

Learning with continuous piecewise linear decision trees. - Qinghua Tao; Zhen Li 032; Jun Xu 008; Na Xie; Shuning Wang; Johan A. K. Suykens (Expert Syst. Appl., 2021)

Distributed Cooperative Driving in Multi-Intersection Road Networks. - Huaxin Pei; Yi Zhang 029; Qinghua Tao; Shuo Feng 002; Li Li 013 (IEEE Trans. Veh. Technol., 2021)

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Yingwen Wu; Cihang Xie; Xiaolin Huang (NeurIPS, 2022)

Trainable Weight Averaging for Fast Convergence and Better Generalization. - Tao Li 054; Zhehao Huang; Qinghua Tao; Yingwen Wu; Xiaolin Huang (CoRR, 2022)

Piecewise Linear Neural Networks and Deep Learning. - Qinghua Tao; Li Li 013; Xiaolin Huang; Xiangming Xi; Shuning Wang; Johan A. K. Suykens (CoRR, 2022)

Short-Term Traffic Flow Prediction Based on the Efficient Hinging Hyperplanes Neural Network. - Qinghua Tao; Zhen Li 032; Jun Xu 008; Shu Lin 002; Bart De Schutter; Johan A. K. Suykens (IEEE Trans. Intell. Transp. Syst., 2022)

Center-Aware Adversarial Autoencoder for Anomaly Detection. - Daoming Li; Qinghua Tao; Jiahao Liu; Huangang Wang (IEEE Trans. Neural Networks Learn. Syst., 2022)

Toward Deep Adaptive Hinging Hyperplanes. - Qinghua Tao; Jun Xu 008; Zhen Li 032; Na Xie; Shuning Wang; Xiaoli Li 011; Johan A. K. Suykens (IEEE Trans. Neural Networks Learn. Syst., 2022)

Measuring the Transferability of ℓ∞ Attacks by the ℓ2 Norm. - Sizhe Chen; Qinghua Tao; Zhixing Ye; Xiaolin Huang (ICASSP, 2023)

Tensorized LSSVMS For Multitask Regression. - Jiani Liu 002; Qinghua Tao; Ce Zhu; Yipeng Liu 001; Johan A. K. Suykens (ICASSP, 2023)

Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions. - Tao Li 054; Zhehao Huang; Qinghua Tao; Yingwen Wu; Xiaolin Huang (ICLR, 2023)

Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation. - Yingyi Chen; Qinghua Tao; Francesco Tonin; Johan A. K. Suykens (NeurIPS, 2023)

Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nyström method. - Qinghua Tao; Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (CoRR, 2023)

Low-Rank Multitask Learning based on Tensorized SVMs and LSSVMs. - Jiani Liu 002; Qinghua Tao; Ce Zhu; Yipeng Liu 001; Xiaolin Huang; Johan A. K. Suykens (CoRR, 2023)

Jigsaw-ViT: Learning jigsaw puzzles in vision transformer. - Yingyi Chen; Xi Shen 001; Yahui Liu; Qinghua Tao; Johan A. K. Suykens (Pattern Recognit. Lett., 2023)

Low Dimensional Trajectory Hypothesis is True: DNNs Can Be Trained in Tiny Subspaces. - Tao Li 054; Lei Tan; Zhehao Huang; Qinghua Tao; Yipeng Liu 001; Xiaolin Huang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Sparsity via Sparse Group k-max Regularization. - Qinghua Tao; Xiangming Xi; Jun Xu 008; Johan A. K. Suykens (ACC, 2024)

Feature Learning using Multi-view Kernel Partial Least Squares. - Xinjie Zeng; Qinghua Tao; Johan A. K. Suykens (ESANN, 2024)

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes. - Yingyi Chen; Qinghua Tao; Francesco Tonin; Johan A. K. Suykens (ICML, 2024)

Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method. - Qinghua Tao; Francesco Tonin; Alex Lambert; Yingyi Chen; Panagiotis Patrinos; Johan A. K. Suykens (ICML, 2024)

Kernel PCA for Out-of-Distribution Detection. - Kun Fang 004; Qinghua Tao; Kexin Lv; Mingzhen He; Xiaolin Huang; Jie Yang 002 (NeurIPS, 2024)

DDoS: Diffusion Distribution Similarity for Out-of-Distribution Detection. - Kun Fang 004; Qinghua Tao; Zuopeng Yang; Xiaolin Huang; Jie Yang 002 (CoRR, 2024)

Tensor-based multi-view spectral clustering via shared latent space. - Qinghua Tao; Francesco Tonin; Panagiotis Patrinos; Johan A. K. Suykens (Inf. Fusion, 2024)

Deep Kernel Principal Component Analysis for multi-level feature learning. - Francesco Tonin; Qinghua Tao; Panagiotis Patrinos; Johan A. K. Suykens (Neural Networks, 2024)

Towards robust neural networks via orthogonal diversity. - Kun Fang 004; Qinghua Tao; Yingwen Wu; Tao Li 054; Jia Cai; Feipeng Cai; Xiaolin Huang; Jie Yang 002 (Pattern Recognit., 2024)

Revisiting Random Weight Perturbation for Efficiently Improving Generalization. - Tao Li 054; Qinghua Tao; Weihao Yan; Yingwen Wu; Zehao Lei; Kun Fang 004; Mingzhen He; Xiaolin Huang (Trans. Mach. Learn. Res., 2024)

Query Attack by Multi-Identity Surrogates. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Xiaolin Huang (IEEE Trans. Artif. Intell., 2024)

Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective. - Kun Fang 004; Qinghua Tao; Xiaolin Huang; Jie Yang 002 (Int. J. Comput. Vis., 2024)

Multi-head ensemble of smoothed classifiers for certified robustness. - Kun Fang 004; Qinghua Tao; Yingwen Wu; Tao Li 054; Xiaolin Huang; Jie Yang 002 (Neural Networks, 2025)

From Dense to Sparse: Event Response for Enhanced Residential Load Forecasting. - Xin Cao; Qinghua Tao; Yingjie Zhou 001; Lu Zhang 063; Le Zhang 001; Dongjin Song; Dapeng Oliver Wu; Ce Zhu (IEEE Trans. Instrum. Meas., 2025)

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations. - Kun Fang 004; Qinghua Tao; Mingzhen He; Kexin Lv; Runze Yang; Haibo Hu; Xiaolin Huang; Jie Yang 002; Longbing Cao (CoRR, 2025)