Selected Publications

Preprints

Fanghui Liu, Xiaolin Huang, Yudong Chen, and Johan A.K. Suykens. Random features for kernel approximation: A Survey on algorithms, theory, and beyond. paper, code
Fanghui Liu, Xiaolin Huang, Yudong Chen, and Johan A.K. Suykens. Towards a unified quadrature framework for large scale kernel methods,. paper
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, and Johan A.K. Suykens. Regularized regression problem in hyper-RKHS for learning kernels. paper

Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, and Johan A.K. Suykens. Analysis of least squares regularized regression in reproducing kernel Krein spaces, Machine Learning. paper
Fanghui Liu, Zhenyu Liao, and Johan A.K. Suykens. Kernel regression in high dimensions: Refined analysis beyond double descent, AISTATS-2021. paper, code.
Fanghui Liu, Xiaolin Huang, Yingyi Chen, and Johan A.K. Suykens. Fast Learning in Reproducing Kernel Krein Spaces via Generalized Measures, AISTATS-2021. paper, code.

Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, and Li Li. Learning data-adaptive nonparametric kernels, Journal of Machine Learning Research (JMLR). paper, code.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, and Johan A.K. Suykens. Random Fourier features via fast surrogate leverage weighted sampling, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20). paper, code.
Fanghui Liu, Xiaolin Huang, Lei Shi, Jie Yang, and Johan A.K. Suykens. A double-variational Bayesian framework in random Fourier features for indefinite kernels, IEEE Transactions on Neural Networks and Learning Systems (TNNLS). paper, code.

Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, and Johan A.K. Suykens. Indefinite kernel logistic regression with Concave-inexact-convex procedure, IEEE Transactions on Neural Networks and Learning Systems (TNNLS). paper, code.
Fanghui Liu, Chen Gong, Xiaolin Huang, Tao Zhou, Jie Yang, and Dacheng Tao. Robust visual tracking revisited: from correlation filter to template matching, IEEE Transactions on Image Processing (TIP). paper
Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, and Li Li: Nonlinear pairwise layer and Its training for kernel learning, The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). paper, code.
Tao Zhou, Fanghui Liu, H. Bhaskar and Jie Yang. Robust visual tracking via online discriminative and low-rank dictionary learning. IEEE Transactions on Cybernetics (TCYB). paper

Fanghui Liu, Chen Gong, Tao Zhou, Keren Fu, Xiangjian He, and Jie Yang. Robust visual tracking via nonnegative multiple linear coding, IEEE Transactions on Multimedia (TMM). paper
Fanghui Liu, Tao Zhou, Chen Gong, Keren Fu, Li Bai and Jie Yang. Inverse nonnegative local coordinate factorization for visual tracking, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). paper, code.
Fanghui Liu, Xiaolin Huang and Jie Yang: Indefinite kernel logistic regression, ACM Multimedia (MM-2017). paper, code.

Fanghui Liu, Tao Zhou, Keren Fu, Irene Yu-Hua Gu, and Jie Yang. Robust visual tracking via inverse nonnegative matrix factorization, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2016). paper, code.
Tao Zhou, H. Bhaskar, Fanghui Liu and Jie Yang. Graph regularized and locality-constrained coding for robust visual tracking. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). paper

Fanghui Liu, Tao Zhou, Irene Yu-Hua Gu, and Jie Yang. Visual tracking via nonnegative regularization multiple locality coding, IEEE International Conference on Computer Vision Workshops (ICCVW-2015). paper