Fanghui Liu

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 82

Top Topics

Kernel Logistic Regression

Kernel Learning

Visual Tracking

Nonnegative Matrix Factorization

Top Venues

Publications

Elías Abad-Rocamora, Fanghui Liu, Grigorios G. Chrysos, Pablo M. Olmos, Volkan Cevher
Efficient local linearity regularization to overcome catastrophic overfitting. CoRR (2024)
Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher
Generalization of Scaled Deep ResNets in the Mean-Field Regime. ICLR (2024)
Fanghui Liu
The Role of Over-Parameterization in Machine Learning - the Good, the Bad, the Ugly. AAAI (2024)
Zhongjie Shi, Fanghui Liu, Yuan Cao, Johan A. K. Suykens
Can overfitted deep neural networks in adversarial training generalize? - An approximation viewpoint. CoRR (2024)
Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios G. Chrysos, Volkan Cevher
Generalization of Scaled Deep ResNets in the Mean-Field Regime. CoRR (2024)
Yihang Chen, Fanghui Liu, Taiji Suzuki, Volkan Cevher
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization. CoRR (2024)
Elías Abad-Rocamora, Yongtao Wu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher
Revisiting character-level adversarial attacks. CoRR (2024)
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios G. Chrysos, Volkan Cevher
Robust NAS under adversarial training: benchmark, theory, and beyond. CoRR (2024)
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher
Robust NAS under adversarial training: benchmark, theory, and beyond. ICLR (2024)
Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James T. Kwok
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy. CoRR (2024)
Fanghui Liu, Leello Tadesse Dadi, Volkan Cevher
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks. CoRR (2024)
Elías Abad-Rocamora, Fanghui Liu, Grigorios Chrysos, Pablo M. Olmos, Volkan Cevher
Efficient local linearity regularization to overcome catastrophic overfitting. ICLR (2024)
Kun Fang, Fanghui Liu, Xiaolin Huang, Jie Yang
End-to-end kernel learning via generative random Fourier features. Pattern Recognit. 134 (2023)
Yongtao Wu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher
On the Convergence of Encoder-only Shallow Transformers. CoRR (2023)
Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher
Federated Learning under Covariate Shifts with Generalization Guarantees. Trans. Mach. Learn. Res. 2023 (2023)
Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher
Federated Learning under Covariate Shifts with Generalization Guarantees. CoRR (2023)
Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. NeurIPS (2023)
Fanghui Liu, Luca Viano, Volkan Cevher
What can online reinforcement learning with function approximation benefit from general coverage conditions? ICML (2023)
Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Francesco Locatello, Volkan Cevher
Benign Overfitting in Deep Neural Networks under Lazy Training. CoRR (2023)
Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
On the Convergence of Encoder-only Shallow Transformers. NeurIPS (2023)
Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher
Benign Overfitting in Deep Neural Networks under Lazy Training. ICML (2023)
Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. CoRR (2023)
Fanghui Liu, Luca Viano, Volkan Cevher
Provable benefits of general coverage conditions in efficient online RL with function approximation. CoRR (2023)
Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Generalization Properties of NAS under Activation and Skip Connection Search. NeurIPS (2022)
Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond. IEEE Trans. Pattern Anal. Mach. Intell. 44 (10) (2022)
Fanghui Liu, Johan A. K. Suykens, Volkan Cevher
On the Double Descent of Random Features Models Trained with SGD. NeurIPS (2022)
Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization). CoRR (2022)
Fanghui Liu, Luca Viano, Volkan Cevher
Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration. CoRR (2022)
Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang
Random Fourier Features for Asymmetric Kernels. CoRR (2022)
Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization). NeurIPS (2022)
Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study. NeurIPS (2022)
Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher
Generalization Properties of NAS under Activation and Skip Connection Search. CoRR (2022)
Elías Abad-Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
Sound and Complete Verification of Polynomial Networks. NeurIPS (2022)
Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study. CoRR (2022)
Elías Abad-Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher
Sound and Complete Verification of Polynomial Networks. CoRR (2022)
Fanghui Liu, Luca Viano, Volkan Cevher
Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration. NeurIPS (2022)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Generalization Properties of hyper-RKHS and its Applications. J. Mach. Learn. Res. 22 (2021)
Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures. AISTATS (2021)
Fanghui Liu, Johan A. K. Suykens, Volkan Cevher
On the Double Descent of Random Features Models Trained with SGD. CoRR (2021)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Analysis of regularized least-squares in reproducing kernel Kreĭn spaces. Mach. Learn. 110 (6) (2021)
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens
Kernel regression in high dimensions: Refined analysis beyond double descent. AISTATS (2021)
Kun Fang, Xiaolin Huang, Fanghui Liu, Jie Yang
End-to-end Kernel Learning via Generative Random Fourier Features. CoRR (2020)
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens
Kernel regression in high dimension: Refined analysis beyond double descent. CoRR (2020)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Analysis of Least Squares Regularized Regression in Reproducing Kernel Krein Spaces. CoRR (2020)
Fanghui Liu, Xiaolin Huang, Lei Shi, Jie Yang, Johan A. K. Suykens
A Double-Variational Bayesian Framework in Random Fourier Features for Indefinite Kernels. IEEE Trans. Neural Networks Learn. Syst. 31 (8) (2020)
Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Random Features for Kernel Approximation: A Survey in Algorithms, Theory, and Beyond. CoRR (2020)
Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines. CoRR (2020)
Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling. AAAI (2020)
Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens
Generalizing Random Fourier Features via Generalized Measures. CoRR (2020)
Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li
Learning Data-adaptive Non-parametric Kernels. J. Mach. Learn. Res. 21 (2020)
Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling. CoRR (2019)
Jiaxuan Xie, Fanghui Liu, Xiaolin Huang, Jie Yang
Sparse Indefinite Kernel Learning on Sphere. Aust. J. Intell. Inf. Process. Syst. 16 (3) (2019)
Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Johan A. K. Suykens
Indefinite Kernel Logistic Regression With Concave-Inexact-Convex Procedure. IEEE Trans. Neural Networks Learn. Syst. 30 (3) (2019)
Jiaxuan Xie, Fanghui Liu, Kaijie Wang, Xiaolin Huang
Deep Kernel Learning via Random Fourier Features. CoRR (2019)
Fanghui Liu, Chen Gong, Xiaolin Huang, Tao Zhou, Jie Yang, Dacheng Tao
Robust Visual Tracking Revisited: From Correlation Filter to Template Matching. CoRR (2019)
Hafiz Tayyab Mustafa, Fanghui Liu, Jie Yang, Zubair Khan, Qiao Huang
Dense Multi-focus Fusion Net: A Deep Unsupervised Convolutional Network for Multi-focus Image Fusion. ICAISC (1) (2019)
Fanghui Liu, Tao Zhou, Chen Gong, Keren Fu, Li Bai, Jie Yang
Inverse Nonnegative Local Coordinate Factorization for Visual Tracking. IEEE Trans. Circuits Syst. Video Technol. 28 (8) (2018)
Tao Zhou, Fanghui Liu, Harish Bhaskar, Jie Yang, Huanlong Zhang, Ping Cai
Online discriminative dictionary learning for robust object tracking. Neurocomputing 275 (2018)
Xingyu Chen, Fanghui Liu, Enmei Tu, Longbing Cao, Jie Yang
Deep-PUMR: Deep Positive and Unlabeled Learning with Manifold Regularization. ICONIP (1) (2018)
Cheng Peng, Fanghui Liu, Jie Yang, Nikola K. Kasabov
Densely Connected Discriminative Correlation Filters for Visual Tracking. IEEE Signal Process. Lett. 25 (7) (2018)
Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li
Nonlinear Pairwise Layer and Its Training for Kernel Learning. AAAI (2018)
Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li
Learning Data-adaptive Nonparametric Kernels. CoRR (2018)
Cheng Peng, Fanghui Liu, Jie Yang, Nikola K. Kasabov
Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters. IEEE Signal Process. Lett. 25 (11) (2018)
Fanghui Liu, Chen Gong, Xiaolin Huang, Tao Zhou, Jie Yang, Dacheng Tao
Robust Visual Tracking Revisited: From Correlation Filter to Template Matching. IEEE Trans. Image Process. 27 (6) (2018)
Tao Zhou, Fanghui Liu, Harish Bhaskar, Jie Yang
Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning. IEEE Trans. Cybern. 48 (9) (2018)
Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens
Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions. CoRR (2018)
Tao Zhou, Fanghui Liu, Harish Bhaskar, Jie Yang, Lei Chen, Ping Cai
Visual tracking via structural patch-based dictionary pair learning. ICIP (2017)
Fanghui Liu, Xiaolin Huang, Jie Yang
Indefinite Kernel Logistic Regression. ACM Multimedia (2017)
Fanghui Liu, Chen Gong, Tao Zhou, Keren Fu, Xiangjian He, Jie Yang
Visual Tracking via Nonnegative Multiple Coding. IEEE Trans. Multim. 19 (12) (2017)
Fanghui Liu, Xiaolin Huang, Cheng Peng, Jie Yang, Nikola K. Kasabov
Robust Kernel Approximation for Classification. ICONIP (1) (2017)
Fanghui Liu, Xiaolin Huang, Jie Yang
Indefinite Kernel Logistic Regression. CoRR (2017)
Tao Zhou, Harish Bhaskar, Fanghui Liu, Jie Yang
Graph Regularized and Locality-Constrained Coding for Robust Visual Tracking. IEEE Trans. Circuits Syst. Video Technol. 27 (10) (2017)
Cheng Peng, Fanghui Liu, Haiyan Yang, Jie Yang, Nikola K. Kasabov
Correlation Filters with Adaptive Memories and Fusion for Visual Tracking. ICONIP (3) (2017)
Tao Zhou, Harish Bhaskar, Fanghui Liu, Jie Yang, Ping Cai
Online learning and joint optimization of combined spatial-temporal models for robust visual tracking. Neurocomputing 226 (2017)
Fanghui Liu, Tao Zhou, Keren Fu, Jie Yang
Kernelized temporal locality learning for real-time visual tracking. Pattern Recognit. Lett. 90 (2017)
Chenjie Ge, Keren Fu, Fanghui Liu, Li Bai, Jie Yang
Co-saliency detection via inter and intra saliency propagation. Signal Process. Image Commun. 44 (2016)
Fanghui Liu, Tao Zhou, Keren Fu, Irene Y. H. Gu, Jie Yang
Robust visual tracking via inverse nonnegative matrix factorization. ICASSP (2016)
Fanghui Liu, Tao Zhou, Keren Fu, Jie Yang
Robust visual tracking via constrained correlation filter coding. Pattern Recognit. Lett. 84 (2016)
Kunqi Gu, Tao Zhou, Fanghui Liu, Jie Yang, Yu Qiao
Correlation filter tracking via bootstrap learning. ICIP (2016)
Fanghui Liu, Tao Zhou, Jie Yang
Geometric affine transformation estimation via correlation filter for visual tracking. Neurocomputing 214 (2016)
Fanghui Liu, Mingna Liu, Tao Zhou, Yu Qiao, Jie Yang
Incremental Robust Nonnegative Matrix Factorization for Object Tracking. ICONIP (2) (2016)
Fanghui Liu, Tao Zhou, Jie Yang, Irene Y. H. Gu
Visual Tracking via Nonnegative Regularization Multiple Locality Coding. ICCV Workshops (2015)
Fanghui Liu, Tao Zhou, Irene Y. H. Gu, Jie Yang
Visual Tracking via Nonnegative Regularization Multiple Locality Coding. CoRR (2015)