Fanghui Liu

According to our database, Fanghui Liu authored at least 61 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Robust NAS under adversarial training: benchmark, theory, and beyond.

Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios G. Chrysos, Volkan Cevher

CoRR, 2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime.

Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios G. Chrysos, Volkan Cevher

CoRR, 2024

Can overfitted deep neural networks in adversarial training generalize? - An approximation viewpoint.

Zhongjie Shi, Fanghui Liu, Yuan Cao, Johan A. K. Suykens

CoRR, 2024

Efficient local linearity regularization to overcome catastrophic overfitting.

Elías Abad-Rocamora, Fanghui Liu, Grigorios G. Chrysos, Pablo M. Olmos, Volkan Cevher

CoRR, 2024

The Role of Over-Parameterization in Machine Learning - the Good, the Bad, the Ugly.

Fanghui Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

End-to-end kernel learning via generative random Fourier features.

Kun Fang, Fanghui Liu, Xiaolin Huang, Jie Yang

Pattern Recognit., 2023

Federated Learning under Covariate Shifts with Generalization Guarantees.

Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

CoRR, 2023

Provable benefits of general coverage conditions in efficient online RL with function approximation.

Fanghui Liu, Luca Viano, Volkan Cevher

CoRR, 2023

On the Convergence of Encoder-only Shallow Transformers.

Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks.

Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Benign Overfitting in Deep Neural Networks under Lazy Training.

Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher

Proceedings of the International Conference on Machine Learning, 2023

What can online reinforcement learning with function approximation benefit from general coverage conditions?

Fanghui Liu, Luca Viano, Volkan Cevher

Proceedings of the International Conference on Machine Learning, 2023

2022

Towards a Unified Quadrature Framework for Large-Scale Kernel Machines.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Random Fourier Features for Asymmetric Kernels.

Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang

CoRR, 2022

Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration.

Fanghui Liu, Luca Viano, Volkan Cevher

CoRR, 2022

Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization).

Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalization Properties of NAS under Activation and Skip Connection Search.

Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study.

Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sound and Complete Verification of Polynomial Networks.

Elías Abad-Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration.

Fanghui Liu, Luca Viano, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Double Descent of Random Features Models Trained with SGD.

Fanghui Liu, Johan A. K. Suykens, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Analysis of regularized least-squares in reproducing kernel Kreĭn spaces.

Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens

Mach. Learn., 2021

Generalization Properties of hyper-RKHS and its Applications.

Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens

J. Mach. Learn. Res., 2021

Kernel regression in high dimensions: Refined analysis beyond double descent.

Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures.

Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

A Double-Variational Bayesian Framework in Random Fourier Features for Indefinite Kernels.

Fanghui Liu, Xiaolin Huang, Lei Shi, Jie Yang, Johan A. K. Suykens

IEEE Trans. Neural Networks Learn. Syst., 2020

Learning Data-adaptive Non-parametric Kernels.

Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

J. Mach. Learn. Res., 2020

Kernel regression in high dimension: Refined analysis beyond double descent.

Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens

CoRR, 2020

Analysis of Least Squares Regularized Regression in Reproducing Kernel Krein Spaces.

Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens

CoRR, 2020

Generalizing Random Fourier Features via Generalized Measures.

Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens

CoRR, 2020

Random Fourier Features via Fast Surrogate Leverage Weighted Sampling.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Indefinite Kernel Logistic Regression With Concave-Inexact-Convex Procedure.

Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Johan A. K. Suykens

IEEE Trans. Neural Networks Learn. Syst., 2019

Deep Kernel Learning via Random Fourier Features.

Jiaxuan Xie, Fanghui Liu, Kaijie Wang, Xiaolin Huang

CoRR, 2019

Sparse Indefinite Kernel Learning on Sphere.

Jiaxuan Xie, Fanghui Liu, Xiaolin Huang, Jie Yang

Aust. J. Intell. Inf. Process. Syst., 2019

Dense Multi-focus Fusion Net: A Deep Unsupervised Convolutional Network for Multi-focus Image Fusion.

Hafiz Tayyab Mustafa, Fanghui Liu, Jie Yang, Zubair Khan, Qiao Huang

Proceedings of the Artificial Intelligence and Soft Computing, 2019

2018

Robust Visual Tracking Revisited: From Correlation Filter to Template Matching.

Fanghui Liu, Chen Gong, Xiaolin Huang, Tao Zhou, Jie Yang, Dacheng Tao

IEEE Trans. Image Process., 2018

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

Tao Zhou, Fanghui Liu, Harish Bhaskar, Jie Yang

IEEE Trans. Cybern., 2018

Inverse Nonnegative Local Coordinate Factorization for Visual Tracking.

Fanghui Liu, Tao Zhou, Chen Gong, Keren Fu, Li Bai, Jie Yang

IEEE Trans. Circuits Syst. Video Technol., 2018

Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters.

Cheng Peng, Fanghui Liu, Jie Yang, Nikola K. Kasabov

IEEE Signal Process. Lett., 2018

Densely Connected Discriminative Correlation Filters for Visual Tracking.

Cheng Peng, Fanghui Liu, Jie Yang, Nikola K. Kasabov

IEEE Signal Process. Lett., 2018

Online discriminative dictionary learning for robust object tracking.

Tao Zhou, Fanghui Liu, Harish Bhaskar, Jie Yang, Huanlong Zhang, Ping Cai

Neurocomputing, 2018

Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions.

Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens

CoRR, 2018

Learning Data-adaptive Nonparametric Kernels.

Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

CoRR, 2018

Deep-PUMR: Deep Positive and Unlabeled Learning with Manifold Regularization.

Xingyu Chen, Fanghui Liu, Enmei Tu, Longbing Cao, Jie Yang

Proceedings of the Neural Information Processing - 25th International Conference, 2018

Nonlinear Pairwise Layer and Its Training for Kernel Learning.

Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Visual Tracking via Nonnegative Multiple Coding.

Fanghui Liu, Chen Gong, Tao Zhou, Keren Fu, Xiangjian He, Jie Yang

IEEE Trans. Multim., 2017

Graph Regularized and Locality-Constrained Coding for Robust Visual Tracking.

Tao Zhou, Harish Bhaskar, Fanghui Liu, Jie Yang

IEEE Trans. Circuits Syst. Video Technol., 2017

Kernelized temporal locality learning for real-time visual tracking.

Fanghui Liu, Tao Zhou, Keren Fu, Jie Yang

Pattern Recognit. Lett., 2017

Online learning and joint optimization of combined spatial-temporal models for robust visual tracking.

Tao Zhou, Harish Bhaskar, Fanghui Liu, Jie Yang, Ping Cai

Neurocomputing, 2017

Indefinite Kernel Logistic Regression.

Fanghui Liu, Xiaolin Huang, Jie Yang

Proceedings of the 2017 ACM on Multimedia Conference, 2017

Correlation Filters with Adaptive Memories and Fusion for Visual Tracking.

Cheng Peng, Fanghui Liu, Haiyan Yang, Jie Yang, Nikola K. Kasabov

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Robust Kernel Approximation for Classification.

Fanghui Liu, Xiaolin Huang, Cheng Peng, Jie Yang, Nikola K. Kasabov

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Visual tracking via structural patch-based dictionary pair learning.

Tao Zhou, Fanghui Liu, Harish Bhaskar, Jie Yang, Lei Chen, Ping Cai

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016

Co-saliency detection via inter and intra saliency propagation.

Chenjie Ge, Keren Fu, Fanghui Liu, Li Bai, Jie Yang

Signal Process. Image Commun., 2016

Robust visual tracking via constrained correlation filter coding.

Fanghui Liu, Tao Zhou, Keren Fu, Jie Yang

Pattern Recognit. Lett., 2016

Geometric affine transformation estimation via correlation filter for visual tracking.

Fanghui Liu, Tao Zhou, Jie Yang

Neurocomputing, 2016

Incremental Robust Nonnegative Matrix Factorization for Object Tracking.

Fanghui Liu, Mingna Liu, Tao Zhou, Yu Qiao, Jie Yang

Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Correlation filter tracking via bootstrap learning.

Kunqi Gu, Tao Zhou, Fanghui Liu, Jie Yang, Yu Qiao

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Robust visual tracking via inverse nonnegative matrix factorization.

Fanghui Liu, Tao Zhou, Keren Fu, Irene Y. H. Gu, Jie Yang

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

Visual Tracking via Nonnegative Regularization Multiple Locality Coding.

Fanghui Liu, Tao Zhou, Jie Yang, Irene Y. H. Gu

Proceedings of the 2015 IEEE International Conference on Computer Vision Workshop, 2015