67 citations · 88 across the 7 of their papers we have counts for
12 papers
Sound and Complete Verification of Polynomial Networks
Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu +2
Polynomial Networks (PNs) have demonstrated promising performance on face and image recognition recently. However, robustness of PNs is unclear and thus obtaining certificates beco…
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study
Yongtao Wu, Zhenyu Zhu, Fanghui Liu +2
Neural tangent kernel (NTK) is a powerful tool to analyze training dynamics of neural networks and their generalization bounds. The study on NTK has been devoted to typical neural…
Understanding Deep Neural Function Approximation in Reinforcement Learning via -Greedy Exploration
Fanghui Liu, Luca Viano, Volkan Cevher
This paper provides a theoretical study of deep neural function approximation in reinforcement learning (RL) with the -greedy exploration under the online setting. This problem…
Random Fourier Features for Asymmetric Kernels
Mingzhen He, Fan He, Fanghui Liu +1
The random Fourier features (RFFs) method is a powerful and popular technique in kernel approximation for scalability of kernel methods. The theoretical foundation of RFFs is based…
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines
Fanghui Liu, Xiaolin Huang, Yudong Chen +1
In this paper, we develop a quadrature framework for large-scale kernel machines via a numerical integration representation. Considering that the integration domain and measure of…
Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens
In this paper, we provide a precise characterization of generalization properties of high dimensional kernel ridge regression across the under- and over-parameterized regimes, depe…