79 citations · 85 across the 5 of their papers we have counts for
6 papers
A Decentralized Framework for Kernel PCA with Projection Consensus Constraints
Fan He, Ruikai Yang, Lei Shi +1
This paper studies kernel PCA in a decentralized setting, where data are distributively observed with full features in local nodes and a fusion center is prohibited. Compared with…
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…
Learning with Asymmetric Kernels: Least Squares and Feature Interpretation
Mingzhen He, Fan He, Lei Shi +2
Asymmetric kernels naturally exist in real life, e.g., for conditional probability and directed graphs. However, most of the existing kernel-based learning methods require kernels…
Online PCB Defect Detector On A New PCB Defect Dataset
Sanli Tang, Fan He, Xiaolin Huang +1
Previous works for PCB defect detection based on image difference and image processing techniques have already achieved promising performance. However, they sometimes fall short be…
Fast Signal Recovery from Saturated Measurements by Linear Loss and Nonconvex Penalties
Fan He, Xiaolin Huang, Yipeng Liu +1
Sign information is the key to overcoming the inevitable saturation error in compressive sensing systems, which causes information loss and results in bias. For sparse signal recov…
Online Robust Principal Component Analysis with Change Point Detection
Wei Xiao, Xiaolin Huang, Jorge Silva +2
Robust PCA methods are typically batch algorithms which requires loading all observations into memory before processing. This makes them inefficient to process big data. In this pa…