79 citations · 100 across the 13 of their papers we have counts for
13 papers
Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
Fan He, Mingzhen He, Lei Shi +2
Ridgeless regression has garnered attention among researchers, particularly in light of the ``Benign Overfitting'' phenomenon, where models interpolating noisy samples demonstrate…
Data Imputation by Pursuing Better Classification: A Supervised Kernel-Based Method
Ruikai Yang, Fan He, Mingzhen He +2
Data imputation, the process of filling in missing feature elements for incomplete data sets, plays a crucial role in data-driven learning. A fundamental belief is that data imputa…
Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature
Ruikai Yang, Fan He, Mingzhen He +2
Random feature (RF) has been widely used for node consistency in decentralized kernel ridge regression (KRR). Currently, the consistency is guaranteed by imposing constraints on co…
Enhancing Kernel Flexibility via Learning Asymmetric Locally-Adaptive Kernels
Fan He, Mingzhen He, Lei Shi +2
The lack of sufficient flexibility is the key bottleneck of kernel-based learning that relies on manually designed, pre-given, and non-trainable kernels. To enhance kernel flexibil…
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…
One-shot Distributed Algorithm for Generalized Eigenvalue Problem
Kexin Lv, Fan He, Xiaolin Huang +2
Nowadays, more and more datasets are stored in a distributed way for the sake of memory storage or data privacy. The generalized eigenvalue problem (GEP) plays a vital role in a la…
Relevance Attack on Detectors
Sizhe Chen, Fan He, Xiaolin Huang +1
This paper focuses on high-transferable adversarial attacks on detectors, which are hard to attack in a black-box manner, because of their multiple-output characteristics and the d…
One-shot Distibuted Algorithm for PCA with RBF Kernels
Fan He, Kexin Lv, Jie Yang +1
This letter proposes a one-shot algorithm for feature-distributed kernel PCA. Our algorithm is inspired by the dual relationship between sample-distributed and feature-distributed…
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…