79 citations · 100 across the 13 of their papers we have counts for
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cs.LG2024
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…
cs.LG2024★ 3 cited
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…
cs.LG2024★ 4 cited
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…