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Jiankun Liu

2 accepted papers

2021

Effective Distributed Learning with Random Features: Improved Bounds and Algorithms

ICLR 2021poster

In this paper, we study the statistical properties of distributed kernel ridge regression together with random features (DKRR-RF), and obtain optimal generalization bounds under the basic setting, which can substantially relax the restriction on the number of local machines in the existing state-of-…

Cited by 25SourcePDFScholar
2021

Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation

NeurIPS 2021spotlight

In this paper, we provide theoretical results of estimation bounds and excess risk upper bounds for support vector machine (SVM) with sparse multi-kernel representation. These convergence rates for multi-kernel SVM are established by analyzing a Lasso-type regularized learning scheme within compo…

Cited by 7SourcePDFScholar